From 8cf60ae7c33a58666efefdf916eaad4cf57f1dcc Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Fri, 4 Feb 2022 11:03:15 +0100
Subject: [PATCH 01/44] new AN_RB_PLIM.b2 reference

---
 .../notebooks/result_AN_RB_PLIM.b2.ipynb      | 969 +++++++++---------
 1 file changed, 473 insertions(+), 496 deletions(-)

diff --git a/test/resources/notebooks/result_AN_RB_PLIM.b2.ipynb b/test/resources/notebooks/result_AN_RB_PLIM.b2.ipynb
index 1342bfd6..b2b29b57 100644
--- a/test/resources/notebooks/result_AN_RB_PLIM.b2.ipynb
+++ b/test/resources/notebooks/result_AN_RB_PLIM.b2.ipynb
@@ -3,19 +3,19 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "87d1811a",
+   "id": "d8fed223",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:47:39.347321Z",
-     "iopub.status.busy": "2021-11-09T08:47:39.345966Z",
-     "iopub.status.idle": "2021-11-09T08:48:18.066635Z",
-     "shell.execute_reply": "2021-11-09T08:48:18.065903Z"
+     "iopub.execute_input": "2022-02-04T02:47:01.735916Z",
+     "iopub.status.busy": "2022-02-04T02:47:01.735171Z",
+     "iopub.status.idle": "2022-02-04T02:47:35.079462Z",
+     "shell.execute_reply": "2022-02-04T02:47:35.078668Z"
     },
     "papermill": {
-     "duration": 38.879119,
-     "end_time": "2021-11-09T08:48:18.066874",
+     "duration": 33.399226,
+     "end_time": "2022-02-04T02:47:35.079671",
      "exception": false,
-     "start_time": "2021-11-09T08:47:39.187755",
+     "start_time": "2022-02-04T02:47:01.680445",
      "status": "completed"
     }
    },
@@ -27,13 +27,13 @@
     "\"\"\"\n",
     "if 'spark' not in locals() and 'spark' not in globals():\n",
     "    import os\n",
-    "    import socket\n",
-    "\n",
     "    from pyspark import SparkContext, SparkConf\n",
     "    from pyspark.sql import SparkSession\n",
+    "    import socket\n",
     "\n",
     "    nxcals_jars = os.getenv('NXCALS_JARS')\n",
-    "    host_name = 'spark-runner.cern.ch' if os.environ.get('CI', 'false') == 'true' else socket.gethostname()\n",
+    "    host_name = socket.gethostname()\n",
+    "\n",
     "    conf = SparkConf()\n",
     "\n",
     "    conf.set('spark.master', 'yarn')\n",
@@ -65,20 +65,19 @@
     "             \"https://cs-ccr-nxcals8.cern.ch:19093,https://cs-ccr-nxcals8.cern.ch:19094\")\n",
     "\n",
     "    sc = SparkContext(conf=conf)\n",
-    "    spark = SparkSession(sc)\n",
-    "\n"
+    "    spark = SparkSession(sc)\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "b6f18dac",
+   "id": "47377ba2",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.13539,
-     "end_time": "2021-11-09T08:48:18.328445",
+     "duration": 0.038833,
+     "end_time": "2022-02-04T02:47:35.158208",
      "exception": false,
-     "start_time": "2021-11-09T08:48:18.193055",
+     "start_time": "2022-02-04T02:47:35.119375",
      "status": "completed"
     },
     "tags": []
@@ -108,14 +107,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "15e7e8bd",
+   "id": "5bb9a19e",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.13146,
-     "end_time": "2021-11-09T08:48:18.592280",
+     "duration": 0.038408,
+     "end_time": "2022-02-04T02:47:35.235105",
      "exception": false,
-     "start_time": "2021-11-09T08:48:18.460820",
+     "start_time": "2022-02-04T02:47:35.196697",
      "status": "completed"
     },
     "tags": []
@@ -138,14 +137,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b02cb9f3",
+   "id": "90dda8f9",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.139618,
-     "end_time": "2021-11-09T08:48:18.873771",
+     "duration": 0.038303,
+     "end_time": "2022-02-04T02:47:35.311811",
      "exception": false,
-     "start_time": "2021-11-09T08:48:18.734153",
+     "start_time": "2022-02-04T02:47:35.273508",
      "status": "completed"
     },
     "tags": []
@@ -157,20 +156,20 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "62abca77",
+   "id": "c8d8cd79",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:48:19.147183Z",
-     "iopub.status.busy": "2021-11-09T08:48:19.146328Z",
-     "iopub.status.idle": "2021-11-09T08:48:22.540498Z",
-     "shell.execute_reply": "2021-11-09T08:48:22.539917Z"
+     "iopub.execute_input": "2022-02-04T02:47:35.402832Z",
+     "iopub.status.busy": "2022-02-04T02:47:35.402105Z",
+     "iopub.status.idle": "2022-02-04T02:47:37.860720Z",
+     "shell.execute_reply": "2022-02-04T02:47:37.861209Z"
     },
     "papermill": {
-     "duration": 3.536405,
-     "end_time": "2021-11-09T08:48:22.540703",
+     "duration": 2.511098,
+     "end_time": "2022-02-04T02:47:37.861415",
      "exception": false,
-     "start_time": "2021-11-09T08:48:19.004298",
+     "start_time": "2022-02-04T02:47:35.350317",
      "status": "completed"
     },
     "tags": []
@@ -180,8 +179,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Analysis executed with lhc-sm-api version: 1.5.18\n",
-      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.66\n",
+      "Analysis executed with lhc-sm-api version: 1.5.19\n",
+      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.67\n",
       "Analysis performed by root\n"
      ]
     }
@@ -212,19 +211,19 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "28d21cec",
+   "id": "6a702bde",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:48:22.809589Z",
-     "iopub.status.busy": "2021-11-09T08:48:22.808729Z",
-     "iopub.status.idle": "2021-11-09T08:48:22.812690Z",
-     "shell.execute_reply": "2021-11-09T08:48:22.811916Z"
+     "iopub.execute_input": "2022-02-04T02:47:37.945376Z",
+     "iopub.status.busy": "2022-02-04T02:47:37.944689Z",
+     "iopub.status.idle": "2022-02-04T02:47:37.946607Z",
+     "shell.execute_reply": "2022-02-04T02:47:37.947085Z"
     },
     "papermill": {
-     "duration": 0.148271,
-     "end_time": "2021-11-09T08:48:22.812855",
+     "duration": 0.04665,
+     "end_time": "2022-02-04T02:47:37.947260",
      "exception": false,
-     "start_time": "2021-11-09T08:48:22.664584",
+     "start_time": "2022-02-04T02:47:37.900610",
      "status": "completed"
     },
     "tags": []
@@ -238,14 +237,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "96fbda97",
+   "id": "fb74b11c",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.138095,
-     "end_time": "2021-11-09T08:48:23.089046",
+     "duration": 0.039131,
+     "end_time": "2022-02-04T02:47:38.026724",
      "exception": false,
-     "start_time": "2021-11-09T08:48:22.950951",
+     "start_time": "2022-02-04T02:47:37.987593",
      "status": "completed"
     },
     "tags": []
@@ -277,14 +276,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "52467086",
+   "id": "e4662bb8",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.145776,
-     "end_time": "2021-11-09T08:48:23.374149",
+     "duration": 0.039439,
+     "end_time": "2022-02-04T02:47:38.105429",
      "exception": false,
-     "start_time": "2021-11-09T08:48:23.228373",
+     "start_time": "2022-02-04T02:47:38.065990",
      "status": "completed"
     },
     "scrolled": false,
@@ -298,19 +297,19 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "ebce53f9",
+   "id": "1f9819e1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:48:23.663792Z",
-     "iopub.status.busy": "2021-11-09T08:48:23.662925Z",
-     "iopub.status.idle": "2021-11-09T08:48:23.665395Z",
-     "shell.execute_reply": "2021-11-09T08:48:23.666020Z"
+     "iopub.execute_input": "2022-02-04T02:47:38.189732Z",
+     "iopub.status.busy": "2022-02-04T02:47:38.189067Z",
+     "iopub.status.idle": "2022-02-04T02:47:38.191483Z",
+     "shell.execute_reply": "2022-02-04T02:47:38.190840Z"
     },
     "papermill": {
-     "duration": 0.151683,
-     "end_time": "2021-11-09T08:48:23.666203",
+     "duration": 0.047039,
+     "end_time": "2022-02-04T02:47:38.191624",
      "exception": false,
-     "start_time": "2021-11-09T08:48:23.514520",
+     "start_time": "2022-02-04T02:47:38.144585",
      "status": "completed"
     },
     "tags": [
@@ -335,19 +334,19 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "6bd98251",
+   "id": "dec868e9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:48:23.958154Z",
-     "iopub.status.busy": "2021-11-09T08:48:23.957207Z",
-     "iopub.status.idle": "2021-11-09T08:48:23.960932Z",
-     "shell.execute_reply": "2021-11-09T08:48:23.961646Z"
+     "iopub.execute_input": "2022-02-04T02:47:38.277236Z",
+     "iopub.status.busy": "2022-02-04T02:47:38.276584Z",
+     "iopub.status.idle": "2022-02-04T02:47:38.278838Z",
+     "shell.execute_reply": "2022-02-04T02:47:38.279329Z"
     },
     "papermill": {
-     "duration": 0.156598,
-     "end_time": "2021-11-09T08:48:23.962041",
+     "duration": 0.048187,
+     "end_time": "2022-02-04T02:47:38.279514",
      "exception": false,
-     "start_time": "2021-11-09T08:48:23.805443",
+     "start_time": "2022-02-04T02:47:38.231327",
      "status": "completed"
     },
     "tags": []
@@ -371,14 +370,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5838e0da",
+   "id": "f3bd3dac",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.144785,
-     "end_time": "2021-11-09T08:48:24.252854",
+     "duration": 0.039626,
+     "end_time": "2022-02-04T02:47:38.358889",
      "exception": false,
-     "start_time": "2021-11-09T08:48:24.108069",
+     "start_time": "2022-02-04T02:47:38.319263",
      "status": "completed"
     },
     "tags": []
@@ -390,20 +389,20 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "21fc0d36",
+   "id": "cc57bc9c",
    "metadata": {
     "deleteable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:48:24.586563Z",
-     "iopub.status.busy": "2021-11-09T08:48:24.575458Z",
-     "iopub.status.idle": "2021-11-09T08:50:11.064105Z",
-     "shell.execute_reply": "2021-11-09T08:50:11.064806Z"
+     "iopub.execute_input": "2022-02-04T02:47:38.452495Z",
+     "iopub.status.busy": "2022-02-04T02:47:38.451743Z",
+     "iopub.status.idle": "2022-02-04T02:49:01.119970Z",
+     "shell.execute_reply": "2022-02-04T02:49:01.120521Z"
     },
     "papermill": {
-     "duration": 106.669271,
-     "end_time": "2021-11-09T08:50:11.065143",
+     "duration": 82.72171,
+     "end_time": "2022-02-04T02:49:01.120772",
      "exception": false,
-     "start_time": "2021-11-09T08:48:24.395872",
+     "start_time": "2022-02-04T02:47:38.399062",
      "status": "completed"
     },
     "scrolled": false,
@@ -459,7 +458,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) IEARTH.IEARTH, STATUS.I_EARTH_PCNT, STATUS.I_MEAS, STATUS.I_REF, IAB.I_A... for system: RPTE.UA23.RB.A12..., className: 51_self_pmd..., source: FGC... at 2017-04-22 04:50:29.760\n"
+      "\tQuerying PM event signal(s) IEARTH.IEARTH, STATUS.I_REF, STATUS.I_EARTH_PCNT, IAB.I_A, STATUS.I_MEAS... for system: RPTE.UA23.RB.A12..., className: 51_self_pmd..., source: FGC... at 2017-04-22 04:50:29.760\n"
      ]
     },
     {
@@ -516,7 +515,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying NXCALS signal(s) RB.A12.EVEN:ST_ABORT_PIC, RB.A12.ODD:ST_ABORT_PIC from 2017-04-22 04:50:28.760 to 2017-04-22 04:51:29.760\n"
+      "\tQuerying NXCALS signal(s) RB.A12.ODD:ST_ABORT_PIC, RB.A12.EVEN:ST_ABORT_PIC from 2017-04-22 04:50:28.760 to 2017-04-22 04:51:29.760\n"
      ]
     },
     {
@@ -611,7 +610,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) RR17.RB.A12:T_RES_BODY_2, RR17.RB.A12:T_RES_BODY_1, RR17.RB.A12:T_RES_BODY_3 for system: RR17.RB.A12, className: DQAMSNRB, source: QPS at 2017-04-22 04:50:30.051\n"
+      "\tQuerying PM event signal(s) RR17.RB.A12:T_RES_BODY_2, RR17.RB.A12:T_RES_BODY_3, RR17.RB.A12:T_RES_BODY_1 for system: RR17.RB.A12, className: DQAMSNRB, source: QPS at 2017-04-22 04:50:30.051\n"
      ]
     },
     {
@@ -630,7 +629,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) RR17.RB.A12:T_RES_BODY_2, RR17.RB.A12:T_RES_BODY_1, RR17.RB.A12:T_RES_BODY_3 for system: RR17.RB.A12, className: DQAMSNRB, source: QPS at 2017-04-22 04:57:58.204\n"
+      "\tQuerying PM event signal(s) RR17.RB.A12:T_RES_BODY_2, RR17.RB.A12:T_RES_BODY_3, RR17.RB.A12:T_RES_BODY_1 for system: RR17.RB.A12, className: DQAMSNRB, source: QPS at 2017-04-22 04:57:58.204\n"
      ]
     },
     {
@@ -649,7 +648,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UA23.RB.A12:T_RES_BODY_2, UA23.RB.A12:T_RES_BODY_1, UA23.RB.A12:T_RES_BODY_3 for system: UA23.RB.A12, className: DQAMSNRB, source: QPS at 2017-04-22 04:50:30.307\n"
+      "\tQuerying PM event signal(s) UA23.RB.A12:T_RES_BODY_1, UA23.RB.A12:T_RES_BODY_2, UA23.RB.A12:T_RES_BODY_3 for system: UA23.RB.A12, className: DQAMSNRB, source: QPS at 2017-04-22 04:50:30.307\n"
      ]
     },
     {
@@ -668,7 +667,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UA23.RB.A12:T_RES_BODY_2, UA23.RB.A12:T_RES_BODY_1, UA23.RB.A12:T_RES_BODY_3 for system: UA23.RB.A12, className: DQAMSNRB, source: QPS at 2017-04-22 04:57:32.404\n"
+      "\tQuerying PM event signal(s) UA23.RB.A12:T_RES_BODY_1, UA23.RB.A12:T_RES_BODY_2, UA23.RB.A12:T_RES_BODY_3 for system: UA23.RB.A12, className: DQAMSNRB, source: QPS at 2017-04-22 04:57:32.404\n"
      ]
     },
     {
@@ -763,7 +762,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) RR17.RB.A12:T_RES_BODY_2, RR17.RB.A12:T_RES_BODY_1, RR17.RB.A12:T_RES_BODY_3 for system: RR17.RB.A12, className: DQAMSNRB, source: QPS at 2015-01-17 12:00:01.257\n"
+      "\tQuerying PM event signal(s) RR17.RB.A12:T_RES_BODY_2, RR17.RB.A12:T_RES_BODY_3, RR17.RB.A12:T_RES_BODY_1 for system: RR17.RB.A12, className: DQAMSNRB, source: QPS at 2015-01-17 12:00:01.257\n"
      ]
     },
     {
@@ -782,7 +781,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) RR17.RB.A12:T_RES_BODY_2, RR17.RB.A12:T_RES_BODY_1, RR17.RB.A12:T_RES_BODY_3 for system: RR17.RB.A12, className: DQAMSNRB, source: QPS at 2015-01-17 12:07:26.204\n"
+      "\tQuerying PM event signal(s) RR17.RB.A12:T_RES_BODY_2, RR17.RB.A12:T_RES_BODY_3, RR17.RB.A12:T_RES_BODY_1 for system: RR17.RB.A12, className: DQAMSNRB, source: QPS at 2015-01-17 12:07:26.204\n"
      ]
     },
     {
@@ -801,7 +800,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UA23.RB.A12:T_RES_BODY_2, UA23.RB.A12:T_RES_BODY_1, UA23.RB.A12:T_RES_BODY_3 for system: UA23.RB.A12, className: DQAMSNRB, source: QPS at 2015-01-17 12:00:01.512\n"
+      "\tQuerying PM event signal(s) UA23.RB.A12:T_RES_BODY_1, UA23.RB.A12:T_RES_BODY_2, UA23.RB.A12:T_RES_BODY_3 for system: UA23.RB.A12, className: DQAMSNRB, source: QPS at 2015-01-17 12:00:01.512\n"
      ]
     },
     {
@@ -820,7 +819,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UA23.RB.A12:T_RES_BODY_2, UA23.RB.A12:T_RES_BODY_1, UA23.RB.A12:T_RES_BODY_3 for system: UA23.RB.A12, className: DQAMSNRB, source: QPS at 2015-01-17 12:07:01.804\n"
+      "\tQuerying PM event signal(s) UA23.RB.A12:T_RES_BODY_1, UA23.RB.A12:T_RES_BODY_2, UA23.RB.A12:T_RES_BODY_3 for system: UA23.RB.A12, className: DQAMSNRB, source: QPS at 2015-01-17 12:07:01.804\n"
      ]
     },
     {
@@ -857,7 +856,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "00ca547c2ea6495aa1758dc37391ec7e",
+       "model_id": "2affa14bb721465fa3c8c31a038c5b3a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -868,28 +867,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Querying Post Mortem failed using the following query: http://pm-api-pro/v2/pmdata/signal?system=QPS&className=DQAMGNSRB_PMREL&source=B34L2&timestampInNanos=1492829434601000000&signal=MB.C33R1:U_DIODE_RB\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Querying Post Mortem failed using the following query: http://pm-api-pro/v2/pmdata/signal?system=QPS&className=DQAMGNSRB_PMREL&source=B33R1&timestampInNanos=1492829435087000000&signal=MB.B34R1:U_DIODE_RB\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Querying Post Mortem failed using the following query: http://pm-api-pro/v2/pmdata/signal?system=QPS&className=DQAMGNSRB_PMREL&source=B8L2&timestampInNanos=1492829436374000000&signal=MB.A10L2:U_DIODE_RB\n",
-      "Querying Post Mortem failed using the following query: http://pm-api-pro/v2/pmdata/signal?system=QPS&className=DQAMGNSRB_PMREL&source=B8L2&timestampInNanos=1492829436374000000&signal=MB.A9L2:U_DIODE_RB\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
@@ -982,7 +959,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) DFLAS.7L2.RB.A12.LD2:U_HTS, DFLAS.7L2.RB.A12.LD1:U_HTS for system: RB.A12, className: DQAMGNDRBEVEN, source: QPS at 2017-04-22 04:50:29.769\n"
+      "\tQuerying PM event signal(s) DFLAS.7L2.RB.A12.LD1:U_HTS, DFLAS.7L2.RB.A12.LD2:U_HTS for system: RB.A12, className: DQAMGNDRBEVEN, source: QPS at 2017-04-22 04:50:29.769\n"
      ]
     },
     {
@@ -1002,7 +979,7 @@
      "output_type": "stream",
      "text": [
       "\tQuerying PM event signal(s) DFLAS.7L2.RB.A12.LD2:U_RES, DFLAS.7L2.RB.A12.LD1:U_RES for system: RB.A12, className: DQAMGNDRBEVEN, source: QPS at 2017-04-22 04:50:29.769\n",
-      "Elapsed: 106.000 s.\n"
+      "Elapsed: 82.366 s.\n"
      ]
     }
    ],
@@ -1111,14 +1088,14 @@
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@@ -1130,20 +1107,20 @@
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@@ -1236,14 +1213,14 @@
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@@ -1260,20 +1237,20 @@
   {
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    "execution_count": 8,
-   "id": "d0493400",
+   "id": "036f9f92",
    "metadata": {
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-     "shell.execute_reply": "2021-11-09T08:50:13.906720Z"
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     "scrolled": false,
@@ -1304,14 +1281,14 @@
   },
   {
    "cell_type": "markdown",
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      "exception": false,
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      "status": "completed"
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@@ -1343,20 +1320,20 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "5bd0386d",
+   "id": "0963d25c",
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-     "shell.execute_reply": "2021-11-09T08:50:16.030405Z"
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      "exception": false,
-     "start_time": "2021-11-09T08:50:14.710437",
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      "status": "completed"
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     "tags": []
@@ -1397,25 +1374,25 @@
      "data": {
       "text/html": [
        "<style  type=\"text/css\" >\n",
-       "</style><table id=\"T_76fb5_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
+       "</style><table id=\"T_ed223_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
-       "                        <th id=\"T_76fb5_level0_row0\" class=\"row_heading level0 row0\" >tau_i_meas</th>\n",
-       "                        <td id=\"T_76fb5_row0_col0\" class=\"data row0 col0\" >90</td>\n",
-       "                        <td id=\"T_76fb5_row0_col1\" class=\"data row0 col1\" >110</td>\n",
-       "                        <td id=\"T_76fb5_row0_col2\" class=\"data row0 col2\" >106</td>\n",
-       "                        <td id=\"T_76fb5_row0_col3\" class=\"data row0 col3\" >True</td>\n",
+       "                        <th id=\"T_ed223_level0_row0\" class=\"row_heading level0 row0\" >tau_i_meas</th>\n",
+       "                        <td id=\"T_ed223_row0_col0\" class=\"data row0 col0\" >90</td>\n",
+       "                        <td id=\"T_ed223_row0_col1\" class=\"data row0 col1\" >110</td>\n",
+       "                        <td id=\"T_ed223_row0_col2\" class=\"data row0 col2\" >106</td>\n",
+       "                        <td id=\"T_ed223_row0_col3\" class=\"data row0 col3\" >True</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_76fb5_level0_row1\" class=\"row_heading level0 row1\" >tau_i_meas_ref</th>\n",
-       "                        <td id=\"T_76fb5_row1_col0\" class=\"data row1 col0\" >90</td>\n",
-       "                        <td id=\"T_76fb5_row1_col1\" class=\"data row1 col1\" >110</td>\n",
-       "                        <td id=\"T_76fb5_row1_col2\" class=\"data row1 col2\" >107</td>\n",
-       "                        <td id=\"T_76fb5_row1_col3\" class=\"data row1 col3\" >True</td>\n",
+       "                        <th id=\"T_ed223_level0_row1\" class=\"row_heading level0 row1\" >tau_i_meas_ref</th>\n",
+       "                        <td id=\"T_ed223_row1_col0\" class=\"data row1 col0\" >90</td>\n",
+       "                        <td id=\"T_ed223_row1_col1\" class=\"data row1 col1\" >110</td>\n",
+       "                        <td id=\"T_ed223_row1_col2\" class=\"data row1 col2\" >107</td>\n",
+       "                        <td id=\"T_ed223_row1_col3\" class=\"data row1 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7ff894d07070>"
+       "<pandas.io.formats.style.Styler at 0x7f3ebebe2df0>"
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@@ -1428,14 +1405,14 @@
   },
   {
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@@ -1462,20 +1439,20 @@
   {
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-   "id": "d371732b",
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@@ -1501,14 +1478,14 @@
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@@ -1525,20 +1502,20 @@
   {
    "cell_type": "code",
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-   "id": "ba8db645",
+   "id": "a985b5b8",
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@@ -1572,14 +1549,14 @@
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@@ -1597,20 +1574,20 @@
   {
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@@ -1643,14 +1620,14 @@
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@@ -1692,20 +1669,20 @@
   {
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-   "id": "b68f7741",
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@@ -1735,39 +1712,39 @@
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+       "</style><table id=\"T_26b44_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
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-       "                        <td id=\"T_e5e5f_row0_col0\" class=\"data row0 col0\" >0.067500</td>\n",
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-       "                        <td id=\"T_e5e5f_row0_col3\" class=\"data row0 col3\" >True</td>\n",
+       "                        <th id=\"T_26b44_level0_row0\" class=\"row_heading level0 row0\" >R_even</th>\n",
+       "                        <td id=\"T_26b44_row0_col0\" class=\"data row0 col0\" >0.067500</td>\n",
+       "                        <td id=\"T_26b44_row0_col1\" class=\"data row0 col1\" >0.082500</td>\n",
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        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_e5e5f_level0_row1\" class=\"row_heading level0 row1\" >R_odd</th>\n",
-       "                        <td id=\"T_e5e5f_row1_col0\" class=\"data row1 col0\" >0.067500</td>\n",
-       "                        <td id=\"T_e5e5f_row1_col1\" class=\"data row1 col1\" >0.082500</td>\n",
-       "                        <td id=\"T_e5e5f_row1_col2\" class=\"data row1 col2\" >0.071291</td>\n",
-       "                        <td id=\"T_e5e5f_row1_col3\" class=\"data row1 col3\" >True</td>\n",
+       "                        <th id=\"T_26b44_level0_row1\" class=\"row_heading level0 row1\" >R_odd</th>\n",
+       "                        <td id=\"T_26b44_row1_col0\" class=\"data row1 col0\" >0.067500</td>\n",
+       "                        <td id=\"T_26b44_row1_col1\" class=\"data row1 col1\" >0.082500</td>\n",
+       "                        <td id=\"T_26b44_row1_col2\" class=\"data row1 col2\" >0.071291</td>\n",
+       "                        <td id=\"T_26b44_row1_col3\" class=\"data row1 col3\" >True</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_e5e5f_level0_row2\" class=\"row_heading level0 row2\" >tau_u_dump_res_even</th>\n",
-       "                        <td id=\"T_e5e5f_row2_col0\" class=\"data row2 col0\" >110.000000</td>\n",
-       "                        <td id=\"T_e5e5f_row2_col1\" class=\"data row2 col1\" >130.000000</td>\n",
-       "                        <td id=\"T_e5e5f_row2_col2\" class=\"data row2 col2\" >113.154836</td>\n",
-       "                        <td id=\"T_e5e5f_row2_col3\" class=\"data row2 col3\" >True</td>\n",
+       "                        <th id=\"T_26b44_level0_row2\" class=\"row_heading level0 row2\" >tau_u_dump_res_even</th>\n",
+       "                        <td id=\"T_26b44_row2_col0\" class=\"data row2 col0\" >110.000000</td>\n",
+       "                        <td id=\"T_26b44_row2_col1\" class=\"data row2 col1\" >130.000000</td>\n",
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+       "                        <td id=\"T_26b44_row2_col3\" class=\"data row2 col3\" >True</td>\n",
        "            </tr>\n",
        "            <tr>\n",
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-       "                        <td id=\"T_e5e5f_row3_col0\" class=\"data row3 col0\" >110.000000</td>\n",
-       "                        <td id=\"T_e5e5f_row3_col1\" class=\"data row3 col1\" >130.000000</td>\n",
-       "                        <td id=\"T_e5e5f_row3_col2\" class=\"data row3 col2\" >113.540531</td>\n",
-       "                        <td id=\"T_e5e5f_row3_col3\" class=\"data row3 col3\" >True</td>\n",
+       "                        <th id=\"T_26b44_level0_row3\" class=\"row_heading level0 row3\" >tau_u_dump_res_odd</th>\n",
+       "                        <td id=\"T_26b44_row3_col0\" class=\"data row3 col0\" >110.000000</td>\n",
+       "                        <td id=\"T_26b44_row3_col1\" class=\"data row3 col1\" >130.000000</td>\n",
+       "                        <td id=\"T_26b44_row3_col2\" class=\"data row3 col2\" >113.540531</td>\n",
+       "                        <td id=\"T_26b44_row3_col3\" class=\"data row3 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7ff894cc9e80>"
+       "<pandas.io.formats.style.Styler at 0x7f3ec1635ac0>"
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@@ -1781,20 +1758,20 @@
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+   "id": "56765f71",
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@@ -1825,25 +1802,25 @@
      "data": {
       "text/html": [
        "<style  type=\"text/css\" >\n",
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+       "</style><table id=\"T_b246e_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
-       "                        <th id=\"T_10e8f_level0_row0\" class=\"row_heading level0 row0\" >t_delay_ee_even</th>\n",
-       "                        <td id=\"T_10e8f_row0_col0\" class=\"data row0 col0\" >0.550000</td>\n",
-       "                        <td id=\"T_10e8f_row0_col1\" class=\"data row0 col1\" >0.650000</td>\n",
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-       "                        <td id=\"T_10e8f_row0_col3\" class=\"data row0 col3\" >True</td>\n",
+       "                        <th id=\"T_b246e_level0_row0\" class=\"row_heading level0 row0\" >t_delay_ee_even</th>\n",
+       "                        <td id=\"T_b246e_row0_col0\" class=\"data row0 col0\" >0.550000</td>\n",
+       "                        <td id=\"T_b246e_row0_col1\" class=\"data row0 col1\" >0.650000</td>\n",
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+       "                        <td id=\"T_b246e_row0_col3\" class=\"data row0 col3\" >True</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_10e8f_level0_row1\" class=\"row_heading level0 row1\" >t_delay_ee_odd</th>\n",
-       "                        <td id=\"T_10e8f_row1_col0\" class=\"data row1 col0\" >0.250000</td>\n",
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-       "                        <td id=\"T_10e8f_row1_col3\" class=\"data row1 col3\" >True</td>\n",
+       "                        <th id=\"T_b246e_level0_row1\" class=\"row_heading level0 row1\" >t_delay_ee_odd</th>\n",
+       "                        <td id=\"T_b246e_row1_col0\" class=\"data row1 col0\" >0.250000</td>\n",
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+       "                        <td id=\"T_b246e_row1_col3\" class=\"data row1 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7ff894ea6c70>"
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@@ -1858,20 +1835,20 @@
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-     "shell.execute_reply": "2021-11-09T08:50:25.040536Z"
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@@ -1893,14 +1870,14 @@
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+   "id": "8a1536bf",
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@@ -1921,20 +1898,20 @@
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-   "id": "07e59e0b",
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     "execution": {
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-     "shell.execute_reply": "2021-11-09T08:50:27.005144Z"
+     "iopub.execute_input": "2022-02-04T02:49:07.926370Z",
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@@ -1960,20 +1937,20 @@
   {
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-   "id": "c1a69e97",
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-     "shell.execute_reply": "2021-11-09T08:50:28.758406Z"
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@@ -1999,20 +1976,20 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "650ec255",
+   "id": "f27cceb1",
    "metadata": {
     "deletable": false,
     "execution": {
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-     "shell.execute_reply": "2021-11-09T08:50:30.357642Z"
+     "iopub.execute_input": "2022-02-04T02:49:10.122191Z",
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+     "iopub.status.idle": "2022-02-04T02:49:10.799910Z",
+     "shell.execute_reply": "2022-02-04T02:49:10.799062Z"
     },
     "papermill": {
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@@ -2038,20 +2015,20 @@
   {
    "cell_type": "code",
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-   "id": "58eadcb6",
+   "id": "dbca2856",
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     "deletable": false,
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-     "shell.execute_reply": "2021-11-09T08:50:32.328864Z"
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     },
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@@ -2076,14 +2053,14 @@
   },
   {
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@@ -2101,20 +2078,20 @@
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@@ -3160,20 +3137,20 @@
   {
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-   "id": "8301d69b",
+   "id": "d41967cb",
    "metadata": {
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-     "shell.execute_reply": "2021-11-09T08:51:35.529222Z"
+     "iopub.execute_input": "2022-02-04T02:50:06.538845Z",
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     },
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@@ -3884,14 +3861,14 @@
   },
   {
    "cell_type": "markdown",
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+   "id": "04b19a09",
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@@ -3913,20 +3890,20 @@
   {
    "cell_type": "code",
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-   "id": "85fb8eed",
+   "id": "0bb3ed93",
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-     "shell.execute_reply": "2021-11-09T08:51:38.777795Z"
+     "iopub.execute_input": "2022-02-04T02:50:07.633651Z",
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@@ -3961,20 +3938,20 @@
   {
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@@ -4000,20 +3977,20 @@
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+   "id": "d94a5f3f",
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@@ -4038,14 +4015,14 @@
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   {
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+   "id": "2b933963",
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@@ -4057,19 +4034,19 @@
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-   "id": "c2fe98ca",
+   "id": "95e7f01c",
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@@ -4081,14 +4058,14 @@
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+   "id": "288a7f08",
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@@ -4101,14 +4078,14 @@
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+   "id": "f68a1c98",
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@@ -4120,20 +4097,20 @@
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@@ -4217,13 +4194,13 @@
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@@ -4252,8 +4229,8 @@
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   "papermill": {
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    "input_path": "/builds/LHCData/lhc-sm-hwc/test/../rb/AN_RB_PLIM.b2.ipynb",
@@ -4270,8 +4247,8 @@
     "t_end": "2017-04-22 04:56:43.323",
     "t_start": "2017-04-22 04:34:15.401"
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-   "start_time": "2021-11-09T08:47:36.640448",
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+   "start_time": "2022-02-04T02:46:59.294586",
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-       "layout": "IPY_MODEL_42bc3648bc424f8f8f7436de1b01d375",
-       "placeholder": "​",
-       "style": "IPY_MODEL_27e0d15dc75b47d5945d63317c07aa7a",
-       "value": "Querying PM U_DIODE_RB, U_REF_N1: 100%"
-      }
-     },
-     "42bc3648bc424f8f8f7436de1b01d375": {
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@@ -4406,7 +4325,7 @@
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-     "5c4fbeede5194e9499df44a43e9e1e40": {
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-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "1.2.0",
-       "_view_name": "StyleView",
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-       "description_width": ""
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "1.5.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_e74e0d088fca4d5ca9b0e3a0a8a666f2",
+        "IPY_MODEL_af1a6a660d484f968f61128bec18df22",
+        "IPY_MODEL_f2096255ffbe4deca2bd5d1068e5f6a4"
+       ],
+       "layout": "IPY_MODEL_74da355f051d46879aaa43ef88394a20"
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-     "8dca623ac1514d43822ed96e93c94aba": {
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@@ -4489,28 +4414,7 @@
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-       "layout": "IPY_MODEL_8dca623ac1514d43822ed96e93c94aba",
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-       "value": " 54/54 [01:05&lt;00:00,  1.04s/it]"
-      }
-     },
-     "c84ae84deb7b4d0e95d84fbd1131c4a2": {
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@@ -4562,31 +4466,7 @@
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-       "bar_style": "success",
-       "description": "",
-       "description_tooltip": null,
-       "layout": "IPY_MODEL_f23d4746298d481181d5655d50b4816e",
-       "max": 54.0,
-       "min": 0.0,
-       "orientation": "horizontal",
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-       "value": 54.0
-      }
-     },
-     "f23d4746298d481181d5655d50b4816e": {
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@@ -4637,6 +4517,103 @@
        "visibility": null,
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+     "95af54c2aff646a295340a9f5a0cb00a": {
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+       "value": " 54/54 [00:52&lt;00:00,  1.19it/s]"
+      }
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-- 
GitLab


From 29d514c0aadef72a5da945a553aeb6e11744042f Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Mon, 7 Feb 2022 13:57:30 +0100
Subject: [PATCH 02/44] [SIGMON-308] fixes for no U_HDS signal (no discharges)

---
 qh/HWC_QHD_PM_LIST_CCC.ipynb | 18 +++++++++++++-----
 1 file changed, 13 insertions(+), 5 deletions(-)

diff --git a/qh/HWC_QHD_PM_LIST_CCC.ipynb b/qh/HWC_QHD_PM_LIST_CCC.ipynb
index 1fc7258b..6fbaffe8 100644
--- a/qh/HWC_QHD_PM_LIST_CCC.ipynb
+++ b/qh/HWC_QHD_PM_LIST_CCC.ipynb
@@ -284,7 +284,11 @@
     "\n",
     "    index = 0\n",
     "    for _, row in source_timestamp_df_i.iterrows():\n",
-    "        analysis.analyze_single_qh_voltage_with_ref(row['source'], row['timestamp'], u_hds_dfss[index], u_hds_ref_dfss[index], nominal_voltage=900)\n",
+    "        if u_hds_dfss[index]:\n",
+    "            analysis.analyze_single_qh_voltage_with_ref(row['source'], row['timestamp'], u_hds_dfss[index], u_hds_ref_dfss[index], nominal_voltage=900)\n",
+    "        else:\n",
+    "            print(f'\\nNo Quench Heater Discharges in {row[\"source\"]} at {row[\"timestamp\"]}')\n",
+    "            analysis.analysis_result.add_qh_analysis(row['timestamp'], row['source'], None, status=True)\n",
     "        index += 1\n",
     "    return analysis.analysis_result\n",
     "\n",
@@ -298,9 +302,13 @@
     "\n",
     "    index = 0\n",
     "    for _, row in source_timestamp_df_i.iterrows():\n",
-    "        analysis.analyze_single_qh_voltage_current_with_ref(row['source'], row['timestamp'], u_hds_dfss[index], i_hds_dfss[index], u_hds_ref_dfss[index], i_hds_ref_dfss[index],\n",
-    "                                                            QuenchHeaterVoltageCurrentAnalysis.plot_voltage_current_resistance_with_ref,\n",
-    "                                                            current_offset=0.085 if query.circuit_type == 'RB' else 0.025, nominal_voltage=900, mean_start_value=50)\n",
+    "        if u_hds_dfss[index] and i_hds_dfss[index]:\n",
+    "            analysis.analyze_single_qh_voltage_current_with_ref(row['source'], row['timestamp'], u_hds_dfss[index], i_hds_dfss[index], u_hds_ref_dfss[index], i_hds_ref_dfss[index],\n",
+    "                                                                QuenchHeaterVoltageCurrentAnalysis.plot_voltage_current_resistance_with_ref,\n",
+    "                                                                current_offset=0.085 if query.circuit_type == 'RB' else 0.025, nominal_voltage=900, mean_start_value=50)\n",
+    "        else:\n",
+    "            print(f'\\nNo Quench Heater Discharges in {row[\"source\"]} at {row[\"timestamp\"]}')\n",
+    "            analysis.analysis_result.add_qh_analysis(row['timestamp'], row['source'], None, status=True)\n",
     "        index += 1\n",
     "    return analysis.analysis_result"
    ]
@@ -447,4 +455,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
\ No newline at end of file
-- 
GitLab


From eae0063ab79a0d09482a9041cceb013e6486d544 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Wed, 9 Feb 2022 13:02:27 +0100
Subject: [PATCH 03/44] Replace AN_PGC1.ipynb

---
 pgc/AN_PGC1.ipynb | 71 ++++++++++++++++++++++++-----------------------
 1 file changed, 36 insertions(+), 35 deletions(-)

diff --git a/pgc/AN_PGC1.ipynb b/pgc/AN_PGC1.ipynb
index 830f190e..a9df8667 100644
--- a/pgc/AN_PGC1.ipynb
+++ b/pgc/AN_PGC1.ipynb
@@ -117,7 +117,12 @@
    },
    "outputs": [],
    "source": [
-    "#User input from ACCTESTING:\n"
+    "#User input from ACCTESTING:\n",
+    "hwc_test = 'PGC.1'\n",
+    "circuit_name = 'RQX.L1'\n",
+    "campaign = 'Recommissioning post LS2'\n",
+    "t_start = '2021-05-17 17:58:26.625000000'\n",
+    "t_end = '2021-05-17 17:58:26.638000000'"
    ]
   },
   {
@@ -150,9 +155,9 @@
     "lhc_circuit = meta_df[lambda x: x['Circuit name'] == circuit_name]\n",
     "\n",
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'] == safety_subsector]\n",
-    "#\n",
-    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))"
+    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
+    "\n",
+    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'].str.find(safety_subsector, 0) != -1]"
    ]
   },
   {
@@ -302,8 +307,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#condemned_circuits = ['RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCSX3.L2', 'RCTX3.L2', 'RSS.A34B1']\n",
-    "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
+    "condemned_circuits = list(pd.read_csv('../condemnded_circuits.csv')['Condemned Circuits'])\n",
     "display(condemned_circuits)"
    ]
   },
@@ -327,7 +331,7 @@
     "#\n",
     "with Timer():\n",
     "    #\n",
-    "    # Main circuits (RB, RQ, IT)\n",
+    "    print('Main circuits (RB, RQ, IT)')\n",
     "    i = j = 0\n",
     "    i_meas_13kA_dfs = []\n",
     "    for circuit_name in lhc_circuits['Circuit name']:\n",
@@ -361,7 +365,7 @@
     "                    i_meas_13kA_dfs.append(i_meas_rtqx2_nxcals_df)\n",
     "        i = i + 1\n",
     "    #\n",
-    "    #Individualy powered circuits (IPQ, IPD)\n",
+    "    print('Individualy powered circuits (IPQ, IPD)')\n",
     "    i = j = 0\n",
     "    i_meas_6kA_dfs = []\n",
     "    source_timestamp_qds_6kA_df = pd.DataFrame()\n",
@@ -396,7 +400,7 @@
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_6kA_df = pd.concat([source_timestamp_fgc_6kA_df, source_timestamp_fgc_df_i], ignore_index=True)                        \n",
     "        i = i + 1\n",
     "    #\n",
-    "    #600A-circuits\n",
+    "    print('600A-circuits')\n",
     "    i = j = 0\n",
     "    i_meas_600A_dfs = []\n",
     "    source_timestamp_qds_600A_df = pd.DataFrame()\n",
@@ -435,10 +439,9 @@
     "                    .with_metadata(circuit_name=circuit_name, system='PC', source='*') \\\n",
     "                    .event_query().df\n",
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_600A_df = pd.concat([source_timestamp_fgc_600A_df, source_timestamp_fgc_df_i], ignore_index=True)                                            \n",
-    "                #j = j + 1\n",
     "        i = i + 1\n",
     "    #\n",
-    "    # 60A, 80A, 120A circuits (to be updated to metadata)\n",
+    "    print('60A, 80A, 120A circuits')\n",
     "    i = j = 0\n",
     "    i_meas_120A_dfs = []\n",
     "    source_timestamp_fgc_120A_df = pd.DataFrame()\n",
@@ -448,29 +451,19 @@
     "            if circuit_type in pgc_120A:\n",
     "                j = j + 1\n",
     "                #print(j, circuit_type, circuit_name)\n",
-    "                df1 = DataQuery.builder(spark).byVariables() \\\n",
-    "                    .system('CMW') \\\n",
-    "                    .startTime(t_start_timestamp).endTime(t_end_timestamp) \\\n",
-    "                    .variableLike('%' + circuit_name + ':I_MEAS') \\\n",
-    "                    .buildDataset()\n",
-    "                i_meas_df = df1.select('nxcals_timestamp', 'nxcals_value').sort('nxcals_timestamp').toPandas()\n",
-    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['nxcals_value'].max()), ', Imin =', int(i_meas_df['nxcals_value'].min()))\n",
-    "                if (int(i_meas_df['nxcals_value'].max()) - int(i_meas_df['nxcals_value'].min())) < 10:\n",
-    "                    print('Powering current is too low')\n",
-    "                i_meas_df.rename(columns={'nxcals_timestamp': 'timestamp', 'nxcals_value': circuit_name + ':I_MEAS'}, inplace=True)\n",
-    "                t0 = i_meas_df['timestamp'].loc[0]\n",
-    "                i_meas_df['time'] = (i_meas_df['timestamp'] - t0)*1e-9\n",
-    "                i_meas_df.set_index('time', inplace = True)\n",
-    "                i_meas_df = i_meas_df.drop('timestamp', 1)\n",
-    "#                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
-    "#                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
-    "#                    .with_circuit_type(circuit_type) \\\n",
-    "#                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
-    "#                    .signal_query() \\\n",
-    "#                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
-    "#                    .convert_index_to_sec().dfs[0]\n",
-    "#                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
+    "                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
+    "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
+    "                    .with_circuit_type(circuit_type) \\\n",
+    "                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
+    "                    .signal_query() \\\n",
+    "                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
+    "                    .convert_index_to_sec().dfs[0]\n",
+    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['I_MEAS'].max()), ', Imin =', int(i_meas_df['I_MEAS'].min()))\n",
+    "                if (int(i_meas_df['I_MEAS'].max()) - int(i_meas_df['I_MEAS'].min())) < 10:\n",
+    "                     print('Powering current is too low')\n",
+    "                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
     "                i_meas_120A_dfs.append(i_meas_df)\n",
+    "\n",
     "                source_timestamp_fgc_df_i = QueryBuilder().with_pm() \\\n",
     "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
     "                    .with_circuit_type(circuit_type) \\\n",
@@ -697,7 +690,7 @@
    "id": "5960da85",
    "metadata": {},
    "source": [
-    "## 8. 60A-80A-120A circuits (metadata to be updated)"
+    "## 8. 60A-80A-120A circuits"
    ]
   },
   {
@@ -792,6 +785,14 @@
     "Time.sleep(5)\n",
     "!{sys.executable} -m jupyter nbconvert --to html $path_to_notebook --output-dir $report_destination_path --output $html_filename --TemplateExporter.exclude_input=True --TagRemovePreprocessor.remove_all_outputs_tags skip_output --TagRemovePreprocessor.remove_cell_tags skip_cell"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "19083843",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -822,4 +823,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
\ No newline at end of file
+}
-- 
GitLab


From 9142f7a011878386c6d23b44c7e5532cdec85bf4 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Wed, 9 Feb 2022 13:03:13 +0100
Subject: [PATCH 04/44] Replace AN_PGC2.ipynb

---
 pgc/AN_PGC2.ipynb | 69 ++++++++++++++++++++++++-----------------------
 1 file changed, 35 insertions(+), 34 deletions(-)

diff --git a/pgc/AN_PGC2.ipynb b/pgc/AN_PGC2.ipynb
index d40c3cd8..bba55805 100644
--- a/pgc/AN_PGC2.ipynb
+++ b/pgc/AN_PGC2.ipynb
@@ -137,7 +137,12 @@
    },
    "outputs": [],
    "source": [
-    "#User input from ACCTESTING\n"
+    "#User input from ACCTESTING\n",
+    "hwc_test = 'PGC.2'\n",
+    "circuit_name = 'RB.A78'\n",
+    "campaign = 'Recommissioning post LS2 - YETS'\n",
+    "t_start = '2021-11-24 07:10:00.628000000'\n",
+    "t_end = '2021-11-24 08:18:00.640000000'"
    ]
   },
   {
@@ -162,7 +167,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "a53cd810",
-   "metadata": {},
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [],
    "source": [
     "from lhcsmapi.metadata.MappingMetadata import MappingMetadata\n",
@@ -170,9 +177,9 @@
     "lhc_circuit = meta_df[lambda x: x['Circuit name'] == circuit_name]\n",
     "\n",
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'] == safety_subsector]\n",
+    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))"
+    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'].str.find(safety_subsector, 0) != -1]"
    ]
   },
   {
@@ -258,8 +265,7 @@
    },
    "outputs": [],
    "source": [
-    "lhc_circuits['pgc_group'] = lhc_circuits.apply(f, axis=1)\n",
-    "#display(lhc_circuits)"
+    "lhc_circuits['pgc_group'] = lhc_circuits.apply(f, axis=1)"
    ]
   },
   {
@@ -324,8 +330,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#condemned_circuits = ['RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCSX3.L2', 'RCTX3.L2', 'RSS.A34B1']\n",
-    "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
+    "condemned_circuits = list(pd.read_csv('../condemnded_circuits.csv')['Condemned Circuits'])\n",
     "display(condemned_circuits)"
    ]
   },
@@ -457,11 +462,9 @@
     "                    .with_metadata(circuit_name=circuit_name, system='PC', source='*') \\\n",
     "                    .event_query().df\n",
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_600A_df = pd.concat([source_timestamp_fgc_600A_df, source_timestamp_fgc_df_i], ignore_index=True)                                            \n",
-    "                #j = j + 1\n",
     "        i = i + 1\n",
     "    #\n",
     "    print('60A, 80A, 120A circuits')\n",
-    "    # to be updated to metadata\n",
     "    i = j = 0\n",
     "    i_meas_120A_dfs = []\n",
     "    source_timestamp_fgc_120A_df = pd.DataFrame()\n",
@@ -471,29 +474,19 @@
     "            if circuit_type in pgc_120A:\n",
     "                j = j + 1\n",
     "                #print(j, circuit_type, circuit_name)\n",
-    "                df1 = DataQuery.builder(spark).byVariables() \\\n",
-    "                    .system('CMW') \\\n",
-    "                    .startTime(t_start_timestamp).endTime(t_end_timestamp) \\\n",
-    "                    .variableLike('%' + circuit_name + ':I_MEAS') \\\n",
-    "                    .buildDataset()\n",
-    "                i_meas_df = df1.select('nxcals_timestamp', 'nxcals_value').sort('nxcals_timestamp').toPandas()\n",
-    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['nxcals_value'].max()), ', Imin =', int(i_meas_df['nxcals_value'].min()))\n",
-    "                if (int(i_meas_df['nxcals_value'].max()) - int(i_meas_df['nxcals_value'].min())) < 10:\n",
-    "                    print('Powering current is too low')\n",
-    "                i_meas_df.rename(columns={'nxcals_timestamp': 'timestamp', 'nxcals_value': circuit_name + ':I_MEAS'}, inplace=True)\n",
-    "                t0 = i_meas_df['timestamp'].loc[0]\n",
-    "                i_meas_df['time'] = (i_meas_df['timestamp'] - t0)*1e-9\n",
-    "                i_meas_df.set_index('time', inplace = True)\n",
-    "                i_meas_df = i_meas_df.drop('timestamp', 1)\n",
-    "#                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
-    "#                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
-    "#                    .with_circuit_type(circuit_type) \\\n",
-    "#                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
-    "#                    .signal_query() \\\n",
-    "#                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
-    "#                    .convert_index_to_sec().dfs[0]\n",
-    "#                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
+    "                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
+    "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
+    "                    .with_circuit_type(circuit_type) \\\n",
+    "                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
+    "                    .signal_query() \\\n",
+    "                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
+    "                    .convert_index_to_sec().dfs[0]\n",
+    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['I_MEAS'].max()), ', Imin =', int(i_meas_df['I_MEAS'].min()))\n",
+    "                if (int(i_meas_df['I_MEAS'].max()) - int(i_meas_df['I_MEAS'].min())) < 10:\n",
+    "                     print('Powering current is too low')\n",
+    "                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
     "                i_meas_120A_dfs.append(i_meas_df)\n",
+    "\n",
     "                source_timestamp_fgc_df_i = QueryBuilder().with_pm() \\\n",
     "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
     "                    .with_circuit_type(circuit_type) \\\n",
@@ -720,7 +713,7 @@
    "id": "b10e17b0",
    "metadata": {},
    "source": [
-    "## 8. 60A-80A-120A circuits (metadata to be updated)"
+    "## 8. 60A-80A-120A circuits"
    ]
   },
   {
@@ -818,6 +811,14 @@
     "Time.sleep(5)\n",
     "!{sys.executable} -m jupyter nbconvert --to html $path_to_notebook --output-dir $report_destination_path --output $html_filename --TemplateExporter.exclude_input=True --TagRemovePreprocessor.remove_all_outputs_tags skip_output --TagRemovePreprocessor.remove_cell_tags skip_cell"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9bd181ca",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -848,4 +849,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
\ No newline at end of file
+}
-- 
GitLab


From ce266151d0f8c8c9aada7bc7e5b32be1198b31da Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Wed, 9 Feb 2022 13:04:07 +0100
Subject: [PATCH 05/44] Replace AN_PGC3.ipynb

---
 pgc/AN_PGC3.ipynb | 55 +++++++++++++++++++++--------------------------
 1 file changed, 24 insertions(+), 31 deletions(-)

diff --git a/pgc/AN_PGC3.ipynb b/pgc/AN_PGC3.ipynb
index 7c63c44e..926043aa 100644
--- a/pgc/AN_PGC3.ipynb
+++ b/pgc/AN_PGC3.ipynb
@@ -137,7 +137,13 @@
    },
    "outputs": [],
    "source": [
-    "#User input fromACCTESTING here\n"
+    "#User input fromACCTESTING here\n",
+    "hwc_test = 'PGC.3'\n",
+    "circuit_name = 'RB.A56'\n",
+    "campaign = 'Recommissioning post LS2'\n",
+    "t_start = '2021-08-01 11:13:58.294000000'\n",
+    "t_end = '2021-08-01 12:28:58.294'\n",
+    "t_end_sec = '4500'"
    ]
   },
   {
@@ -170,9 +176,9 @@
     "lhc_circuit = meta_df[lambda x: x['Circuit name'] == circuit_name]\n",
     "\n",
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'] == safety_subsector]\n",
+    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))"
+    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'].str.find(safety_subsector, 0) != -1]"
    ]
   },
   {
@@ -324,8 +330,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#condemned_circuits = ['RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCSX3.L2', 'RCTX3.L2', 'RSS.A34B1']\n",
-    "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
+    "condemned_circuits = list(pd.read_csv('../condemnded_circuits.csv')['Condemned Circuits'])\n",
     "display(condemned_circuits)"
    ]
   },
@@ -457,11 +462,9 @@
     "                    .with_metadata(circuit_name=circuit_name, system='PC', source='*') \\\n",
     "                    .event_query().df\n",
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_600A_df = pd.concat([source_timestamp_fgc_600A_df, source_timestamp_fgc_df_i], ignore_index=True)                                            \n",
-    "                #j = j + 1\n",
     "        i = i + 1\n",
     "    #\n",
     "    print('60A, 80A, 120A circuits')\n",
-    "    # to be updated to metadata\n",
     "    i = j = 0\n",
     "    i_meas_120A_dfs = []\n",
     "    source_timestamp_fgc_120A_df = pd.DataFrame()\n",
@@ -471,29 +474,19 @@
     "            if circuit_type in pgc_120A:\n",
     "                j = j + 1\n",
     "                #print(j, circuit_type, circuit_name)\n",
-    "                df1 = DataQuery.builder(spark).byVariables() \\\n",
-    "                    .system('CMW') \\\n",
-    "                    .startTime(t_start_timestamp).endTime(t_end_timestamp) \\\n",
-    "                    .variableLike('%' + circuit_name + ':I_MEAS') \\\n",
-    "                    .buildDataset()\n",
-    "                i_meas_df = df1.select('nxcals_timestamp', 'nxcals_value').sort('nxcals_timestamp').toPandas()\n",
-    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['nxcals_value'].max()), ', Imin =', int(i_meas_df['nxcals_value'].min()))\n",
-    "                if (int(i_meas_df['nxcals_value'].max()) - int(i_meas_df['nxcals_value'].min())) < 10:\n",
-    "                    print('Powering current is too low')\n",
-    "                i_meas_df.rename(columns={'nxcals_timestamp': 'timestamp', 'nxcals_value': circuit_name + ':I_MEAS'}, inplace=True)\n",
-    "                t0 = i_meas_df['timestamp'].loc[0]\n",
-    "                i_meas_df['time'] = (i_meas_df['timestamp'] - t0)*1e-9\n",
-    "                i_meas_df.set_index('time', inplace = True)\n",
-    "                i_meas_df = i_meas_df.drop('timestamp', 1)\n",
-    "#                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
-    "#                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
-    "#                    .with_circuit_type(circuit_type) \\\n",
-    "#                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
-    "#                    .signal_query() \\\n",
-    "#                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
-    "#                    .convert_index_to_sec().dfs[0]\n",
-    "#                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
+    "                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
+    "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
+    "                    .with_circuit_type(circuit_type) \\\n",
+    "                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
+    "                    .signal_query() \\\n",
+    "                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
+    "                    .convert_index_to_sec().dfs[0]\n",
+    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['I_MEAS'].max()), ', Imin =', int(i_meas_df['I_MEAS'].min()))\n",
+    "                if (int(i_meas_df['I_MEAS'].max()) - int(i_meas_df['I_MEAS'].min())) < 10:\n",
+    "                     print('Powering current is too low')\n",
+    "                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
     "                i_meas_120A_dfs.append(i_meas_df)\n",
+    "\n",
     "                source_timestamp_fgc_df_i = QueryBuilder().with_pm() \\\n",
     "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
     "                    .with_circuit_type(circuit_type) \\\n",
@@ -726,7 +719,7 @@
    "id": "8dfeb8c4",
    "metadata": {},
    "source": [
-    "## 8. 60A-80A-120A circuits (metadata to be updated)"
+    "## 8. 60A-80A-120A circuits"
    ]
   },
   {
@@ -862,4 +855,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
\ No newline at end of file
+}
-- 
GitLab


From 09d255f7c78c7e7088d32b7b888ed95a8e7f4351 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Wed, 9 Feb 2022 13:05:05 +0100
Subject: [PATCH 06/44] Replace AN_PGC4.ipynb

---
 pgc/AN_PGC4.ipynb | 63 ++++++++++++++++++++++++-----------------------
 1 file changed, 32 insertions(+), 31 deletions(-)

diff --git a/pgc/AN_PGC4.ipynb b/pgc/AN_PGC4.ipynb
index a22960d0..c5e6c1fc 100644
--- a/pgc/AN_PGC4.ipynb
+++ b/pgc/AN_PGC4.ipynb
@@ -136,7 +136,13 @@
    },
    "outputs": [],
    "source": [
-    "#User input from ACCTESTING here\n"
+    "#User input from ACCTESTING here\n",
+    "hwc_test = 'PGC.4'\n",
+    "circuit_name = 'RB.A56'\n",
+    "campaign = 'Recommissioning post LS2'\n",
+    "t_start = '2021-08-01 12:43:34.927000000'\n",
+    "t_end = '2021-08-01 13:58:34.927'\n",
+    "t_end_sec = '4500'"
    ]
   },
   {
@@ -169,9 +175,9 @@
     "lhc_circuit = meta_df[lambda x: x['Circuit name'] == circuit_name]\n",
     "\n",
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'] == safety_subsector]\n",
+    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))"
+    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'].str.find(safety_subsector, 0) != -1]"
    ]
   },
   {
@@ -323,8 +329,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#condemned_circuits = ['RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCSX3.L2', 'RCTX3.L2', 'RSS.A34B1']\n",
-    "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
+    "condemned_circuits = list(pd.read_csv('../condemnded_circuits.csv')['Condemned Circuits'])\n",
     "display(condemned_circuits)"
    ]
   },
@@ -456,11 +461,9 @@
     "                    .with_metadata(circuit_name=circuit_name, system='PC', source='*') \\\n",
     "                    .event_query().df\n",
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_600A_df = pd.concat([source_timestamp_fgc_600A_df, source_timestamp_fgc_df_i], ignore_index=True)                                            \n",
-    "                #j = j + 1\n",
     "        i = i + 1\n",
     "    #\n",
     "    print('60A, 80A, 120A circuits')\n",
-    "    # to be updated to metadata\n",
     "    i = j = 0\n",
     "    i_meas_120A_dfs = []\n",
     "    source_timestamp_fgc_120A_df = pd.DataFrame()\n",
@@ -470,29 +473,19 @@
     "            if circuit_type in pgc_120A:\n",
     "                j = j + 1\n",
     "                #print(j, circuit_type, circuit_name)\n",
-    "                df1 = DataQuery.builder(spark).byVariables() \\\n",
-    "                    .system('CMW') \\\n",
-    "                    .startTime(t_start_timestamp).endTime(t_end_timestamp) \\\n",
-    "                    .variableLike('%' + circuit_name + ':I_MEAS') \\\n",
-    "                    .buildDataset()\n",
-    "                i_meas_df = df1.select('nxcals_timestamp', 'nxcals_value').sort('nxcals_timestamp').toPandas()\n",
-    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['nxcals_value'].max()), ', Imin =', int(i_meas_df['nxcals_value'].min()))\n",
-    "                if (int(i_meas_df['nxcals_value'].max()) - int(i_meas_df['nxcals_value'].min())) < 10:\n",
-    "                    print('Powering current is too low')\n",
-    "                i_meas_df.rename(columns={'nxcals_timestamp': 'timestamp', 'nxcals_value': circuit_name + ':I_MEAS'}, inplace=True)\n",
-    "                t0 = i_meas_df['timestamp'].loc[0]\n",
-    "                i_meas_df['time'] = (i_meas_df['timestamp'] - t0)*1e-9\n",
-    "                i_meas_df.set_index('time', inplace = True)\n",
-    "                i_meas_df = i_meas_df.drop('timestamp', 1)\n",
-    "#                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
-    "#                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
-    "#                    .with_circuit_type(circuit_type) \\\n",
-    "#                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
-    "#                    .signal_query() \\\n",
-    "#                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
-    "#                    .convert_index_to_sec().dfs[0]\n",
-    "#                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
+    "                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
+    "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
+    "                    .with_circuit_type(circuit_type) \\\n",
+    "                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
+    "                    .signal_query() \\\n",
+    "                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
+    "                    .convert_index_to_sec().dfs[0]\n",
+    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['I_MEAS'].max()), ', Imin =', int(i_meas_df['I_MEAS'].min()))\n",
+    "                if (int(i_meas_df['I_MEAS'].max()) - int(i_meas_df['I_MEAS'].min())) < 10:\n",
+    "                     print('Powering current is too low')\n",
+    "                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
     "                i_meas_120A_dfs.append(i_meas_df)\n",
+    "\n",
     "                source_timestamp_fgc_df_i = QueryBuilder().with_pm() \\\n",
     "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
     "                    .with_circuit_type(circuit_type) \\\n",
@@ -721,7 +714,7 @@
    "id": "c39cf821",
    "metadata": {},
    "source": [
-    "## 8. 60A-80A-120A circuits (metadata to be updated)"
+    "## 8. 60A-80A-120A circuits"
    ]
   },
   {
@@ -819,6 +812,14 @@
     "Time.sleep(5)\n",
     "!{sys.executable} -m jupyter nbconvert --to html $path_to_notebook --output-dir $report_destination_path --output $html_filename --TemplateExporter.exclude_input=True --TagRemovePreprocessor.remove_all_outputs_tags skip_output --TagRemovePreprocessor.remove_cell_tags skip_cell"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "890234d5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -849,4 +850,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
\ No newline at end of file
+}
-- 
GitLab


From 8b090f228353d2eb7b9ce6b64be7a30b72db3078 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Wed, 9 Feb 2022 13:08:14 +0100
Subject: [PATCH 07/44] Upload New File

---
 condemnded_circuits.csv | 14 ++++++++++++++
 1 file changed, 14 insertions(+)
 create mode 100644 condemnded_circuits.csv

diff --git a/condemnded_circuits.csv b/condemnded_circuits.csv
new file mode 100644
index 00000000..5068ee0a
--- /dev/null
+++ b/condemnded_circuits.csv
@@ -0,0 +1,14 @@
+Condemned Circuits
+RCO.A78B1
+RCO.A78B2
+RCO.A12B1
+RCO.A45B1
+RSS.A34B1
+RCBXH1.L2
+RCOSX3.L2
+RCOX3.L2
+RCSSX3.L2
+RCOSX3.L1
+RCBH31.R7B1
+RCBV26.R5B1
+RCBH11.R1B1
-- 
GitLab


From 70506ae504c2547d0a3c73257e252e51805331b6 Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Wed, 9 Feb 2022 14:59:06 +0100
Subject: [PATCH 08/44] [SIGMON-308] stop time

---
 qh/HWC_QHD_PM_LIST_CCC.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/qh/HWC_QHD_PM_LIST_CCC.ipynb b/qh/HWC_QHD_PM_LIST_CCC.ipynb
index 6fbaffe8..e3855a18 100644
--- a/qh/HWC_QHD_PM_LIST_CCC.ipynb
+++ b/qh/HWC_QHD_PM_LIST_CCC.ipynb
@@ -92,7 +92,7 @@
    },
    "outputs": [],
    "source": [
-    "stop_time = input(\"Start_time? [\" + stop_time_def + \"]:\")\n",
+    "stop_time = input(\"Stop_time? [\" + stop_time_def + \"]:\")\n",
     "stop_time = stop_time or stop_time_def"
    ]
   },
-- 
GitLab


From 794c14490b05551ce1cfaa4c99ccbb522badf2be Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Thu, 10 Feb 2022 12:55:12 +0100
Subject: [PATCH 09/44] html ref updated

---
 test/resources/reports/HWC_QHD_PM_LIST_CCC.html | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/resources/reports/HWC_QHD_PM_LIST_CCC.html b/test/resources/reports/HWC_QHD_PM_LIST_CCC.html
index 16208514..2f33b08c 100644
--- a/test/resources/reports/HWC_QHD_PM_LIST_CCC.html
+++ b/test/resources/reports/HWC_QHD_PM_LIST_CCC.html
@@ -13126,7 +13126,7 @@ Analysis executed with lhc-sm-hwc notebooks version: 1.5.66
 <div class="cell border-box-sizing code_cell rendered">
 
 </div>start_time = input("Start_time? [" + start_time_def + "]:")
-start_time = start_time or start_time_defstop_time = input("Start_time? [" + stop_time_def + "]:")
+start_time = start_time or start_time_defstop_time = input("Stop_time? [" + stop_time_def + "]:")
 stop_time = stop_time or stop_time_def
 <div class="cell border-box-sizing code_cell rendered">
 
-- 
GitLab


From 4ed6c3f7da118622e5031c977b74003b863b3414 Mon Sep 17 00:00:00 2001
From: Marc-Antoine Galilee <marc-antoine.galilee@cern.ch>
Date: Fri, 11 Feb 2022 13:15:33 +0100
Subject: [PATCH 10/44] QF_CERN_container_images_cache

---
 .gitlab-ci.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 082625e7..a197b738 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -74,7 +74,7 @@ deploy_production_eos:
     - tags
 
 test_papermill_nxcals:
-  image: python:3.8
+  image: registry.cern.ch/docker.io/library/python:3.8
   stage: test
   artifacts:
     untracked: true
@@ -101,4 +101,4 @@ notebooks_exec:
   only:
     - pipelines
     - web
-    - schedules
\ No newline at end of file
+    - schedules
-- 
GitLab


From f5e1c1c38326bf9df1569ae0292023bb4912acbf Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Fri, 11 Feb 2022 14:30:18 +0100
Subject: [PATCH 11/44] [SIGMON-257] i_meas sychronized to both fgc and pic

---
 rb/AN_RB_PLI3.d2.ipynb | 21 +++++++++++++--------
 1 file changed, 13 insertions(+), 8 deletions(-)

diff --git a/rb/AN_RB_PLI3.d2.ipynb b/rb/AN_RB_PLI3.d2.ipynb
index 4d7735ce..98bad9ae 100644
--- a/rb/AN_RB_PLI3.d2.ipynb
+++ b/rb/AN_RB_PLI3.d2.ipynb
@@ -208,11 +208,14 @@
     "    timestamp_pic = rb_query.find_timestamp_pic(timestamp_fgc, spark=spark, duration=[(t_end-timestamp_fgc, 'ns')])\n",
     "    timestamp_pic_ref = rb_query.find_timestamp_pic(timestamp_fgc_ref, spark=spark, duration=[(t_end_ref-timestamp_fgc_ref, 'ns')])\n",
     "    i_a_df, i_ref_df = rb_query.query_pc_pm(timestamp_fgc, timestamp_fgc, signal_names=['I_A', 'I_REF'])\n",
-    "    i_meas_df, i_earth_df, i_earth_pcnt_df, v_meas_df = rb_query.query_pc_pm(timestamp_fgc, min(timestamp_pic), signal_names=['I_MEAS', 'I_EARTH', 'I_EARTH_PCNT', 'V_MEAS'])\n",
+    "    # time scale is normalized to timestamp_pic\n",
+    "    i_meas_pic_df, i_earth_pic_df, i_earth_pcnt_pic_df, v_meas_pic_df = rb_query.query_pc_pm(timestamp_fgc, min(timestamp_pic), signal_names=['I_MEAS', 'I_EARTH', 'I_EARTH_PCNT', 'V_MEAS'])\n",
+    "    # time scale is normalized to timestamp_fgc\n",
+    "    i_meas_fgc_df, i_earth_fgc_df, i_earth_pcnt_fgc_df, v_meas_fgc_df = rb_query.query_pc_pm(timestamp_fgc, timestamp_fgc, signal_names=['I_MEAS', 'I_EARTH', 'I_EARTH_PCNT', 'V_MEAS'])\n",
     "    \n",
     "    # PC Reference\n",
     "    i_meas_nxcals_pic_sync_df = rb_query.query_signal_nxcals(t_start, t_end, t0=min(timestamp_pic), system='PC', signal_names='I_MEAS', spark=spark)[0]\n",
-    "    i_meas_nxcals_pic_sync_ref_df = rb_query.query_signal_nxcals(t_start_ref, t_end_ref, t0=min(timestamp_pic_ref), system='PC', signal_names='I_MEAS', spark=spark)[0] \n",
+    "    i_meas_nxcals_pic_sync_ref_df = rb_query.query_signal_nxcals(t_start_ref, t_end_ref, t0=min(timestamp_pic_ref), system='PC', signal_names='I_MEAS', spark=spark)[0]\n",
     "    if isinstance(t_start_ref, int):\n",
     "        source_timestamp_pc_ref = rb_query.find_source_timestamp_pc(t_start_ref, t_end_ref)\n",
     "        timestamp_fgc_ref = source_timestamp_pc_ref.at[0, 'timestamp']\n",
@@ -220,8 +223,10 @@
     "        timestamp_fgc_ref = float('nan')\n",
     "    \n",
     "    # PIC Reference\n",
-    "    #timestamp_pic_ref = rb_query.find_timestamp_pic(timestamp_fgc_ref, spark=spark, duration=[(t_end_ref-timestamp_fgc_ref, 'ns')])\n",
-    "    i_meas_ref_df = rb_query.query_pc_pm(timestamp_fgc_ref, min(timestamp_pic_ref), signal_names=['I_MEAS'])[0]\n",
+    "    # time scale is normalized to timestamp_pic_ref\n",
+    "    i_meas_ref_pic_df = rb_query.query_pc_pm(timestamp_fgc_ref, min(timestamp_pic_ref), signal_names=['I_MEAS'])[0]\n",
+    "    # time scale is normalized to timestamp_fgc_ref\n",
+    "    i_meas_ref_fgc_df = rb_query.query_pc_pm(timestamp_fgc_ref, timestamp_fgc_ref, signal_names=['I_MEAS'])[0]\n",
     "    \n",
     "    # EE Voltage\n",
     "    source_timestamp_ee_odd_df = rb_query.find_source_timestamp_ee(timestamp_fgc, system='EE_ODD')\n",
@@ -396,7 +401,7 @@
    },
    "outputs": [],
    "source": [
-    "rb_analysis.analyze_i_meas_pc(circuit_name, timestamp_fgc, timestamp_fgc_ref, min(timestamp_pic), i_meas_df, i_meas_ref_df)"
+    "rb_analysis.analyze_i_meas_pc(circuit_name, timestamp_fgc, timestamp_fgc_ref, min(timestamp_pic), i_meas_fgc_df, i_meas_ref_fgc_df)"
    ]
   },
   {
@@ -433,7 +438,7 @@
    "outputs": [],
    "source": [
     "title = create_hwc_plot_title_with_circuit_name(circuit_name=circuit_name, hwc_test=hwc_test, t_start=t_start, t_end=t_end, signal='I_MEAS smoothness')\n",
-    "rb_analysis.plot_i_meas_smoothness(i_meas_df, title=title)"
+    "rb_analysis.plot_i_meas_smoothness(i_meas_pic_df, title=title)"
    ]
   },
   {
@@ -459,7 +464,7 @@
    "outputs": [],
    "source": [
     "title = create_hwc_plot_title_with_circuit_name(circuit_name=circuit_name, hwc_test=hwc_test, t_start=t_start, t_end=t_end, signal='V_MEAS')\n",
-    "rb_analysis.assert_v_meas(timestamp_ee_even, min(timestamp_pic), t_after_ee=1, v_meas_df=v_meas_df, value_min=-4.2, value_max=-3.2, title=title, xmax=15)"
+    "rb_analysis.assert_v_meas(timestamp_ee_even, min(timestamp_pic), t_after_ee=1, v_meas_df=v_meas_pic_df, value_min=-4.2, value_max=-3.2, title=title, xmax=15)"
    ]
   },
   {
@@ -509,7 +514,7 @@
    },
    "outputs": [],
    "source": [
-    "rb_analysis.analyze_char_time_u_dump_res_ee(circuit_name, timestamp_fgc, [u_dump_res_odd_df, u_dump_res_even_df], i_meas_df)"
+    "rb_analysis.analyze_char_time_u_dump_res_ee(circuit_name, timestamp_fgc, [u_dump_res_odd_df, u_dump_res_even_df], i_meas_pic_df)"
    ]
   },
   {
-- 
GitLab


From 1b0c43c4cb302d4435af2dcd2e90a77f672aee10 Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Fri, 11 Feb 2022 14:33:22 +0100
Subject: [PATCH 12/44] [SIGMON-257] tests commented to generate a reference

---
 test/test_notebooks.py | 150 ++++++++++++++++++++---------------------
 1 file changed, 75 insertions(+), 75 deletions(-)

diff --git a/test/test_notebooks.py b/test/test_notebooks.py
index c4508ac7..4f3090f8 100644
--- a/test/test_notebooks.py
+++ b/test/test_notebooks.py
@@ -63,30 +63,30 @@ PGC_NOTEBOOKS = [
 ]
 
 RB_NOTEBOOKS = [
-    ('rb', 'AN_RB_PIC2', 'PIC2 FAST ABORT REQ VIA PIC', 'RB.A12', 'Before LS2', '2018-12-06 17:03:17.072000000',
-     '2018-12-06 17:21:45.530000000', []),
-    ('rb', 'AN_RB_PLI1.a2', 'PLI1.a2', 'RB.A12', 'HWC_2017', '2017-04-21 15:42:31.569', '2017-04-21 16:01:35.843', []),
-    ('rb', 'AN_RB_PLI1.b2', 'PLI1.b2', 'RB.A12', 'HWC_2018_1', '2018-03-16 18:55:57.270', '2018-03-16 19:07:00.286',
-     []),
-    ('rb', 'AN_RB_PLI1.d2', 'PLI1.d2', 'RB.A12', 'HWC_2018_1', '2017-04-21 17:10:50.001', '2017-04-21 17:24:09.828',
-     []),
-    ('rb', 'AN_RB_PLI2.b2', 'PLI2.b2', 'RB.A12', 'HWC_2018_1', '2018-03-16 21:22:00.406', '2018-03-16 21:36:11.440',
-     []),
-    ('rb', 'AN_RB_PLI2.f1', 'PLI2.f1', 'RB.A23', 'Recommissioning post LS2', '2021-05-04 16:21:48.535000000',
-     '2021-05-04 16:38:52.126000000', ['AN_RB_PLI2.f1.csv']),
-    ('rb', 'AN_RB_PLI2.s1', 'PLI2.s1', 'RB.A12', 'HWC_2014', '2014-12-11 16:49:47.759', '2014-12-11 19:02:01.401',
-     ['AN_RB_PLI2.s1_BUSBAR_RESISTANCE.csv']),
-    ('rb', 'AN_RB_PLI3.a5', 'PLI3.a5', 'RB.A12', 'HWC_2017', '2017-04-22 08:57:30.399', '2017-04-22 11:32:09.824',
-     ['AN_RB_PLI3.a5_BUSBAR_RESISTANCE.csv', 'AN_RB_PLI3.a5_MAGNET_RESISTANCE.csv']),
+    # ('rb', 'AN_RB_PIC2', 'PIC2 FAST ABORT REQ VIA PIC', 'RB.A12', 'Before LS2', '2018-12-06 17:03:17.072000000',
+    #  '2018-12-06 17:21:45.530000000', []),
+    # ('rb', 'AN_RB_PLI1.a2', 'PLI1.a2', 'RB.A12', 'HWC_2017', '2017-04-21 15:42:31.569', '2017-04-21 16:01:35.843', []),
+    # ('rb', 'AN_RB_PLI1.b2', 'PLI1.b2', 'RB.A12', 'HWC_2018_1', '2018-03-16 18:55:57.270', '2018-03-16 19:07:00.286',
+    #  []),
+    # ('rb', 'AN_RB_PLI1.d2', 'PLI1.d2', 'RB.A12', 'HWC_2018_1', '2017-04-21 17:10:50.001', '2017-04-21 17:24:09.828',
+    #  []),
+    # ('rb', 'AN_RB_PLI2.b2', 'PLI2.b2', 'RB.A12', 'HWC_2018_1', '2018-03-16 21:22:00.406', '2018-03-16 21:36:11.440',
+    #  []),
+    # ('rb', 'AN_RB_PLI2.f1', 'PLI2.f1', 'RB.A23', 'Recommissioning post LS2', '2021-05-04 16:21:48.535000000',
+    #  '2021-05-04 16:38:52.126000000', ['AN_RB_PLI2.f1.csv']),
+    # ('rb', 'AN_RB_PLI2.s1', 'PLI2.s1', 'RB.A12', 'HWC_2014', '2014-12-11 16:49:47.759', '2014-12-11 19:02:01.401',
+    #  ['AN_RB_PLI2.s1_BUSBAR_RESISTANCE.csv']),
+    # ('rb', 'AN_RB_PLI3.a5', 'PLI3.a5', 'RB.A12', 'HWC_2017', '2017-04-22 08:57:30.399', '2017-04-22 11:32:09.824',
+    #  ['AN_RB_PLI3.a5_BUSBAR_RESISTANCE.csv', 'AN_RB_PLI3.a5_MAGNET_RESISTANCE.csv']),
     ('rb', 'AN_RB_PLI3.d2', 'PLI3.d2', 'RB.A34', 'Recommissioning post LS2', '2021-03-24 22:19:06.563000000',
      '2021-03-24 22:44:23.159000000', []),
-    ('rb', 'AN_RB_PLIM.b2', 'PLIM.b2', 'RB.A12', 'HWC_2018_1', '2017-04-22 04:34:15.401', '2017-04-22 04:56:43.323',
-     []),
-    ('rb', 'AN_RB_PLIS.s2', 'PLIS.s2', 'RB.A12', 'HWC_2014', '2014-12-12 19:04:12.478', '2014-12-12 22:03:18.179',
-     ['AN_RB_PLIS.s2_BUSBAR_RESISTANCE.csv']),
-    ('rb', 'AN_RB_PNO.a6', 'PNO.a6', 'RB.A12', 'HWC_2014', '2014-12-12 19:04:12.478', '2014-12-12 22:03:18.179',
-     ['AN_RB_PNO.a6_BUSBAR_RESISTANCE.csv', 'AN_RB_PNO.a6_MAGNET_RESISTANCE.csv']),
-    ('rb', 'AN_RB_PNO.b2', 'PNO.b2', 'RB.A12', 'HWC_2018_1', '2018-03-17 11:34:53.954', '2018-03-17 16:06:41.537', []),
+    # ('rb', 'AN_RB_PLIM.b2', 'PLIM.b2', 'RB.A12', 'HWC_2018_1', '2017-04-22 04:34:15.401', '2017-04-22 04:56:43.323',
+    #  []),
+    # ('rb', 'AN_RB_PLIS.s2', 'PLIS.s2', 'RB.A12', 'HWC_2014', '2014-12-12 19:04:12.478', '2014-12-12 22:03:18.179',
+    #  ['AN_RB_PLIS.s2_BUSBAR_RESISTANCE.csv']),
+    # ('rb', 'AN_RB_PNO.a6', 'PNO.a6', 'RB.A12', 'HWC_2014', '2014-12-12 19:04:12.478', '2014-12-12 22:03:18.179',
+    #  ['AN_RB_PNO.a6_BUSBAR_RESISTANCE.csv', 'AN_RB_PNO.a6_MAGNET_RESISTANCE.csv']),
+    # ('rb', 'AN_RB_PNO.b2', 'PNO.b2', 'RB.A12', 'HWC_2018_1', '2018-03-17 11:34:53.954', '2018-03-17 16:06:41.537', []),
 ]
 
 RQ_NOTEBOOKS = [
@@ -166,7 +166,7 @@ def setup():
     os.environ[lhcsmapi.nb_version_env] = version
 
 
-@pytest.mark.parametrize('directory,notebook,hwc_test,circuit_name,campaign,t_start,t_end,csv_files', HWC_NOTEBOOKS)
+@pytest.mark.parametrize('directory,notebook,hwc_test,circuit_name,campaign,t_start,t_end,csv_files', RB_NOTEBOOKS)
 def test_hwc_notebook(directory, notebook, hwc_test, circuit_name, campaign, t_start, t_end, csv_files):
     _test_notebook(directory,
                    notebook,
@@ -181,58 +181,58 @@ def test_hwc_notebook(directory, notebook, hwc_test, circuit_name, campaign, t_s
                    csv_files)
 
 
-@pytest.mark.parametrize('directory,notebook,circuit_name,timestamp_fgc,csv_files', FGC_SEARCH_NOTEBOOKS)
-def test_fgc_search_notebook(directory, notebook, circuit_name, timestamp_fgc, csv_files):
-    _test_notebook(directory,
-                   notebook,
-                   {
-                       'circuit_name': circuit_name,
-                       'timestamp_fgc': timestamp_fgc,
-                       'author': 'test',
-                       'is_automatic': True
-                   },
-                   csv_files)
-
-
-@pytest.mark.parametrize('directory,notebook,circuit_type,circuit_names,timestamps_fgc,csv_files',
-                         FGC_2_SEARCH_NOTEBOOKS)
-def test_fgc_2_search_notebook(directory, notebook, circuit_type, circuit_names, timestamps_fgc, csv_files):
-    _test_notebook(directory,
-                   notebook,
-                   {
-                       'circuit_type': circuit_type,
-                       'circuit_names': circuit_names,
-                       'timestamps_fgc': timestamps_fgc,
-                       'author': 'test',
-                       'is_automatic': True
-                   },
-                   csv_files)
-
-
-@pytest.mark.parametrize('directory,notebook,circuit_name,discharge_level,start_time,end_time,csv_files', QH_NOTEBOOKS)
-def test_qh_search_notebook(directory, notebook, circuit_name, discharge_level, start_time, end_time, csv_files):
-    _test_notebook(directory,
-                   notebook,
-                   {
-                       'circuit_name': circuit_name,
-                       'discharge_level': discharge_level,
-                       'start_time': start_time,
-                       'end_time': end_time,
-                       'is_automatic': True
-                   },
-                   csv_files)
-
-
-@pytest.mark.parametrize('directory,notebook,start_time,stop_time,csv_files', QHD_PM_LIST)
-def test_qh_list_notebook(directory, notebook, start_time, stop_time, csv_files):
-    _test_notebook(directory,
-                   notebook,
-                   {
-                       'start_time': start_time,
-                       'stop_time': stop_time,
-                       'initial_charge_check': True
-                   },
-                   csv_files)
+# @pytest.mark.parametrize('directory,notebook,circuit_name,timestamp_fgc,csv_files', FGC_SEARCH_NOTEBOOKS)
+# def test_fgc_search_notebook(directory, notebook, circuit_name, timestamp_fgc, csv_files):
+#     _test_notebook(directory,
+#                    notebook,
+#                    {
+#                        'circuit_name': circuit_name,
+#                        'timestamp_fgc': timestamp_fgc,
+#                        'author': 'test',
+#                        'is_automatic': True
+#                    },
+#                    csv_files)
+#
+#
+# @pytest.mark.parametrize('directory,notebook,circuit_type,circuit_names,timestamps_fgc,csv_files',
+#                          FGC_2_SEARCH_NOTEBOOKS)
+# def test_fgc_2_search_notebook(directory, notebook, circuit_type, circuit_names, timestamps_fgc, csv_files):
+#     _test_notebook(directory,
+#                    notebook,
+#                    {
+#                        'circuit_type': circuit_type,
+#                        'circuit_names': circuit_names,
+#                        'timestamps_fgc': timestamps_fgc,
+#                        'author': 'test',
+#                        'is_automatic': True
+#                    },
+#                    csv_files)
+#
+#
+# @pytest.mark.parametrize('directory,notebook,circuit_name,discharge_level,start_time,end_time,csv_files', QH_NOTEBOOKS)
+# def test_qh_search_notebook(directory, notebook, circuit_name, discharge_level, start_time, end_time, csv_files):
+#     _test_notebook(directory,
+#                    notebook,
+#                    {
+#                        'circuit_name': circuit_name,
+#                        'discharge_level': discharge_level,
+#                        'start_time': start_time,
+#                        'end_time': end_time,
+#                        'is_automatic': True
+#                    },
+#                    csv_files)
+#
+#
+# @pytest.mark.parametrize('directory,notebook,start_time,stop_time,csv_files', QHD_PM_LIST)
+# def test_qh_list_notebook(directory, notebook, start_time, stop_time, csv_files):
+#     _test_notebook(directory,
+#                    notebook,
+#                    {
+#                        'start_time': start_time,
+#                        'stop_time': stop_time,
+#                        'initial_charge_check': True
+#                    },
+#                    csv_files)
 
 
 def _test_notebook(directory, notebook_name, notebook_parameters, csv_files):
-- 
GitLab


From 7b14ba063993f1fdbd6bb36086552e93da1e41d3 Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Mon, 14 Feb 2022 08:38:33 +0100
Subject: [PATCH 13/44] [SIGMON-257] new references for RB_PLI3.d2

---
 .../notebooks/result_AN_RB_PLI3.d2.ipynb      | 784 +++++++++---------
 test/resources/reports/AN_RB_PLI3.d2.html     |  70 +-
 2 files changed, 448 insertions(+), 406 deletions(-)

diff --git a/test/resources/notebooks/result_AN_RB_PLI3.d2.ipynb b/test/resources/notebooks/result_AN_RB_PLI3.d2.ipynb
index 6d4fde64..e03f6dca 100644
--- a/test/resources/notebooks/result_AN_RB_PLI3.d2.ipynb
+++ b/test/resources/notebooks/result_AN_RB_PLI3.d2.ipynb
@@ -3,19 +3,19 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "634b36f9",
+   "id": "b82dd51f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:08:02.982317Z",
-     "iopub.status.busy": "2021-11-09T09:08:02.981472Z",
-     "iopub.status.idle": "2021-11-09T09:08:43.103216Z",
-     "shell.execute_reply": "2021-11-09T09:08:43.102092Z"
+     "iopub.execute_input": "2022-02-11T13:55:13.844738Z",
+     "iopub.status.busy": "2022-02-11T13:55:13.844005Z",
+     "iopub.status.idle": "2022-02-11T13:56:10.858865Z",
+     "shell.execute_reply": "2022-02-11T13:56:10.858043Z"
     },
     "papermill": {
-     "duration": 40.309301,
-     "end_time": "2021-11-09T09:08:43.103490",
+     "duration": 57.067183,
+     "end_time": "2022-02-11T13:56:10.859095",
      "exception": false,
-     "start_time": "2021-11-09T09:08:02.794189",
+     "start_time": "2022-02-11T13:55:13.791912",
      "status": "completed"
     }
    },
@@ -27,13 +27,13 @@
     "\"\"\"\n",
     "if 'spark' not in locals() and 'spark' not in globals():\n",
     "    import os\n",
-    "    import socket\n",
-    "\n",
     "    from pyspark import SparkContext, SparkConf\n",
     "    from pyspark.sql import SparkSession\n",
+    "    import socket\n",
     "\n",
     "    nxcals_jars = os.getenv('NXCALS_JARS')\n",
-    "    host_name = 'spark-runner.cern.ch' if os.environ.get('CI', 'false') == 'true' else socket.gethostname()\n",
+    "    host_name = socket.gethostname()\n",
+    "\n",
     "    conf = SparkConf()\n",
     "\n",
     "    conf.set('spark.master', 'yarn')\n",
@@ -65,20 +65,19 @@
     "             \"https://cs-ccr-nxcals8.cern.ch:19093,https://cs-ccr-nxcals8.cern.ch:19094\")\n",
     "\n",
     "    sc = SparkContext(conf=conf)\n",
-    "    spark = SparkSession(sc)\n",
-    "\n"
+    "    spark = SparkSession(sc)\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "fd4f976f",
+   "id": "776d8eb2",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.137695,
-     "end_time": "2021-11-09T09:08:43.379289",
+     "duration": 0.037014,
+     "end_time": "2022-02-11T13:56:10.935898",
      "exception": false,
-     "start_time": "2021-11-09T09:08:43.241594",
+     "start_time": "2022-02-11T13:56:10.898884",
      "status": "completed"
     },
     "tags": []
@@ -106,14 +105,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b68678d8",
+   "id": "1e6a66ac",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.129918,
-     "end_time": "2021-11-09T09:08:43.644380",
+     "duration": 0.037434,
+     "end_time": "2022-02-11T13:56:11.010606",
      "exception": false,
-     "start_time": "2021-11-09T09:08:43.514462",
+     "start_time": "2022-02-11T13:56:10.973172",
      "status": "completed"
     },
     "tags": []
@@ -136,14 +135,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "174d6488",
+   "id": "d1908361",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.13481,
-     "end_time": "2021-11-09T09:08:43.915818",
+     "duration": 0.036187,
+     "end_time": "2022-02-11T13:56:11.083796",
      "exception": false,
-     "start_time": "2021-11-09T09:08:43.781008",
+     "start_time": "2022-02-11T13:56:11.047609",
      "status": "completed"
     },
     "tags": []
@@ -155,20 +154,20 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "4b1328ea",
+   "id": "a6f5452f",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:08:44.191321Z",
-     "iopub.status.busy": "2021-11-09T09:08:44.190405Z",
-     "iopub.status.idle": "2021-11-09T09:08:47.880144Z",
-     "shell.execute_reply": "2021-11-09T09:08:47.879418Z"
+     "iopub.execute_input": "2022-02-11T13:56:11.167510Z",
+     "iopub.status.busy": "2022-02-11T13:56:11.166798Z",
+     "iopub.status.idle": "2022-02-11T13:56:14.564803Z",
+     "shell.execute_reply": "2022-02-11T13:56:14.565453Z"
     },
     "papermill": {
-     "duration": 3.833615,
-     "end_time": "2021-11-09T09:08:47.880354",
+     "duration": 3.445395,
+     "end_time": "2022-02-11T13:56:14.565642",
      "exception": false,
-     "start_time": "2021-11-09T09:08:44.046739",
+     "start_time": "2022-02-11T13:56:11.120247",
      "status": "completed"
     },
     "scrolled": true,
@@ -179,8 +178,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Analysis executed with lhc-sm-api version: 1.5.18\n",
-      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.66\n",
+      "Analysis executed with lhc-sm-api version: 1.5.19\n",
+      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.67\n",
       "Analysis performed by root\n"
      ]
     }
@@ -211,19 +210,19 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "09a09288",
+   "id": "b3d35874",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:08:48.124072Z",
-     "iopub.status.busy": "2021-11-09T09:08:48.123345Z",
-     "iopub.status.idle": "2021-11-09T09:08:48.127315Z",
-     "shell.execute_reply": "2021-11-09T09:08:48.126460Z"
+     "iopub.execute_input": "2022-02-11T13:56:14.647097Z",
+     "iopub.status.busy": "2022-02-11T13:56:14.646409Z",
+     "iopub.status.idle": "2022-02-11T13:56:14.649402Z",
+     "shell.execute_reply": "2022-02-11T13:56:14.648738Z"
     },
     "papermill": {
-     "duration": 0.128453,
-     "end_time": "2021-11-09T09:08:48.127495",
+     "duration": 0.04574,
+     "end_time": "2022-02-11T13:56:14.649543",
      "exception": false,
-     "start_time": "2021-11-09T09:08:47.999042",
+     "start_time": "2022-02-11T13:56:14.603803",
      "status": "completed"
     },
     "tags": []
@@ -237,14 +236,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3f7ae5e4",
+   "id": "34756261",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.119547,
-     "end_time": "2021-11-09T09:08:48.367358",
+     "duration": 0.037627,
+     "end_time": "2022-02-11T13:56:14.725473",
      "exception": false,
-     "start_time": "2021-11-09T09:08:48.247811",
+     "start_time": "2022-02-11T13:56:14.687846",
      "status": "completed"
     },
     "tags": []
@@ -276,20 +275,20 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "b8217c08",
+   "id": "3b9b1e37",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:08:48.623561Z",
-     "iopub.status.busy": "2021-11-09T09:08:48.622862Z",
-     "iopub.status.idle": "2021-11-09T09:08:48.625922Z",
-     "shell.execute_reply": "2021-11-09T09:08:48.625196Z"
+     "iopub.execute_input": "2022-02-11T13:56:14.807997Z",
+     "iopub.status.busy": "2022-02-11T13:56:14.807314Z",
+     "iopub.status.idle": "2022-02-11T13:56:14.810240Z",
+     "shell.execute_reply": "2022-02-11T13:56:14.809553Z"
     },
     "papermill": {
-     "duration": 0.137115,
-     "end_time": "2021-11-09T09:08:48.626072",
+     "duration": 0.046951,
+     "end_time": "2022-02-11T13:56:14.810405",
      "exception": false,
-     "start_time": "2021-11-09T09:08:48.488957",
+     "start_time": "2022-02-11T13:56:14.763454",
      "status": "completed"
     },
     "scrolled": false,
@@ -309,19 +308,19 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "8bfa338b",
+   "id": "1a4b6dff",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:08:48.885463Z",
-     "iopub.status.busy": "2021-11-09T09:08:48.884608Z",
-     "iopub.status.idle": "2021-11-09T09:08:48.887530Z",
-     "shell.execute_reply": "2021-11-09T09:08:48.886871Z"
+     "iopub.execute_input": "2022-02-11T13:56:14.892040Z",
+     "iopub.status.busy": "2022-02-11T13:56:14.891344Z",
+     "iopub.status.idle": "2022-02-11T13:56:14.894235Z",
+     "shell.execute_reply": "2022-02-11T13:56:14.893583Z"
     },
     "papermill": {
-     "duration": 0.136292,
-     "end_time": "2021-11-09T09:08:48.887714",
+     "duration": 0.046456,
+     "end_time": "2022-02-11T13:56:14.894377",
      "exception": false,
-     "start_time": "2021-11-09T09:08:48.751422",
+     "start_time": "2022-02-11T13:56:14.847921",
      "status": "completed"
     },
     "tags": [
@@ -346,19 +345,19 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "fd9f471e",
+   "id": "2cd90c31",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:08:49.150161Z",
-     "iopub.status.busy": "2021-11-09T09:08:49.149372Z",
-     "iopub.status.idle": "2021-11-09T09:08:49.152399Z",
-     "shell.execute_reply": "2021-11-09T09:08:49.152982Z"
+     "iopub.execute_input": "2022-02-11T13:56:14.976551Z",
+     "iopub.status.busy": "2022-02-11T13:56:14.975840Z",
+     "iopub.status.idle": "2022-02-11T13:56:14.979351Z",
+     "shell.execute_reply": "2022-02-11T13:56:14.978685Z"
     },
     "papermill": {
-     "duration": 0.132361,
-     "end_time": "2021-11-09T09:08:49.153183",
+     "duration": 0.046835,
+     "end_time": "2022-02-11T13:56:14.979512",
      "exception": false,
-     "start_time": "2021-11-09T09:08:49.020822",
+     "start_time": "2022-02-11T13:56:14.932677",
      "status": "completed"
     },
     "tags": []
@@ -382,13 +381,13 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a0a72e15",
+   "id": "cb749438",
    "metadata": {
     "papermill": {
-     "duration": 0.133007,
-     "end_time": "2021-11-09T09:08:49.419472",
+     "duration": 0.038649,
+     "end_time": "2022-02-11T13:56:15.058333",
      "exception": false,
-     "start_time": "2021-11-09T09:08:49.286465",
+     "start_time": "2022-02-11T13:56:15.019684",
      "status": "completed"
     },
     "tags": []
@@ -400,20 +399,20 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "e6eb858e",
+   "id": "2fa30010",
    "metadata": {
     "deleteable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:08:49.699529Z",
-     "iopub.status.busy": "2021-11-09T09:08:49.683918Z",
-     "iopub.status.idle": "2021-11-09T09:09:57.462170Z",
-     "shell.execute_reply": "2021-11-09T09:09:57.461135Z"
+     "iopub.execute_input": "2022-02-11T13:56:15.165117Z",
+     "iopub.status.busy": "2022-02-11T13:56:15.144312Z",
+     "iopub.status.idle": "2022-02-11T13:57:15.524154Z",
+     "shell.execute_reply": "2022-02-11T13:57:15.524740Z"
     },
     "papermill": {
-     "duration": 67.904957,
-     "end_time": "2021-11-09T09:09:57.462443",
+     "duration": 60.42821,
+     "end_time": "2022-02-11T13:57:15.524960",
      "exception": false,
-     "start_time": "2021-11-09T09:08:49.557486",
+     "start_time": "2022-02-11T13:56:15.096750",
      "status": "completed"
     },
     "scrolled": false,
@@ -552,13 +551,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) STATUS.V_MEAS, IEARTH.I_EARTH, STATUS.I_MEAS, STATUS.I_EARTH_PCNT for system: RPTE.UA43.RB.A34, className: lhc_self_pmd, source: FGC at 2021-03-24 22:37:42.880\n"
+      "\tQuerying PM event signal(s) STATUS.I_EARTH_PCNT, STATUS.V_MEAS, IEARTH.I_EARTH, STATUS.I_MEAS for system: RPTE.UA43.RB.A34, className: lhc_self_pmd, source: FGC at 2021-03-24 22:37:42.880\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_signal_nxcals: 8/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_pc_pm: 8/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -567,6 +566,13 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\tQuerying PM event signal(s) STATUS.I_EARTH_PCNT, STATUS.V_MEAS, IEARTH.I_EARTH, STATUS.I_MEAS for system: RPTE.UA43.RB.A34, className: lhc_self_pmd, source: FGC at 2021-03-24 22:37:42.880\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
@@ -582,7 +588,19 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_pc: 10/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_signal_nxcals: 10/30.</text>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_pc: 11/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -601,7 +619,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_pc_pm: 11/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_pc_pm: 12/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -620,7 +638,26 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_ee: 12/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_pc_pm: 13/30.</text>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\tQuerying PM event signal(s) STATUS.I_MEAS for system: RPTE.UA43.RB.A34, className: 51_self_pmd, source: FGC at 2015-04-01 19:17:52.120\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_ee: 14/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -639,7 +676,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_u_dump_res_pm: 13/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_u_dump_res_pm: 15/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -658,7 +695,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_ee: 14/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_ee: 16/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -677,7 +714,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_u_dump_res_pm: 15/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_u_dump_res_pm: 17/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -696,7 +733,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 16/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 18/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -709,13 +746,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UJ33.RB.A34:T_RES_BODY_1, UJ33.RB.A34:T_RES_BODY_2, UJ33.RB.A34:T_RES_BODY_3 for system: UJ33.RB.A34, className: DQAMSNRB, source: QPS at 2021-03-24 22:43:06.046\n"
+      "\tQuerying PM event signal(s) UJ33.RB.A34:T_RES_BODY_1, UJ33.RB.A34:T_RES_BODY_3, UJ33.RB.A34:T_RES_BODY_2 for system: UJ33.RB.A34, className: DQAMSNRB, source: QPS at 2021-03-24 22:43:06.046\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 17/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 19/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -728,13 +765,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UJ33.RB.A34:T_RES_BODY_1, UJ33.RB.A34:T_RES_BODY_2, UJ33.RB.A34:T_RES_BODY_3 for system: UJ33.RB.A34, className: DQAMSNRB, source: QPS at 2021-03-24 22:50:35.604\n"
+      "\tQuerying PM event signal(s) UJ33.RB.A34:T_RES_BODY_1, UJ33.RB.A34:T_RES_BODY_3, UJ33.RB.A34:T_RES_BODY_2 for system: UJ33.RB.A34, className: DQAMSNRB, source: QPS at 2021-03-24 22:50:35.604\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 18/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 20/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -747,13 +784,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UA43.RB.A34:T_RES_BODY_1, UA43.RB.A34:T_RES_BODY_3, UA43.RB.A34:T_RES_BODY_2 for system: UA43.RB.A34, className: DQAMSNRB, source: QPS at 2021-03-24 22:43:06.546\n"
+      "\tQuerying PM event signal(s) UA43.RB.A34:T_RES_BODY_1, UA43.RB.A34:T_RES_BODY_2, UA43.RB.A34:T_RES_BODY_3 for system: UA43.RB.A34, className: DQAMSNRB, source: QPS at 2021-03-24 22:43:06.546\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 19/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 21/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -766,13 +803,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UA43.RB.A34:T_RES_BODY_1, UA43.RB.A34:T_RES_BODY_3, UA43.RB.A34:T_RES_BODY_2 for system: UA43.RB.A34, className: DQAMSNRB, source: QPS at 2021-03-24 22:50:50.804\n"
+      "\tQuerying PM event signal(s) UA43.RB.A34:T_RES_BODY_1, UA43.RB.A34:T_RES_BODY_2, UA43.RB.A34:T_RES_BODY_3 for system: UA43.RB.A34, className: DQAMSNRB, source: QPS at 2021-03-24 22:50:50.804\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_ee: 20/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_ee: 22/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -791,7 +828,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_ee: 21/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function find_source_timestamp_ee: 23/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -810,7 +847,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_u_dump_res_pm: 22/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_u_dump_res_pm: 24/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -829,7 +866,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_u_dump_res_pm: 23/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_u_dump_res_pm: 25/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -848,7 +885,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 24/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 26/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -861,13 +898,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UJ33.RB.A34:T_RES_BODY_1, UJ33.RB.A34:T_RES_BODY_2, UJ33.RB.A34:T_RES_BODY_3 for system: UJ33.RB.A34, className: DQAMSNRB, source: QPS at 2015-04-01 19:19:39.046\n"
+      "\tQuerying PM event signal(s) UJ33.RB.A34:T_RES_BODY_1, UJ33.RB.A34:T_RES_BODY_3, UJ33.RB.A34:T_RES_BODY_2 for system: UJ33.RB.A34, className: DQAMSNRB, source: QPS at 2015-04-01 19:19:39.046\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 25/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 27/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -880,13 +917,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UJ33.RB.A34:T_RES_BODY_1, UJ33.RB.A34:T_RES_BODY_2, UJ33.RB.A34:T_RES_BODY_3 for system: UJ33.RB.A34, className: DQAMSNRB, source: QPS at 2015-04-01 19:27:07.404\n"
+      "\tQuerying PM event signal(s) UJ33.RB.A34:T_RES_BODY_1, UJ33.RB.A34:T_RES_BODY_3, UJ33.RB.A34:T_RES_BODY_2 for system: UJ33.RB.A34, className: DQAMSNRB, source: QPS at 2015-04-01 19:27:07.404\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 26/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 28/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -899,13 +936,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UA43.RB.A34:T_RES_BODY_1, UA43.RB.A34:T_RES_BODY_3, UA43.RB.A34:T_RES_BODY_2 for system: UA43.RB.A34, className: DQAMSNRB, source: QPS at 2015-04-01 19:19:39.262\n"
+      "\tQuerying PM event signal(s) UA43.RB.A34:T_RES_BODY_1, UA43.RB.A34:T_RES_BODY_2, UA43.RB.A34:T_RES_BODY_3 for system: UA43.RB.A34, className: DQAMSNRB, source: QPS at 2015-04-01 19:19:39.262\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 27/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_ee_t_res_pm: 29/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -918,13 +955,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) UA43.RB.A34:T_RES_BODY_1, UA43.RB.A34:T_RES_BODY_3, UA43.RB.A34:T_RES_BODY_2 for system: UA43.RB.A34, className: DQAMSNRB, source: QPS at 2015-04-01 19:27:14.204\n"
+      "\tQuerying PM event signal(s) UA43.RB.A34:T_RES_BODY_1, UA43.RB.A34:T_RES_BODY_2, UA43.RB.A34:T_RES_BODY_3 for system: UA43.RB.A34, className: DQAMSNRB, source: QPS at 2015-04-01 19:27:14.204\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function find_timestamp_leads: 28/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function find_timestamp_leads: 30/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -943,7 +980,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_leads: 29/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_leads: 31/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -962,7 +999,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_leads: 30/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_leads: 32/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -975,13 +1012,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) DFLAS.7R3.RB.A34.LD3:U_RES, DFLAS.7R3.RB.A34.LD4:U_RES for system: RB.A34, className: DQAMGNDRBODD, source: QPS at 2021-03-24 22:43:06.012\n"
+      "\tQuerying PM event signal(s) DFLAS.7R3.RB.A34.LD4:U_RES, DFLAS.7R3.RB.A34.LD3:U_RES for system: RB.A34, className: DQAMGNDRBODD, source: QPS at 2021-03-24 22:43:06.012\n"
      ]
     },
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function find_timestamp_leads: 31/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function find_timestamp_leads: 33/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1000,7 +1037,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_leads: 32/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_leads: 34/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1019,7 +1056,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RB.A34 query function query_leads: 33/30.</text>"
+       "<text style=color:blue>Executing RB.A34 query function query_leads: 35/30.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1039,7 +1076,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Elapsed: 67.302 s.\n"
+      "Elapsed: 60.068 s.\n"
      ]
     }
    ],
@@ -1078,11 +1115,14 @@
     "    timestamp_pic = rb_query.find_timestamp_pic(timestamp_fgc, spark=spark, duration=[(t_end-timestamp_fgc, 'ns')])\n",
     "    timestamp_pic_ref = rb_query.find_timestamp_pic(timestamp_fgc_ref, spark=spark, duration=[(t_end_ref-timestamp_fgc_ref, 'ns')])\n",
     "    i_a_df, i_ref_df = rb_query.query_pc_pm(timestamp_fgc, timestamp_fgc, signal_names=['I_A', 'I_REF'])\n",
-    "    i_meas_df, i_earth_df, i_earth_pcnt_df, v_meas_df = rb_query.query_pc_pm(timestamp_fgc, min(timestamp_pic), signal_names=['I_MEAS', 'I_EARTH', 'I_EARTH_PCNT', 'V_MEAS'])\n",
+    "    # time scale is normalized to timestamp_pic\n",
+    "    i_meas_pic_df, i_earth_pic_df, i_earth_pcnt_pic_df, v_meas_pic_df = rb_query.query_pc_pm(timestamp_fgc, min(timestamp_pic), signal_names=['I_MEAS', 'I_EARTH', 'I_EARTH_PCNT', 'V_MEAS'])\n",
+    "    # time scale is normalized to timestamp_fgc\n",
+    "    i_meas_fgc_df, i_earth_fgc_df, i_earth_pcnt_fgc_df, v_meas_fgc_df = rb_query.query_pc_pm(timestamp_fgc, timestamp_fgc, signal_names=['I_MEAS', 'I_EARTH', 'I_EARTH_PCNT', 'V_MEAS'])\n",
     "    \n",
     "    # PC Reference\n",
     "    i_meas_nxcals_pic_sync_df = rb_query.query_signal_nxcals(t_start, t_end, t0=min(timestamp_pic), system='PC', signal_names='I_MEAS', spark=spark)[0]\n",
-    "    i_meas_nxcals_pic_sync_ref_df = rb_query.query_signal_nxcals(t_start_ref, t_end_ref, t0=min(timestamp_pic_ref), system='PC', signal_names='I_MEAS', spark=spark)[0] \n",
+    "    i_meas_nxcals_pic_sync_ref_df = rb_query.query_signal_nxcals(t_start_ref, t_end_ref, t0=min(timestamp_pic_ref), system='PC', signal_names='I_MEAS', spark=spark)[0]\n",
     "    if isinstance(t_start_ref, int):\n",
     "        source_timestamp_pc_ref = rb_query.find_source_timestamp_pc(t_start_ref, t_end_ref)\n",
     "        timestamp_fgc_ref = source_timestamp_pc_ref.at[0, 'timestamp']\n",
@@ -1090,8 +1130,10 @@
     "        timestamp_fgc_ref = float('nan')\n",
     "    \n",
     "    # PIC Reference\n",
-    "    #timestamp_pic_ref = rb_query.find_timestamp_pic(timestamp_fgc_ref, spark=spark, duration=[(t_end_ref-timestamp_fgc_ref, 'ns')])\n",
-    "    i_meas_ref_df = rb_query.query_pc_pm(timestamp_fgc_ref, min(timestamp_pic_ref), signal_names=['I_MEAS'])[0]\n",
+    "    # time scale is normalized to timestamp_pic_ref\n",
+    "    i_meas_ref_pic_df = rb_query.query_pc_pm(timestamp_fgc_ref, min(timestamp_pic_ref), signal_names=['I_MEAS'])[0]\n",
+    "    # time scale is normalized to timestamp_fgc_ref\n",
+    "    i_meas_ref_fgc_df = rb_query.query_pc_pm(timestamp_fgc_ref, timestamp_fgc_ref, signal_names=['I_MEAS'])[0]\n",
     "    \n",
     "    # EE Voltage\n",
     "    source_timestamp_ee_odd_df = rb_query.find_source_timestamp_ee(timestamp_fgc, system='EE_ODD')\n",
@@ -1154,14 +1196,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "51d8c1c1",
+   "id": "6a2aa99f",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.272445,
-     "end_time": "2021-11-09T09:09:57.994566",
+     "duration": 0.076461,
+     "end_time": "2022-02-11T13:57:15.678937",
      "exception": false,
-     "start_time": "2021-11-09T09:09:57.722121",
+     "start_time": "2022-02-11T13:57:15.602476",
      "status": "completed"
     },
     "tags": []
@@ -1173,20 +1215,20 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "438ef17e",
+   "id": "61b02ef0",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:09:58.563967Z",
-     "iopub.status.busy": "2021-11-09T09:09:58.563083Z",
-     "iopub.status.idle": "2021-11-09T09:09:58.579441Z",
-     "shell.execute_reply": "2021-11-09T09:09:58.580114Z"
+     "iopub.execute_input": "2022-02-11T13:57:15.848527Z",
+     "iopub.status.busy": "2022-02-11T13:57:15.847545Z",
+     "iopub.status.idle": "2022-02-11T13:57:15.861945Z",
+     "shell.execute_reply": "2022-02-11T13:57:15.861268Z"
     },
     "papermill": {
-     "duration": 0.309588,
-     "end_time": "2021-11-09T09:09:58.580365",
+     "duration": 0.106108,
+     "end_time": "2022-02-11T13:57:15.862103",
      "exception": false,
-     "start_time": "2021-11-09T09:09:58.270777",
+     "start_time": "2022-02-11T13:57:15.755995",
      "status": "completed"
     },
     "tags": []
@@ -1286,14 +1328,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aee55d4e",
+   "id": "35b40fd5",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.28941,
-     "end_time": "2021-11-09T09:09:59.153259",
+     "duration": 0.077979,
+     "end_time": "2022-02-11T13:57:16.017459",
      "exception": false,
-     "start_time": "2021-11-09T09:09:58.863849",
+     "start_time": "2022-02-11T13:57:15.939480",
      "status": "completed"
     },
     "tags": []
@@ -1310,20 +1352,20 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "b8d85175",
+   "id": "2f4bff0b",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:09:59.731429Z",
-     "iopub.status.busy": "2021-11-09T09:09:59.728516Z",
-     "iopub.status.idle": "2021-11-09T09:10:00.156888Z",
-     "shell.execute_reply": "2021-11-09T09:10:00.157563Z"
+     "iopub.execute_input": "2022-02-11T13:57:16.182567Z",
+     "iopub.status.busy": "2022-02-11T13:57:16.181853Z",
+     "iopub.status.idle": "2022-02-11T13:57:16.548293Z",
+     "shell.execute_reply": "2022-02-11T13:57:16.548857Z"
     },
     "papermill": {
-     "duration": 0.72109,
-     "end_time": "2021-11-09T09:10:00.157811",
+     "duration": 0.454135,
+     "end_time": "2022-02-11T13:57:16.549044",
      "exception": false,
-     "start_time": "2021-11-09T09:09:59.436721",
+     "start_time": "2022-02-11T13:57:16.094909",
      "status": "completed"
     },
     "tags": []
@@ -1353,13 +1395,13 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c836905c",
+   "id": "32c7ff4a",
    "metadata": {
     "papermill": {
-     "duration": 0.284587,
-     "end_time": "2021-11-09T09:10:00.717133",
+     "duration": 0.147744,
+     "end_time": "2022-02-11T13:57:16.776357",
      "exception": false,
-     "start_time": "2021-11-09T09:10:00.432546",
+     "start_time": "2022-02-11T13:57:16.628613",
      "status": "completed"
     },
     "tags": []
@@ -1373,19 +1415,19 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "a924a43f",
+   "id": "162eb55a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:01.421386Z",
-     "iopub.status.busy": "2021-11-09T09:10:01.420515Z",
-     "iopub.status.idle": "2021-11-09T09:10:01.836327Z",
-     "shell.execute_reply": "2021-11-09T09:10:01.836997Z"
+     "iopub.execute_input": "2022-02-11T13:57:16.955825Z",
+     "iopub.status.busy": "2022-02-11T13:57:16.950460Z",
+     "iopub.status.idle": "2022-02-11T13:57:17.357702Z",
+     "shell.execute_reply": "2022-02-11T13:57:17.358225Z"
     },
     "papermill": {
-     "duration": 0.808995,
-     "end_time": "2021-11-09T09:10:01.837286",
+     "duration": 0.502945,
+     "end_time": "2022-02-11T13:57:17.358427",
      "exception": false,
-     "start_time": "2021-11-09T09:10:01.028291",
+     "start_time": "2022-02-11T13:57:16.855482",
      "status": "completed"
     },
     "scrolled": false,
@@ -1418,14 +1460,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "178b0651",
+   "id": "8a398d98",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.288496,
-     "end_time": "2021-11-09T09:10:02.410145",
+     "duration": 0.081017,
+     "end_time": "2022-02-11T13:57:17.520693",
      "exception": false,
-     "start_time": "2021-11-09T09:10:02.121649",
+     "start_time": "2022-02-11T13:57:17.439676",
      "status": "completed"
     },
     "tags": []
@@ -1457,20 +1499,20 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "18ee5dd6",
+   "id": "c9e0fecd",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:02.991912Z",
-     "iopub.status.busy": "2021-11-09T09:10:02.991080Z",
-     "iopub.status.idle": "2021-11-09T09:10:03.863143Z",
-     "shell.execute_reply": "2021-11-09T09:10:03.862342Z"
+     "iopub.execute_input": "2022-02-11T13:57:17.690318Z",
+     "iopub.status.busy": "2022-02-11T13:57:17.689649Z",
+     "iopub.status.idle": "2022-02-11T13:57:18.503568Z",
+     "shell.execute_reply": "2022-02-11T13:57:18.504171Z"
     },
     "papermill": {
-     "duration": 1.168059,
-     "end_time": "2021-11-09T09:10:03.863346",
+     "duration": 0.901731,
+     "end_time": "2022-02-11T13:57:18.504398",
      "exception": false,
-     "start_time": "2021-11-09T09:10:02.695287",
+     "start_time": "2022-02-11T13:57:17.602667",
      "status": "completed"
     },
     "tags": []
@@ -1478,7 +1520,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 936x468 with 2 Axes>"
       ]
@@ -1509,19 +1551,19 @@
     }
    ],
    "source": [
-    "rb_analysis.analyze_i_meas_pc(circuit_name, timestamp_fgc, timestamp_fgc_ref, min(timestamp_pic), i_meas_df, i_meas_ref_df)"
+    "rb_analysis.analyze_i_meas_pc(circuit_name, timestamp_fgc, timestamp_fgc_ref, min(timestamp_pic), i_meas_fgc_df, i_meas_ref_fgc_df)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "d3021fbf",
+   "id": "04d2ea5f",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.268398,
-     "end_time": "2021-11-09T09:10:04.415505",
+     "duration": 0.086089,
+     "end_time": "2022-02-11T13:57:18.676755",
      "exception": false,
-     "start_time": "2021-11-09T09:10:04.147107",
+     "start_time": "2022-02-11T13:57:18.590666",
      "status": "completed"
     },
     "tags": []
@@ -1548,20 +1590,20 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "2f3271fd",
+   "id": "dc198cd1",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:04.957724Z",
-     "iopub.status.busy": "2021-11-09T09:10:04.956859Z",
-     "iopub.status.idle": "2021-11-09T09:10:05.556796Z",
-     "shell.execute_reply": "2021-11-09T09:10:05.557543Z"
+     "iopub.execute_input": "2022-02-11T13:57:18.854762Z",
+     "iopub.status.busy": "2022-02-11T13:57:18.854091Z",
+     "iopub.status.idle": "2022-02-11T13:57:19.388602Z",
+     "shell.execute_reply": "2022-02-11T13:57:19.389135Z"
     },
     "papermill": {
-     "duration": 0.890691,
-     "end_time": "2021-11-09T09:10:05.557851",
+     "duration": 0.626881,
+     "end_time": "2022-02-11T13:57:19.389321",
      "exception": false,
-     "start_time": "2021-11-09T09:10:04.667160",
+     "start_time": "2022-02-11T13:57:18.762440",
      "status": "completed"
     },
     "scrolled": true,
@@ -1583,19 +1625,19 @@
    ],
    "source": [
     "title = create_hwc_plot_title_with_circuit_name(circuit_name=circuit_name, hwc_test=hwc_test, t_start=t_start, t_end=t_end, signal='I_MEAS smoothness')\n",
-    "rb_analysis.plot_i_meas_smoothness(i_meas_df, title=title)"
+    "rb_analysis.plot_i_meas_smoothness(i_meas_pic_df, title=title)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "b3f63a32",
+   "id": "4f433e9a",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.307888,
-     "end_time": "2021-11-09T09:10:06.177796",
+     "duration": 0.085591,
+     "end_time": "2022-02-11T13:57:19.560596",
      "exception": false,
-     "start_time": "2021-11-09T09:10:05.869908",
+     "start_time": "2022-02-11T13:57:19.475005",
      "status": "completed"
     },
     "tags": []
@@ -1612,20 +1654,20 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "cdf6f4fe",
+   "id": "24a27297",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:06.856685Z",
-     "iopub.status.busy": "2021-11-09T09:10:06.855852Z",
-     "iopub.status.idle": "2021-11-09T09:10:07.200620Z",
-     "shell.execute_reply": "2021-11-09T09:10:07.199976Z"
+     "iopub.execute_input": "2022-02-11T13:57:19.740018Z",
+     "iopub.status.busy": "2022-02-11T13:57:19.739335Z",
+     "iopub.status.idle": "2022-02-11T13:57:20.098758Z",
+     "shell.execute_reply": "2022-02-11T13:57:20.098212Z"
     },
     "papermill": {
-     "duration": 0.72665,
-     "end_time": "2021-11-09T09:10:07.200835",
+     "duration": 0.452175,
+     "end_time": "2022-02-11T13:57:20.098910",
      "exception": false,
-     "start_time": "2021-11-09T09:10:06.474185",
+     "start_time": "2022-02-11T13:57:19.646735",
      "status": "completed"
     },
     "tags": []
@@ -1654,19 +1696,19 @@
    ],
    "source": [
     "title = create_hwc_plot_title_with_circuit_name(circuit_name=circuit_name, hwc_test=hwc_test, t_start=t_start, t_end=t_end, signal='V_MEAS')\n",
-    "rb_analysis.assert_v_meas(timestamp_ee_even, min(timestamp_pic), t_after_ee=1, v_meas_df=v_meas_df, value_min=-4.2, value_max=-3.2, title=title, xmax=15)"
+    "rb_analysis.assert_v_meas(timestamp_ee_even, min(timestamp_pic), t_after_ee=1, v_meas_df=v_meas_pic_df, value_min=-4.2, value_max=-3.2, title=title, xmax=15)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "173679a6",
+   "id": "fe0eecc6",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.302646,
-     "end_time": "2021-11-09T09:10:07.824265",
+     "duration": 0.087118,
+     "end_time": "2022-02-11T13:57:20.273715",
      "exception": false,
-     "start_time": "2021-11-09T09:10:07.521619",
+     "start_time": "2022-02-11T13:57:20.186597",
      "status": "completed"
     },
     "tags": []
@@ -1708,20 +1750,20 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "79f5bd17",
+   "id": "35099f54",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:08.443708Z",
-     "iopub.status.busy": "2021-11-09T09:10:08.442863Z",
-     "iopub.status.idle": "2021-11-09T09:10:09.270165Z",
-     "shell.execute_reply": "2021-11-09T09:10:09.269195Z"
+     "iopub.execute_input": "2022-02-11T13:57:20.467501Z",
+     "iopub.status.busy": "2022-02-11T13:57:20.466812Z",
+     "iopub.status.idle": "2022-02-11T13:57:21.084808Z",
+     "shell.execute_reply": "2022-02-11T13:57:21.084248Z"
     },
     "papermill": {
-     "duration": 1.147022,
-     "end_time": "2021-11-09T09:10:09.270402",
+     "duration": 0.723336,
+     "end_time": "2022-02-11T13:57:21.084961",
      "exception": false,
-     "start_time": "2021-11-09T09:10:08.123380",
+     "start_time": "2022-02-11T13:57:20.361625",
      "status": "completed"
     },
     "tags": []
@@ -1751,39 +1793,39 @@
      "data": {
       "text/html": [
        "<style  type=\"text/css\" >\n",
-       "</style><table id=\"T_0b14d_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
+       "</style><table id=\"T_bf787_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
-       "                        <th id=\"T_0b14d_level0_row0\" class=\"row_heading level0 row0\" >R_even</th>\n",
-       "                        <td id=\"T_0b14d_row0_col0\" class=\"data row0 col0\" >0.067500</td>\n",
-       "                        <td id=\"T_0b14d_row0_col1\" class=\"data row0 col1\" >0.082500</td>\n",
-       "                        <td id=\"T_0b14d_row0_col2\" class=\"data row0 col2\" >0.070096</td>\n",
-       "                        <td id=\"T_0b14d_row0_col3\" class=\"data row0 col3\" >True</td>\n",
+       "                        <th id=\"T_bf787_level0_row0\" class=\"row_heading level0 row0\" >R_even</th>\n",
+       "                        <td id=\"T_bf787_row0_col0\" class=\"data row0 col0\" >0.067500</td>\n",
+       "                        <td id=\"T_bf787_row0_col1\" class=\"data row0 col1\" >0.082500</td>\n",
+       "                        <td id=\"T_bf787_row0_col2\" class=\"data row0 col2\" >0.070096</td>\n",
+       "                        <td id=\"T_bf787_row0_col3\" class=\"data row0 col3\" >True</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_0b14d_level0_row1\" class=\"row_heading level0 row1\" >R_odd</th>\n",
-       "                        <td id=\"T_0b14d_row1_col0\" class=\"data row1 col0\" >0.067500</td>\n",
-       "                        <td id=\"T_0b14d_row1_col1\" class=\"data row1 col1\" >0.082500</td>\n",
-       "                        <td id=\"T_0b14d_row1_col2\" class=\"data row1 col2\" >0.071221</td>\n",
-       "                        <td id=\"T_0b14d_row1_col3\" class=\"data row1 col3\" >True</td>\n",
+       "                        <th id=\"T_bf787_level0_row1\" class=\"row_heading level0 row1\" >R_odd</th>\n",
+       "                        <td id=\"T_bf787_row1_col0\" class=\"data row1 col0\" >0.067500</td>\n",
+       "                        <td id=\"T_bf787_row1_col1\" class=\"data row1 col1\" >0.082500</td>\n",
+       "                        <td id=\"T_bf787_row1_col2\" class=\"data row1 col2\" >0.071221</td>\n",
+       "                        <td id=\"T_bf787_row1_col3\" class=\"data row1 col3\" >True</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_0b14d_level0_row2\" class=\"row_heading level0 row2\" >tau_u_dump_res_even</th>\n",
-       "                        <td id=\"T_0b14d_row2_col0\" class=\"data row2 col0\" >110.000000</td>\n",
-       "                        <td id=\"T_0b14d_row2_col1\" class=\"data row2 col1\" >130.000000</td>\n",
-       "                        <td id=\"T_0b14d_row2_col2\" class=\"data row2 col2\" >117.203386</td>\n",
-       "                        <td id=\"T_0b14d_row2_col3\" class=\"data row2 col3\" >True</td>\n",
+       "                        <th id=\"T_bf787_level0_row2\" class=\"row_heading level0 row2\" >tau_u_dump_res_even</th>\n",
+       "                        <td id=\"T_bf787_row2_col0\" class=\"data row2 col0\" >110.000000</td>\n",
+       "                        <td id=\"T_bf787_row2_col1\" class=\"data row2 col1\" >130.000000</td>\n",
+       "                        <td id=\"T_bf787_row2_col2\" class=\"data row2 col2\" >117.203386</td>\n",
+       "                        <td id=\"T_bf787_row2_col3\" class=\"data row2 col3\" >True</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_0b14d_level0_row3\" class=\"row_heading level0 row3\" >tau_u_dump_res_odd</th>\n",
-       "                        <td id=\"T_0b14d_row3_col0\" class=\"data row3 col0\" >110.000000</td>\n",
-       "                        <td id=\"T_0b14d_row3_col1\" class=\"data row3 col1\" >130.000000</td>\n",
-       "                        <td id=\"T_0b14d_row3_col2\" class=\"data row3 col2\" >116.907515</td>\n",
-       "                        <td id=\"T_0b14d_row3_col3\" class=\"data row3 col3\" >True</td>\n",
+       "                        <th id=\"T_bf787_level0_row3\" class=\"row_heading level0 row3\" >tau_u_dump_res_odd</th>\n",
+       "                        <td id=\"T_bf787_row3_col0\" class=\"data row3 col0\" >110.000000</td>\n",
+       "                        <td id=\"T_bf787_row3_col1\" class=\"data row3 col1\" >130.000000</td>\n",
+       "                        <td id=\"T_bf787_row3_col2\" class=\"data row3 col2\" >116.907515</td>\n",
+       "                        <td id=\"T_bf787_row3_col3\" class=\"data row3 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7fc042c59e80>"
+       "<pandas.io.formats.style.Styler at 0x7f03b80ed250>"
       ]
      },
      "metadata": {},
@@ -1791,26 +1833,26 @@
     }
    ],
    "source": [
-    "rb_analysis.analyze_char_time_u_dump_res_ee(circuit_name, timestamp_fgc, [u_dump_res_odd_df, u_dump_res_even_df], i_meas_df)"
+    "rb_analysis.analyze_char_time_u_dump_res_ee(circuit_name, timestamp_fgc, [u_dump_res_odd_df, u_dump_res_even_df], i_meas_pic_df)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "6d5c9492",
+   "id": "53d5d78c",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:09.899722Z",
-     "iopub.status.busy": "2021-11-09T09:10:09.898556Z",
-     "iopub.status.idle": "2021-11-09T09:10:10.539475Z",
-     "shell.execute_reply": "2021-11-09T09:10:10.538815Z"
+     "iopub.execute_input": "2022-02-11T13:57:21.276490Z",
+     "iopub.status.busy": "2022-02-11T13:57:21.275773Z",
+     "iopub.status.idle": "2022-02-11T13:57:21.843935Z",
+     "shell.execute_reply": "2022-02-11T13:57:21.843245Z"
     },
     "papermill": {
-     "duration": 0.956923,
-     "end_time": "2021-11-09T09:10:10.539693",
+     "duration": 0.667664,
+     "end_time": "2022-02-11T13:57:21.844094",
      "exception": false,
-     "start_time": "2021-11-09T09:10:09.582770",
+     "start_time": "2022-02-11T13:57:21.176430",
      "status": "completed"
     },
     "tags": []
@@ -1840,25 +1882,25 @@
      "data": {
       "text/html": [
        "<style  type=\"text/css\" >\n",
-       "</style><table id=\"T_0270a_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
+       "</style><table id=\"T_3f7be_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
-       "                        <th id=\"T_0270a_level0_row0\" class=\"row_heading level0 row0\" >t_delay_ee_even</th>\n",
-       "                        <td id=\"T_0270a_row0_col0\" class=\"data row0 col0\" >0.550000</td>\n",
-       "                        <td id=\"T_0270a_row0_col1\" class=\"data row0 col1\" >0.650000</td>\n",
-       "                        <td id=\"T_0270a_row0_col2\" class=\"data row0 col2\" >0.596000</td>\n",
-       "                        <td id=\"T_0270a_row0_col3\" class=\"data row0 col3\" >True</td>\n",
+       "                        <th id=\"T_3f7be_level0_row0\" class=\"row_heading level0 row0\" >t_delay_ee_even</th>\n",
+       "                        <td id=\"T_3f7be_row0_col0\" class=\"data row0 col0\" >0.550000</td>\n",
+       "                        <td id=\"T_3f7be_row0_col1\" class=\"data row0 col1\" >0.650000</td>\n",
+       "                        <td id=\"T_3f7be_row0_col2\" class=\"data row0 col2\" >0.596000</td>\n",
+       "                        <td id=\"T_3f7be_row0_col3\" class=\"data row0 col3\" >True</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_0270a_level0_row1\" class=\"row_heading level0 row1\" >t_delay_ee_odd</th>\n",
-       "                        <td id=\"T_0270a_row1_col0\" class=\"data row1 col0\" >0.050000</td>\n",
-       "                        <td id=\"T_0270a_row1_col1\" class=\"data row1 col1\" >0.150000</td>\n",
-       "                        <td id=\"T_0270a_row1_col2\" class=\"data row1 col2\" >0.096000</td>\n",
-       "                        <td id=\"T_0270a_row1_col3\" class=\"data row1 col3\" >True</td>\n",
+       "                        <th id=\"T_3f7be_level0_row1\" class=\"row_heading level0 row1\" >t_delay_ee_odd</th>\n",
+       "                        <td id=\"T_3f7be_row1_col0\" class=\"data row1 col0\" >0.050000</td>\n",
+       "                        <td id=\"T_3f7be_row1_col1\" class=\"data row1 col1\" >0.150000</td>\n",
+       "                        <td id=\"T_3f7be_row1_col2\" class=\"data row1 col2\" >0.096000</td>\n",
+       "                        <td id=\"T_3f7be_row1_col3\" class=\"data row1 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7fc042c63eb0>"
+       "<pandas.io.formats.style.Styler at 0x7f03b80a2a60>"
       ]
      },
      "metadata": {},
@@ -1873,20 +1915,20 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "63762450",
+   "id": "8fc75862",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:11.198966Z",
-     "iopub.status.busy": "2021-11-09T09:10:11.198117Z",
-     "iopub.status.idle": "2021-11-09T09:10:11.205288Z",
-     "shell.execute_reply": "2021-11-09T09:10:11.205891Z"
+     "iopub.execute_input": "2022-02-11T13:57:22.042796Z",
+     "iopub.status.busy": "2022-02-11T13:57:22.042120Z",
+     "iopub.status.idle": "2022-02-11T13:57:22.044770Z",
+     "shell.execute_reply": "2022-02-11T13:57:22.045262Z"
     },
     "papermill": {
-     "duration": 0.332524,
-     "end_time": "2021-11-09T09:10:11.206111",
+     "duration": 0.107376,
+     "end_time": "2022-02-11T13:57:22.045460",
      "exception": false,
-     "start_time": "2021-11-09T09:10:10.873587",
+     "start_time": "2022-02-11T13:57:21.938084",
      "status": "completed"
     },
     "tags": []
@@ -1908,14 +1950,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "23189b73",
+   "id": "68af5b14",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.311571,
-     "end_time": "2021-11-09T09:10:11.833819",
+     "duration": 0.094724,
+     "end_time": "2022-02-11T13:57:22.234193",
      "exception": false,
-     "start_time": "2021-11-09T09:10:11.522248",
+     "start_time": "2022-02-11T13:57:22.139469",
      "status": "completed"
     },
     "tags": []
@@ -1936,20 +1978,20 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "fdbc307a",
+   "id": "c4ca7543",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:12.482430Z",
-     "iopub.status.busy": "2021-11-09T09:10:12.481617Z",
-     "iopub.status.idle": "2021-11-09T09:10:13.211701Z",
-     "shell.execute_reply": "2021-11-09T09:10:13.210956Z"
+     "iopub.execute_input": "2022-02-11T13:57:22.458775Z",
+     "iopub.status.busy": "2022-02-11T13:57:22.443135Z",
+     "iopub.status.idle": "2022-02-11T13:57:23.082725Z",
+     "shell.execute_reply": "2022-02-11T13:57:23.083254Z"
     },
     "papermill": {
-     "duration": 1.058541,
-     "end_time": "2021-11-09T09:10:13.211928",
+     "duration": 0.754622,
+     "end_time": "2022-02-11T13:57:23.083453",
      "exception": false,
-     "start_time": "2021-11-09T09:10:12.153387",
+     "start_time": "2022-02-11T13:57:22.328831",
      "status": "completed"
     },
     "tags": []
@@ -1975,20 +2017,20 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "0efcd510",
+   "id": "b2babc6f",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:13.869231Z",
-     "iopub.status.busy": "2021-11-09T09:10:13.868345Z",
-     "iopub.status.idle": "2021-11-09T09:10:15.011853Z",
-     "shell.execute_reply": "2021-11-09T09:10:15.010759Z"
+     "iopub.execute_input": "2022-02-11T13:57:23.304099Z",
+     "iopub.status.busy": "2022-02-11T13:57:23.303411Z",
+     "iopub.status.idle": "2022-02-11T13:57:24.396864Z",
+     "shell.execute_reply": "2022-02-11T13:57:24.397401Z"
     },
     "papermill": {
-     "duration": 1.480614,
-     "end_time": "2021-11-09T09:10:15.012073",
+     "duration": 1.216979,
+     "end_time": "2022-02-11T13:57:24.397586",
      "exception": false,
-     "start_time": "2021-11-09T09:10:13.531459",
+     "start_time": "2022-02-11T13:57:23.180607",
      "status": "completed"
     },
     "scrolled": false,
@@ -2015,20 +2057,20 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "1e5e6bff",
+   "id": "e7f8a81a",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T09:10:15.709761Z",
-     "iopub.status.busy": "2021-11-09T09:10:15.708840Z",
-     "iopub.status.idle": "2021-11-09T09:10:16.451783Z",
-     "shell.execute_reply": "2021-11-09T09:10:16.452322Z"
+     "iopub.execute_input": "2022-02-11T13:57:24.630008Z",
+     "iopub.status.busy": "2022-02-11T13:57:24.626790Z",
+     "iopub.status.idle": "2022-02-11T13:57:25.252457Z",
+     "shell.execute_reply": "2022-02-11T13:57:25.252972Z"
     },
     "papermill": {
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@@ -2054,20 +2096,20 @@
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@@ -2092,14 +2134,14 @@
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@@ -2121,20 +2163,20 @@
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@@ -2169,20 +2211,20 @@
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@@ -2216,20 +2258,20 @@
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@@ -2256,20 +2298,20 @@
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@@ -2295,14 +2337,14 @@
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@@ -2314,19 +2356,19 @@
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@@ -2338,14 +2380,14 @@
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@@ -2358,14 +2400,14 @@
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@@ -2377,20 +2419,20 @@
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@@ -2450,7 +2492,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[NbConvertApp] Writing 1460298 bytes to ./results/reports/AN_RB_PLI3.d2.html\r\n"
+      "[NbConvertApp] Writing 1460622 bytes to ./results/reports/AN_RB_PLI3.d2.html\r\n"
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@@ -2474,13 +2516,13 @@
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@@ -2509,8 +2551,8 @@
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@@ -2527,8 +2569,8 @@
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+   "start_time": "2022-02-11T13:55:10.018015",
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diff --git a/test/resources/reports/AN_RB_PLI3.d2.html b/test/resources/reports/AN_RB_PLI3.d2.html
index bf51eeb6..e0af2ca7 100644
--- a/test/resources/reports/AN_RB_PLI3.d2.html
+++ b/test/resources/reports/AN_RB_PLI3.d2.html
@@ -13161,8 +13161,8 @@ The aim of this test is to verify the correct functionality of the PC when a pow
 
 
 <div class="output_subarea output_stream output_stdout output_text">
-<pre>Analysis executed with lhc-sm-api version: 1.5.18
-Analysis executed with lhc-sm-hwc notebooks version: 1.5.66
+<pre>Analysis executed with lhc-sm-api version: 1.5.19
+Analysis executed with lhc-sm-hwc notebooks version: 1.5.67
 Analysis performed by root
 </pre>
 </div>
@@ -13470,7 +13470,7 @@ The actual characteristic time contains steps, which indicate a quenching magnet
 
 
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
 "
 >
 </div>
@@ -13686,34 +13686,34 @@ The opening delay was 300±50 ms prior to YETS 2017/8</li>
 
 <div class="output_html rendered_html output_subarea ">
 <style  type="text/css" >
-</style><table id="T_c2a75_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
+</style><table id="T_bf787_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
                 <tr>
-                        <th id="T_c2a75_level0_row0" class="row_heading level0 row0" >R_even</th>
-                        <td id="T_c2a75_row0_col0" class="data row0 col0" >0.067500</td>
-                        <td id="T_c2a75_row0_col1" class="data row0 col1" >0.082500</td>
-                        <td id="T_c2a75_row0_col2" class="data row0 col2" >0.070096</td>
-                        <td id="T_c2a75_row0_col3" class="data row0 col3" >True</td>
+                        <th id="T_bf787_level0_row0" class="row_heading level0 row0" >R_even</th>
+                        <td id="T_bf787_row0_col0" class="data row0 col0" >0.067500</td>
+                        <td id="T_bf787_row0_col1" class="data row0 col1" >0.082500</td>
+                        <td id="T_bf787_row0_col2" class="data row0 col2" >0.070096</td>
+                        <td id="T_bf787_row0_col3" class="data row0 col3" >True</td>
             </tr>
             <tr>
-                        <th id="T_c2a75_level0_row1" class="row_heading level0 row1" >R_odd</th>
-                        <td id="T_c2a75_row1_col0" class="data row1 col0" >0.067500</td>
-                        <td id="T_c2a75_row1_col1" class="data row1 col1" >0.082500</td>
-                        <td id="T_c2a75_row1_col2" class="data row1 col2" >0.071221</td>
-                        <td id="T_c2a75_row1_col3" class="data row1 col3" >True</td>
+                        <th id="T_bf787_level0_row1" class="row_heading level0 row1" >R_odd</th>
+                        <td id="T_bf787_row1_col0" class="data row1 col0" >0.067500</td>
+                        <td id="T_bf787_row1_col1" class="data row1 col1" >0.082500</td>
+                        <td id="T_bf787_row1_col2" class="data row1 col2" >0.071221</td>
+                        <td id="T_bf787_row1_col3" class="data row1 col3" >True</td>
             </tr>
             <tr>
-                        <th id="T_c2a75_level0_row2" class="row_heading level0 row2" >tau_u_dump_res_even</th>
-                        <td id="T_c2a75_row2_col0" class="data row2 col0" >110.000000</td>
-                        <td id="T_c2a75_row2_col1" class="data row2 col1" >130.000000</td>
-                        <td id="T_c2a75_row2_col2" class="data row2 col2" >117.203386</td>
-                        <td id="T_c2a75_row2_col3" class="data row2 col3" >True</td>
+                        <th id="T_bf787_level0_row2" class="row_heading level0 row2" >tau_u_dump_res_even</th>
+                        <td id="T_bf787_row2_col0" class="data row2 col0" >110.000000</td>
+                        <td id="T_bf787_row2_col1" class="data row2 col1" >130.000000</td>
+                        <td id="T_bf787_row2_col2" class="data row2 col2" >117.203386</td>
+                        <td id="T_bf787_row2_col3" class="data row2 col3" >True</td>
             </tr>
             <tr>
-                        <th id="T_c2a75_level0_row3" class="row_heading level0 row3" >tau_u_dump_res_odd</th>
-                        <td id="T_c2a75_row3_col0" class="data row3 col0" >110.000000</td>
-                        <td id="T_c2a75_row3_col1" class="data row3 col1" >130.000000</td>
-                        <td id="T_c2a75_row3_col2" class="data row3 col2" >116.907515</td>
-                        <td id="T_c2a75_row3_col3" class="data row3 col3" >True</td>
+                        <th id="T_bf787_level0_row3" class="row_heading level0 row3" >tau_u_dump_res_odd</th>
+                        <td id="T_bf787_row3_col0" class="data row3 col0" >110.000000</td>
+                        <td id="T_bf787_row3_col1" class="data row3 col1" >130.000000</td>
+                        <td id="T_bf787_row3_col2" class="data row3 col2" >116.907515</td>
+                        <td id="T_bf787_row3_col3" class="data row3 col3" >True</td>
             </tr>
     </tbody></table>
 </div>
@@ -13765,20 +13765,20 @@ The opening delay was 300±50 ms prior to YETS 2017/8</li>
 
 <div class="output_html rendered_html output_subarea ">
 <style  type="text/css" >
-</style><table id="T_86ae7_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
+</style><table id="T_3f7be_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
                 <tr>
-                        <th id="T_86ae7_level0_row0" class="row_heading level0 row0" >t_delay_ee_even</th>
-                        <td id="T_86ae7_row0_col0" class="data row0 col0" >0.550000</td>
-                        <td id="T_86ae7_row0_col1" class="data row0 col1" >0.650000</td>
-                        <td id="T_86ae7_row0_col2" class="data row0 col2" >0.596000</td>
-                        <td id="T_86ae7_row0_col3" class="data row0 col3" >True</td>
+                        <th id="T_3f7be_level0_row0" class="row_heading level0 row0" >t_delay_ee_even</th>
+                        <td id="T_3f7be_row0_col0" class="data row0 col0" >0.550000</td>
+                        <td id="T_3f7be_row0_col1" class="data row0 col1" >0.650000</td>
+                        <td id="T_3f7be_row0_col2" class="data row0 col2" >0.596000</td>
+                        <td id="T_3f7be_row0_col3" class="data row0 col3" >True</td>
             </tr>
             <tr>
-                        <th id="T_86ae7_level0_row1" class="row_heading level0 row1" >t_delay_ee_odd</th>
-                        <td id="T_86ae7_row1_col0" class="data row1 col0" >0.050000</td>
-                        <td id="T_86ae7_row1_col1" class="data row1 col1" >0.150000</td>
-                        <td id="T_86ae7_row1_col2" class="data row1 col2" >0.096000</td>
-                        <td id="T_86ae7_row1_col3" class="data row1 col3" >True</td>
+                        <th id="T_3f7be_level0_row1" class="row_heading level0 row1" >t_delay_ee_odd</th>
+                        <td id="T_3f7be_row1_col0" class="data row1 col0" >0.050000</td>
+                        <td id="T_3f7be_row1_col1" class="data row1 col1" >0.150000</td>
+                        <td id="T_3f7be_row1_col2" class="data row1 col2" >0.096000</td>
+                        <td id="T_3f7be_row1_col3" class="data row1 col3" >True</td>
             </tr>
     </tbody></table>
 </div>
-- 
GitLab


From c186a3d1d96fcb0ed2b50326eb417d8eb4699a1f Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Mon, 14 Feb 2022 09:17:47 +0100
Subject: [PATCH 14/44] [SIGMON-257] tests uncommented

---
 test/test_notebooks.py | 150 ++++++++++++++++++++---------------------
 1 file changed, 75 insertions(+), 75 deletions(-)

diff --git a/test/test_notebooks.py b/test/test_notebooks.py
index 4f3090f8..c4508ac7 100644
--- a/test/test_notebooks.py
+++ b/test/test_notebooks.py
@@ -63,30 +63,30 @@ PGC_NOTEBOOKS = [
 ]
 
 RB_NOTEBOOKS = [
-    # ('rb', 'AN_RB_PIC2', 'PIC2 FAST ABORT REQ VIA PIC', 'RB.A12', 'Before LS2', '2018-12-06 17:03:17.072000000',
-    #  '2018-12-06 17:21:45.530000000', []),
-    # ('rb', 'AN_RB_PLI1.a2', 'PLI1.a2', 'RB.A12', 'HWC_2017', '2017-04-21 15:42:31.569', '2017-04-21 16:01:35.843', []),
-    # ('rb', 'AN_RB_PLI1.b2', 'PLI1.b2', 'RB.A12', 'HWC_2018_1', '2018-03-16 18:55:57.270', '2018-03-16 19:07:00.286',
-    #  []),
-    # ('rb', 'AN_RB_PLI1.d2', 'PLI1.d2', 'RB.A12', 'HWC_2018_1', '2017-04-21 17:10:50.001', '2017-04-21 17:24:09.828',
-    #  []),
-    # ('rb', 'AN_RB_PLI2.b2', 'PLI2.b2', 'RB.A12', 'HWC_2018_1', '2018-03-16 21:22:00.406', '2018-03-16 21:36:11.440',
-    #  []),
-    # ('rb', 'AN_RB_PLI2.f1', 'PLI2.f1', 'RB.A23', 'Recommissioning post LS2', '2021-05-04 16:21:48.535000000',
-    #  '2021-05-04 16:38:52.126000000', ['AN_RB_PLI2.f1.csv']),
-    # ('rb', 'AN_RB_PLI2.s1', 'PLI2.s1', 'RB.A12', 'HWC_2014', '2014-12-11 16:49:47.759', '2014-12-11 19:02:01.401',
-    #  ['AN_RB_PLI2.s1_BUSBAR_RESISTANCE.csv']),
-    # ('rb', 'AN_RB_PLI3.a5', 'PLI3.a5', 'RB.A12', 'HWC_2017', '2017-04-22 08:57:30.399', '2017-04-22 11:32:09.824',
-    #  ['AN_RB_PLI3.a5_BUSBAR_RESISTANCE.csv', 'AN_RB_PLI3.a5_MAGNET_RESISTANCE.csv']),
+    ('rb', 'AN_RB_PIC2', 'PIC2 FAST ABORT REQ VIA PIC', 'RB.A12', 'Before LS2', '2018-12-06 17:03:17.072000000',
+     '2018-12-06 17:21:45.530000000', []),
+    ('rb', 'AN_RB_PLI1.a2', 'PLI1.a2', 'RB.A12', 'HWC_2017', '2017-04-21 15:42:31.569', '2017-04-21 16:01:35.843', []),
+    ('rb', 'AN_RB_PLI1.b2', 'PLI1.b2', 'RB.A12', 'HWC_2018_1', '2018-03-16 18:55:57.270', '2018-03-16 19:07:00.286',
+     []),
+    ('rb', 'AN_RB_PLI1.d2', 'PLI1.d2', 'RB.A12', 'HWC_2018_1', '2017-04-21 17:10:50.001', '2017-04-21 17:24:09.828',
+     []),
+    ('rb', 'AN_RB_PLI2.b2', 'PLI2.b2', 'RB.A12', 'HWC_2018_1', '2018-03-16 21:22:00.406', '2018-03-16 21:36:11.440',
+     []),
+    ('rb', 'AN_RB_PLI2.f1', 'PLI2.f1', 'RB.A23', 'Recommissioning post LS2', '2021-05-04 16:21:48.535000000',
+     '2021-05-04 16:38:52.126000000', ['AN_RB_PLI2.f1.csv']),
+    ('rb', 'AN_RB_PLI2.s1', 'PLI2.s1', 'RB.A12', 'HWC_2014', '2014-12-11 16:49:47.759', '2014-12-11 19:02:01.401',
+     ['AN_RB_PLI2.s1_BUSBAR_RESISTANCE.csv']),
+    ('rb', 'AN_RB_PLI3.a5', 'PLI3.a5', 'RB.A12', 'HWC_2017', '2017-04-22 08:57:30.399', '2017-04-22 11:32:09.824',
+     ['AN_RB_PLI3.a5_BUSBAR_RESISTANCE.csv', 'AN_RB_PLI3.a5_MAGNET_RESISTANCE.csv']),
     ('rb', 'AN_RB_PLI3.d2', 'PLI3.d2', 'RB.A34', 'Recommissioning post LS2', '2021-03-24 22:19:06.563000000',
      '2021-03-24 22:44:23.159000000', []),
-    # ('rb', 'AN_RB_PLIM.b2', 'PLIM.b2', 'RB.A12', 'HWC_2018_1', '2017-04-22 04:34:15.401', '2017-04-22 04:56:43.323',
-    #  []),
-    # ('rb', 'AN_RB_PLIS.s2', 'PLIS.s2', 'RB.A12', 'HWC_2014', '2014-12-12 19:04:12.478', '2014-12-12 22:03:18.179',
-    #  ['AN_RB_PLIS.s2_BUSBAR_RESISTANCE.csv']),
-    # ('rb', 'AN_RB_PNO.a6', 'PNO.a6', 'RB.A12', 'HWC_2014', '2014-12-12 19:04:12.478', '2014-12-12 22:03:18.179',
-    #  ['AN_RB_PNO.a6_BUSBAR_RESISTANCE.csv', 'AN_RB_PNO.a6_MAGNET_RESISTANCE.csv']),
-    # ('rb', 'AN_RB_PNO.b2', 'PNO.b2', 'RB.A12', 'HWC_2018_1', '2018-03-17 11:34:53.954', '2018-03-17 16:06:41.537', []),
+    ('rb', 'AN_RB_PLIM.b2', 'PLIM.b2', 'RB.A12', 'HWC_2018_1', '2017-04-22 04:34:15.401', '2017-04-22 04:56:43.323',
+     []),
+    ('rb', 'AN_RB_PLIS.s2', 'PLIS.s2', 'RB.A12', 'HWC_2014', '2014-12-12 19:04:12.478', '2014-12-12 22:03:18.179',
+     ['AN_RB_PLIS.s2_BUSBAR_RESISTANCE.csv']),
+    ('rb', 'AN_RB_PNO.a6', 'PNO.a6', 'RB.A12', 'HWC_2014', '2014-12-12 19:04:12.478', '2014-12-12 22:03:18.179',
+     ['AN_RB_PNO.a6_BUSBAR_RESISTANCE.csv', 'AN_RB_PNO.a6_MAGNET_RESISTANCE.csv']),
+    ('rb', 'AN_RB_PNO.b2', 'PNO.b2', 'RB.A12', 'HWC_2018_1', '2018-03-17 11:34:53.954', '2018-03-17 16:06:41.537', []),
 ]
 
 RQ_NOTEBOOKS = [
@@ -166,7 +166,7 @@ def setup():
     os.environ[lhcsmapi.nb_version_env] = version
 
 
-@pytest.mark.parametrize('directory,notebook,hwc_test,circuit_name,campaign,t_start,t_end,csv_files', RB_NOTEBOOKS)
+@pytest.mark.parametrize('directory,notebook,hwc_test,circuit_name,campaign,t_start,t_end,csv_files', HWC_NOTEBOOKS)
 def test_hwc_notebook(directory, notebook, hwc_test, circuit_name, campaign, t_start, t_end, csv_files):
     _test_notebook(directory,
                    notebook,
@@ -181,58 +181,58 @@ def test_hwc_notebook(directory, notebook, hwc_test, circuit_name, campaign, t_s
                    csv_files)
 
 
-# @pytest.mark.parametrize('directory,notebook,circuit_name,timestamp_fgc,csv_files', FGC_SEARCH_NOTEBOOKS)
-# def test_fgc_search_notebook(directory, notebook, circuit_name, timestamp_fgc, csv_files):
-#     _test_notebook(directory,
-#                    notebook,
-#                    {
-#                        'circuit_name': circuit_name,
-#                        'timestamp_fgc': timestamp_fgc,
-#                        'author': 'test',
-#                        'is_automatic': True
-#                    },
-#                    csv_files)
-#
-#
-# @pytest.mark.parametrize('directory,notebook,circuit_type,circuit_names,timestamps_fgc,csv_files',
-#                          FGC_2_SEARCH_NOTEBOOKS)
-# def test_fgc_2_search_notebook(directory, notebook, circuit_type, circuit_names, timestamps_fgc, csv_files):
-#     _test_notebook(directory,
-#                    notebook,
-#                    {
-#                        'circuit_type': circuit_type,
-#                        'circuit_names': circuit_names,
-#                        'timestamps_fgc': timestamps_fgc,
-#                        'author': 'test',
-#                        'is_automatic': True
-#                    },
-#                    csv_files)
-#
-#
-# @pytest.mark.parametrize('directory,notebook,circuit_name,discharge_level,start_time,end_time,csv_files', QH_NOTEBOOKS)
-# def test_qh_search_notebook(directory, notebook, circuit_name, discharge_level, start_time, end_time, csv_files):
-#     _test_notebook(directory,
-#                    notebook,
-#                    {
-#                        'circuit_name': circuit_name,
-#                        'discharge_level': discharge_level,
-#                        'start_time': start_time,
-#                        'end_time': end_time,
-#                        'is_automatic': True
-#                    },
-#                    csv_files)
-#
-#
-# @pytest.mark.parametrize('directory,notebook,start_time,stop_time,csv_files', QHD_PM_LIST)
-# def test_qh_list_notebook(directory, notebook, start_time, stop_time, csv_files):
-#     _test_notebook(directory,
-#                    notebook,
-#                    {
-#                        'start_time': start_time,
-#                        'stop_time': stop_time,
-#                        'initial_charge_check': True
-#                    },
-#                    csv_files)
+@pytest.mark.parametrize('directory,notebook,circuit_name,timestamp_fgc,csv_files', FGC_SEARCH_NOTEBOOKS)
+def test_fgc_search_notebook(directory, notebook, circuit_name, timestamp_fgc, csv_files):
+    _test_notebook(directory,
+                   notebook,
+                   {
+                       'circuit_name': circuit_name,
+                       'timestamp_fgc': timestamp_fgc,
+                       'author': 'test',
+                       'is_automatic': True
+                   },
+                   csv_files)
+
+
+@pytest.mark.parametrize('directory,notebook,circuit_type,circuit_names,timestamps_fgc,csv_files',
+                         FGC_2_SEARCH_NOTEBOOKS)
+def test_fgc_2_search_notebook(directory, notebook, circuit_type, circuit_names, timestamps_fgc, csv_files):
+    _test_notebook(directory,
+                   notebook,
+                   {
+                       'circuit_type': circuit_type,
+                       'circuit_names': circuit_names,
+                       'timestamps_fgc': timestamps_fgc,
+                       'author': 'test',
+                       'is_automatic': True
+                   },
+                   csv_files)
+
+
+@pytest.mark.parametrize('directory,notebook,circuit_name,discharge_level,start_time,end_time,csv_files', QH_NOTEBOOKS)
+def test_qh_search_notebook(directory, notebook, circuit_name, discharge_level, start_time, end_time, csv_files):
+    _test_notebook(directory,
+                   notebook,
+                   {
+                       'circuit_name': circuit_name,
+                       'discharge_level': discharge_level,
+                       'start_time': start_time,
+                       'end_time': end_time,
+                       'is_automatic': True
+                   },
+                   csv_files)
+
+
+@pytest.mark.parametrize('directory,notebook,start_time,stop_time,csv_files', QHD_PM_LIST)
+def test_qh_list_notebook(directory, notebook, start_time, stop_time, csv_files):
+    _test_notebook(directory,
+                   notebook,
+                   {
+                       'start_time': start_time,
+                       'stop_time': stop_time,
+                       'initial_charge_check': True
+                   },
+                   csv_files)
 
 
 def _test_notebook(directory, notebook_name, notebook_parameters, csv_files):
-- 
GitLab


From ff6cfb00055138961c702739d4fddc45e70074c5 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:16:10 +0100
Subject: [PATCH 15/44] Replace AN_PGC1.ipynb

---
 pgc/AN_PGC1.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pgc/AN_PGC1.ipynb b/pgc/AN_PGC1.ipynb
index a9df8667..adef3136 100644
--- a/pgc/AN_PGC1.ipynb
+++ b/pgc/AN_PGC1.ipynb
@@ -157,7 +157,7 @@
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
     "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'].str.find(safety_subsector, 0) != -1]"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -307,7 +307,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "condemned_circuits = list(pd.read_csv('../condemnded_circuits.csv')['Condemned Circuits'])\n",
+    "condemned_circuits = list(pd.read_csv('./condemnded_circuits.csv')['Condemned Circuits'])\n",
     "display(condemned_circuits)"
    ]
   },
-- 
GitLab


From e2a1c2751785be61b7b48f93046528444587bcc2 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:22:09 +0100
Subject: [PATCH 16/44] Delete condemnded_circuits.csv

---
 condemnded_circuits.csv | 14 --------------
 1 file changed, 14 deletions(-)
 delete mode 100644 condemnded_circuits.csv

diff --git a/condemnded_circuits.csv b/condemnded_circuits.csv
deleted file mode 100644
index 5068ee0a..00000000
--- a/condemnded_circuits.csv
+++ /dev/null
@@ -1,14 +0,0 @@
-Condemned Circuits
-RCO.A78B1
-RCO.A78B2
-RCO.A12B1
-RCO.A45B1
-RSS.A34B1
-RCBXH1.L2
-RCOSX3.L2
-RCOX3.L2
-RCSSX3.L2
-RCOSX3.L1
-RCBH31.R7B1
-RCBV26.R5B1
-RCBH11.R1B1
-- 
GitLab


From 6f7a5dec5b2102c905d98669e3351b31ece9839c Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:33:01 +0100
Subject: [PATCH 17/44] Upload New File

---
 pgc/condemnded_circuits.csv | 14 ++++++++++++++
 1 file changed, 14 insertions(+)
 create mode 100644 pgc/condemnded_circuits.csv

diff --git a/pgc/condemnded_circuits.csv b/pgc/condemnded_circuits.csv
new file mode 100644
index 00000000..5068ee0a
--- /dev/null
+++ b/pgc/condemnded_circuits.csv
@@ -0,0 +1,14 @@
+Condemned Circuits
+RCO.A78B1
+RCO.A78B2
+RCO.A12B1
+RCO.A45B1
+RSS.A34B1
+RCBXH1.L2
+RCOSX3.L2
+RCOX3.L2
+RCSSX3.L2
+RCOSX3.L1
+RCBH31.R7B1
+RCBV26.R5B1
+RCBH11.R1B1
-- 
GitLab


From 27e07c985fc3e494855b12d2fc9209891073eaee Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:33:34 +0100
Subject: [PATCH 18/44] Replace AN_PGC1.ipynb

-- 
GitLab


From 9ecb9ab47efeb58f722f54355aebcac58ebe58f2 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:35:02 +0100
Subject: [PATCH 19/44] Replace AN_PGC2.ipynb

---
 pgc/AN_PGC2.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pgc/AN_PGC2.ipynb b/pgc/AN_PGC2.ipynb
index bba55805..e319c75b 100644
--- a/pgc/AN_PGC2.ipynb
+++ b/pgc/AN_PGC2.ipynb
@@ -179,7 +179,7 @@
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
     "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'].str.find(safety_subsector, 0) != -1]"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -330,7 +330,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "condemned_circuits = list(pd.read_csv('../condemnded_circuits.csv')['Condemned Circuits'])\n",
+    "condemned_circuits = list(pd.read_csv('./condemnded_circuits.csv')['Condemned Circuits'])\n",
     "display(condemned_circuits)"
    ]
   },
-- 
GitLab


From 78f7d4114dd0396bbff8074e36dca003b89b7923 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:35:53 +0100
Subject: [PATCH 20/44] Replace AN_PGC2.ipynb

-- 
GitLab


From 4821c3e50b696aaa862bf0182ab828155b3c7e82 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:36:47 +0100
Subject: [PATCH 21/44] Replace AN_PGC3.ipynb

---
 pgc/AN_PGC3.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pgc/AN_PGC3.ipynb b/pgc/AN_PGC3.ipynb
index 926043aa..84ad300f 100644
--- a/pgc/AN_PGC3.ipynb
+++ b/pgc/AN_PGC3.ipynb
@@ -178,7 +178,7 @@
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
     "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'].str.find(safety_subsector, 0) != -1]"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -330,7 +330,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "condemned_circuits = list(pd.read_csv('../condemnded_circuits.csv')['Condemned Circuits'])\n",
+    "condemned_circuits = list(pd.read_csv('./condemnded_circuits.csv')['Condemned Circuits'])\n",
     "display(condemned_circuits)"
    ]
   },
-- 
GitLab


From eb5e446f4bac2d2eaf21f469603d064e4cc8087e Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:37:26 +0100
Subject: [PATCH 22/44] Replace AN_PGC3.ipynb

-- 
GitLab


From 76e9519e37a0290cafb880ee2a9f30c862414169 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:38:59 +0100
Subject: [PATCH 23/44] Replace AN_PGC4.ipynb

---
 pgc/AN_PGC4.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pgc/AN_PGC4.ipynb b/pgc/AN_PGC4.ipynb
index c5e6c1fc..e30e2538 100644
--- a/pgc/AN_PGC4.ipynb
+++ b/pgc/AN_PGC4.ipynb
@@ -177,7 +177,7 @@
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
     "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'].str.find(safety_subsector, 0) != -1]"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -329,7 +329,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "condemned_circuits = list(pd.read_csv('../condemnded_circuits.csv')['Condemned Circuits'])\n",
+    "condemned_circuits = list(pd.read_csv('./condemnded_circuits.csv')['Condemned Circuits'])\n",
     "display(condemned_circuits)"
    ]
   },
-- 
GitLab


From afe0944c97ef84b089225f8d3cc252f7f4b9ce70 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Mon, 14 Feb 2022 17:40:17 +0100
Subject: [PATCH 24/44] Replace AN_PGC4.ipynb

-- 
GitLab


From 56f9b87ab9521a43bf606710aa3190c002c60b3e Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Thu, 17 Feb 2022 12:42:48 +0100
Subject: [PATCH 25/44] [SIGMON-309] ad-hoc fix

---
 600A/AN_600A_FPA.ipynb | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/600A/AN_600A_FPA.ipynb b/600A/AN_600A_FPA.ipynb
index 6a247fa8..bb7643f4 100644
--- a/600A/AN_600A_FPA.ipynb
+++ b/600A/AN_600A_FPA.ipynb
@@ -186,7 +186,7 @@
     "    timestamp_pic = query.find_timestamp_pic(timestamp_fgc, spark=spark)\n",
     "\n",
     "    # EE\n",
-    "    if 'EE' in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name):\n",
+    "    if 'EE' in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name, timestamp_query=timestamp_fgc):\n",
     "        query.max_executions += 2\n",
     "        source_timestamp_ee_df = query.find_source_timestamp_ee(timestamp_fgc)\n",
     "        timestamp_ee = lhcsmnb.utils.get_at(source_timestamp_ee_df, 0, 'timestamp')\n",
@@ -204,7 +204,7 @@
     "    i_dcct_df, i_didt_df, u_res_df, u_diff_df = query.query_qds_pm(timestamp_qds, timestamp_qds, signal_names=['I_DCCT', 'I_DIDT', 'U_RES', 'U_DIFF'])\n",
     "\n",
     "    # LEADS\n",
-    "    leads_name = [x for x in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name) if 'LEADS' in x][0]\n",
+    "    leads_name = [x for x in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name, timestamp_query=timestamp_fgc) if 'LEADS' in x][0]\n",
     "    source_timestamp_leads_df = query.find_timestamp_leads(timestamp_fgc, leads_name)\n",
     "\n",
     "    u_hts_leads_dfs = query.query_leads(timestamp_fgc, source_timestamp_leads_df, system=leads_name, signal_names=['U_HTS'], spark=spark, duration=[(300, 's'), (900, 's')])\n",
@@ -215,7 +215,7 @@
     "    timestamp_dct = {'FGC': timestamp_fgc, 'PIC': timestamp_pic, \n",
     "                     'QDS_A': lhcsmnb.utils.get_at(source_timestamp_qds_df, 0, 'timestamp', default=np.nan),\n",
     "                     'QDS_B': lhcsmnb.utils.get_at(source_timestamp_qds_df, 1, 'timestamp', default=np.nan)}\n",
-    "    if 'EE' in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name):\n",
+    "    if 'EE' in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name, timestamp_query=timestamp_fgc):\n",
     "        timestamp_dct['EE'] = lhcsmnb.utils.get_at(source_timestamp_ee_df, 0, 'timestamp', default=np.nan)"
    ]
   },
@@ -368,7 +368,7 @@
    },
    "outputs": [],
    "source": [
-    "if 'EE' in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name):\n",
+    "if 'EE' in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name, timestamp_query=timestamp_fgc):\n",
     "    analysis.analyze_u_dump_res_ee(circuit_name, timestamp_fgc, i_meas_df, u_dump_res_df, col_name='U_EE_max')\n",
     "else:\n",
     "    print('Circuit %s does not contain an EE system, analysis skipped.' % circuit_name)"
@@ -382,7 +382,7 @@
    },
    "outputs": [],
    "source": [
-    "if 'EE' in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name):\n",
+    "if 'EE' in SignalMetadata.get_system_types_per_circuit_name(circuit_type, circuit_name, timestamp_query=timestamp_fgc):\n",
     "    analysis.results_table['EE analysis'] = get_expert_decision('EE analysis: ', ['PASS', 'FAIL']) \n",
     "else:\n",
     "    analysis.results_table['EE analysis'] = 'No EE'"
@@ -657,4 +657,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
\ No newline at end of file
+}
-- 
GitLab


From 5d460b3cadfdc65c78e08355e2dbfd7df6e6c0f9 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Sun, 20 Feb 2022 12:54:04 +0100
Subject: [PATCH 26/44] Delete condemnded_circuits.csv

---
 pgc/condemnded_circuits.csv | 14 --------------
 1 file changed, 14 deletions(-)
 delete mode 100644 pgc/condemnded_circuits.csv

diff --git a/pgc/condemnded_circuits.csv b/pgc/condemnded_circuits.csv
deleted file mode 100644
index 5068ee0a..00000000
--- a/pgc/condemnded_circuits.csv
+++ /dev/null
@@ -1,14 +0,0 @@
-Condemned Circuits
-RCO.A78B1
-RCO.A78B2
-RCO.A12B1
-RCO.A45B1
-RSS.A34B1
-RCBXH1.L2
-RCOSX3.L2
-RCOX3.L2
-RCSSX3.L2
-RCOSX3.L1
-RCBH31.R7B1
-RCBV26.R5B1
-RCBH11.R1B1
-- 
GitLab


From 35421f6ee573505b4e7bf5373de6c445c719c89f Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Sun, 20 Feb 2022 12:54:45 +0100
Subject: [PATCH 27/44] Replace AN_PGC1.ipynb

---
 pgc/AN_PGC1.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pgc/AN_PGC1.ipynb b/pgc/AN_PGC1.ipynb
index adef3136..8a8d9c69 100644
--- a/pgc/AN_PGC1.ipynb
+++ b/pgc/AN_PGC1.ipynb
@@ -307,7 +307,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "condemned_circuits = list(pd.read_csv('./condemnded_circuits.csv')['Condemned Circuits'])\n",
+    "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
     "display(condemned_circuits)"
    ]
   },
-- 
GitLab


From 0a0e529e20e60c74babf56be2d3d14b77a7e4898 Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Sun, 20 Feb 2022 12:55:09 +0100
Subject: [PATCH 28/44] Replace AN_PGC2.ipynb

---
 pgc/AN_PGC2.ipynb | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/pgc/AN_PGC2.ipynb b/pgc/AN_PGC2.ipynb
index e319c75b..5eaac59a 100644
--- a/pgc/AN_PGC2.ipynb
+++ b/pgc/AN_PGC2.ipynb
@@ -179,7 +179,8 @@
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
     "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]\n",
+    "lhc_circ = meta_df[meta_df[['Circuit name'] == circuit_name]\n"
    ]
   },
   {
@@ -330,7 +331,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "condemned_circuits = list(pd.read_csv('./condemnded_circuits.csv')['Condemned Circuits'])\n",
+    "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
     "display(condemned_circuits)"
    ]
   },
-- 
GitLab


From b2813922020c509976ff774f061d7b202b8df1fa Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Sun, 20 Feb 2022 12:56:05 +0100
Subject: [PATCH 29/44] Replace AN_PGC3.ipynb

---
 pgc/AN_PGC3.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pgc/AN_PGC3.ipynb b/pgc/AN_PGC3.ipynb
index 84ad300f..e2f8ccce 100644
--- a/pgc/AN_PGC3.ipynb
+++ b/pgc/AN_PGC3.ipynb
@@ -330,7 +330,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "condemned_circuits = list(pd.read_csv('./condemnded_circuits.csv')['Condemned Circuits'])\n",
+    "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
     "display(condemned_circuits)"
    ]
   },
-- 
GitLab


From 0edc136ff93c3e7337a4370ac76a7cc21caf8a0c Mon Sep 17 00:00:00 2001
From: Per Hagen <per.hagen@cern.ch>
Date: Sun, 20 Feb 2022 12:56:49 +0100
Subject: [PATCH 30/44] Replace AN_PGC4.ipynb

---
 pgc/AN_PGC4.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pgc/AN_PGC4.ipynb b/pgc/AN_PGC4.ipynb
index e30e2538..f0a6dddb 100644
--- a/pgc/AN_PGC4.ipynb
+++ b/pgc/AN_PGC4.ipynb
@@ -329,7 +329,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "condemned_circuits = list(pd.read_csv('./condemnded_circuits.csv')['Condemned Circuits'])\n",
+    "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
     "display(condemned_circuits)"
    ]
   },
-- 
GitLab


From 604e08a85bd6d5db54962c729c94bebb87a5b2c0 Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Mon, 21 Feb 2022 10:03:51 +0100
Subject: [PATCH 31/44] [SIGMON-315] AN_RQ_PNO.b3

---
 rq/AN_RQ_PNO.b3.ipynb | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/rq/AN_RQ_PNO.b3.ipynb b/rq/AN_RQ_PNO.b3.ipynb
index 7063fea5..a18bb745 100644
--- a/rq/AN_RQ_PNO.b3.ipynb
+++ b/rq/AN_RQ_PNO.b3.ipynb
@@ -204,7 +204,7 @@
     "    # PC\n",
     "    i_meas_nxcals_dfs =  RqCircuitQuery(circuit_type, circuit_names).query_signal_nxcals(t_start, t_end, t0=t_start, system='PC', signal_names='I_MEAS', spark=spark)\n",
     "    i_meas_raw_nxcals_dfs =  RqCircuitQuery(circuit_type, circuit_names).query_raw_signal_nxcals(t_start, t_end, system='PC', signal_names='I_MEAS', spark=spark)\n",
-    "    plateau_start, plateau_end = RqCircuitQuery(circuit_type, circuit_names).calculate_current_plateau_start_end(t_start, t_end, i_meas_threshold=500, min_duration_in_sec=600, time_shift_in_sec=(240, 60), spark=spark)\n",
+    "    plateau_start, plateau_end = RqCircuitQuery(circuit_type, circuit_names).calculate_current_plateau_start_end(t_start, t_end, i_meas_threshold=300, min_duration_in_sec=600, time_shift_in_sec=(240, 60), spark=spark)\n",
     "\n",
     "    source_timestamp_df = rqd_query.find_source_timestamp_pc(t_start, t_end)\n",
     "    timestamp_fgc_rqd = source_timestamp_df.at[0, 'timestamp']\n",
@@ -287,21 +287,21 @@
     "        # # RQD\n",
     "        u_res_rqd_feature_df, i_meas_rqd_feature_df = rqd_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_RES', spark=spark)\n",
     "        res_busbar_rqd_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rq_analysis, i_meas_rqd_feature_df, u_res_rqd_feature_df, 'U_RES', Time.to_unix_timestamp(t_start), circuit_names[0])\n",
-    "        res_busbar_rqd_df = convert_to_col(res_busbar_rqd_row_df, signal_name='U_RES')\n",
+    "        res_busbar_rqd_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_busbar_rqd_row_df, signal_name='U_RES')\n",
     "        # # RQF\n",
     "        u_res_rqf_feature_df, i_meas_rqf_feature_df = rqf_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_RES', spark=spark)\n",
     "        res_busbar_rqf_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rq_analysis, i_meas_rqf_feature_df, u_res_rqf_feature_df, 'U_RES', Time.to_unix_timestamp(t_start), circuit_names[1])\n",
-    "        res_busbar_rqf_df = convert_to_col(res_busbar_rqf_row_df, signal_name='U_RES')\n",
+    "        res_busbar_rqf_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_busbar_rqf_row_df, signal_name='U_RES')\n",
     "\n",
     "        # MAGNET\n",
     "        # # RQD\n",
     "        u_mag_rqd_feature_df, i_meas_rqd_feature_df = rqd_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_MAG', spark=spark)\n",
     "        res_magnet_rqd_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rq_analysis, i_meas_rqd_feature_df, u_mag_rqd_feature_df, 'U_MAG', Time.to_unix_timestamp(t_start), circuit_names[0])\n",
-    "        res_magnet_rqd_df = convert_to_col(res_magnet_rqd_row_df, signal_name='U_MAG')\n",
+    "        res_magnet_rqd_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_magnet_rqd_row_df, signal_name='U_MAG')\n",
     "        # # RQF\n",
     "        u_mag_rqf_feature_df, i_meas_rqf_feature_df = rqf_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_MAG', spark=spark)\n",
     "        res_magnet_rqf_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rq_analysis, i_meas_rqf_feature_df, u_mag_rqf_feature_df, 'U_MAG', Time.to_unix_timestamp(t_start), circuit_names[1])\n",
-    "        res_magnet_rqf_df = convert_to_col(res_magnet_rqf_row_df, signal_name='U_MAG')\n",
+    "        res_magnet_rqf_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_magnet_rqf_row_df, signal_name='U_MAG')\n",
     "    else:\n",
     "        res_busbar_rqd_df, res_busbar_rqf_df, res_magnet_rqd_df, res_magnet_rqf_df = 4*[pd.DataFrame()]\n",
     "\n",
@@ -852,7 +852,7 @@
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqf_df.empty:\n",
     "    rqf_magnet_metadata_resistance_df = rq_analysis.merge_busbar_metadata_with_resistance(res_magnet_rqf_df, circuit_type, circuit_names, res_col='R_MAG')\n",
-    "    rq_analysis.display_busbar_metadata_resistance_with_threshold(rqd_magnet_metadata_resistance_df, threshold=50e-9, res_col='R_MAG')"
+    "    rq_analysis.display_busbar_metadata_resistance_with_threshold(rqf_magnet_metadata_resistance_df, threshold=50e-9, res_col='R_MAG')"
    ]
   },
   {
@@ -1098,4 +1098,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
\ No newline at end of file
+}
-- 
GitLab


From 03fa21ce2d78e640f2b2a8824b4cffc14c285680 Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Mon, 21 Feb 2022 10:18:53 +0100
Subject: [PATCH 32/44] [SIGMON-315] AN_RB_PNO.b2

---
 rb/AN_RB_PNO.b2.ipynb | 20 +++++++++++++++-----
 1 file changed, 15 insertions(+), 5 deletions(-)

diff --git a/rb/AN_RB_PNO.b2.ipynb b/rb/AN_RB_PNO.b2.ipynb
index 74cc39ad..f7b2c5a7 100644
--- a/rb/AN_RB_PNO.b2.ipynb
+++ b/rb/AN_RB_PNO.b2.ipynb
@@ -202,7 +202,7 @@
     "    i_meas_nxcals_df = rb_query.query_signal_nxcals(t_start, t_end, t0=t_start, system='PC', signal_names='I_MEAS', spark=spark)[0] \n",
     "    \n",
     "    i_meas_raw_nxcals_df = rb_query.query_raw_signal_nxcals(t_start, t_end, system='PC', signal_names='I_MEAS', spark=spark)[0]\n",
-    "    plateau_start, plateau_end = rb_analysis.find_plateau_start_and_end(i_meas_raw_nxcals_df, i_meas_threshold=0, min_duration_in_sec=360, time_shift_in_sec=(240, 120))\n",
+    "    plateau_start, plateau_end = rb_analysis.find_plateau_start_and_end(i_meas_raw_nxcals_df, i_meas_threshold=50, min_duration_in_sec=360, time_shift_in_sec=(240, 120))\n",
     "\n",
     "    source_timestamp_pc = rb_query.find_source_timestamp_pc(t_start, t_end)\n",
     "    timestamp_fgc = source_timestamp_pc.at[0, 'timestamp']\n",
@@ -278,12 +278,12 @@
     "            from lhcsmapi.analysis.busbar.BusbarResistanceAnalysis import MultipleBusbarResistanceAnalysis\n",
     "            u_res_feature_df, i_meas_feature_df = rb_query.get_busbar_resistances(t_start, t_end, plateau_start, plateau_end, signal_name='U_RES', spark=spark)\n",
     "            res_busbar_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rb_analysis, i_meas_feature_df, u_res_feature_df, 'U_RES', Time.to_unix_timestamp(t_start), circuit_name)\n",
-    "            res_busbar_df = convert_to_col(res_busbar_row_df, signal_name='U_RES')\n",
+    "            res_busbar_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_busbar_row_df, signal_name='U_RES')\n",
     "\n",
     "            # MAGNET\n",
     "            u_mag_feature_df, i_meas_feature_df = rb_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_MAG', spark=spark)\n",
     "            res_magnet_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rb_analysis, i_meas_feature_df, u_mag_feature_df, 'U_MAG', Time.to_unix_timestamp(t_start), circuit_name)\n",
-    "            res_magnet_df = convert_to_col(res_magnet_row_df, signal_name='U_MAG')\n",
+    "            res_magnet_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_magnet_row_df, signal_name='U_MAG')\n",
     "        else:\n",
     "            res_busbar_df = pd.DataFrame()\n",
     "            res_magnet_df = pd.DataFrame()\n",
@@ -695,7 +695,7 @@
    "outputs": [],
    "source": [
     "if t_pnob2 > 1800 and not res_busbar_df.empty:\n",
-    "    res_magnet_outliers_df = rb_analysis.analyze_busbar_magnet_resistance(res_magnet_df, signal_name='R_RES', value_max=3e-9)\n",
+    "    res_magnet_outliers_df = rb_analysis.analyze_busbar_magnet_resistance(res_magnet_df, signal_name='R_MAG', value_max=3e-9)\n",
     "else:\n",
     "    res_magnet_outliers_df = pd.DataFrame()"
    ]
@@ -934,6 +934,16 @@
     "\n",
     "!mkdir -p $report_destination_path\n",
     "\n",
+    "if not res_busbar_df.empty:\n",
+    "    csv_path = f'{report_destination_path}/{report_filename}_BUSBAR_RESISTANCE.csv'\n",
+    "    res_busbar_df.to_csv(csv_path)\n",
+    "    print('Busbar resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
+    "if not res_magnet_df.empty:\n",
+    "    csv_path = f'{report_destination_path}/{report_filename}_MAGNET_RESISTANCE.csv'\n",
+    "    res_magnet_df.to_csv(csv_path)\n",
+    "    print('Magnet resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
     "html_filename = f'{report_filename}.html'\n",
     "html_path = f'{report_destination_path}/{report_filename}.html'\n",
     "print('Compact notebook report saved to (Windows): ' + '\\\\\\\\cernbox-smb' + html_path.replace('/', '\\\\'))\n",
@@ -992,4 +1002,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
\ No newline at end of file
+}
-- 
GitLab


From 12cab91c0b9bbbbb010bcadafe11ae746a9c5474 Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Mon, 21 Feb 2022 10:39:55 +0100
Subject: [PATCH 33/44] [SIGMON-315] AN_RQ_PNO.b3 save busbar and magnet
 resistance

---
 rq/AN_RQ_PNO.b3.ipynb | 21 +++++++++++++++++++++
 1 file changed, 21 insertions(+)

diff --git a/rq/AN_RQ_PNO.b3.ipynb b/rq/AN_RQ_PNO.b3.ipynb
index a18bb745..483bbd07 100644
--- a/rq/AN_RQ_PNO.b3.ipynb
+++ b/rq/AN_RQ_PNO.b3.ipynb
@@ -1040,6 +1040,27 @@
     "report_filename = report_filename_template.format(circuit_name, hwc_test, Time.to_datetime(t_start).strftime(\"%Y-%m-%d-%Hh%M\"), analysis_start_time, signature)\n",
     "\n",
     "!mkdir -p $report_destination_path\n",
+    "\n",
+    "if not res_busbar_rqd_df.empty:",
+    "    csv_path = f'{report_destination_path}/{report_filename}_RQD_BUSBAR_RESISTANCE.csv'\n",
+    "    res_busbar_rqd_df.to_csv(csv_path)\n",
+    "    print('RQD busbar resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
+    "if not res_busbar_rqf_df.empty:",
+    "    csv_path = f'{report_destination_path}/{report_filename}_RQF_BUSBAR_RESISTANCE.csv'\n",
+    "    res_busbar_rqf_df.to_csv(csv_path)\n",
+    "    print('RQF busbar resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
+    "if not res_magnet_rqd_df.empty:",
+    "    csv_path = f'{report_destination_path}/{report_filename}_RQD_MAGNET_RESISTANCE.csv'\n",
+    "    res_magnet_rqd_df.to_csv(csv_path)\n",
+    "    print('RQD magnet resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
+    "if not res_magnet_rqf_df.empty:",
+    "    csv_path = f'{report_destination_path}/{report_filename}_RQF_MAGNET_RESISTANCE.csv'\n",
+    "    res_magnet_rqf_df.to_csv(csv_path)\n",
+    "    print('RQF magnet resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
     "html_filename = f'{report_filename}.html'\n",
     "html_path = f'{report_destination_path}/{report_filename}.html'\n",
     "print('Compact notebook report saved to (Windows): ' + '\\\\\\\\cernbox-smb' + html_path.replace('/', '\\\\'))\n",
-- 
GitLab


From 53b265619e34faf5d86678ace7ed2181ef1aea73 Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Mon, 21 Feb 2022 10:42:57 +0100
Subject: [PATCH 34/44] [SIGMON-315] regenerate references

---
 test/test_notebooks.py | 114 ++++++++++++++++++++++-------------------
 1 file changed, 61 insertions(+), 53 deletions(-)

diff --git a/test/test_notebooks.py b/test/test_notebooks.py
index c4508ac7..516c2452 100644
--- a/test/test_notebooks.py
+++ b/test/test_notebooks.py
@@ -118,6 +118,14 @@ RQ_NOTEBOOKS = [
      []),
 ]
 
+TO_TEST = [
+    ('rq', 'AN_RQ_PNO.b3', 'PNO.b3', 'RQD.A12', 'HWC_2018_1', '2018-03-18 07:17:37.130', '2018-03-18 12:13:29.766',
+     ['AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv', 'AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv',
+      'AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv', 'AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv']),
+    ('rb', 'AN_RB_PNO.b2', 'PNO.b2', 'RB.A12', 'HWC_2018_1', '2018-03-17 11:34:53.954', '2018-03-17 16:06:41.537',
+     ['AN_RB_PNO.b2_BUSBAR_RESISTANCE.csv', 'AN_RB_PNO.b2_MAGNET_RESISTANCE.csv'])
+]
+
 HWC_NOTEBOOKS = [nb for notebooks in [RQ_NOTEBOOKS, RB_NOTEBOOKS, NQPS_NOTEBOOKS, IT_NOTEBOOKS,
                                       IPQ_NOTEBOOKS, IPD_NOTEBOOKS, PGC_NOTEBOOKS] for nb in notebooks]
 
@@ -166,7 +174,7 @@ def setup():
     os.environ[lhcsmapi.nb_version_env] = version
 
 
-@pytest.mark.parametrize('directory,notebook,hwc_test,circuit_name,campaign,t_start,t_end,csv_files', HWC_NOTEBOOKS)
+@pytest.mark.parametrize('directory,notebook,hwc_test,circuit_name,campaign,t_start,t_end,csv_files', TO_TEST)
 def test_hwc_notebook(directory, notebook, hwc_test, circuit_name, campaign, t_start, t_end, csv_files):
     _test_notebook(directory,
                    notebook,
@@ -181,58 +189,58 @@ def test_hwc_notebook(directory, notebook, hwc_test, circuit_name, campaign, t_s
                    csv_files)
 
 
-@pytest.mark.parametrize('directory,notebook,circuit_name,timestamp_fgc,csv_files', FGC_SEARCH_NOTEBOOKS)
-def test_fgc_search_notebook(directory, notebook, circuit_name, timestamp_fgc, csv_files):
-    _test_notebook(directory,
-                   notebook,
-                   {
-                       'circuit_name': circuit_name,
-                       'timestamp_fgc': timestamp_fgc,
-                       'author': 'test',
-                       'is_automatic': True
-                   },
-                   csv_files)
-
-
-@pytest.mark.parametrize('directory,notebook,circuit_type,circuit_names,timestamps_fgc,csv_files',
-                         FGC_2_SEARCH_NOTEBOOKS)
-def test_fgc_2_search_notebook(directory, notebook, circuit_type, circuit_names, timestamps_fgc, csv_files):
-    _test_notebook(directory,
-                   notebook,
-                   {
-                       'circuit_type': circuit_type,
-                       'circuit_names': circuit_names,
-                       'timestamps_fgc': timestamps_fgc,
-                       'author': 'test',
-                       'is_automatic': True
-                   },
-                   csv_files)
-
-
-@pytest.mark.parametrize('directory,notebook,circuit_name,discharge_level,start_time,end_time,csv_files', QH_NOTEBOOKS)
-def test_qh_search_notebook(directory, notebook, circuit_name, discharge_level, start_time, end_time, csv_files):
-    _test_notebook(directory,
-                   notebook,
-                   {
-                       'circuit_name': circuit_name,
-                       'discharge_level': discharge_level,
-                       'start_time': start_time,
-                       'end_time': end_time,
-                       'is_automatic': True
-                   },
-                   csv_files)
-
-
-@pytest.mark.parametrize('directory,notebook,start_time,stop_time,csv_files', QHD_PM_LIST)
-def test_qh_list_notebook(directory, notebook, start_time, stop_time, csv_files):
-    _test_notebook(directory,
-                   notebook,
-                   {
-                       'start_time': start_time,
-                       'stop_time': stop_time,
-                       'initial_charge_check': True
-                   },
-                   csv_files)
+# @pytest.mark.parametrize('directory,notebook,circuit_name,timestamp_fgc,csv_files', FGC_SEARCH_NOTEBOOKS)
+# def test_fgc_search_notebook(directory, notebook, circuit_name, timestamp_fgc, csv_files):
+#     _test_notebook(directory,
+#                    notebook,
+#                    {
+#                        'circuit_name': circuit_name,
+#                        'timestamp_fgc': timestamp_fgc,
+#                        'author': 'test',
+#                        'is_automatic': True
+#                    },
+#                    csv_files)
+#
+#
+# @pytest.mark.parametrize('directory,notebook,circuit_type,circuit_names,timestamps_fgc,csv_files',
+#                          FGC_2_SEARCH_NOTEBOOKS)
+# def test_fgc_2_search_notebook(directory, notebook, circuit_type, circuit_names, timestamps_fgc, csv_files):
+#     _test_notebook(directory,
+#                    notebook,
+#                    {
+#                        'circuit_type': circuit_type,
+#                        'circuit_names': circuit_names,
+#                        'timestamps_fgc': timestamps_fgc,
+#                        'author': 'test',
+#                        'is_automatic': True
+#                    },
+#                    csv_files)
+#
+#
+# @pytest.mark.parametrize('directory,notebook,circuit_name,discharge_level,start_time,end_time,csv_files', QH_NOTEBOOKS)
+# def test_qh_search_notebook(directory, notebook, circuit_name, discharge_level, start_time, end_time, csv_files):
+#     _test_notebook(directory,
+#                    notebook,
+#                    {
+#                        'circuit_name': circuit_name,
+#                        'discharge_level': discharge_level,
+#                        'start_time': start_time,
+#                        'end_time': end_time,
+#                        'is_automatic': True
+#                    },
+#                    csv_files)
+#
+#
+# @pytest.mark.parametrize('directory,notebook,start_time,stop_time,csv_files', QHD_PM_LIST)
+# def test_qh_list_notebook(directory, notebook, start_time, stop_time, csv_files):
+#     _test_notebook(directory,
+#                    notebook,
+#                    {
+#                        'start_time': start_time,
+#                        'stop_time': stop_time,
+#                        'initial_charge_check': True
+#                    },
+#                    csv_files)
 
 
 def _test_notebook(directory, notebook_name, notebook_parameters, csv_files):
-- 
GitLab


From d70649421df1294907eeb8e08df8de58e03400b7 Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Mon, 21 Feb 2022 13:45:42 +0100
Subject: [PATCH 35/44] [SIGMON-315] fix

---
 test/test_notebooks.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/test_notebooks.py b/test/test_notebooks.py
index 516c2452..92137171 100644
--- a/test/test_notebooks.py
+++ b/test/test_notebooks.py
@@ -123,7 +123,7 @@ TO_TEST = [
      ['AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv', 'AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv',
       'AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv', 'AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv']),
     ('rb', 'AN_RB_PNO.b2', 'PNO.b2', 'RB.A12', 'HWC_2018_1', '2018-03-17 11:34:53.954', '2018-03-17 16:06:41.537',
-     ['AN_RB_PNO.b2_BUSBAR_RESISTANCE.csv', 'AN_RB_PNO.b2_MAGNET_RESISTANCE.csv'])
+     [])
 ]
 
 HWC_NOTEBOOKS = [nb for notebooks in [RQ_NOTEBOOKS, RB_NOTEBOOKS, NQPS_NOTEBOOKS, IT_NOTEBOOKS,
-- 
GitLab


From fb64ceed7d6d12b2a5291ed6969743d46add8b09 Mon Sep 17 00:00:00 2001
From: agchadaj <agata.chadaj@cern.ch>
Date: Mon, 21 Feb 2022 14:50:01 +0100
Subject: [PATCH 36/44] new references

---
 pgc/AN_PGC2.ipynb                             |   5 +-
 test/resources/notebooks/result_AN_PGC1.ipynb | 638 +++++++--------
 test/resources/notebooks/result_AN_PGC3.ipynb | 737 +++++++++---------
 test/resources/notebooks/result_AN_PGC4.ipynb | 610 ++++++++-------
 test/resources/reports/AN_PGC1.html           |  19 +-
 test/resources/reports/AN_PGC3.html           | 124 +--
 test/resources/reports/AN_PGC4.html           |  13 +-
 7 files changed, 1108 insertions(+), 1038 deletions(-)

diff --git a/pgc/AN_PGC2.ipynb b/pgc/AN_PGC2.ipynb
index 5eaac59a..9c4c1eed 100644
--- a/pgc/AN_PGC2.ipynb
+++ b/pgc/AN_PGC2.ipynb
@@ -179,8 +179,7 @@
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
     "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]\n",
-    "lhc_circ = meta_df[meta_df[['Circuit name'] == circuit_name]\n"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -850,4 +849,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}
\ No newline at end of file
diff --git a/test/resources/notebooks/result_AN_PGC1.ipynb b/test/resources/notebooks/result_AN_PGC1.ipynb
index 7a72ecb2..71ec6973 100644
--- a/test/resources/notebooks/result_AN_PGC1.ipynb
+++ b/test/resources/notebooks/result_AN_PGC1.ipynb
@@ -3,19 +3,19 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "665ec46b",
+   "id": "c61b92a0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:01.432786Z",
-     "iopub.status.busy": "2022-01-11T13:21:01.432066Z",
-     "iopub.status.idle": "2022-01-11T13:21:37.362771Z",
-     "shell.execute_reply": "2022-01-11T13:21:37.361865Z"
+     "iopub.execute_input": "2022-02-21T12:57:14.787091Z",
+     "iopub.status.busy": "2022-02-21T12:57:14.786699Z",
+     "iopub.status.idle": "2022-02-21T12:57:51.279515Z",
+     "shell.execute_reply": "2022-02-21T12:57:51.278321Z"
     },
     "papermill": {
-     "duration": 35.986207,
-     "end_time": "2022-01-11T13:21:37.362986",
+     "duration": 36.542612,
+     "end_time": "2022-02-21T12:57:51.282610",
      "exception": false,
-     "start_time": "2022-01-11T13:21:01.376779",
+     "start_time": "2022-02-21T12:57:14.739998",
      "status": "completed"
     }
    },
@@ -73,10 +73,10 @@
    "id": "b73d981e",
    "metadata": {
     "papermill": {
-     "duration": 0.041589,
-     "end_time": "2022-01-11T13:21:37.446567",
+     "duration": 0.040996,
+     "end_time": "2022-02-21T12:57:51.366275",
      "exception": false,
-     "start_time": "2022-01-11T13:21:37.404978",
+     "start_time": "2022-02-21T12:57:51.325279",
      "status": "completed"
     },
     "tags": []
@@ -90,10 +90,10 @@
    "id": "6ace70fc",
    "metadata": {
     "papermill": {
-     "duration": 0.040471,
-     "end_time": "2022-01-11T13:21:37.527774",
+     "duration": 0.041,
+     "end_time": "2022-02-21T12:57:51.448164",
      "exception": false,
-     "start_time": "2022-01-11T13:21:37.487303",
+     "start_time": "2022-02-21T12:57:51.407164",
      "status": "completed"
     },
     "tags": []
@@ -125,10 +125,10 @@
    "id": "d14e9800",
    "metadata": {
     "papermill": {
-     "duration": 0.040475,
-     "end_time": "2022-01-11T13:21:37.608902",
+     "duration": 0.041233,
+     "end_time": "2022-02-21T12:57:51.530480",
      "exception": false,
-     "start_time": "2022-01-11T13:21:37.568427",
+     "start_time": "2022-02-21T12:57:51.489247",
      "status": "completed"
     },
     "tags": []
@@ -143,16 +143,16 @@
    "id": "222c2e87",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:37.697962Z",
-     "iopub.status.busy": "2022-01-11T13:21:37.697289Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.143711Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.142800Z"
+     "iopub.execute_input": "2022-02-21T12:57:51.615265Z",
+     "iopub.status.busy": "2022-02-21T12:57:51.614927Z",
+     "iopub.status.idle": "2022-02-21T12:57:54.163110Z",
+     "shell.execute_reply": "2022-02-21T12:57:54.162189Z"
     },
     "papermill": {
-     "duration": 2.494193,
-     "end_time": "2022-01-11T13:21:40.143866",
+     "duration": 2.59353,
+     "end_time": "2022-02-21T12:57:54.165180",
      "exception": false,
-     "start_time": "2022-01-11T13:21:37.649673",
+     "start_time": "2022-02-21T12:57:51.571650",
      "status": "completed"
     },
     "tags": []
@@ -204,16 +204,16 @@
    "id": "d46be93a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.234899Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.234232Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.237654Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.236971Z"
+     "iopub.execute_input": "2022-02-21T12:57:54.260597Z",
+     "iopub.status.busy": "2022-02-21T12:57:54.260257Z",
+     "iopub.status.idle": "2022-02-21T12:57:54.266626Z",
+     "shell.execute_reply": "2022-02-21T12:57:54.265747Z"
     },
     "papermill": {
-     "duration": 0.051484,
-     "end_time": "2022-01-11T13:21:40.237800",
+     "duration": 0.061468,
+     "end_time": "2022-02-21T12:57:54.268797",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.186316",
+     "start_time": "2022-02-21T12:57:54.207329",
      "status": "completed"
     },
     "tags": []
@@ -223,8 +223,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Analysis executed with lhc-sm-api version: 1.5.18\n",
-      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.66\n",
+      "Analysis executed with lhc-sm-api version: 1.5.19\n",
+      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.67\n",
       "user = root\n"
      ]
     }
@@ -243,16 +243,16 @@
    "id": "9dd25d8b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.328033Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.327351Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.329464Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.330076Z"
+     "iopub.execute_input": "2022-02-21T12:57:54.358520Z",
+     "iopub.status.busy": "2022-02-21T12:57:54.358185Z",
+     "iopub.status.idle": "2022-02-21T12:57:54.362252Z",
+     "shell.execute_reply": "2022-02-21T12:57:54.361393Z"
     },
     "papermill": {
-     "duration": 0.050283,
-     "end_time": "2022-01-11T13:21:40.330256",
+     "duration": 0.051998,
+     "end_time": "2022-02-21T12:57:54.364357",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.279973",
+     "start_time": "2022-02-21T12:57:54.312359",
      "status": "completed"
     },
     "tags": []
@@ -269,10 +269,10 @@
    "id": "d71e3168",
    "metadata": {
     "papermill": {
-     "duration": 0.043769,
-     "end_time": "2022-01-11T13:21:40.416879",
+     "duration": 0.046278,
+     "end_time": "2022-02-21T12:57:54.456035",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.373110",
+     "start_time": "2022-02-21T12:57:54.409757",
      "status": "completed"
     },
     "tags": []
@@ -286,10 +286,10 @@
    "id": "7d619e42",
    "metadata": {
     "papermill": {
-     "duration": 0.043049,
-     "end_time": "2022-01-11T13:21:40.503058",
+     "duration": 0.042387,
+     "end_time": "2022-02-21T12:57:54.540950",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.460009",
+     "start_time": "2022-02-21T12:57:54.498563",
      "status": "completed"
     },
     "tags": []
@@ -305,16 +305,16 @@
    "id": "a6088011",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.604255Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.603568Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.634517Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.633890Z"
+     "iopub.execute_input": "2022-02-21T12:57:54.628190Z",
+     "iopub.status.busy": "2022-02-21T12:57:54.627865Z",
+     "iopub.status.idle": "2022-02-21T12:57:54.632077Z",
+     "shell.execute_reply": "2022-02-21T12:57:54.631328Z"
     },
     "papermill": {
-     "duration": 0.088131,
-     "end_time": "2022-01-11T13:21:40.634688",
+     "duration": 0.050191,
+     "end_time": "2022-02-21T12:57:54.633896",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.546557",
+     "start_time": "2022-02-21T12:57:54.583705",
      "status": "completed"
     },
     "tags": [
@@ -323,25 +323,30 @@
    },
    "outputs": [],
    "source": [
-    "#User input from ACCTESTING:\n"
+    "#User input from ACCTESTING:\n",
+    "hwc_test = 'PGC.1'\n",
+    "circuit_name = 'RQX.L1'\n",
+    "campaign = 'Recommissioning post LS2'\n",
+    "t_start = '2021-05-17 17:58:26.625000000'\n",
+    "t_end = '2021-05-17 17:58:26.638000000'"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "117203a1",
+   "id": "34396261",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.729586Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.728821Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.732989Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.732450Z"
+     "iopub.execute_input": "2022-02-21T12:57:54.721084Z",
+     "iopub.status.busy": "2022-02-21T12:57:54.720734Z",
+     "iopub.status.idle": "2022-02-21T12:57:54.725854Z",
+     "shell.execute_reply": "2022-02-21T12:57:54.725019Z"
     },
     "papermill": {
-     "duration": 0.055124,
-     "end_time": "2022-01-11T13:21:40.733159",
+     "duration": 0.05143,
+     "end_time": "2022-02-21T12:57:54.727854",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.678035",
+     "start_time": "2022-02-21T12:57:54.676424",
      "status": "completed"
     },
     "tags": [
@@ -369,16 +374,16 @@
    "id": "1ebdaee8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.827205Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.826530Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.830498Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.831114Z"
+     "iopub.execute_input": "2022-02-21T12:57:54.815589Z",
+     "iopub.status.busy": "2022-02-21T12:57:54.815251Z",
+     "iopub.status.idle": "2022-02-21T12:57:54.820771Z",
+     "shell.execute_reply": "2022-02-21T12:57:54.819786Z"
     },
     "papermill": {
-     "duration": 0.054508,
-     "end_time": "2022-01-11T13:21:40.831291",
+     "duration": 0.052072,
+     "end_time": "2022-02-21T12:57:54.822852",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.776783",
+     "start_time": "2022-02-21T12:57:54.770780",
      "status": "completed"
     },
     "tags": []
@@ -405,10 +410,10 @@
    "id": "f6056bf0",
    "metadata": {
     "papermill": {
-     "duration": 0.043257,
-     "end_time": "2022-01-11T13:21:40.918815",
+     "duration": 0.043043,
+     "end_time": "2022-02-21T12:57:54.909258",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.875558",
+     "start_time": "2022-02-21T12:57:54.866215",
      "status": "completed"
     },
     "tags": []
@@ -423,16 +428,16 @@
    "id": "01c781d1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.021676Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.020932Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.034296Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.033722Z"
+     "iopub.execute_input": "2022-02-21T12:57:54.997769Z",
+     "iopub.status.busy": "2022-02-21T12:57:54.997452Z",
+     "iopub.status.idle": "2022-02-21T12:57:55.015901Z",
+     "shell.execute_reply": "2022-02-21T12:57:55.015104Z"
     },
     "papermill": {
-     "duration": 0.0716,
-     "end_time": "2022-01-11T13:21:41.034463",
+     "duration": 0.065585,
+     "end_time": "2022-02-21T12:57:55.017992",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.962863",
+     "start_time": "2022-02-21T12:57:54.952407",
      "status": "completed"
     },
     "tags": []
@@ -452,9 +457,9 @@
     "lhc_circuit = meta_df[lambda x: x['Circuit name'] == circuit_name]\n",
     "\n",
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'] == safety_subsector]\n",
-    "#\n",
-    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))"
+    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
+    "\n",
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -462,10 +467,10 @@
    "id": "1d11e5fe",
    "metadata": {
     "papermill": {
-     "duration": 0.044547,
-     "end_time": "2022-01-11T13:21:41.123832",
+     "duration": 0.043808,
+     "end_time": "2022-02-21T12:57:55.106044",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.079285",
+     "start_time": "2022-02-21T12:57:55.062236",
      "status": "completed"
     },
     "tags": []
@@ -480,16 +485,16 @@
    "id": "9e58ff62",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.225064Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.224344Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.233661Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.233070Z"
+     "iopub.execute_input": "2022-02-21T12:57:55.197199Z",
+     "iopub.status.busy": "2022-02-21T12:57:55.196871Z",
+     "iopub.status.idle": "2022-02-21T12:57:55.210943Z",
+     "shell.execute_reply": "2022-02-21T12:57:55.210131Z"
     },
     "papermill": {
-     "duration": 0.065187,
-     "end_time": "2022-01-11T13:21:41.233813",
+     "duration": 0.063326,
+     "end_time": "2022-02-21T12:57:55.213156",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.168626",
+     "start_time": "2022-02-21T12:57:55.149830",
      "status": "completed"
     },
     "tags": []
@@ -518,8 +523,8 @@
     "    t_end = Time.to_string_short((Time.to_unix_timestamp(t_start) + (2 * 3600 + 40 * 60) * 1e9))\n",
     "t_end_sec = int((Time.to_unix_timestamp(t_end) - Time.to_unix_timestamp(t_start))*1e-9)\n",
     "#\n",
-    "t_start_utc = Time.to_string_short((Time.to_unix_timestamp(t_start) - 2 * 3600 * 1e9))\n",
-    "t_end_utc = Time.to_string_short((Time.to_unix_timestamp(t_end) - 2 * 3600 * 1e9))\n",
+    "t_start_timestamp = Time.to_unix_timestamp(t_start)\n",
+    "t_end_timestamp = Time.to_unix_timestamp(t_end)\n",
     "#\n",
     "print('hwc_test = \\'%s\\'\\ncircuit_name = \\'%s\\'\\ncampaign = \\'%s\\'\\nt_start = \\'%s\\'\\nt_end = \\'%s\\'\\nt_end_sec = \\'%s\\'' % (hwc_test, circuit_name, campaign, t_start, t_end, t_end_sec))"
    ]
@@ -529,10 +534,10 @@
    "id": "f1517845",
    "metadata": {
     "papermill": {
-     "duration": 0.044486,
-     "end_time": "2022-01-11T13:21:41.322880",
+     "duration": 0.044253,
+     "end_time": "2022-02-21T12:57:55.302654",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.278394",
+     "start_time": "2022-02-21T12:57:55.258401",
      "status": "completed"
     },
     "tags": []
@@ -547,16 +552,16 @@
    "id": "232fc80f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.417693Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.417028Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.419946Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.419375Z"
+     "iopub.execute_input": "2022-02-21T12:57:55.396548Z",
+     "iopub.status.busy": "2022-02-21T12:57:55.396194Z",
+     "iopub.status.idle": "2022-02-21T12:57:55.402978Z",
+     "shell.execute_reply": "2022-02-21T12:57:55.402021Z"
     },
     "papermill": {
-     "duration": 0.05286,
-     "end_time": "2022-01-11T13:21:41.420099",
+     "duration": 0.058073,
+     "end_time": "2022-02-21T12:57:55.405274",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.367239",
+     "start_time": "2022-02-21T12:57:55.347201",
      "status": "completed"
     },
     "tags": []
@@ -575,16 +580,16 @@
    "id": "ea08249d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.516573Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.515858Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.518082Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.518577Z"
+     "iopub.execute_input": "2022-02-21T12:57:55.498108Z",
+     "iopub.status.busy": "2022-02-21T12:57:55.497744Z",
+     "iopub.status.idle": "2022-02-21T12:57:55.503936Z",
+     "shell.execute_reply": "2022-02-21T12:57:55.503188Z"
     },
     "papermill": {
-     "duration": 0.05418,
-     "end_time": "2022-01-11T13:21:41.518838",
+     "duration": 0.0549,
+     "end_time": "2022-02-21T12:57:55.506035",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.464658",
+     "start_time": "2022-02-21T12:57:55.451135",
      "status": "completed"
     },
     "tags": []
@@ -611,16 +616,16 @@
    "id": "04a64410",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.618072Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.617403Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.628867Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.628317Z"
+     "iopub.execute_input": "2022-02-21T12:57:55.597220Z",
+     "iopub.status.busy": "2022-02-21T12:57:55.596938Z",
+     "iopub.status.idle": "2022-02-21T12:57:55.609361Z",
+     "shell.execute_reply": "2022-02-21T12:57:55.608657Z"
     },
     "papermill": {
-     "duration": 0.06423,
-     "end_time": "2022-01-11T13:21:41.629030",
+     "duration": 0.060502,
+     "end_time": "2022-02-21T12:57:55.611313",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.564800",
+     "start_time": "2022-02-21T12:57:55.550811",
      "status": "completed"
     },
     "scrolled": false,
@@ -649,10 +654,10 @@
    "id": "84e43979",
    "metadata": {
     "papermill": {
-     "duration": 0.046219,
-     "end_time": "2022-01-11T13:21:41.720961",
+     "duration": 0.045947,
+     "end_time": "2022-02-21T12:57:55.702210",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.674742",
+     "start_time": "2022-02-21T12:57:55.656263",
      "status": "completed"
     },
     "tags": []
@@ -667,16 +672,16 @@
    "id": "6ca962e0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.826293Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.825607Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.829320Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.828643Z"
+     "iopub.execute_input": "2022-02-21T12:57:55.796635Z",
+     "iopub.status.busy": "2022-02-21T12:57:55.796294Z",
+     "iopub.status.idle": "2022-02-21T12:57:55.803811Z",
+     "shell.execute_reply": "2022-02-21T12:57:55.803057Z"
     },
     "papermill": {
-     "duration": 0.058068,
-     "end_time": "2022-01-11T13:21:41.829495",
+     "duration": 0.057967,
+     "end_time": "2022-02-21T12:57:55.805932",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.771427",
+     "start_time": "2022-02-21T12:57:55.747965",
      "status": "completed"
     },
     "tags": []
@@ -707,10 +712,10 @@
    "id": "9aa74719",
    "metadata": {
     "papermill": {
-     "duration": 0.046315,
-     "end_time": "2022-01-11T13:21:41.922607",
+     "duration": 0.047189,
+     "end_time": "2022-02-21T12:57:55.900515",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.876292",
+     "start_time": "2022-02-21T12:57:55.853326",
      "status": "completed"
     },
     "tags": []
@@ -725,16 +730,16 @@
    "id": "9422eb28",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:42.024147Z",
-     "iopub.status.busy": "2022-01-11T13:21:42.023463Z",
-     "iopub.status.idle": "2022-01-11T13:21:42.025975Z",
-     "shell.execute_reply": "2022-01-11T13:21:42.026477Z"
+     "iopub.execute_input": "2022-02-21T12:57:55.996863Z",
+     "iopub.status.busy": "2022-02-21T12:57:55.996533Z",
+     "iopub.status.idle": "2022-02-21T12:57:56.003787Z",
+     "shell.execute_reply": "2022-02-21T12:57:56.003001Z"
     },
     "papermill": {
-     "duration": 0.057498,
-     "end_time": "2022-01-11T13:21:42.026662",
+     "duration": 0.058272,
+     "end_time": "2022-02-21T12:57:56.005899",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.969164",
+     "start_time": "2022-02-21T12:57:55.947627",
      "status": "completed"
     },
     "tags": []
@@ -762,10 +767,10 @@
    "id": "ac0ba414",
    "metadata": {
     "papermill": {
-     "duration": 0.048557,
-     "end_time": "2022-01-11T13:21:42.123109",
+     "duration": 0.046992,
+     "end_time": "2022-02-21T12:57:56.099816",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.074552",
+     "start_time": "2022-02-21T12:57:56.052824",
      "status": "completed"
     },
     "tags": []
@@ -779,10 +784,10 @@
    "id": "495ea87f",
    "metadata": {
     "papermill": {
-     "duration": 0.046816,
-     "end_time": "2022-01-11T13:21:42.217018",
+     "duration": 0.047054,
+     "end_time": "2022-02-21T12:57:56.193798",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.170202",
+     "start_time": "2022-02-21T12:57:56.146744",
      "status": "completed"
     },
     "tags": []
@@ -800,16 +805,16 @@
    "id": "84bc60a4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:42.319418Z",
-     "iopub.status.busy": "2022-01-11T13:21:42.318716Z",
-     "iopub.status.idle": "2022-01-11T13:21:42.322601Z",
-     "shell.execute_reply": "2022-01-11T13:21:42.321895Z"
+     "iopub.execute_input": "2022-02-21T12:57:56.289962Z",
+     "iopub.status.busy": "2022-02-21T12:57:56.289634Z",
+     "iopub.status.idle": "2022-02-21T12:57:56.324476Z",
+     "shell.execute_reply": "2022-02-21T12:57:56.323684Z"
     },
     "papermill": {
-     "duration": 0.058478,
-     "end_time": "2022-01-11T13:21:42.322751",
+     "duration": 0.085591,
+     "end_time": "2022-02-21T12:57:56.326615",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.264273",
+     "start_time": "2022-02-21T12:57:56.241024",
      "status": "completed"
     },
     "tags": []
@@ -838,7 +843,6 @@
     }
    ],
    "source": [
-    "#condemned_circuits = ['RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCSX3.L2', 'RCTX3.L2', 'RSS.A34B1']\n",
     "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
     "display(condemned_circuits)"
    ]
@@ -848,10 +852,10 @@
    "id": "ce188af0",
    "metadata": {
     "papermill": {
-     "duration": 0.047962,
-     "end_time": "2022-01-11T13:21:42.418472",
+     "duration": 0.04762,
+     "end_time": "2022-02-21T12:57:56.421706",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.370510",
+     "start_time": "2022-02-21T12:57:56.374086",
      "status": "completed"
     },
     "tags": []
@@ -866,22 +870,29 @@
    "id": "72bb0d91",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:42.556484Z",
-     "iopub.status.busy": "2022-01-11T13:21:42.541155Z",
-     "iopub.status.idle": "2022-01-11T13:44:57.508548Z",
-     "shell.execute_reply": "2022-01-11T13:44:57.509171Z"
+     "iopub.execute_input": "2022-02-21T12:57:56.519143Z",
+     "iopub.status.busy": "2022-02-21T12:57:56.518787Z",
+     "iopub.status.idle": "2022-02-21T13:26:27.824916Z",
+     "shell.execute_reply": "2022-02-21T13:26:27.824131Z"
     },
     "papermill": {
-     "duration": 1395.042991,
-     "end_time": "2022-01-11T13:44:57.509593",
+     "duration": 1711.357507,
+     "end_time": "2022-02-21T13:26:27.827120",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.466602",
+     "start_time": "2022-02-21T12:57:56.469613",
      "status": "completed"
     },
     "scrolled": false,
     "tags": []
    },
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Main circuits (RB, RQ, IT)\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -900,7 +911,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "3 type = RQ , name = RQF.A12 , Imax = 11200\n"
+      "3 type = RQ , name = RQF.A12 , Imax = 11200\n",
+      "Individualy powered circuits (IPQ, IPD)\n"
      ]
     },
     {
@@ -963,7 +975,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "9 type = IPQ4 , name = RQ9.R1 , Imax = 5390\n"
+      "9 type = IPQ4 , name = RQ9.R1 , Imax = 5390\n",
+      "600A-circuits\n"
      ]
     },
     {
@@ -1235,6 +1248,13 @@
       "38 type = 600A , name = RSS.A12B2 , Imax = 200 , Imin = -200\n"
      ]
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "60A, 80A, 120A circuits\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -2010,7 +2030,7 @@
      "output_type": "stream",
      "text": [
       "111 type = 80-120A , name = RCBCV9.R1B2 , Imax = 100 , Imin = -100\n",
-      "Elapsed: 1394.826 s.\n"
+      "Elapsed: 1711.256 s.\n"
      ]
     }
    ],
@@ -2018,7 +2038,7 @@
     "#\n",
     "with Timer():\n",
     "    #\n",
-    "    # Main circuits (RB, RQ, IT)\n",
+    "    print('Main circuits (RB, RQ, IT)')\n",
     "    i = j = 0\n",
     "    i_meas_13kA_dfs = []\n",
     "    for circuit_name in lhc_circuits['Circuit name']:\n",
@@ -2052,7 +2072,7 @@
     "                    i_meas_13kA_dfs.append(i_meas_rtqx2_nxcals_df)\n",
     "        i = i + 1\n",
     "    #\n",
-    "    #Individualy powered circuits (IPQ, IPD)\n",
+    "    print('Individualy powered circuits (IPQ, IPD)')\n",
     "    i = j = 0\n",
     "    i_meas_6kA_dfs = []\n",
     "    source_timestamp_qds_6kA_df = pd.DataFrame()\n",
@@ -2087,7 +2107,7 @@
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_6kA_df = pd.concat([source_timestamp_fgc_6kA_df, source_timestamp_fgc_df_i], ignore_index=True)                        \n",
     "        i = i + 1\n",
     "    #\n",
-    "    #600A-circuits\n",
+    "    print('600A-circuits')\n",
     "    i = j = 0\n",
     "    i_meas_600A_dfs = []\n",
     "    source_timestamp_qds_600A_df = pd.DataFrame()\n",
@@ -2126,10 +2146,9 @@
     "                    .with_metadata(circuit_name=circuit_name, system='PC', source='*') \\\n",
     "                    .event_query().df\n",
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_600A_df = pd.concat([source_timestamp_fgc_600A_df, source_timestamp_fgc_df_i], ignore_index=True)                                            \n",
-    "                #j = j + 1\n",
     "        i = i + 1\n",
     "    #\n",
-    "    # 60A, 80A, 120A circuits (to be updated to metadata)\n",
+    "    print('60A, 80A, 120A circuits')\n",
     "    i = j = 0\n",
     "    i_meas_120A_dfs = []\n",
     "    source_timestamp_fgc_120A_df = pd.DataFrame()\n",
@@ -2139,29 +2158,19 @@
     "            if circuit_type in pgc_120A:\n",
     "                j = j + 1\n",
     "                #print(j, circuit_type, circuit_name)\n",
-    "                df1 = DataQuery.builder(spark).byVariables() \\\n",
-    "                    .system('CMW') \\\n",
-    "                    .startTime(t_start_utc).endTime(t_end_utc) \\\n",
-    "                    .variableLike('%' + circuit_name + ':I_MEAS') \\\n",
-    "                    .buildDataset()\n",
-    "                i_meas_df = df1.select('nxcals_timestamp', 'nxcals_value').sort('nxcals_timestamp').toPandas()\n",
-    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['nxcals_value'].max()), ', Imin =', int(i_meas_df['nxcals_value'].min()))\n",
-    "                if (int(i_meas_df['nxcals_value'].max()) - int(i_meas_df['nxcals_value'].min())) < 10:\n",
-    "                    print('Powering current is too low')\n",
-    "                i_meas_df.rename(columns={'nxcals_timestamp': 'timestamp', 'nxcals_value': circuit_name + ':I_MEAS'}, inplace=True)\n",
-    "                t0 = i_meas_df['timestamp'].loc[0]\n",
-    "                i_meas_df['time'] = (i_meas_df['timestamp'] - t0)*1e-9\n",
-    "                i_meas_df.set_index('time', inplace = True)\n",
-    "                i_meas_df = i_meas_df.drop('timestamp', 1)\n",
-    "#                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
-    "#                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
-    "#                    .with_circuit_type(circuit_type) \\\n",
-    "#                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
-    "#                    .signal_query() \\\n",
-    "#                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
-    "#                    .convert_index_to_sec().dfs[0]\n",
-    "#                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
+    "                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
+    "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
+    "                    .with_circuit_type(circuit_type) \\\n",
+    "                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
+    "                    .signal_query() \\\n",
+    "                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
+    "                    .convert_index_to_sec().dfs[0]\n",
+    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['I_MEAS'].max()), ', Imin =', int(i_meas_df['I_MEAS'].min()))\n",
+    "                if (int(i_meas_df['I_MEAS'].max()) - int(i_meas_df['I_MEAS'].min())) < 10:\n",
+    "                     print('Powering current is too low')\n",
+    "                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
     "                i_meas_120A_dfs.append(i_meas_df)\n",
+    "\n",
     "                source_timestamp_fgc_df_i = QueryBuilder().with_pm() \\\n",
     "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
     "                    .with_circuit_type(circuit_type) \\\n",
@@ -2177,10 +2186,10 @@
    "id": "cd0d3460",
    "metadata": {
     "papermill": {
-     "duration": 0.115365,
-     "end_time": "2022-01-11T13:44:57.741504",
+     "duration": 0.117484,
+     "end_time": "2022-02-21T13:26:28.062561",
      "exception": false,
-     "start_time": "2022-01-11T13:44:57.626139",
+     "start_time": "2022-02-21T13:26:27.945077",
      "status": "completed"
     },
     "tags": []
@@ -2195,16 +2204,16 @@
    "id": "6a50570d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:44:57.986049Z",
-     "iopub.status.busy": "2022-01-11T13:44:57.980944Z",
-     "iopub.status.idle": "2022-01-11T13:44:58.766306Z",
-     "shell.execute_reply": "2022-01-11T13:44:58.766845Z"
+     "iopub.execute_input": "2022-02-21T13:26:28.298008Z",
+     "iopub.status.busy": "2022-02-21T13:26:28.297676Z",
+     "iopub.status.idle": "2022-02-21T13:26:29.081391Z",
+     "shell.execute_reply": "2022-02-21T13:26:29.080268Z"
     },
     "papermill": {
-     "duration": 0.90957,
-     "end_time": "2022-01-11T13:44:58.767030",
+     "duration": 0.904874,
+     "end_time": "2022-02-21T13:26:29.084459",
      "exception": false,
-     "start_time": "2022-01-11T13:44:57.857460",
+     "start_time": "2022-02-21T13:26:28.179585",
      "status": "completed"
     },
     "scrolled": false,
@@ -2253,10 +2262,10 @@
    "id": "e6208e4d",
    "metadata": {
     "papermill": {
-     "duration": 0.11527,
-     "end_time": "2022-01-11T13:44:58.998494",
+     "duration": 0.118489,
+     "end_time": "2022-02-21T13:26:29.322124",
      "exception": false,
-     "start_time": "2022-01-11T13:44:58.883224",
+     "start_time": "2022-02-21T13:26:29.203635",
      "status": "completed"
     },
     "tags": []
@@ -2271,16 +2280,16 @@
    "id": "c563ba9b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:44:59.250695Z",
-     "iopub.status.busy": "2022-01-11T13:44:59.249996Z",
-     "iopub.status.idle": "2022-01-11T13:45:01.205310Z",
-     "shell.execute_reply": "2022-01-11T13:45:01.205847Z"
+     "iopub.execute_input": "2022-02-21T13:26:29.560790Z",
+     "iopub.status.busy": "2022-02-21T13:26:29.560467Z",
+     "iopub.status.idle": "2022-02-21T13:26:31.672519Z",
+     "shell.execute_reply": "2022-02-21T13:26:31.671523Z"
     },
     "papermill": {
-     "duration": 2.091731,
-     "end_time": "2022-01-11T13:45:01.206032",
+     "duration": 2.234408,
+     "end_time": "2022-02-21T13:26:31.674985",
      "exception": false,
-     "start_time": "2022-01-11T13:44:59.114301",
+     "start_time": "2022-02-21T13:26:29.440577",
      "status": "completed"
     },
     "scrolled": false,
@@ -2324,10 +2333,10 @@
    "id": "f0eced15",
    "metadata": {
     "papermill": {
-     "duration": 0.119028,
-     "end_time": "2022-01-11T13:45:01.443776",
+     "duration": 0.120931,
+     "end_time": "2022-02-21T13:26:31.916236",
      "exception": false,
-     "start_time": "2022-01-11T13:45:01.324748",
+     "start_time": "2022-02-21T13:26:31.795305",
      "status": "completed"
     },
     "tags": []
@@ -2342,16 +2351,16 @@
    "id": "43062b9d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:01.689268Z",
-     "iopub.status.busy": "2022-01-11T13:45:01.688581Z",
-     "iopub.status.idle": "2022-01-11T13:45:01.698683Z",
-     "shell.execute_reply": "2022-01-11T13:45:01.699198Z"
+     "iopub.execute_input": "2022-02-21T13:26:32.162082Z",
+     "iopub.status.busy": "2022-02-21T13:26:32.161743Z",
+     "iopub.status.idle": "2022-02-21T13:26:32.176764Z",
+     "shell.execute_reply": "2022-02-21T13:26:32.176021Z"
     },
     "papermill": {
-     "duration": 0.137126,
-     "end_time": "2022-01-11T13:45:01.699378",
+     "duration": 0.139158,
+     "end_time": "2022-02-21T13:26:32.178636",
      "exception": false,
-     "start_time": "2022-01-11T13:45:01.562252",
+     "start_time": "2022-02-21T13:26:32.039478",
      "status": "completed"
     },
     "tags": []
@@ -2416,10 +2425,10 @@
    "id": "bcfd777f",
    "metadata": {
     "papermill": {
-     "duration": 0.119159,
-     "end_time": "2022-01-11T13:45:01.938280",
+     "duration": 0.122664,
+     "end_time": "2022-02-21T13:26:32.422602",
      "exception": false,
-     "start_time": "2022-01-11T13:45:01.819121",
+     "start_time": "2022-02-21T13:26:32.299938",
      "status": "completed"
     },
     "tags": []
@@ -2434,16 +2443,16 @@
    "id": "1e1beb27",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:02.194530Z",
-     "iopub.status.busy": "2022-01-11T13:45:02.187761Z",
-     "iopub.status.idle": "2022-01-11T13:45:02.197748Z",
-     "shell.execute_reply": "2022-01-11T13:45:02.198230Z"
+     "iopub.execute_input": "2022-02-21T13:26:32.670491Z",
+     "iopub.status.busy": "2022-02-21T13:26:32.670151Z",
+     "iopub.status.idle": "2022-02-21T13:26:32.699586Z",
+     "shell.execute_reply": "2022-02-21T13:26:32.697764Z"
     },
     "papermill": {
-     "duration": 0.140339,
-     "end_time": "2022-01-11T13:45:02.198430",
+     "duration": 0.157298,
+     "end_time": "2022-02-21T13:26:32.702119",
      "exception": false,
-     "start_time": "2022-01-11T13:45:02.058091",
+     "start_time": "2022-02-21T13:26:32.544821",
      "status": "completed"
     },
     "tags": []
@@ -2521,10 +2530,10 @@
    "id": "86c6d219",
    "metadata": {
     "papermill": {
-     "duration": 0.119965,
-     "end_time": "2022-01-11T13:45:02.438184",
+     "duration": 0.122133,
+     "end_time": "2022-02-21T13:26:32.949246",
      "exception": false,
-     "start_time": "2022-01-11T13:45:02.318219",
+     "start_time": "2022-02-21T13:26:32.827113",
      "status": "completed"
     },
     "tags": []
@@ -2539,16 +2548,16 @@
    "id": "4e577a00",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:02.701020Z",
-     "iopub.status.busy": "2022-01-11T13:45:02.697568Z",
-     "iopub.status.idle": "2022-01-11T13:45:07.575204Z",
-     "shell.execute_reply": "2022-01-11T13:45:07.575733Z"
+     "iopub.execute_input": "2022-02-21T13:26:33.198159Z",
+     "iopub.status.busy": "2022-02-21T13:26:33.197814Z",
+     "iopub.status.idle": "2022-02-21T13:26:38.223493Z",
+     "shell.execute_reply": "2022-02-21T13:26:38.222448Z"
     },
     "papermill": {
-     "duration": 5.014916,
-     "end_time": "2022-01-11T13:45:07.575933",
+     "duration": 5.153879,
+     "end_time": "2022-02-21T13:26:38.225942",
      "exception": false,
-     "start_time": "2022-01-11T13:45:02.561017",
+     "start_time": "2022-02-21T13:26:33.072063",
      "status": "completed"
     },
     "scrolled": false,
@@ -2592,10 +2601,10 @@
    "id": "e0239395",
    "metadata": {
     "papermill": {
-     "duration": 0.121552,
-     "end_time": "2022-01-11T13:45:07.820672",
+     "duration": 0.124858,
+     "end_time": "2022-02-21T13:26:38.476070",
      "exception": false,
-     "start_time": "2022-01-11T13:45:07.699120",
+     "start_time": "2022-02-21T13:26:38.351212",
      "status": "completed"
     },
     "tags": []
@@ -2610,16 +2619,16 @@
    "id": "f6b92bfe",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:08.076466Z",
-     "iopub.status.busy": "2022-01-11T13:45:08.075772Z",
-     "iopub.status.idle": "2022-01-11T13:45:08.078093Z",
-     "shell.execute_reply": "2022-01-11T13:45:08.078616Z"
+     "iopub.execute_input": "2022-02-21T13:26:38.726346Z",
+     "iopub.status.busy": "2022-02-21T13:26:38.726007Z",
+     "iopub.status.idle": "2022-02-21T13:26:38.736376Z",
+     "shell.execute_reply": "2022-02-21T13:26:38.735645Z"
     },
     "papermill": {
-     "duration": 0.13591,
-     "end_time": "2022-01-11T13:45:08.078791",
+     "duration": 0.138104,
+     "end_time": "2022-02-21T13:26:38.738344",
      "exception": false,
-     "start_time": "2022-01-11T13:45:07.942881",
+     "start_time": "2022-02-21T13:26:38.600240",
      "status": "completed"
     },
     "tags": []
@@ -2656,10 +2665,10 @@
    "id": "dfb6a404",
    "metadata": {
     "papermill": {
-     "duration": 0.122397,
-     "end_time": "2022-01-11T13:45:08.323234",
+     "duration": 0.127219,
+     "end_time": "2022-02-21T13:26:38.990680",
      "exception": false,
-     "start_time": "2022-01-11T13:45:08.200837",
+     "start_time": "2022-02-21T13:26:38.863461",
      "status": "completed"
     },
     "tags": []
@@ -2674,16 +2683,16 @@
    "id": "854a9486",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:08.576129Z",
-     "iopub.status.busy": "2022-01-11T13:45:08.571481Z",
-     "iopub.status.idle": "2022-01-11T13:45:08.578690Z",
-     "shell.execute_reply": "2022-01-11T13:45:08.579204Z"
+     "iopub.execute_input": "2022-02-21T13:26:39.248186Z",
+     "iopub.status.busy": "2022-02-21T13:26:39.247849Z",
+     "iopub.status.idle": "2022-02-21T13:26:39.255181Z",
+     "shell.execute_reply": "2022-02-21T13:26:39.254270Z"
     },
     "papermill": {
-     "duration": 0.134067,
-     "end_time": "2022-01-11T13:45:08.579415",
+     "duration": 0.136314,
+     "end_time": "2022-02-21T13:26:39.257218",
      "exception": false,
-     "start_time": "2022-01-11T13:45:08.445348",
+     "start_time": "2022-02-21T13:26:39.120904",
      "status": "completed"
     },
     "tags": []
@@ -2711,16 +2720,16 @@
    "id": "5960da85",
    "metadata": {
     "papermill": {
-     "duration": 0.125766,
-     "end_time": "2022-01-11T13:45:08.831138",
+     "duration": 0.125169,
+     "end_time": "2022-02-21T13:26:39.507855",
      "exception": false,
-     "start_time": "2022-01-11T13:45:08.705372",
+     "start_time": "2022-02-21T13:26:39.382686",
      "status": "completed"
     },
     "tags": []
    },
    "source": [
-    "## 8. 60A-80A-120A circuits (metadata to be updated)"
+    "## 8. 60A-80A-120A circuits"
    ]
   },
   {
@@ -2729,16 +2738,16 @@
    "id": "e17886b9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:09.109740Z",
-     "iopub.status.busy": "2022-01-11T13:45:09.109016Z",
-     "iopub.status.idle": "2022-01-11T13:45:22.455349Z",
-     "shell.execute_reply": "2022-01-11T13:45:22.454663Z"
+     "iopub.execute_input": "2022-02-21T13:26:39.761305Z",
+     "iopub.status.busy": "2022-02-21T13:26:39.760803Z",
+     "iopub.status.idle": "2022-02-21T13:26:53.441458Z",
+     "shell.execute_reply": "2022-02-21T13:26:53.440614Z"
     },
     "papermill": {
-     "duration": 13.498623,
-     "end_time": "2022-01-11T13:45:22.455515",
+     "duration": 13.810266,
+     "end_time": "2022-02-21T13:26:53.443668",
      "exception": false,
-     "start_time": "2022-01-11T13:45:08.956892",
+     "start_time": "2022-02-21T13:26:39.633402",
      "status": "completed"
     },
     "scrolled": false,
@@ -2747,7 +2756,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1008x504 with 1 Axes>"
       ]
@@ -2782,10 +2791,10 @@
    "id": "0edb3097",
    "metadata": {
     "papermill": {
-     "duration": 0.12469,
-     "end_time": "2022-01-11T13:45:22.706007",
+     "duration": 0.126579,
+     "end_time": "2022-02-21T13:26:53.697679",
      "exception": false,
-     "start_time": "2022-01-11T13:45:22.581317",
+     "start_time": "2022-02-21T13:26:53.571100",
      "status": "completed"
     },
     "tags": []
@@ -2800,16 +2809,16 @@
    "id": "33fa95b5",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:22.967364Z",
-     "iopub.status.busy": "2022-01-11T13:45:22.966698Z",
-     "iopub.status.idle": "2022-01-11T13:45:22.969631Z",
-     "shell.execute_reply": "2022-01-11T13:45:22.969071Z"
+     "iopub.execute_input": "2022-02-21T13:26:53.953361Z",
+     "iopub.status.busy": "2022-02-21T13:26:53.953019Z",
+     "iopub.status.idle": "2022-02-21T13:26:53.960161Z",
+     "shell.execute_reply": "2022-02-21T13:26:53.959465Z"
     },
     "papermill": {
-     "duration": 0.138531,
-     "end_time": "2022-01-11T13:45:22.969775",
+     "duration": 0.138834,
+     "end_time": "2022-02-21T13:26:53.962763",
      "exception": false,
-     "start_time": "2022-01-11T13:45:22.831244",
+     "start_time": "2022-02-21T13:26:53.823929",
      "status": "completed"
     },
     "tags": []
@@ -2837,10 +2846,10 @@
    "id": "616ccb4b",
    "metadata": {
     "papermill": {
-     "duration": 0.125249,
-     "end_time": "2022-01-11T13:45:23.220206",
+     "duration": 0.12709,
+     "end_time": "2022-02-21T13:26:54.217103",
      "exception": false,
-     "start_time": "2022-01-11T13:45:23.094957",
+     "start_time": "2022-02-21T13:26:54.090013",
      "status": "completed"
     },
     "tags": []
@@ -2855,16 +2864,16 @@
    "id": "cbcfa560",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:23.476456Z",
-     "iopub.status.busy": "2022-01-11T13:45:23.475770Z",
-     "iopub.status.idle": "2022-01-11T13:45:23.478231Z",
-     "shell.execute_reply": "2022-01-11T13:45:23.477585Z"
+     "iopub.execute_input": "2022-02-21T13:26:54.474987Z",
+     "iopub.status.busy": "2022-02-21T13:26:54.474679Z",
+     "iopub.status.idle": "2022-02-21T13:26:54.478683Z",
+     "shell.execute_reply": "2022-02-21T13:26:54.477926Z"
     },
     "papermill": {
-     "duration": 0.132572,
-     "end_time": "2022-01-11T13:45:23.478376",
+     "duration": 0.135544,
+     "end_time": "2022-02-21T13:26:54.480601",
      "exception": false,
-     "start_time": "2022-01-11T13:45:23.345804",
+     "start_time": "2022-02-21T13:26:54.345057",
      "status": "completed"
     },
     "tags": []
@@ -2881,16 +2890,16 @@
    "id": "ece2a7d3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:45:23.743493Z",
-     "iopub.status.busy": "2022-01-11T13:45:23.742779Z",
-     "iopub.status.idle": "2022-01-11T13:45:33.114008Z",
-     "shell.execute_reply": "2022-01-11T13:45:33.113210Z"
+     "iopub.execute_input": "2022-02-21T13:26:54.743329Z",
+     "iopub.status.busy": "2022-02-21T13:26:54.742987Z",
+     "iopub.status.idle": "2022-02-21T13:27:04.742614Z",
+     "shell.execute_reply": "2022-02-21T13:27:04.741534Z"
     },
     "papermill": {
-     "duration": 9.510566,
-     "end_time": "2022-01-11T13:45:33.114185",
+     "duration": 10.13496,
+     "end_time": "2022-02-21T13:27:04.745397",
      "exception": false,
-     "start_time": "2022-01-11T13:45:23.603619",
+     "start_time": "2022-02-21T13:26:54.610437",
      "status": "completed"
     },
     "scrolled": false,
@@ -2951,7 +2960,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[NbConvertApp] Writing 463252 bytes to ./results/reports/AN_PGC1.html\r\n"
+      "[NbConvertApp] Writing 463374 bytes to ./results/reports/AN_PGC1.html\r\n"
      ]
     }
    ],
@@ -2970,6 +2979,23 @@
     "Time.sleep(5)\n",
     "!{sys.executable} -m jupyter nbconvert --to html $path_to_notebook --output-dir $report_destination_path --output $html_filename --TemplateExporter.exclude_input=True --TagRemovePreprocessor.remove_all_outputs_tags skip_output --TagRemovePreprocessor.remove_cell_tags skip_cell"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "19083843",
+   "metadata": {
+    "papermill": {
+     "duration": 0.132351,
+     "end_time": "2022-02-21T13:27:05.011212",
+     "exception": false,
+     "start_time": "2022-02-21T13:27:04.878861",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -2992,8 +3018,8 @@
   },
   "papermill": {
    "default_parameters": {},
-   "duration": 1474.695284,
-   "end_time": "2022-01-11T13:45:33.958951",
+   "duration": 1793.525673,
+   "end_time": "2022-02-21T13:27:05.969948",
    "environment_variables": {},
    "exception": null,
    "input_path": "/builds/LHCData/lhc-sm-hwc/test/../pgc/AN_PGC1.ipynb",
@@ -3010,8 +3036,8 @@
     "t_end": "2021-06-07 16:55:11.684000000",
     "t_start": "2021-06-07 16:55:11.672000000"
    },
-   "start_time": "2022-01-11T13:20:59.263667",
-   "version": "2.3.3"
+   "start_time": "2022-02-21T12:57:12.444275",
+   "version": "2.3.4"
   },
   "sparkconnect": {
    "bundled_options": [
diff --git a/test/resources/notebooks/result_AN_PGC3.ipynb b/test/resources/notebooks/result_AN_PGC3.ipynb
index 409973c3..5965d030 100644
--- a/test/resources/notebooks/result_AN_PGC3.ipynb
+++ b/test/resources/notebooks/result_AN_PGC3.ipynb
@@ -3,19 +3,19 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "6f228404",
+   "id": "35fd1fe9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:22:42.982747Z",
-     "iopub.status.busy": "2022-01-11T13:22:42.982030Z",
-     "iopub.status.idle": "2022-01-11T13:23:19.002811Z",
-     "shell.execute_reply": "2022-01-11T13:23:19.000362Z"
+     "iopub.execute_input": "2022-02-21T12:56:06.458007Z",
+     "iopub.status.busy": "2022-02-21T12:56:06.457615Z",
+     "iopub.status.idle": "2022-02-21T12:56:40.707304Z",
+     "shell.execute_reply": "2022-02-21T12:56:40.706112Z"
     },
     "papermill": {
-     "duration": 36.095218,
-     "end_time": "2022-01-11T13:23:19.003027",
+     "duration": 34.302662,
+     "end_time": "2022-02-21T12:56:40.714843",
      "exception": false,
-     "start_time": "2022-01-11T13:22:42.907809",
+     "start_time": "2022-02-21T12:56:06.412181",
      "status": "completed"
     }
    },
@@ -73,10 +73,10 @@
    "id": "bddfc06f",
    "metadata": {
     "papermill": {
-     "duration": 0.04327,
-     "end_time": "2022-01-11T13:23:19.095753",
+     "duration": 0.041428,
+     "end_time": "2022-02-21T12:56:40.800314",
      "exception": false,
-     "start_time": "2022-01-11T13:23:19.052483",
+     "start_time": "2022-02-21T12:56:40.758886",
      "status": "completed"
     },
     "tags": []
@@ -90,10 +90,10 @@
    "id": "211ec43f",
    "metadata": {
     "papermill": {
-     "duration": 0.041243,
-     "end_time": "2022-01-11T13:23:19.178431",
+     "duration": 0.043503,
+     "end_time": "2022-02-21T12:56:40.885840",
      "exception": false,
-     "start_time": "2022-01-11T13:23:19.137188",
+     "start_time": "2022-02-21T12:56:40.842337",
      "status": "completed"
     },
     "tags": []
@@ -145,10 +145,10 @@
    "id": "9cda6b85",
    "metadata": {
     "papermill": {
-     "duration": 0.041223,
-     "end_time": "2022-01-11T13:23:19.261104",
+     "duration": 0.04197,
+     "end_time": "2022-02-21T12:56:40.972313",
      "exception": false,
-     "start_time": "2022-01-11T13:23:19.219881",
+     "start_time": "2022-02-21T12:56:40.930343",
      "status": "completed"
     },
     "tags": []
@@ -163,16 +163,16 @@
    "id": "d6cf3461",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:19.360460Z",
-     "iopub.status.busy": "2022-01-11T13:23:19.359749Z",
-     "iopub.status.idle": "2022-01-11T13:23:22.746616Z",
-     "shell.execute_reply": "2022-01-11T13:23:22.745937Z"
+     "iopub.execute_input": "2022-02-21T12:56:41.058579Z",
+     "iopub.status.busy": "2022-02-21T12:56:41.058215Z",
+     "iopub.status.idle": "2022-02-21T12:56:44.916374Z",
+     "shell.execute_reply": "2022-02-21T12:56:44.915339Z"
     },
     "papermill": {
-     "duration": 3.44428,
-     "end_time": "2022-01-11T13:23:22.746777",
+     "duration": 3.90422,
+     "end_time": "2022-02-21T12:56:44.918373",
      "exception": false,
-     "start_time": "2022-01-11T13:23:19.302497",
+     "start_time": "2022-02-21T12:56:41.014153",
      "status": "completed"
     },
     "tags": []
@@ -224,16 +224,16 @@
    "id": "49dcd5e6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:22.837918Z",
-     "iopub.status.busy": "2022-01-11T13:23:22.837245Z",
-     "iopub.status.idle": "2022-01-11T13:23:22.840169Z",
-     "shell.execute_reply": "2022-01-11T13:23:22.839531Z"
+     "iopub.execute_input": "2022-02-21T12:56:45.007619Z",
+     "iopub.status.busy": "2022-02-21T12:56:45.007258Z",
+     "iopub.status.idle": "2022-02-21T12:56:45.013346Z",
+     "shell.execute_reply": "2022-02-21T12:56:45.012579Z"
     },
     "papermill": {
-     "duration": 0.050742,
-     "end_time": "2022-01-11T13:23:22.840311",
+     "duration": 0.051632,
+     "end_time": "2022-02-21T12:56:45.015264",
      "exception": false,
-     "start_time": "2022-01-11T13:23:22.789569",
+     "start_time": "2022-02-21T12:56:44.963632",
      "status": "completed"
     },
     "tags": []
@@ -243,8 +243,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Analysis executed with lhc-sm-api version: 1.5.18\n",
-      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.66\n",
+      "Analysis executed with lhc-sm-api version: 1.5.19\n",
+      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.67\n",
       "user = root\n"
      ]
     }
@@ -263,16 +263,16 @@
    "id": "9547db78",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:22.929674Z",
-     "iopub.status.busy": "2022-01-11T13:23:22.929003Z",
-     "iopub.status.idle": "2022-01-11T13:23:22.931439Z",
-     "shell.execute_reply": "2022-01-11T13:23:22.930779Z"
+     "iopub.execute_input": "2022-02-21T12:56:45.103651Z",
+     "iopub.status.busy": "2022-02-21T12:56:45.103304Z",
+     "iopub.status.idle": "2022-02-21T12:56:45.107339Z",
+     "shell.execute_reply": "2022-02-21T12:56:45.106568Z"
     },
     "papermill": {
-     "duration": 0.049054,
-     "end_time": "2022-01-11T13:23:22.931583",
+     "duration": 0.050557,
+     "end_time": "2022-02-21T12:56:45.109189",
      "exception": false,
-     "start_time": "2022-01-11T13:23:22.882529",
+     "start_time": "2022-02-21T12:56:45.058632",
      "status": "completed"
     },
     "tags": []
@@ -289,10 +289,10 @@
    "id": "65ce0028",
    "metadata": {
     "papermill": {
-     "duration": 0.042521,
-     "end_time": "2022-01-11T13:23:23.016527",
+     "duration": 0.042774,
+     "end_time": "2022-02-21T12:56:45.194720",
      "exception": false,
-     "start_time": "2022-01-11T13:23:22.974006",
+     "start_time": "2022-02-21T12:56:45.151946",
      "status": "completed"
     },
     "tags": []
@@ -306,10 +306,10 @@
    "id": "93e660b6",
    "metadata": {
     "papermill": {
-     "duration": 0.044503,
-     "end_time": "2022-01-11T13:23:23.103403",
+     "duration": 0.04268,
+     "end_time": "2022-02-21T12:56:45.280257",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.058900",
+     "start_time": "2022-02-21T12:56:45.237577",
      "status": "completed"
     },
     "tags": []
@@ -325,16 +325,16 @@
    "id": "622b9fc3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:23.194174Z",
-     "iopub.status.busy": "2022-01-11T13:23:23.193513Z",
-     "iopub.status.idle": "2022-01-11T13:23:23.196646Z",
-     "shell.execute_reply": "2022-01-11T13:23:23.196120Z"
+     "iopub.execute_input": "2022-02-21T12:56:45.368062Z",
+     "iopub.status.busy": "2022-02-21T12:56:45.367717Z",
+     "iopub.status.idle": "2022-02-21T12:56:45.372477Z",
+     "shell.execute_reply": "2022-02-21T12:56:45.371594Z"
     },
     "papermill": {
-     "duration": 0.050104,
-     "end_time": "2022-01-11T13:23:23.196790",
+     "duration": 0.051479,
+     "end_time": "2022-02-21T12:56:45.374523",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.146686",
+     "start_time": "2022-02-21T12:56:45.323044",
      "status": "completed"
     },
     "tags": [
@@ -343,25 +343,31 @@
    },
    "outputs": [],
    "source": [
-    "#User input fromACCTESTING here\n"
+    "#User input fromACCTESTING here\n",
+    "hwc_test = 'PGC.3'\n",
+    "circuit_name = 'RB.A56'\n",
+    "campaign = 'Recommissioning post LS2'\n",
+    "t_start = '2021-08-01 11:13:58.294000000'\n",
+    "t_end = '2021-08-01 12:28:58.294'\n",
+    "t_end_sec = '4500'"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "cc9fceb2",
+   "id": "a637fce2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:23.288797Z",
-     "iopub.status.busy": "2022-01-11T13:23:23.288122Z",
-     "iopub.status.idle": "2022-01-11T13:23:23.290895Z",
-     "shell.execute_reply": "2022-01-11T13:23:23.290337Z"
+     "iopub.execute_input": "2022-02-21T12:56:45.464100Z",
+     "iopub.status.busy": "2022-02-21T12:56:45.463749Z",
+     "iopub.status.idle": "2022-02-21T12:56:45.468889Z",
+     "shell.execute_reply": "2022-02-21T12:56:45.468060Z"
     },
     "papermill": {
-     "duration": 0.051949,
-     "end_time": "2022-01-11T13:23:23.291044",
+     "duration": 0.052165,
+     "end_time": "2022-02-21T12:56:45.470771",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.239095",
+     "start_time": "2022-02-21T12:56:45.418606",
      "status": "completed"
     },
     "tags": [
@@ -389,16 +395,16 @@
    "id": "bbd53e38",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:23.382454Z",
-     "iopub.status.busy": "2022-01-11T13:23:23.381775Z",
-     "iopub.status.idle": "2022-01-11T13:23:23.384571Z",
-     "shell.execute_reply": "2022-01-11T13:23:23.385054Z"
+     "iopub.execute_input": "2022-02-21T12:56:45.564912Z",
+     "iopub.status.busy": "2022-02-21T12:56:45.564584Z",
+     "iopub.status.idle": "2022-02-21T12:56:45.575430Z",
+     "shell.execute_reply": "2022-02-21T12:56:45.574646Z"
     },
     "papermill": {
-     "duration": 0.051153,
-     "end_time": "2022-01-11T13:23:23.385228",
+     "duration": 0.069052,
+     "end_time": "2022-02-21T12:56:45.582841",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.334075",
+     "start_time": "2022-02-21T12:56:45.513789",
      "status": "completed"
     },
     "tags": []
@@ -425,10 +431,10 @@
    "id": "b8c31c41",
    "metadata": {
     "papermill": {
-     "duration": 0.043449,
-     "end_time": "2022-01-11T13:23:23.471799",
+     "duration": 0.04322,
+     "end_time": "2022-02-21T12:56:45.669750",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.428350",
+     "start_time": "2022-02-21T12:56:45.626530",
      "status": "completed"
     },
     "tags": []
@@ -443,16 +449,16 @@
    "id": "20e13f0c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:23.565615Z",
-     "iopub.status.busy": "2022-01-11T13:23:23.564907Z",
-     "iopub.status.idle": "2022-01-11T13:23:23.577363Z",
-     "shell.execute_reply": "2022-01-11T13:23:23.576834Z"
+     "iopub.execute_input": "2022-02-21T12:56:45.759180Z",
+     "iopub.status.busy": "2022-02-21T12:56:45.758849Z",
+     "iopub.status.idle": "2022-02-21T12:56:45.786411Z",
+     "shell.execute_reply": "2022-02-21T12:56:45.784911Z"
     },
     "papermill": {
-     "duration": 0.062029,
-     "end_time": "2022-01-11T13:23:23.577530",
+     "duration": 0.080709,
+     "end_time": "2022-02-21T12:56:45.794114",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.515501",
+     "start_time": "2022-02-21T12:56:45.713405",
      "status": "completed"
     },
     "tags": []
@@ -472,9 +478,9 @@
     "lhc_circuit = meta_df[lambda x: x['Circuit name'] == circuit_name]\n",
     "\n",
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'] == safety_subsector]\n",
+    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -482,10 +488,10 @@
    "id": "22e4ac90",
    "metadata": {
     "papermill": {
-     "duration": 0.045293,
-     "end_time": "2022-01-11T13:23:23.667868",
+     "duration": 0.04611,
+     "end_time": "2022-02-21T12:56:45.884881",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.622575",
+     "start_time": "2022-02-21T12:56:45.838771",
      "status": "completed"
     },
     "tags": []
@@ -501,16 +507,16 @@
    "id": "0ca7cae6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:23.767351Z",
-     "iopub.status.busy": "2022-01-11T13:23:23.766671Z",
-     "iopub.status.idle": "2022-01-11T13:23:23.774211Z",
-     "shell.execute_reply": "2022-01-11T13:23:23.773681Z"
+     "iopub.execute_input": "2022-02-21T12:56:45.987127Z",
+     "iopub.status.busy": "2022-02-21T12:56:45.986793Z",
+     "iopub.status.idle": "2022-02-21T12:56:46.019509Z",
+     "shell.execute_reply": "2022-02-21T12:56:46.018569Z"
     },
     "papermill": {
-     "duration": 0.062529,
-     "end_time": "2022-01-11T13:23:23.774362",
+     "duration": 0.093445,
+     "end_time": "2022-02-21T12:56:46.024235",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.711833",
+     "start_time": "2022-02-21T12:56:45.930790",
      "status": "completed"
     },
     "tags": []
@@ -540,8 +546,8 @@
     "    t_end = Time.to_string_short((Time.to_unix_timestamp(t_start) + (5 * 60) * 1e9))\n",
     "t_end_sec = int((Time.to_unix_timestamp(t_end) - Time.to_unix_timestamp(t_start))*1e-9)\n",
     "#\n",
-    "t_start_utc = Time.to_string_short((Time.to_unix_timestamp(t_start) - 2 * 3600 * 1e9))\n",
-    "t_end_utc = Time.to_string_short((Time.to_unix_timestamp(t_end) - 2 * 3600 * 1e9))\n",
+    "t_start_timestamp = Time.to_unix_timestamp(t_start)\n",
+    "t_end_timestamp = Time.to_unix_timestamp(t_end)\n",
     "#\n",
     "print('hwc_test = \\'%s\\'\\ncircuit_name = \\'%s\\'\\ncampaign = \\'%s\\'\\nt_start = \\'%s\\'\\nt_end = \\'%s\\'\\nt_end_sec = \\'%s\\'' % (hwc_test, circuit_name, campaign, t_start, t_end, t_end_sec))"
    ]
@@ -551,10 +557,10 @@
    "id": "d5d77dca",
    "metadata": {
     "papermill": {
-     "duration": 0.044246,
-     "end_time": "2022-01-11T13:23:23.862812",
+     "duration": 0.045334,
+     "end_time": "2022-02-21T12:56:46.115110",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.818566",
+     "start_time": "2022-02-21T12:56:46.069776",
      "status": "completed"
     },
     "tags": []
@@ -569,16 +575,16 @@
    "id": "d2b2881b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:23.957516Z",
-     "iopub.status.busy": "2022-01-11T13:23:23.956780Z",
-     "iopub.status.idle": "2022-01-11T13:23:23.959006Z",
-     "shell.execute_reply": "2022-01-11T13:23:23.959522Z"
+     "iopub.execute_input": "2022-02-21T12:56:46.207830Z",
+     "iopub.status.busy": "2022-02-21T12:56:46.207507Z",
+     "iopub.status.idle": "2022-02-21T12:56:46.211940Z",
+     "shell.execute_reply": "2022-02-21T12:56:46.211278Z"
     },
     "papermill": {
-     "duration": 0.051995,
-     "end_time": "2022-01-11T13:23:23.959688",
+     "duration": 0.054354,
+     "end_time": "2022-02-21T12:56:46.213985",
      "exception": false,
-     "start_time": "2022-01-11T13:23:23.907693",
+     "start_time": "2022-02-21T12:56:46.159631",
      "status": "completed"
     },
     "tags": []
@@ -597,16 +603,16 @@
    "id": "1a5123b9",
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2022-01-11T13:23:24.059066Z"
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-     "end_time": "2022-01-11T13:23:24.059248",
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@@ -633,16 +639,16 @@
    "id": "38d02a39",
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2022-01-11T13:23:24.167767Z"
+     "iopub.execute_input": "2022-02-21T12:56:46.406330Z",
+     "iopub.status.busy": "2022-02-21T12:56:46.406027Z",
+     "iopub.status.idle": "2022-02-21T12:56:46.419600Z",
+     "shell.execute_reply": "2022-02-21T12:56:46.418893Z"
     },
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-     "duration": 0.061989,
-     "end_time": "2022-01-11T13:23:24.168495",
+     "duration": 0.062282,
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      "exception": false,
-     "start_time": "2022-01-11T13:23:24.106506",
+     "start_time": "2022-02-21T12:56:46.359145",
      "status": "completed"
     },
     "scrolled": false,
@@ -671,10 +677,10 @@
    "id": "01f3fdd0",
    "metadata": {
     "papermill": {
-     "duration": 0.049398,
-     "end_time": "2022-01-11T13:23:24.263207",
+     "duration": 0.045571,
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      "exception": false,
-     "start_time": "2022-01-11T13:23:24.213809",
+     "start_time": "2022-02-21T12:56:46.467124",
      "status": "completed"
     },
     "tags": []
@@ -689,16 +695,16 @@
    "id": "9218db46",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:24.362731Z",
-     "iopub.status.busy": "2022-01-11T13:23:24.362014Z",
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-     "shell.execute_reply": "2022-01-11T13:23:24.364678Z"
+     "iopub.execute_input": "2022-02-21T12:56:46.606594Z",
+     "iopub.status.busy": "2022-02-21T12:56:46.606259Z",
+     "iopub.status.idle": "2022-02-21T12:56:46.613566Z",
+     "shell.execute_reply": "2022-02-21T12:56:46.612925Z"
     },
     "papermill": {
-     "duration": 0.056767,
-     "end_time": "2022-01-11T13:23:24.365400",
+     "duration": 0.056449,
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      "exception": false,
-     "start_time": "2022-01-11T13:23:24.308633",
+     "start_time": "2022-02-21T12:56:46.559011",
      "status": "completed"
     },
     "tags": []
@@ -709,9 +715,9 @@
      "output_type": "stream",
      "text": [
       "Circuit type SIGMON\n",
-      "600A       47\n",
+      "600A       49\n",
       "60A        94\n",
-      "80-120A    16\n",
+      "80-120A    18\n",
       "IPQ2        3\n",
       "IPQ4        1\n",
       "RB          1\n",
@@ -729,10 +735,10 @@
    "id": "c9f9c03b",
    "metadata": {
     "papermill": {
-     "duration": 0.047172,
-     "end_time": "2022-01-11T13:23:24.460088",
+     "duration": 0.046901,
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      "exception": false,
-     "start_time": "2022-01-11T13:23:24.412916",
+     "start_time": "2022-02-21T12:56:46.662593",
      "status": "completed"
     },
     "tags": []
@@ -747,16 +753,16 @@
    "id": "9226f736",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:24.563246Z",
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-     "shell.execute_reply": "2022-01-11T13:23:24.565657Z"
+     "iopub.execute_input": "2022-02-21T12:56:46.805591Z",
+     "iopub.status.busy": "2022-02-21T12:56:46.805263Z",
+     "iopub.status.idle": "2022-02-21T12:56:46.811944Z",
+     "shell.execute_reply": "2022-02-21T12:56:46.811279Z"
     },
     "papermill": {
-     "duration": 0.058005,
-     "end_time": "2022-01-11T13:23:24.566366",
+     "duration": 0.057963,
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      "exception": false,
-     "start_time": "2022-01-11T13:23:24.508361",
+     "start_time": "2022-02-21T12:56:46.756062",
      "status": "completed"
     },
     "tags": []
@@ -767,9 +773,9 @@
      "output_type": "stream",
      "text": [
       "pgc_group\n",
-      "pgc_120A    110\n",
+      "pgc_120A    112\n",
       "pgc_13kA      3\n",
-      "pgc_600A     47\n",
+      "pgc_600A     49\n",
       "pgc_6kA       4\n",
       "Name: Circuit name, dtype: int64\n"
      ]
@@ -784,10 +790,10 @@
    "id": "9089d72c",
    "metadata": {
     "papermill": {
-     "duration": 0.0471,
-     "end_time": "2022-01-11T13:23:24.660119",
+     "duration": 0.048452,
+     "end_time": "2022-02-21T12:56:46.909432",
      "exception": false,
-     "start_time": "2022-01-11T13:23:24.613019",
+     "start_time": "2022-02-21T12:56:46.860980",
      "status": "completed"
     },
     "tags": []
@@ -801,10 +807,10 @@
    "id": "4fd71c69",
    "metadata": {
     "papermill": {
-     "duration": 0.046943,
-     "end_time": "2022-01-11T13:23:24.754285",
+     "duration": 0.046607,
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      "exception": false,
-     "start_time": "2022-01-11T13:23:24.707342",
+     "start_time": "2022-02-21T12:56:46.956072",
      "status": "completed"
     },
     "tags": []
@@ -822,16 +828,16 @@
    "id": "31770057",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:23:24.856777Z",
-     "iopub.status.busy": "2022-01-11T13:23:24.856093Z",
-     "iopub.status.idle": "2022-01-11T13:23:24.859930Z",
-     "shell.execute_reply": "2022-01-11T13:23:24.859341Z"
+     "iopub.execute_input": "2022-02-21T12:56:47.099098Z",
+     "iopub.status.busy": "2022-02-21T12:56:47.098760Z",
+     "iopub.status.idle": "2022-02-21T12:56:47.106770Z",
+     "shell.execute_reply": "2022-02-21T12:56:47.106069Z"
     },
     "papermill": {
-     "duration": 0.058977,
-     "end_time": "2022-01-11T13:23:24.860084",
+     "duration": 0.058878,
+     "end_time": "2022-02-21T12:56:47.108631",
      "exception": false,
-     "start_time": "2022-01-11T13:23:24.801107",
+     "start_time": "2022-02-21T12:56:47.049753",
      "status": "completed"
     },
     "tags": []
@@ -860,7 +866,6 @@
     }
    ],
    "source": [
-    "#condemned_circuits = ['RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCSX3.L2', 'RCTX3.L2', 'RSS.A34B1']\n",
     "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
     "display(condemned_circuits)"
    ]
@@ -870,10 +875,10 @@
    "id": "3bdf96d4",
    "metadata": {
     "papermill": {
-     "duration": 0.047538,
-     "end_time": "2022-01-11T13:23:24.955306",
+     "duration": 0.047808,
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      "exception": false,
-     "start_time": "2022-01-11T13:23:24.907768",
+     "start_time": "2022-02-21T12:56:47.156468",
      "status": "completed"
     },
     "tags": []
@@ -888,16 +893,16 @@
    "id": "ee1872f7",
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2022-01-11T13:32:20.395269Z"
+     "iopub.execute_input": "2022-02-21T12:56:47.301561Z",
+     "iopub.status.busy": "2022-02-21T12:56:47.301232Z",
+     "iopub.status.idle": "2022-02-21T13:16:08.099071Z",
+     "shell.execute_reply": "2022-02-21T13:16:08.098292Z"
     },
     "papermill": {
-     "duration": 535.392686,
-     "end_time": "2022-01-11T13:32:20.395666",
+     "duration": 1160.849573,
+     "end_time": "2022-02-21T13:16:08.101597",
      "exception": false,
-     "start_time": "2022-01-11T13:23:25.002980",
+     "start_time": "2022-02-21T12:56:47.252024",
      "status": "completed"
     },
     "scrolled": false,
@@ -1036,252 +1041,266 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "11 type = 600A , name = RQS.A34B2 , Imax = 550 , Imin = 0\n"
+      "11 type = 600A , name = RQ6.R3B1 , Imax = 400 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "12 type = 600A , name = RQS.L4B1 , Imax = 550 , Imin = 0\n"
+      "12 type = 600A , name = RQ6.R3B2 , Imax = 400 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "13 type = 600A , name = RQS.R3B1 , Imax = 550 , Imin = 0\n"
+      "13 type = 600A , name = RQS.A34B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "14 type = 600A , name = RQT12.L4B1 , Imax = 550 , Imin = 0\n"
+      "14 type = 600A , name = RQS.L4B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "15 type = 600A , name = RQT12.L4B2 , Imax = 550 , Imin = 0\n"
+      "15 type = 600A , name = RQS.R3B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "16 type = 600A , name = RQT12.R3B1 , Imax = 550 , Imin = 0\n"
+      "16 type = 600A , name = RQT12.L4B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "17 type = 600A , name = RQT12.R3B2 , Imax = 550 , Imin = 0\n"
+      "17 type = 600A , name = RQT12.L4B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "18 type = 600A , name = RQT13.L4B1 , Imax = 550 , Imin = 0\n"
+      "18 type = 600A , name = RQT12.R3B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "19 type = 600A , name = RQT13.L4B2 , Imax = 550 , Imin = 0\n"
+      "19 type = 600A , name = RQT12.R3B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "20 type = 600A , name = RQT13.R3B1 , Imax = 550 , Imin = 0\n"
+      "20 type = 600A , name = RQT13.L4B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "21 type = 600A , name = RQT13.R3B2 , Imax = 550 , Imin = 0\n"
+      "21 type = 600A , name = RQT13.L4B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "22 type = 600A , name = RQTD.A34B1 , Imax = 550 , Imin = 0\n"
+      "22 type = 600A , name = RQT13.R3B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "23 type = 600A , name = RQTD.A34B2 , Imax = 550 , Imin = 0\n"
+      "23 type = 600A , name = RQT13.R3B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "24 type = 600A , name = RQTF.A34B1 , Imax = 550 , Imin = 0\n"
+      "24 type = 600A , name = RQTD.A34B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "25 type = 600A , name = RQTF.A34B2 , Imax = 550 , Imin = 0\n"
+      "25 type = 600A , name = RQTD.A34B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "26 type = 600A , name = RQTL10.R3B1 , Imax = 450 , Imin = 0\n"
+      "26 type = 600A , name = RQTF.A34B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "27 type = 600A , name = RQTL10.R3B2 , Imax = 450 , Imin = 0\n"
+      "27 type = 600A , name = RQTF.A34B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "28 type = 600A , name = RQTL11.L4B1 , Imax = 550 , Imin = 0\n"
+      "28 type = 600A , name = RQTL10.R3B1 , Imax = 450 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "29 type = 600A , name = RQTL11.L4B2 , Imax = 550 , Imin = 0\n"
+      "29 type = 600A , name = RQTL10.R3B2 , Imax = 450 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "30 type = 600A , name = RQTL11.R3B1 , Imax = 500 , Imin = 0\n"
+      "30 type = 600A , name = RQTL11.L4B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "31 type = 600A , name = RQTL11.R3B2 , Imax = 500 , Imin = 0\n"
+      "31 type = 600A , name = RQTL11.L4B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "32 type = 600A , name = RQTL7.R3B1 , Imax = 550 , Imin = 0\n"
+      "32 type = 600A , name = RQTL11.R3B1 , Imax = 500 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "33 type = 600A , name = RQTL7.R3B2 , Imax = 550 , Imin = -1\n"
+      "33 type = 600A , name = RQTL11.R3B2 , Imax = 500 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "34 type = 600A , name = RQTL8.R3B1 , Imax = 550 , Imin = 0\n"
+      "34 type = 600A , name = RQTL7.R3B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "35 type = 600A , name = RQTL8.R3B2 , Imax = 550 , Imin = 0\n"
+      "35 type = 600A , name = RQTL7.R3B2 , Imax = 550 , Imin = -1\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "36 type = 600A , name = RQTL9.R3B1 , Imax = 450 , Imin = 0\n"
+      "36 type = 600A , name = RQTL8.R3B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "37 type = 600A , name = RQTL9.R3B2 , Imax = 425 , Imin = 0\n"
+      "37 type = 600A , name = RQTL8.R3B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "38 type = 600A , name = RSD1.A34B1 , Imax = 550 , Imin = 0\n"
+      "38 type = 600A , name = RQTL9.R3B1 , Imax = 450 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "39 type = 600A , name = RSD1.A34B2 , Imax = 550 , Imin = 0\n"
+      "39 type = 600A , name = RQTL9.R3B2 , Imax = 425 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "40 type = 600A , name = RSD2.A34B1 , Imax = 550 , Imin = 0\n"
+      "40 type = 600A , name = RSD1.A34B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "41 type = 600A , name = RSD2.A34B2 , Imax = 550 , Imin = 0\n"
+      "41 type = 600A , name = RSD1.A34B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "42 type = 600A , name = RSF1.A34B1 , Imax = 550 , Imin = 0\n"
+      "42 type = 600A , name = RSD2.A34B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "43 type = 600A , name = RSF1.A34B2 , Imax = 550 , Imin = 0\n"
+      "43 type = 600A , name = RSD2.A34B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "44 type = 600A , name = RSF2.A34B1 , Imax = 550 , Imin = 0\n"
+      "44 type = 600A , name = RSF1.A34B1 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "45 type = 600A , name = RSF2.A34B2 , Imax = 550 , Imin = 0\n"
+      "45 type = 600A , name = RSF1.A34B2 , Imax = 550 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "46 type = 600A , name = RSS.A34B2 , Imax = 200 , Imin = 0\n",
+      "46 type = 600A , name = RSF2.A34B1 , Imax = 550 , Imin = 0\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "47 type = 600A , name = RSF2.A34B2 , Imax = 550 , Imin = 0\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "48 type = 600A , name = RSS.A34B2 , Imax = 200 , Imin = 0\n",
       "60A, 80A, 120A circuits\n"
      ]
     },
@@ -1961,99 +1980,113 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "97 type = 80-120A , name = RCBCH7.L4B1 , Imax = 100 , Imin = 0\n"
+      "97 type = 80-120A , name = RCBCH6.R3B2 , Imax = 80 , Imin = 0\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "98 type = 80-120A , name = RCBCH7.L4B1 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "98 type = 80-120A , name = RCBCH7.R3B1 , Imax = 100 , Imin = 0\n"
+      "99 type = 80-120A , name = RCBCH7.R3B1 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "99 type = 80-120A , name = RCBCH8.L4B2 , Imax = 100 , Imin = 0\n"
+      "100 type = 80-120A , name = RCBCH8.L4B2 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "100 type = 80-120A , name = RCBCH8.R3B2 , Imax = 100 , Imin = 0\n"
+      "101 type = 80-120A , name = RCBCH8.R3B2 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "101 type = 80-120A , name = RCBCH9.L4B1 , Imax = 100 , Imin = 0\n"
+      "102 type = 80-120A , name = RCBCH9.L4B1 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "102 type = 80-120A , name = RCBCH9.R3B1 , Imax = 100 , Imin = 0\n"
+      "103 type = 80-120A , name = RCBCH9.R3B1 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "103 type = 80-120A , name = RCBCV10.L4B1 , Imax = 100 , Imin = 0\n"
+      "104 type = 80-120A , name = RCBCV10.L4B1 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "104 type = 80-120A , name = RCBCV10.R3B1 , Imax = 100 , Imin = 0\n"
+      "105 type = 80-120A , name = RCBCV10.R3B1 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "105 type = 80-120A , name = RCBCV7.L4B2 , Imax = 100 , Imin = 0\n"
+      "106 type = 80-120A , name = RCBCV6.R3B1 , Imax = 80 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "106 type = 80-120A , name = RCBCV7.R3B2 , Imax = 100 , Imin = 0\n"
+      "107 type = 80-120A , name = RCBCV7.L4B2 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "107 type = 80-120A , name = RCBCV8.L4B1 , Imax = 100 , Imin = 0\n"
+      "108 type = 80-120A , name = RCBCV7.R3B2 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "108 type = 80-120A , name = RCBCV8.R3B1 , Imax = 100 , Imin = 0\n"
+      "109 type = 80-120A , name = RCBCV8.L4B1 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "109 type = 80-120A , name = RCBCV9.L4B2 , Imax = 100 , Imin = 0\n"
+      "110 type = 80-120A , name = RCBCV8.R3B1 , Imax = 100 , Imin = 0\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "110 type = 80-120A , name = RCBCV9.R3B2 , Imax = 100 , Imin = 0\n",
-      "Elapsed: 535.288 s.\n"
+      "111 type = 80-120A , name = RCBCV9.L4B2 , Imax = 100 , Imin = 0\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "112 type = 80-120A , name = RCBCV9.R3B2 , Imax = 100 , Imin = 0\n",
+      "Elapsed: 1160.752 s.\n"
      ]
     }
    ],
@@ -2169,11 +2202,9 @@
     "                    .with_metadata(circuit_name=circuit_name, system='PC', source='*') \\\n",
     "                    .event_query().df\n",
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_600A_df = pd.concat([source_timestamp_fgc_600A_df, source_timestamp_fgc_df_i], ignore_index=True)                                            \n",
-    "                #j = j + 1\n",
     "        i = i + 1\n",
     "    #\n",
     "    print('60A, 80A, 120A circuits')\n",
-    "    # to be updated to metadata\n",
     "    i = j = 0\n",
     "    i_meas_120A_dfs = []\n",
     "    source_timestamp_fgc_120A_df = pd.DataFrame()\n",
@@ -2183,29 +2214,19 @@
     "            if circuit_type in pgc_120A:\n",
     "                j = j + 1\n",
     "                #print(j, circuit_type, circuit_name)\n",
-    "                df1 = DataQuery.builder(spark).byVariables() \\\n",
-    "                    .system('CMW') \\\n",
-    "                    .startTime(t_start_utc).endTime(t_end_utc) \\\n",
-    "                    .variableLike('%' + circuit_name + ':I_MEAS') \\\n",
-    "                    .buildDataset()\n",
-    "                i_meas_df = df1.select('nxcals_timestamp', 'nxcals_value').sort('nxcals_timestamp').toPandas()\n",
-    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['nxcals_value'].max()), ', Imin =', int(i_meas_df['nxcals_value'].min()))\n",
-    "                if (int(i_meas_df['nxcals_value'].max()) - int(i_meas_df['nxcals_value'].min())) < 10:\n",
-    "                    print('Powering current is too low')\n",
-    "                i_meas_df.rename(columns={'nxcals_timestamp': 'timestamp', 'nxcals_value': circuit_name + ':I_MEAS'}, inplace=True)\n",
-    "                t0 = i_meas_df['timestamp'].loc[0]\n",
-    "                i_meas_df['time'] = (i_meas_df['timestamp'] - t0)*1e-9\n",
-    "                i_meas_df.set_index('time', inplace = True)\n",
-    "                i_meas_df = i_meas_df.drop('timestamp', 1)\n",
-    "#                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
-    "#                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
-    "#                    .with_circuit_type(circuit_type) \\\n",
-    "#                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
-    "#                    .signal_query() \\\n",
-    "#                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
-    "#                    .convert_index_to_sec().dfs[0]\n",
-    "#                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
+    "                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
+    "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
+    "                    .with_circuit_type(circuit_type) \\\n",
+    "                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
+    "                    .signal_query() \\\n",
+    "                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
+    "                    .convert_index_to_sec().dfs[0]\n",
+    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['I_MEAS'].max()), ', Imin =', int(i_meas_df['I_MEAS'].min()))\n",
+    "                if (int(i_meas_df['I_MEAS'].max()) - int(i_meas_df['I_MEAS'].min())) < 10:\n",
+    "                     print('Powering current is too low')\n",
+    "                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
     "                i_meas_120A_dfs.append(i_meas_df)\n",
+    "\n",
     "                source_timestamp_fgc_df_i = QueryBuilder().with_pm() \\\n",
     "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
     "                    .with_circuit_type(circuit_type) \\\n",
@@ -2221,10 +2242,10 @@
    "id": "ac062994",
    "metadata": {
     "papermill": {
-     "duration": 0.116136,
-     "end_time": "2022-01-11T13:32:20.631764",
+     "duration": 0.117662,
+     "end_time": "2022-02-21T13:16:08.339037",
      "exception": false,
-     "start_time": "2022-01-11T13:32:20.515628",
+     "start_time": "2022-02-21T13:16:08.221375",
      "status": "completed"
     },
     "tags": []
@@ -2239,16 +2260,16 @@
    "id": "3c6dca52",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:20.877263Z",
-     "iopub.status.busy": "2022-01-11T13:32:20.876558Z",
-     "iopub.status.idle": "2022-01-11T13:32:21.360509Z",
-     "shell.execute_reply": "2022-01-11T13:32:21.361011Z"
+     "iopub.execute_input": "2022-02-21T13:16:08.576902Z",
+     "iopub.status.busy": "2022-02-21T13:16:08.576565Z",
+     "iopub.status.idle": "2022-02-21T13:16:09.067254Z",
+     "shell.execute_reply": "2022-02-21T13:16:09.066468Z"
     },
     "papermill": {
-     "duration": 0.614105,
-     "end_time": "2022-01-11T13:32:21.361214",
+     "duration": 0.612612,
+     "end_time": "2022-02-21T13:16:09.069832",
      "exception": false,
-     "start_time": "2022-01-11T13:32:20.747109",
+     "start_time": "2022-02-21T13:16:08.457220",
      "status": "completed"
     },
     "scrolled": false,
@@ -2297,10 +2318,10 @@
    "id": "a59781d6",
    "metadata": {
     "papermill": {
-     "duration": 0.117377,
-     "end_time": "2022-01-11T13:32:21.597258",
+     "duration": 0.120851,
+     "end_time": "2022-02-21T13:16:09.310985",
      "exception": false,
-     "start_time": "2022-01-11T13:32:21.479881",
+     "start_time": "2022-02-21T13:16:09.190134",
      "status": "completed"
     },
     "tags": []
@@ -2315,16 +2336,16 @@
    "id": "18356ef1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:21.850644Z",
-     "iopub.status.busy": "2022-01-11T13:32:21.849287Z",
-     "iopub.status.idle": "2022-01-11T13:32:22.446830Z",
-     "shell.execute_reply": "2022-01-11T13:32:22.446276Z"
+     "iopub.execute_input": "2022-02-21T13:16:09.551568Z",
+     "iopub.status.busy": "2022-02-21T13:16:09.551215Z",
+     "iopub.status.idle": "2022-02-21T13:16:10.132652Z",
+     "shell.execute_reply": "2022-02-21T13:16:10.131843Z"
     },
     "papermill": {
-     "duration": 0.732142,
-     "end_time": "2022-01-11T13:32:22.447006",
+     "duration": 0.704228,
+     "end_time": "2022-02-21T13:16:10.135099",
      "exception": false,
-     "start_time": "2022-01-11T13:32:21.714864",
+     "start_time": "2022-02-21T13:16:09.430871",
      "status": "completed"
     },
     "scrolled": false,
@@ -2368,10 +2389,10 @@
    "id": "648eb0c7",
    "metadata": {
     "papermill": {
-     "duration": 0.118542,
-     "end_time": "2022-01-11T13:32:22.684714",
+     "duration": 0.120955,
+     "end_time": "2022-02-21T13:16:10.378245",
      "exception": false,
-     "start_time": "2022-01-11T13:32:22.566172",
+     "start_time": "2022-02-21T13:16:10.257290",
      "status": "completed"
     },
     "tags": []
@@ -2386,16 +2407,16 @@
    "id": "0511d485",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:22.931822Z",
-     "iopub.status.busy": "2022-01-11T13:32:22.931149Z",
-     "iopub.status.idle": "2022-01-11T13:32:22.941495Z",
-     "shell.execute_reply": "2022-01-11T13:32:22.940885Z"
+     "iopub.execute_input": "2022-02-21T13:16:10.622340Z",
+     "iopub.status.busy": "2022-02-21T13:16:10.622008Z",
+     "iopub.status.idle": "2022-02-21T13:16:10.635101Z",
+     "shell.execute_reply": "2022-02-21T13:16:10.634409Z"
     },
     "papermill": {
-     "duration": 0.137868,
-     "end_time": "2022-01-11T13:32:22.941645",
+     "duration": 0.13742,
+     "end_time": "2022-02-21T13:16:10.636980",
      "exception": false,
-     "start_time": "2022-01-11T13:32:22.803777",
+     "start_time": "2022-02-21T13:16:10.499560",
      "status": "completed"
     },
     "tags": []
@@ -2460,10 +2481,10 @@
    "id": "7f7627e6",
    "metadata": {
     "papermill": {
-     "duration": 0.11977,
-     "end_time": "2022-01-11T13:32:23.181203",
+     "duration": 0.122983,
+     "end_time": "2022-02-21T13:16:10.883034",
      "exception": false,
-     "start_time": "2022-01-11T13:32:23.061433",
+     "start_time": "2022-02-21T13:16:10.760051",
      "status": "completed"
     },
     "tags": []
@@ -2478,16 +2499,16 @@
    "id": "68f12f88",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:23.429370Z",
-     "iopub.status.busy": "2022-01-11T13:32:23.428707Z",
-     "iopub.status.idle": "2022-01-11T13:32:23.431985Z",
-     "shell.execute_reply": "2022-01-11T13:32:23.431321Z"
+     "iopub.execute_input": "2022-02-21T13:16:11.141350Z",
+     "iopub.status.busy": "2022-02-21T13:16:11.141021Z",
+     "iopub.status.idle": "2022-02-21T13:16:11.148255Z",
+     "shell.execute_reply": "2022-02-21T13:16:11.147476Z"
     },
     "papermill": {
-     "duration": 0.130503,
-     "end_time": "2022-01-11T13:32:23.432130",
+     "duration": 0.144301,
+     "end_time": "2022-02-21T13:16:11.150446",
      "exception": false,
-     "start_time": "2022-01-11T13:32:23.301627",
+     "start_time": "2022-02-21T13:16:11.006145",
      "status": "completed"
     },
     "tags": []
@@ -2515,10 +2536,10 @@
    "id": "8f6b2ae5",
    "metadata": {
     "papermill": {
-     "duration": 0.120881,
-     "end_time": "2022-01-11T13:32:23.674293",
+     "duration": 0.124116,
+     "end_time": "2022-02-21T13:16:11.398867",
      "exception": false,
-     "start_time": "2022-01-11T13:32:23.553412",
+     "start_time": "2022-02-21T13:16:11.274751",
      "status": "completed"
     },
     "tags": []
@@ -2533,16 +2554,16 @@
    "id": "7e88e73c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:23.948222Z",
-     "iopub.status.busy": "2022-01-11T13:32:23.933422Z",
-     "iopub.status.idle": "2022-01-11T13:32:25.826347Z",
-     "shell.execute_reply": "2022-01-11T13:32:25.825659Z"
+     "iopub.execute_input": "2022-02-21T13:16:11.649229Z",
+     "iopub.status.busy": "2022-02-21T13:16:11.648897Z",
+     "iopub.status.idle": "2022-02-21T13:16:13.560729Z",
+     "shell.execute_reply": "2022-02-21T13:16:13.559652Z"
     },
     "papermill": {
-     "duration": 2.031017,
-     "end_time": "2022-01-11T13:32:25.826518",
+     "duration": 2.039615,
+     "end_time": "2022-02-21T13:16:13.563186",
      "exception": false,
-     "start_time": "2022-01-11T13:32:23.795501",
+     "start_time": "2022-02-21T13:16:11.523571",
      "status": "completed"
     },
     "scrolled": false,
@@ -2551,7 +2572,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1008x720 with 1 Axes>"
       ]
@@ -2586,10 +2607,10 @@
    "id": "2161e061",
    "metadata": {
     "papermill": {
-     "duration": 0.122927,
-     "end_time": "2022-01-11T13:32:26.073758",
+     "duration": 0.125545,
+     "end_time": "2022-02-21T13:16:13.814631",
      "exception": false,
-     "start_time": "2022-01-11T13:32:25.950831",
+     "start_time": "2022-02-21T13:16:13.689086",
      "status": "completed"
     },
     "tags": []
@@ -2604,16 +2625,16 @@
    "id": "f6d06f54",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:26.343618Z",
-     "iopub.status.busy": "2022-01-11T13:32:26.342881Z",
-     "iopub.status.idle": "2022-01-11T13:32:26.573234Z",
-     "shell.execute_reply": "2022-01-11T13:32:26.573765Z"
+     "iopub.execute_input": "2022-02-21T13:16:14.069564Z",
+     "iopub.status.busy": "2022-02-21T13:16:14.069218Z",
+     "iopub.status.idle": "2022-02-21T13:16:14.319253Z",
+     "shell.execute_reply": "2022-02-21T13:16:14.318479Z"
     },
     "papermill": {
-     "duration": 0.375263,
-     "end_time": "2022-01-11T13:32:26.573963",
+     "duration": 0.378944,
+     "end_time": "2022-02-21T13:16:14.321215",
      "exception": false,
-     "start_time": "2022-01-11T13:32:26.198700",
+     "start_time": "2022-02-21T13:16:13.942271",
      "status": "completed"
     },
     "scrolled": false,
@@ -3334,10 +3355,10 @@
    "id": "c16d7aef",
    "metadata": {
     "papermill": {
-     "duration": 0.124984,
-     "end_time": "2022-01-11T13:32:26.824694",
+     "duration": 0.127183,
+     "end_time": "2022-02-21T13:16:14.575735",
      "exception": false,
-     "start_time": "2022-01-11T13:32:26.699710",
+     "start_time": "2022-02-21T13:16:14.448552",
      "status": "completed"
     },
     "tags": []
@@ -3352,16 +3373,16 @@
    "id": "233a33b4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:27.090132Z",
-     "iopub.status.busy": "2022-01-11T13:32:27.089442Z",
-     "iopub.status.idle": "2022-01-11T13:32:27.114636Z",
-     "shell.execute_reply": "2022-01-11T13:32:27.113965Z"
+     "iopub.execute_input": "2022-02-21T13:16:14.833812Z",
+     "iopub.status.busy": "2022-02-21T13:16:14.833495Z",
+     "iopub.status.idle": "2022-02-21T13:16:14.871158Z",
+     "shell.execute_reply": "2022-02-21T13:16:14.870449Z"
     },
     "papermill": {
-     "duration": 0.164806,
-     "end_time": "2022-01-11T13:32:27.114788",
+     "duration": 0.170085,
+     "end_time": "2022-02-21T13:16:14.873054",
      "exception": false,
-     "start_time": "2022-01-11T13:32:26.949982",
+     "start_time": "2022-02-21T13:16:14.702969",
      "status": "completed"
     },
     "scrolled": false,
@@ -3846,16 +3867,16 @@
    "id": "8dfeb8c4",
    "metadata": {
     "papermill": {
-     "duration": 0.131842,
-     "end_time": "2022-01-11T13:32:27.372991",
+     "duration": 0.128979,
+     "end_time": "2022-02-21T13:16:15.131560",
      "exception": false,
-     "start_time": "2022-01-11T13:32:27.241149",
+     "start_time": "2022-02-21T13:16:15.002581",
      "status": "completed"
     },
     "tags": []
    },
    "source": [
-    "## 8. 60A-80A-120A circuits (metadata to be updated)"
+    "## 8. 60A-80A-120A circuits"
    ]
   },
   {
@@ -3864,16 +3885,16 @@
    "id": "66489e71",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:27.671474Z",
-     "iopub.status.busy": "2022-01-11T13:32:27.670694Z",
-     "iopub.status.idle": "2022-01-11T13:32:31.412681Z",
-     "shell.execute_reply": "2022-01-11T13:32:31.413172Z"
+     "iopub.execute_input": "2022-02-21T13:16:15.402279Z",
+     "iopub.status.busy": "2022-02-21T13:16:15.401880Z",
+     "iopub.status.idle": "2022-02-21T13:16:19.265371Z",
+     "shell.execute_reply": "2022-02-21T13:16:19.264623Z"
     },
     "papermill": {
-     "duration": 3.911086,
-     "end_time": "2022-01-11T13:32:31.413366",
+     "duration": 3.997704,
+     "end_time": "2022-02-21T13:16:19.268376",
      "exception": false,
-     "start_time": "2022-01-11T13:32:27.502280",
+     "start_time": "2022-02-21T13:16:15.270672",
      "status": "completed"
     },
     "scrolled": false,
@@ -3882,7 +3903,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1008x504 with 1 Axes>"
       ]
@@ -3917,10 +3938,10 @@
    "id": "31c79c05",
    "metadata": {
     "papermill": {
-     "duration": 0.129614,
-     "end_time": "2022-01-11T13:32:31.676102",
+     "duration": 0.132905,
+     "end_time": "2022-02-21T13:16:19.546601",
      "exception": false,
-     "start_time": "2022-01-11T13:32:31.546488",
+     "start_time": "2022-02-21T13:16:19.413696",
      "status": "completed"
     },
     "tags": []
@@ -3935,16 +3956,16 @@
    "id": "66d9d5ba",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:31.944542Z",
-     "iopub.status.busy": "2022-01-11T13:32:31.943825Z",
-     "iopub.status.idle": "2022-01-11T13:32:31.960677Z",
-     "shell.execute_reply": "2022-01-11T13:32:31.961195Z"
+     "iopub.execute_input": "2022-02-21T13:16:19.814225Z",
+     "iopub.status.busy": "2022-02-21T13:16:19.813901Z",
+     "iopub.status.idle": "2022-02-21T13:16:19.844220Z",
+     "shell.execute_reply": "2022-02-21T13:16:19.843485Z"
     },
     "papermill": {
-     "duration": 0.157801,
-     "end_time": "2022-01-11T13:32:31.961394",
+     "duration": 0.16655,
+     "end_time": "2022-02-21T13:16:19.846089",
      "exception": false,
-     "start_time": "2022-01-11T13:32:31.803593",
+     "start_time": "2022-02-21T13:16:19.679539",
      "status": "completed"
     },
     "scrolled": false,
@@ -4222,10 +4243,10 @@
    "id": "9d552077",
    "metadata": {
     "papermill": {
-     "duration": 0.129506,
-     "end_time": "2022-01-11T13:32:32.220166",
+     "duration": 0.193422,
+     "end_time": "2022-02-21T13:16:20.172760",
      "exception": false,
-     "start_time": "2022-01-11T13:32:32.090660",
+     "start_time": "2022-02-21T13:16:19.979338",
      "status": "completed"
     },
     "tags": []
@@ -4240,16 +4261,16 @@
    "id": "8007c366",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:32.493192Z",
-     "iopub.status.busy": "2022-01-11T13:32:32.492530Z",
-     "iopub.status.idle": "2022-01-11T13:32:32.495484Z",
-     "shell.execute_reply": "2022-01-11T13:32:32.494816Z"
+     "iopub.execute_input": "2022-02-21T13:16:20.454427Z",
+     "iopub.status.busy": "2022-02-21T13:16:20.454102Z",
+     "iopub.status.idle": "2022-02-21T13:16:20.457973Z",
+     "shell.execute_reply": "2022-02-21T13:16:20.457270Z"
     },
     "papermill": {
-     "duration": 0.137639,
-     "end_time": "2022-01-11T13:32:32.495632",
+     "duration": 0.14201,
+     "end_time": "2022-02-21T13:16:20.459994",
      "exception": false,
-     "start_time": "2022-01-11T13:32:32.357993",
+     "start_time": "2022-02-21T13:16:20.317984",
      "status": "completed"
     },
     "tags": []
@@ -4266,16 +4287,16 @@
    "id": "933ece93",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:32:32.769715Z",
-     "iopub.status.busy": "2022-01-11T13:32:32.769012Z",
-     "iopub.status.idle": "2022-01-11T13:32:42.151445Z",
-     "shell.execute_reply": "2022-01-11T13:32:42.152024Z"
+     "iopub.execute_input": "2022-02-21T13:16:20.728670Z",
+     "iopub.status.busy": "2022-02-21T13:16:20.728346Z",
+     "iopub.status.idle": "2022-02-21T13:16:30.298327Z",
+     "shell.execute_reply": "2022-02-21T13:16:30.297301Z"
     },
     "papermill": {
-     "duration": 9.526732,
-     "end_time": "2022-01-11T13:32:42.152267",
+     "duration": 9.70716,
+     "end_time": "2022-02-21T13:16:30.300934",
      "exception": false,
-     "start_time": "2022-01-11T13:32:32.625535",
+     "start_time": "2022-02-21T13:16:20.593774",
      "status": "completed"
     },
     "scrolled": false,
@@ -4336,7 +4357,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[NbConvertApp] Writing 517492 bytes to ./results/reports/AN_PGC3.html\r\n"
+      "[NbConvertApp] Writing 522870 bytes to ./results/reports/AN_PGC3.html\r\n"
      ]
     }
    ],
@@ -4362,10 +4383,10 @@
    "id": "3c46ab34",
    "metadata": {
     "papermill": {
-     "duration": 0.136646,
-     "end_time": "2022-01-11T13:32:42.432970",
+     "duration": 0.1353,
+     "end_time": "2022-02-21T13:16:30.573745",
      "exception": false,
-     "start_time": "2022-01-11T13:32:42.296324",
+     "start_time": "2022-02-21T13:16:30.438445",
      "status": "completed"
     },
     "tags": []
@@ -4394,8 +4415,8 @@
   },
   "papermill": {
    "default_parameters": {},
-   "duration": 602.914603,
-   "end_time": "2022-01-11T13:32:43.284330",
+   "duration": 1227.32075,
+   "end_time": "2022-02-21T13:16:31.538002",
    "environment_variables": {},
    "exception": null,
    "input_path": "/builds/LHCData/lhc-sm-hwc/test/../pgc/AN_PGC3.ipynb",
@@ -4412,8 +4433,8 @@
     "t_end": "2021-05-29 21:33:00.748000000",
     "t_start": "2021-05-29 21:33:00.736000000"
    },
-   "start_time": "2022-01-11T13:22:40.369727",
-   "version": "2.3.3"
+   "start_time": "2022-02-21T12:56:04.217252",
+   "version": "2.3.4"
   },
   "sparkconnect": {
    "bundled_options": [
diff --git a/test/resources/notebooks/result_AN_PGC4.ipynb b/test/resources/notebooks/result_AN_PGC4.ipynb
index 3fae5aed..d39f3e48 100644
--- a/test/resources/notebooks/result_AN_PGC4.ipynb
+++ b/test/resources/notebooks/result_AN_PGC4.ipynb
@@ -3,19 +3,19 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "972cfe32",
+   "id": "ce6af06a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:13.202835Z",
-     "iopub.status.busy": "2022-01-11T13:28:13.202002Z",
-     "iopub.status.idle": "2022-01-11T13:28:48.672835Z",
-     "shell.execute_reply": "2022-01-11T13:28:48.672036Z"
+     "iopub.execute_input": "2022-02-21T12:56:29.194858Z",
+     "iopub.status.busy": "2022-02-21T12:56:29.194491Z",
+     "iopub.status.idle": "2022-02-21T12:57:05.222211Z",
+     "shell.execute_reply": "2022-02-21T12:57:05.220996Z"
     },
     "papermill": {
-     "duration": 35.529445,
-     "end_time": "2022-01-11T13:28:48.673050",
+     "duration": 36.076858,
+     "end_time": "2022-02-21T12:57:05.225310",
      "exception": false,
-     "start_time": "2022-01-11T13:28:13.143605",
+     "start_time": "2022-02-21T12:56:29.148452",
      "status": "completed"
     }
    },
@@ -73,10 +73,10 @@
    "id": "e189d8c9",
    "metadata": {
     "papermill": {
-     "duration": 0.040309,
-     "end_time": "2022-01-11T13:28:48.754896",
+     "duration": 0.041675,
+     "end_time": "2022-02-21T12:57:05.309796",
      "exception": false,
-     "start_time": "2022-01-11T13:28:48.714587",
+     "start_time": "2022-02-21T12:57:05.268121",
      "status": "completed"
     },
     "tags": []
@@ -90,10 +90,10 @@
    "id": "aaa1c695",
    "metadata": {
     "papermill": {
-     "duration": 0.040144,
-     "end_time": "2022-01-11T13:28:48.835430",
+     "duration": 0.042752,
+     "end_time": "2022-02-21T12:57:05.394787",
      "exception": false,
-     "start_time": "2022-01-11T13:28:48.795286",
+     "start_time": "2022-02-21T12:57:05.352035",
      "status": "completed"
     },
     "tags": []
@@ -144,10 +144,10 @@
    "id": "41a5b13e",
    "metadata": {
     "papermill": {
-     "duration": 0.040024,
-     "end_time": "2022-01-11T13:28:48.915781",
+     "duration": 0.041703,
+     "end_time": "2022-02-21T12:57:05.478376",
      "exception": false,
-     "start_time": "2022-01-11T13:28:48.875757",
+     "start_time": "2022-02-21T12:57:05.436673",
      "status": "completed"
     },
     "tags": []
@@ -162,16 +162,16 @@
    "id": "e0caa89b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:49.003808Z",
-     "iopub.status.busy": "2022-01-11T13:28:49.003124Z",
-     "iopub.status.idle": "2022-01-11T13:28:52.188497Z",
-     "shell.execute_reply": "2022-01-11T13:28:52.187882Z"
+     "iopub.execute_input": "2022-02-21T12:57:05.563726Z",
+     "iopub.status.busy": "2022-02-21T12:57:05.563364Z",
+     "iopub.status.idle": "2022-02-21T12:57:08.444675Z",
+     "shell.execute_reply": "2022-02-21T12:57:08.443571Z"
     },
     "papermill": {
-     "duration": 3.232928,
-     "end_time": "2022-01-11T13:28:52.188659",
+     "duration": 2.928085,
+     "end_time": "2022-02-21T12:57:08.447906",
      "exception": false,
-     "start_time": "2022-01-11T13:28:48.955731",
+     "start_time": "2022-02-21T12:57:05.519821",
      "status": "completed"
     },
     "tags": []
@@ -223,16 +223,16 @@
    "id": "2d827d6a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:52.277934Z",
-     "iopub.status.busy": "2022-01-11T13:28:52.277263Z",
-     "iopub.status.idle": "2022-01-11T13:28:52.281123Z",
-     "shell.execute_reply": "2022-01-11T13:28:52.280474Z"
+     "iopub.execute_input": "2022-02-21T12:57:08.541937Z",
+     "iopub.status.busy": "2022-02-21T12:57:08.541592Z",
+     "iopub.status.idle": "2022-02-21T12:57:08.548222Z",
+     "shell.execute_reply": "2022-02-21T12:57:08.547291Z"
     },
     "papermill": {
-     "duration": 0.050451,
-     "end_time": "2022-01-11T13:28:52.281267",
+     "duration": 0.055285,
+     "end_time": "2022-02-21T12:57:08.551229",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.230816",
+     "start_time": "2022-02-21T12:57:08.495944",
      "status": "completed"
     },
     "tags": []
@@ -242,8 +242,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Analysis executed with lhc-sm-api version: 1.5.18\n",
-      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.66\n",
+      "Analysis executed with lhc-sm-api version: 1.5.19\n",
+      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.67\n",
       "user = root\n"
      ]
     }
@@ -262,16 +262,16 @@
    "id": "e1956bdf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:52.371767Z",
-     "iopub.status.busy": "2022-01-11T13:28:52.371076Z",
-     "iopub.status.idle": "2022-01-11T13:28:52.373219Z",
-     "shell.execute_reply": "2022-01-11T13:28:52.373916Z"
+     "iopub.execute_input": "2022-02-21T12:57:08.639861Z",
+     "iopub.status.busy": "2022-02-21T12:57:08.639535Z",
+     "iopub.status.idle": "2022-02-21T12:57:08.643952Z",
+     "shell.execute_reply": "2022-02-21T12:57:08.642748Z"
     },
     "papermill": {
-     "duration": 0.050704,
-     "end_time": "2022-01-11T13:28:52.374124",
+     "duration": 0.051305,
+     "end_time": "2022-02-21T12:57:08.646109",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.323420",
+     "start_time": "2022-02-21T12:57:08.594804",
      "status": "completed"
     },
     "tags": []
@@ -288,10 +288,10 @@
    "id": "d206483b",
    "metadata": {
     "papermill": {
-     "duration": 0.042645,
-     "end_time": "2022-01-11T13:28:52.459361",
+     "duration": 0.042939,
+     "end_time": "2022-02-21T12:57:08.732407",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.416716",
+     "start_time": "2022-02-21T12:57:08.689468",
      "status": "completed"
     },
     "tags": []
@@ -305,10 +305,10 @@
    "id": "8f130a2f",
    "metadata": {
     "papermill": {
-     "duration": 0.042081,
-     "end_time": "2022-01-11T13:28:52.543686",
+     "duration": 0.042695,
+     "end_time": "2022-02-21T12:57:08.817792",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.501605",
+     "start_time": "2022-02-21T12:57:08.775097",
      "status": "completed"
     },
     "tags": []
@@ -324,16 +324,16 @@
    "id": "416b1e8a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:52.633748Z",
-     "iopub.status.busy": "2022-01-11T13:28:52.633066Z",
-     "iopub.status.idle": "2022-01-11T13:28:52.635072Z",
-     "shell.execute_reply": "2022-01-11T13:28:52.635563Z"
+     "iopub.execute_input": "2022-02-21T12:57:08.906941Z",
+     "iopub.status.busy": "2022-02-21T12:57:08.906598Z",
+     "iopub.status.idle": "2022-02-21T12:57:08.911687Z",
+     "shell.execute_reply": "2022-02-21T12:57:08.910780Z"
     },
     "papermill": {
-     "duration": 0.049811,
-     "end_time": "2022-01-11T13:28:52.635746",
+     "duration": 0.052752,
+     "end_time": "2022-02-21T12:57:08.913789",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.585935",
+     "start_time": "2022-02-21T12:57:08.861037",
      "status": "completed"
     },
     "tags": [
@@ -342,25 +342,31 @@
    },
    "outputs": [],
    "source": [
-    "#User input from ACCTESTING here\n"
+    "#User input from ACCTESTING here\n",
+    "hwc_test = 'PGC.4'\n",
+    "circuit_name = 'RB.A56'\n",
+    "campaign = 'Recommissioning post LS2'\n",
+    "t_start = '2021-08-01 12:43:34.927000000'\n",
+    "t_end = '2021-08-01 13:58:34.927'\n",
+    "t_end_sec = '4500'"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "dedd7790",
+   "id": "badf66a6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:52.726898Z",
-     "iopub.status.busy": "2022-01-11T13:28:52.726215Z",
-     "iopub.status.idle": "2022-01-11T13:28:52.729023Z",
-     "shell.execute_reply": "2022-01-11T13:28:52.728281Z"
+     "iopub.execute_input": "2022-02-21T12:57:09.002753Z",
+     "iopub.status.busy": "2022-02-21T12:57:09.002444Z",
+     "iopub.status.idle": "2022-02-21T12:57:09.007500Z",
+     "shell.execute_reply": "2022-02-21T12:57:09.006680Z"
     },
     "papermill": {
-     "duration": 0.051007,
-     "end_time": "2022-01-11T13:28:52.729170",
+     "duration": 0.052486,
+     "end_time": "2022-02-21T12:57:09.009431",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.678163",
+     "start_time": "2022-02-21T12:57:08.956945",
      "status": "completed"
     },
     "tags": [
@@ -388,16 +394,16 @@
    "id": "5162b3fb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:52.820951Z",
-     "iopub.status.busy": "2022-01-11T13:28:52.820262Z",
-     "iopub.status.idle": "2022-01-11T13:28:52.822984Z",
-     "shell.execute_reply": "2022-01-11T13:28:52.823512Z"
+     "iopub.execute_input": "2022-02-21T12:57:09.099323Z",
+     "iopub.status.busy": "2022-02-21T12:57:09.098951Z",
+     "iopub.status.idle": "2022-02-21T12:57:09.104538Z",
+     "shell.execute_reply": "2022-02-21T12:57:09.103628Z"
     },
     "papermill": {
-     "duration": 0.05154,
-     "end_time": "2022-01-11T13:28:52.823703",
+     "duration": 0.058602,
+     "end_time": "2022-02-21T12:57:09.111718",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.772163",
+     "start_time": "2022-02-21T12:57:09.053116",
      "status": "completed"
     },
     "tags": []
@@ -424,10 +430,10 @@
    "id": "478adf10",
    "metadata": {
     "papermill": {
-     "duration": 0.043356,
-     "end_time": "2022-01-11T13:28:52.910472",
+     "duration": 0.04354,
+     "end_time": "2022-02-21T12:57:09.199527",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.867116",
+     "start_time": "2022-02-21T12:57:09.155987",
      "status": "completed"
     },
     "tags": []
@@ -442,16 +448,16 @@
    "id": "32b0c2fd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:53.004648Z",
-     "iopub.status.busy": "2022-01-11T13:28:53.003936Z",
-     "iopub.status.idle": "2022-01-11T13:28:53.015984Z",
-     "shell.execute_reply": "2022-01-11T13:28:53.015269Z"
+     "iopub.execute_input": "2022-02-21T12:57:09.289051Z",
+     "iopub.status.busy": "2022-02-21T12:57:09.288695Z",
+     "iopub.status.idle": "2022-02-21T12:57:09.306651Z",
+     "shell.execute_reply": "2022-02-21T12:57:09.305709Z"
     },
     "papermill": {
-     "duration": 0.062008,
-     "end_time": "2022-01-11T13:28:53.016134",
+     "duration": 0.065731,
+     "end_time": "2022-02-21T12:57:09.308801",
      "exception": false,
-     "start_time": "2022-01-11T13:28:52.954126",
+     "start_time": "2022-02-21T12:57:09.243070",
      "status": "completed"
     },
     "tags": []
@@ -471,9 +477,9 @@
     "lhc_circuit = meta_df[lambda x: x['Circuit name'] == circuit_name]\n",
     "\n",
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'] == safety_subsector]\n",
+    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -481,10 +487,10 @@
    "id": "1006733e",
    "metadata": {
     "papermill": {
-     "duration": 0.043887,
-     "end_time": "2022-01-11T13:28:53.103499",
+     "duration": 0.045347,
+     "end_time": "2022-02-21T12:57:09.399116",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.059612",
+     "start_time": "2022-02-21T12:57:09.353769",
      "status": "completed"
     },
     "tags": []
@@ -500,16 +506,16 @@
    "id": "4a6243f0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:53.203551Z",
-     "iopub.status.busy": "2022-01-11T13:28:53.202768Z",
-     "iopub.status.idle": "2022-01-11T13:28:53.209922Z",
-     "shell.execute_reply": "2022-01-11T13:28:53.209216Z"
+     "iopub.execute_input": "2022-02-21T12:57:09.493313Z",
+     "iopub.status.busy": "2022-02-21T12:57:09.492987Z",
+     "iopub.status.idle": "2022-02-21T12:57:09.507893Z",
+     "shell.execute_reply": "2022-02-21T12:57:09.507034Z"
     },
     "papermill": {
-     "duration": 0.062428,
-     "end_time": "2022-01-11T13:28:53.210088",
+     "duration": 0.064367,
+     "end_time": "2022-02-21T12:57:09.509886",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.147660",
+     "start_time": "2022-02-21T12:57:09.445519",
      "status": "completed"
     },
     "tags": []
@@ -539,8 +545,8 @@
     "    t_end = Time.to_string_short((Time.to_unix_timestamp(t_start) + (5 * 60) * 1e9))\n",
     "t_end_sec = int((Time.to_unix_timestamp(t_end) - Time.to_unix_timestamp(t_start))*1e-9)\n",
     "#\n",
-    "t_start_utc = Time.to_string_short((Time.to_unix_timestamp(t_start) - 2 * 3600 * 1e9))\n",
-    "t_end_utc = Time.to_string_short((Time.to_unix_timestamp(t_end) - 2 * 3600 * 1e9))\n",
+    "t_start_timestamp = Time.to_unix_timestamp(t_start)\n",
+    "t_end_timestamp = Time.to_unix_timestamp(t_end)\n",
     "#\n",
     "print('hwc_test = \\'%s\\'\\ncircuit_name = \\'%s\\'\\ncampaign = \\'%s\\'\\nt_start = \\'%s\\'\\nt_end = \\'%s\\'\\nt_end_sec = \\'%s\\'' % (hwc_test, circuit_name, campaign, t_start, t_end, t_end_sec))"
    ]
@@ -550,10 +556,10 @@
    "id": "07d6194f",
    "metadata": {
     "papermill": {
-     "duration": 0.045491,
-     "end_time": "2022-01-11T13:28:53.301256",
+     "duration": 0.045835,
+     "end_time": "2022-02-21T12:57:09.601807",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.255765",
+     "start_time": "2022-02-21T12:57:09.555972",
      "status": "completed"
     },
     "tags": []
@@ -568,16 +574,16 @@
    "id": "8c5330c1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:53.398066Z",
-     "iopub.status.busy": "2022-01-11T13:28:53.397356Z",
-     "iopub.status.idle": "2022-01-11T13:28:53.400926Z",
-     "shell.execute_reply": "2022-01-11T13:28:53.400243Z"
+     "iopub.execute_input": "2022-02-21T12:57:09.698255Z",
+     "iopub.status.busy": "2022-02-21T12:57:09.697930Z",
+     "iopub.status.idle": "2022-02-21T12:57:09.702680Z",
+     "shell.execute_reply": "2022-02-21T12:57:09.701882Z"
     },
     "papermill": {
-     "duration": 0.054203,
-     "end_time": "2022-01-11T13:28:53.401085",
+     "duration": 0.057657,
+     "end_time": "2022-02-21T12:57:09.704906",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.346882",
+     "start_time": "2022-02-21T12:57:09.647249",
      "status": "completed"
     },
     "tags": []
@@ -596,16 +602,16 @@
    "id": "b34e13f4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:53.497207Z",
-     "iopub.status.busy": "2022-01-11T13:28:53.496532Z",
-     "iopub.status.idle": "2022-01-11T13:28:53.498686Z",
-     "shell.execute_reply": "2022-01-11T13:28:53.499207Z"
+     "iopub.execute_input": "2022-02-21T12:57:09.802952Z",
+     "iopub.status.busy": "2022-02-21T12:57:09.802611Z",
+     "iopub.status.idle": "2022-02-21T12:57:09.808555Z",
+     "shell.execute_reply": "2022-02-21T12:57:09.807738Z"
     },
     "papermill": {
-     "duration": 0.053933,
-     "end_time": "2022-01-11T13:28:53.499407",
+     "duration": 0.059484,
+     "end_time": "2022-02-21T12:57:09.810586",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.445474",
+     "start_time": "2022-02-21T12:57:09.751102",
      "status": "completed"
     },
     "tags": []
@@ -632,16 +638,16 @@
    "id": "5eaa704a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:53.594756Z",
-     "iopub.status.busy": "2022-01-11T13:28:53.594088Z",
-     "iopub.status.idle": "2022-01-11T13:28:53.607156Z",
-     "shell.execute_reply": "2022-01-11T13:28:53.607673Z"
+     "iopub.execute_input": "2022-02-21T12:57:09.904003Z",
+     "iopub.status.busy": "2022-02-21T12:57:09.903680Z",
+     "iopub.status.idle": "2022-02-21T12:57:09.917101Z",
+     "shell.execute_reply": "2022-02-21T12:57:09.916081Z"
     },
     "papermill": {
-     "duration": 0.063222,
-     "end_time": "2022-01-11T13:28:53.607873",
+     "duration": 0.062808,
+     "end_time": "2022-02-21T12:57:09.919107",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.544651",
+     "start_time": "2022-02-21T12:57:09.856299",
      "status": "completed"
     },
     "scrolled": false,
@@ -670,10 +676,10 @@
    "id": "6735a845",
    "metadata": {
     "papermill": {
-     "duration": 0.04577,
-     "end_time": "2022-01-11T13:28:53.699319",
+     "duration": 0.047702,
+     "end_time": "2022-02-21T12:57:10.012957",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.653549",
+     "start_time": "2022-02-21T12:57:09.965255",
      "status": "completed"
     },
     "tags": []
@@ -688,16 +694,16 @@
    "id": "05570ea8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:53.798835Z",
-     "iopub.status.busy": "2022-01-11T13:28:53.798127Z",
-     "iopub.status.idle": "2022-01-11T13:28:53.801129Z",
-     "shell.execute_reply": "2022-01-11T13:28:53.800593Z"
+     "iopub.execute_input": "2022-02-21T12:57:10.109905Z",
+     "iopub.status.busy": "2022-02-21T12:57:10.109578Z",
+     "iopub.status.idle": "2022-02-21T12:57:10.117287Z",
+     "shell.execute_reply": "2022-02-21T12:57:10.116472Z"
     },
     "papermill": {
-     "duration": 0.056201,
-     "end_time": "2022-01-11T13:28:53.801281",
+     "duration": 0.059601,
+     "end_time": "2022-02-21T12:57:10.119176",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.745080",
+     "start_time": "2022-02-21T12:57:10.059575",
      "status": "completed"
     },
     "tags": []
@@ -728,10 +734,10 @@
    "id": "90e222da",
    "metadata": {
     "papermill": {
-     "duration": 0.045968,
-     "end_time": "2022-01-11T13:28:53.893442",
+     "duration": 0.046207,
+     "end_time": "2022-02-21T12:57:10.216774",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.847474",
+     "start_time": "2022-02-21T12:57:10.170567",
      "status": "completed"
     },
     "tags": []
@@ -746,16 +752,16 @@
    "id": "7bdfca07",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:53.993603Z",
-     "iopub.status.busy": "2022-01-11T13:28:53.992922Z",
-     "iopub.status.idle": "2022-01-11T13:28:53.996021Z",
-     "shell.execute_reply": "2022-01-11T13:28:53.995444Z"
+     "iopub.execute_input": "2022-02-21T12:57:10.313759Z",
+     "iopub.status.busy": "2022-02-21T12:57:10.313376Z",
+     "iopub.status.idle": "2022-02-21T12:57:10.328238Z",
+     "shell.execute_reply": "2022-02-21T12:57:10.324715Z"
     },
     "papermill": {
-     "duration": 0.056237,
-     "end_time": "2022-01-11T13:28:53.996167",
+     "duration": 0.068453,
+     "end_time": "2022-02-21T12:57:10.331537",
      "exception": false,
-     "start_time": "2022-01-11T13:28:53.939930",
+     "start_time": "2022-02-21T12:57:10.263084",
      "status": "completed"
     },
     "tags": []
@@ -783,10 +789,10 @@
    "id": "14af456c",
    "metadata": {
     "papermill": {
-     "duration": 0.047117,
-     "end_time": "2022-01-11T13:28:54.089994",
+     "duration": 0.047457,
+     "end_time": "2022-02-21T12:57:10.426791",
      "exception": false,
-     "start_time": "2022-01-11T13:28:54.042877",
+     "start_time": "2022-02-21T12:57:10.379334",
      "status": "completed"
     },
     "tags": []
@@ -800,10 +806,10 @@
    "id": "c920a8ee",
    "metadata": {
     "papermill": {
-     "duration": 0.046462,
-     "end_time": "2022-01-11T13:28:54.195027",
+     "duration": 0.047186,
+     "end_time": "2022-02-21T12:57:10.521531",
      "exception": false,
-     "start_time": "2022-01-11T13:28:54.148565",
+     "start_time": "2022-02-21T12:57:10.474345",
      "status": "completed"
     },
     "tags": []
@@ -821,16 +827,16 @@
    "id": "e11f7736",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:54.297158Z",
-     "iopub.status.busy": "2022-01-11T13:28:54.296506Z",
-     "iopub.status.idle": "2022-01-11T13:28:54.300234Z",
-     "shell.execute_reply": "2022-01-11T13:28:54.299585Z"
+     "iopub.execute_input": "2022-02-21T12:57:10.618280Z",
+     "iopub.status.busy": "2022-02-21T12:57:10.617967Z",
+     "iopub.status.idle": "2022-02-21T12:57:10.626515Z",
+     "shell.execute_reply": "2022-02-21T12:57:10.625778Z"
     },
     "papermill": {
-     "duration": 0.058327,
-     "end_time": "2022-01-11T13:28:54.300376",
+     "duration": 0.059659,
+     "end_time": "2022-02-21T12:57:10.628518",
      "exception": false,
-     "start_time": "2022-01-11T13:28:54.242049",
+     "start_time": "2022-02-21T12:57:10.568859",
      "status": "completed"
     },
     "tags": []
@@ -859,7 +865,6 @@
     }
    ],
    "source": [
-    "#condemned_circuits = ['RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCSX3.L2', 'RCTX3.L2', 'RSS.A34B1']\n",
     "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
     "display(condemned_circuits)"
    ]
@@ -869,10 +874,10 @@
    "id": "fa10f3d7",
    "metadata": {
     "papermill": {
-     "duration": 0.04724,
-     "end_time": "2022-01-11T13:28:54.395303",
+     "duration": 0.047669,
+     "end_time": "2022-02-21T12:57:10.724473",
      "exception": false,
-     "start_time": "2022-01-11T13:28:54.348063",
+     "start_time": "2022-02-21T12:57:10.676804",
      "status": "completed"
     },
     "tags": []
@@ -887,16 +892,16 @@
    "id": "7bc600be",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:28:54.521161Z",
-     "iopub.status.busy": "2022-01-11T13:28:54.504076Z",
-     "iopub.status.idle": "2022-01-11T13:56:53.637095Z",
-     "shell.execute_reply": "2022-01-11T13:56:53.637698Z"
+     "iopub.execute_input": "2022-02-21T12:57:10.822217Z",
+     "iopub.status.busy": "2022-02-21T12:57:10.821885Z",
+     "iopub.status.idle": "2022-02-21T13:10:10.873016Z",
+     "shell.execute_reply": "2022-02-21T13:10:10.872152Z"
     },
     "papermill": {
-     "duration": 1679.1955,
-     "end_time": "2022-01-11T13:56:53.638159",
+     "duration": 780.103407,
+     "end_time": "2022-02-21T13:10:10.875626",
      "exception": false,
-     "start_time": "2022-01-11T13:28:54.442659",
+     "start_time": "2022-02-21T12:57:10.772219",
      "status": "completed"
     },
     "scrolled": false,
@@ -2140,7 +2145,7 @@
      "text": [
       "110 type = 80-120A , name = RCBCV9.R4B1 , Imax = 0 , Imin = 0\n",
       "Powering current is too low\n",
-      "Elapsed: 1679.096 s.\n"
+      "Elapsed: 780.004 s.\n"
      ]
     }
    ],
@@ -2256,11 +2261,9 @@
     "                    .with_metadata(circuit_name=circuit_name, system='PC', source='*') \\\n",
     "                    .event_query().df\n",
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_600A_df = pd.concat([source_timestamp_fgc_600A_df, source_timestamp_fgc_df_i], ignore_index=True)                                            \n",
-    "                #j = j + 1\n",
     "        i = i + 1\n",
     "    #\n",
     "    print('60A, 80A, 120A circuits')\n",
-    "    # to be updated to metadata\n",
     "    i = j = 0\n",
     "    i_meas_120A_dfs = []\n",
     "    source_timestamp_fgc_120A_df = pd.DataFrame()\n",
@@ -2270,29 +2273,19 @@
     "            if circuit_type in pgc_120A:\n",
     "                j = j + 1\n",
     "                #print(j, circuit_type, circuit_name)\n",
-    "                df1 = DataQuery.builder(spark).byVariables() \\\n",
-    "                    .system('CMW') \\\n",
-    "                    .startTime(t_start_utc).endTime(t_end_utc) \\\n",
-    "                    .variableLike('%' + circuit_name + ':I_MEAS') \\\n",
-    "                    .buildDataset()\n",
-    "                i_meas_df = df1.select('nxcals_timestamp', 'nxcals_value').sort('nxcals_timestamp').toPandas()\n",
-    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['nxcals_value'].max()), ', Imin =', int(i_meas_df['nxcals_value'].min()))\n",
-    "                if (int(i_meas_df['nxcals_value'].max()) - int(i_meas_df['nxcals_value'].min())) < 10:\n",
-    "                    print('Powering current is too low')\n",
-    "                i_meas_df.rename(columns={'nxcals_timestamp': 'timestamp', 'nxcals_value': circuit_name + ':I_MEAS'}, inplace=True)\n",
-    "                t0 = i_meas_df['timestamp'].loc[0]\n",
-    "                i_meas_df['time'] = (i_meas_df['timestamp'] - t0)*1e-9\n",
-    "                i_meas_df.set_index('time', inplace = True)\n",
-    "                i_meas_df = i_meas_df.drop('timestamp', 1)\n",
-    "#                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
-    "#                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
-    "#                    .with_circuit_type(circuit_type) \\\n",
-    "#                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
-    "#                    .signal_query() \\\n",
-    "#                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
-    "#                    .convert_index_to_sec().dfs[0]\n",
-    "#                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
+    "                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
+    "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
+    "                    .with_circuit_type(circuit_type) \\\n",
+    "                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
+    "                    .signal_query() \\\n",
+    "                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
+    "                    .convert_index_to_sec().dfs[0]\n",
+    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['I_MEAS'].max()), ', Imin =', int(i_meas_df['I_MEAS'].min()))\n",
+    "                if (int(i_meas_df['I_MEAS'].max()) - int(i_meas_df['I_MEAS'].min())) < 10:\n",
+    "                     print('Powering current is too low')\n",
+    "                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
     "                i_meas_120A_dfs.append(i_meas_df)\n",
+    "\n",
     "                source_timestamp_fgc_df_i = QueryBuilder().with_pm() \\\n",
     "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
     "                    .with_circuit_type(circuit_type) \\\n",
@@ -2308,10 +2301,10 @@
    "id": "1e31cde6",
    "metadata": {
     "papermill": {
-     "duration": 0.119602,
-     "end_time": "2022-01-11T13:56:53.874566",
+     "duration": 0.11678,
+     "end_time": "2022-02-21T13:10:11.109488",
      "exception": false,
-     "start_time": "2022-01-11T13:56:53.754964",
+     "start_time": "2022-02-21T13:10:10.992708",
      "status": "completed"
     },
     "tags": []
@@ -2326,16 +2319,16 @@
    "id": "8a51f006",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:56:54.120067Z",
-     "iopub.status.busy": "2022-01-11T13:56:54.119328Z",
-     "iopub.status.idle": "2022-01-11T13:56:54.587912Z",
-     "shell.execute_reply": "2022-01-11T13:56:54.588455Z"
+     "iopub.execute_input": "2022-02-21T13:10:11.354670Z",
+     "iopub.status.busy": "2022-02-21T13:10:11.354326Z",
+     "iopub.status.idle": "2022-02-21T13:10:11.850880Z",
+     "shell.execute_reply": "2022-02-21T13:10:11.850137Z"
     },
     "papermill": {
-     "duration": 0.598009,
-     "end_time": "2022-01-11T13:56:54.588657",
+     "duration": 0.622632,
+     "end_time": "2022-02-21T13:10:11.853368",
      "exception": false,
-     "start_time": "2022-01-11T13:56:53.990648",
+     "start_time": "2022-02-21T13:10:11.230736",
      "status": "completed"
     },
     "scrolled": false,
@@ -2384,10 +2377,10 @@
    "id": "a054188b",
    "metadata": {
     "papermill": {
-     "duration": 0.115881,
-     "end_time": "2022-01-11T13:56:54.821005",
+     "duration": 0.118115,
+     "end_time": "2022-02-21T13:10:12.091620",
      "exception": false,
-     "start_time": "2022-01-11T13:56:54.705124",
+     "start_time": "2022-02-21T13:10:11.973505",
      "status": "completed"
     },
     "tags": []
@@ -2402,16 +2395,16 @@
    "id": "9b19ff88",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:56:55.080272Z",
-     "iopub.status.busy": "2022-01-11T13:56:55.073117Z",
-     "iopub.status.idle": "2022-01-11T13:56:55.841599Z",
-     "shell.execute_reply": "2022-01-11T13:56:55.841015Z"
+     "iopub.execute_input": "2022-02-21T13:10:12.330137Z",
+     "iopub.status.busy": "2022-02-21T13:10:12.329808Z",
+     "iopub.status.idle": "2022-02-21T13:10:13.224283Z",
+     "shell.execute_reply": "2022-02-21T13:10:13.223432Z"
     },
     "papermill": {
-     "duration": 0.905067,
-     "end_time": "2022-01-11T13:56:55.841756",
+     "duration": 1.016735,
+     "end_time": "2022-02-21T13:10:13.226584",
      "exception": false,
-     "start_time": "2022-01-11T13:56:54.936689",
+     "start_time": "2022-02-21T13:10:12.209849",
      "status": "completed"
     },
     "scrolled": false,
@@ -2455,10 +2448,10 @@
    "id": "aa89cb52",
    "metadata": {
     "papermill": {
-     "duration": 0.117301,
-     "end_time": "2022-01-11T13:56:56.076671",
+     "duration": 0.121445,
+     "end_time": "2022-02-21T13:10:13.468011",
      "exception": false,
-     "start_time": "2022-01-11T13:56:55.959370",
+     "start_time": "2022-02-21T13:10:13.346566",
      "status": "completed"
     },
     "tags": []
@@ -2473,16 +2466,16 @@
    "id": "d4c651cd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:56:56.319736Z",
-     "iopub.status.busy": "2022-01-11T13:56:56.319066Z",
-     "iopub.status.idle": "2022-01-11T13:56:56.328906Z",
-     "shell.execute_reply": "2022-01-11T13:56:56.328339Z"
+     "iopub.execute_input": "2022-02-21T13:10:13.713049Z",
+     "iopub.status.busy": "2022-02-21T13:10:13.712715Z",
+     "iopub.status.idle": "2022-02-21T13:10:13.731418Z",
+     "shell.execute_reply": "2022-02-21T13:10:13.730641Z"
     },
     "papermill": {
-     "duration": 0.134648,
-     "end_time": "2022-01-11T13:56:56.329063",
+     "duration": 0.145412,
+     "end_time": "2022-02-21T13:10:13.733704",
      "exception": false,
-     "start_time": "2022-01-11T13:56:56.194415",
+     "start_time": "2022-02-21T13:10:13.588292",
      "status": "completed"
     },
     "tags": []
@@ -2547,10 +2540,10 @@
    "id": "5f0a4c1b",
    "metadata": {
     "papermill": {
-     "duration": 0.119549,
-     "end_time": "2022-01-11T13:56:56.568483",
+     "duration": 0.121248,
+     "end_time": "2022-02-21T13:10:13.977479",
      "exception": false,
-     "start_time": "2022-01-11T13:56:56.448934",
+     "start_time": "2022-02-21T13:10:13.856231",
      "status": "completed"
     },
     "tags": []
@@ -2565,16 +2558,16 @@
    "id": "c7e36e22",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:56:56.814172Z",
-     "iopub.status.busy": "2022-01-11T13:56:56.813496Z",
-     "iopub.status.idle": "2022-01-11T13:56:56.816830Z",
-     "shell.execute_reply": "2022-01-11T13:56:56.816179Z"
+     "iopub.execute_input": "2022-02-21T13:10:14.223946Z",
+     "iopub.status.busy": "2022-02-21T13:10:14.223627Z",
+     "iopub.status.idle": "2022-02-21T13:10:14.230275Z",
+     "shell.execute_reply": "2022-02-21T13:10:14.229622Z"
     },
     "papermill": {
-     "duration": 0.129396,
-     "end_time": "2022-01-11T13:56:56.816970",
+     "duration": 0.13251,
+     "end_time": "2022-02-21T13:10:14.232330",
      "exception": false,
-     "start_time": "2022-01-11T13:56:56.687574",
+     "start_time": "2022-02-21T13:10:14.099820",
      "status": "completed"
     },
     "tags": []
@@ -2602,10 +2595,10 @@
    "id": "634f83d5",
    "metadata": {
     "papermill": {
-     "duration": 0.119645,
-     "end_time": "2022-01-11T13:56:57.056871",
+     "duration": 0.132732,
+     "end_time": "2022-02-21T13:10:14.487585",
      "exception": false,
-     "start_time": "2022-01-11T13:56:56.937226",
+     "start_time": "2022-02-21T13:10:14.354853",
      "status": "completed"
     },
     "tags": []
@@ -2620,16 +2613,16 @@
    "id": "0499262e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:56:57.327215Z",
-     "iopub.status.busy": "2022-01-11T13:56:57.326496Z",
-     "iopub.status.idle": "2022-01-11T13:56:58.938716Z",
-     "shell.execute_reply": "2022-01-11T13:56:58.939250Z"
+     "iopub.execute_input": "2022-02-21T13:10:14.735482Z",
+     "iopub.status.busy": "2022-02-21T13:10:14.735156Z",
+     "iopub.status.idle": "2022-02-21T13:10:16.370460Z",
+     "shell.execute_reply": "2022-02-21T13:10:16.369682Z"
     },
     "papermill": {
-     "duration": 1.762583,
-     "end_time": "2022-01-11T13:56:58.939460",
+     "duration": 1.762954,
+     "end_time": "2022-02-21T13:10:16.373268",
      "exception": false,
-     "start_time": "2022-01-11T13:56:57.176877",
+     "start_time": "2022-02-21T13:10:14.610314",
      "status": "completed"
     },
     "scrolled": false,
@@ -2673,10 +2666,10 @@
    "id": "1724c576",
    "metadata": {
     "papermill": {
-     "duration": 0.121559,
-     "end_time": "2022-01-11T13:56:59.182406",
+     "duration": 0.12375,
+     "end_time": "2022-02-21T13:10:16.623325",
      "exception": false,
-     "start_time": "2022-01-11T13:56:59.060847",
+     "start_time": "2022-02-21T13:10:16.499575",
      "status": "completed"
     },
     "tags": []
@@ -2691,16 +2684,16 @@
    "id": "f4ac4b34",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:56:59.446863Z",
-     "iopub.status.busy": "2022-01-11T13:56:59.435167Z",
-     "iopub.status.idle": "2022-01-11T13:56:59.674489Z",
-     "shell.execute_reply": "2022-01-11T13:56:59.675006Z"
+     "iopub.execute_input": "2022-02-21T13:10:16.873006Z",
+     "iopub.status.busy": "2022-02-21T13:10:16.872666Z",
+     "iopub.status.idle": "2022-02-21T13:10:17.119837Z",
+     "shell.execute_reply": "2022-02-21T13:10:17.119061Z"
     },
     "papermill": {
-     "duration": 0.37097,
-     "end_time": "2022-01-11T13:56:59.675257",
+     "duration": 0.374997,
+     "end_time": "2022-02-21T13:10:17.122109",
      "exception": false,
-     "start_time": "2022-01-11T13:56:59.304287",
+     "start_time": "2022-02-21T13:10:16.747112",
      "status": "completed"
     },
     "tags": []
@@ -3400,10 +3393,10 @@
    "id": "e4b7e929",
    "metadata": {
     "papermill": {
-     "duration": 0.127062,
-     "end_time": "2022-01-11T13:56:59.931964",
+     "duration": 0.125794,
+     "end_time": "2022-02-21T13:10:17.375212",
      "exception": false,
-     "start_time": "2022-01-11T13:56:59.804902",
+     "start_time": "2022-02-21T13:10:17.249418",
      "status": "completed"
     },
     "tags": []
@@ -3418,16 +3411,16 @@
    "id": "ef620705",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:57:00.196061Z",
-     "iopub.status.busy": "2022-01-11T13:57:00.195340Z",
-     "iopub.status.idle": "2022-01-11T13:57:00.217341Z",
-     "shell.execute_reply": "2022-01-11T13:57:00.217876Z"
+     "iopub.execute_input": "2022-02-21T13:10:17.629287Z",
+     "iopub.status.busy": "2022-02-21T13:10:17.628960Z",
+     "iopub.status.idle": "2022-02-21T13:10:17.663287Z",
+     "shell.execute_reply": "2022-02-21T13:10:17.662554Z"
     },
     "papermill": {
-     "duration": 0.161593,
-     "end_time": "2022-01-11T13:57:00.218081",
+     "duration": 0.17012,
+     "end_time": "2022-02-21T13:10:17.671851",
      "exception": false,
-     "start_time": "2022-01-11T13:57:00.056488",
+     "start_time": "2022-02-21T13:10:17.501731",
      "status": "completed"
     },
     "tags": []
@@ -3839,16 +3832,16 @@
    "id": "c39cf821",
    "metadata": {
     "papermill": {
-     "duration": 0.126864,
-     "end_time": "2022-01-11T13:57:00.472068",
+     "duration": 0.126531,
+     "end_time": "2022-02-21T13:10:17.925778",
      "exception": false,
-     "start_time": "2022-01-11T13:57:00.345204",
+     "start_time": "2022-02-21T13:10:17.799247",
      "status": "completed"
     },
     "tags": []
    },
    "source": [
-    "## 8. 60A-80A-120A circuits (metadata to be updated)"
+    "## 8. 60A-80A-120A circuits"
    ]
   },
   {
@@ -3857,16 +3850,16 @@
    "id": "f08fb69e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:57:00.739007Z",
-     "iopub.status.busy": "2022-01-11T13:57:00.732996Z",
-     "iopub.status.idle": "2022-01-11T13:57:06.600326Z",
-     "shell.execute_reply": "2022-01-11T13:57:06.600830Z"
+     "iopub.execute_input": "2022-02-21T13:10:18.183576Z",
+     "iopub.status.busy": "2022-02-21T13:10:18.183232Z",
+     "iopub.status.idle": "2022-02-21T13:10:24.206050Z",
+     "shell.execute_reply": "2022-02-21T13:10:24.205017Z"
     },
     "papermill": {
-     "duration": 6.002587,
-     "end_time": "2022-01-11T13:57:06.601025",
+     "duration": 6.154699,
+     "end_time": "2022-02-21T13:10:24.208214",
      "exception": false,
-     "start_time": "2022-01-11T13:57:00.598438",
+     "start_time": "2022-02-21T13:10:18.053515",
      "status": "completed"
     },
     "scrolled": false,
@@ -3875,7 +3868,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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HzfhLngBFxLDSS80w8oX8NvV64anjIOAh8l3TdSo/5Iuv64F3NXDXH3IHIzPJd18qZQrytro/pXRHWxMWr5Xfe5cnid3p+pTS3yp/pLzHnlL+3Ldm/rtGxHrt5HUQuUnYFTXra03yCW008IYy7sfK7+NSvmO9RCoaKPu+5BPTMndvU0pXke+A7x0RtceCC1JKL9ZmlFKanFKKlNL4BuZbcSj5TtpjVWkTgR0i4o3VI5anaz8nr+/fdJRxSumrKaUvppQuSildkVI6gRyMLiCf6LskpTQf2AU4ntycZS/yMeR64OmI+Fg7k9fmVb2PrVL2sbWA68jHj63rTPa/KaWFXS1/D7g1pVR5allZP3eQg/sf1oxbeXr3BliyD3+MfCf6mZo6P4t8N7P2uDQ6pRRdKWh54n0hsBlwZErp1arBw8rveXUmnVszTr281yXfBZ1Dbi7VE4ZRv3ywfBlXL7/XAnZPKZ2ZUrokpbQ3OTg/OCK26YEyLiI3s55EXg8fJj+tGgdcHG30xtiezq7biPgSuXXA2SmlG6qHdfE41ZSU0sQyzwlVyU3Vt262epnX71JK41NKl6WUTiOfH4aRbxxVdKrc5fx+ALlJ6kyAlNIC8pP3vSNirU6Ucx755uIFJc8DyK9bHE9+3aBLZSzGk29qVT9Rv4h8vui1p1bt1N2+WqaPkQPsE2sHpJQWN5jHmSml2TVpe5IDz9NSSs80kXcz5pDX5zuil7pn76lmAv3R2eTHgYl8Mn+k5oRbCYzqBRK3Ae8p/96D3JyndrrV6aKI2Iu8I9xNvkvfyMVym1JKL5GbcX21XMTtRL6LeRDwu4jYPqU0pcx7PXKb/r3JL7fWWpOOg8ZtyG2jX2pnnHXI7WrbK/fMiPg1MD4i1i3LMRbYnNw0rSMXk5fxa8DREXEb+fH2xSmlJxqYvj31miU9WH5vXsr/RGm2dxzwXGlu8Sfg0pTSnVXTbUPHTT7XJzchfAPlSWoTZd8MeLYE3bUeAN5C3j7VgdQjTcxvidLt65bAhRHx+qpBt5ODvcPIPSVVHEtuottQl+L1pJT+FRGXkOvRlimlLi1LuUA4CTip3GDYoZTrCOCCiHg8pXRLR/mUJjMTyPtgvc8pjKyT1i3rvxv9u05apT491kZ6pSvhdcu/96DtY0S3nGDLDYLzyMezr6eUfl0zSuXEv3KdyVepGac277XIgfWGwPu7Wq9KXiPIx8xqL6WUFpX5t3VjpraMc8rv21JKD9eMewH5+DkW+Geph6vVjPNqCZI7ayL5fdY3ptx8C/K5ZQr5hsYnyL00NqSz6zbyZ0NOJT8hO6q9cftYl+tbD5hD3v4TqxNTSpMj4kmWbRZVXe45LKteufcjPxm4qeY4fzP53H0Q5QZMCcJG1OT5WkppTkQMIzcZ/ltKqbqp+MURcTFwYkT8ttT1Tq3bqpu09wGDasp5C/DxiDiuckOrBPrVryUsKtckTemg7vboMrXjDcDfa2/edlK9fbZyg/ieJvJtSkppfkR8gdxq4rGIeJD84OCKlFKXPgnQkYEUWP0rpTSprYEppRnl4LJVRKxSXcFSSi+T78xR532Uf5Gj4S59PyjyNzsuJ1/g7pFSaurJV62U0ivkJgxXRsRT5KDjo8C3y055HflC/wfkZmivke9GHgIcSGPfOgty85UvtjNOoweks8lN1w4m3wE9jAbfe0spzQPeExE7kO+UvJt8B2ZCRByYUqq0wa0buHbH+wgppeMj4jxyM7udyXdevxwRp6SUKt8+CvL6OLCNbCB3h7sk27bK3IO662Rfefp4InXuhpHfYTo2pbSgtC//OrkddlSdJEaV32uXtOdSO+/aFY+X3+vQDUFK2S8nAZMi4l5yPT2EfPLqyK+AD5Rpbia/OLuI/BTsaOrvY711sdWoRW0NKMFAPVHzexL5SXqPKEHVOeRjxwkppe/UGe3Z8ntUnWGVtOXurJYL/0nkp4t71z4h6YIfkIOPapuR6+2zwLYRsXI5ptWW8eWqYOjp8vv5OvN4rvyuBO7HkJvKVtuV/GSrYRGxCfkO94+rgqqKS8mB1S40GFh1dt1GxKHkfek64D/Lk5H+qkv1rYc8TV7HbdWVt1X9XV3uKTXjjiKfj56tSqsc589tY96HsvTJ9v4s3yrnEHLAtx/5Yrzeu6eXlmnfRW521tl1uwu5UxzI1231fID8/jLAneSmyhVPkFuTdFkDdbenl6knNXPOau/6pjuuy86KiN+Tr8t2IdezoyLiNzUBfLcYSIFVI35LDg4+TlWnBO1JKc2NiD8C+0bEHiml6xqdWQmqriA3oxvXxhOF7lR5+bGyg25HbtN+YkppmRNudO5Dwv8i35W+oYFHu+0GCCmluyLiHuCwiDiX3JTxipqni+3PIDcZvAMg8geX7yE/lasEVq+WYWvV5Nvehy3rNafZtvxe5m5+SunfwI+AH5UmidcCX4mI00rzun+Rn+LcVmk20Y5HyB0/bE/Ny+w12luv/ya/DLxmSmlanWWYztIOXLpNRKxOPoBdz9KOT6ptR+7I4UPkph7rk+/Kfar81Ppq+fkIeV9tT+VOWU90LlC7H0Hbwfqa5BPbL1NKn64Z1vBL3S3uJfK7Tmu0d3OrGVVB1SHAt2uaY1WrPDneieUv/Hckb8e7a/KuXPhvS+4t9dpuKPIp5OaK1SoXvHeSn+7twNJmlZWOkt7Csh9lrxwT6nVAU0mrPIm+APhLzThdeRJeqfeD6wwbUvO7XZ1dt+XC9JwyzT51As9+JaX0XEQ8Q65btSppd/VSce4gB1YbseyNO0padYuFO8lP5ndi+cBqR+DhyrkrIrYg38S8iPoX8LsDn46I/0gp3U0+H76nZpwHyu+G61YX1u2h5Ju0B1P/CfnPyAFiZRk+xrJPlWtvInRKI3W3F5apLY+QOySpdzOnGZWbmm8hB5NtqVyH1Wsy2tAHx+n42vI58vo/pzQX/yVwQLkuu7O9aTst9dLLXH31QzsvvtcZdwPyhdg04J1tjHNIyW+/qrQ3kaP1J6l6YbtmugNZ9iXFPcg76r3A2t24vDsBa7Yx7NxS9s9WlTuRA6vq8d5E3llrXw4cT/3OK45pbx1TvhNW/l15OfOL7SzDkWWcX5bfDXVCQE03tyUtyM34nqtK+1TJ979qxv0ZXeu8otJd/wjqd2xQ6QJ/q/L3fuXvHzWwviqdV0yivLBeu3wdrVeWdl7xvZr091XWc539ZXwbZWu4u/Wq+db9oHTJaxala92y/var8/PNks8vyt+jyvjDqf/9oreW+lu3S+AG69Jb2lpGcjCYqPqeHTmQTlR1lFDSVyef8C6oSX8dOZitfRF4AnVewK0aPoMudpRDk92t1xl3InVe5q9Xh1jaO+d+bcx3vZq/G+5unbwvVo5tdT/XUDP+neSbCRtWpW1Y0ibVjDuSHGjNIzdR68z67mrnFW+m/e9YHVST/pcyfvXxaTC5ue0CuvCh7PbKTr74WUi+u75mzbBj6eD43tV1Sz7/LCIfC5frVKFm3P7U3fqpZT71vks0lXa6x6d7O6+ofCfzipr0ymcJzq5KW5d8TXM79b9jdXxVWuWDvm9rY76jy/CfNFDGyvcO63W3/sfa+TS6bsu2mU07x07yU7SF7dWZrtajTtbdXl8mln4r8lt1hkXNctSes5ZLqxpW6bzihXplqMn7OXLAX522eVnGZc6J1O+8otIx0dvqlGG5b2qx9JMqe9YOa/bHJ1ZVUkrPR8T7yT0q3VyeRN1EbrqzFvmEtx/5JcLnq6b7R0R8hNyF9b3l/Y7byYHTpuSDxfbkC1kidz/+e/IFwfnA+3KrvGXKsuRuZnnh7jHgppTS2A4W42PkrtavYukH5dYmNzvalfxe0Hll3H+S7xR9pbRtfpj8JOVT5KZ9jXQ7DLlZy3uAUyNiN3L71enk7jR3J6+vXcu4D5IvDj8TEbPJQeyLadnmHxeRDy4HleVutB3s8ZE757iyTBfkE8HWLO1oAvJ2+g5wdkRsTb5b8l7yAbIt9wI3RMRPyAeAvcknql+mlCpd0u5a8ryMvC5nktfhJ8k94D0MkFL6bUScT34U/bZS3pfJdw13Ir9jVHlv646IOJl8wfK3iPgNue5tRq6LO5DXYXvrdSK52dGxpS7dXObxGfIBr/qF4I7sQP7e1i/IB9T2HEY+KNb9DEFKaXZEXA3sExGjUn65dbknURFReZp2f0qpevgbgKsj4gryU8BZ5P3sUPJJ7Ig6eSXgiZTS6A7KPg74TkRcR27u9zz5RDaW/ITtOXLvdxW3kdvL/7TsewvI2/yxksdBETGHpc1LPkWuo2vTObcB4yLiWErvnymlZrq27i1fJ3/I95JyfLyN3HPjpuRj090sW5/+VIY10oHFqeRtfi/5XaKDaoY/WrWPQu4x60bgzxHxo5L2WXKTzC/VTHs9uYnUr4GRdfL+a8pPqAGIiA+y9NMOry9px5e/p6WUftzRwqSU7i/HmaMi4nLyBeU25F5PbyI3La32WfKTrUkR8UPyMX9/8r56YkrpyY7m2Zmyp5RejYj/pXwGICJ+Tj6GvpN8/nmUxpoBNrxuI3+C4lzyeeU3wH/WnDNnppSq78q3eZyqWqZKJwDbVaXdnFK6uWrczmzPfcnn8xPIF34V3yM/Zf9VRJxObsp1ALnb7E+mlGbUlO8o8rvNkHvW27RqnvemlP5QNe5E8rF915TSZNqRUpoU+R3mA8q1zZXkfeyz5OPZhKpxX4qI/yF3oV2ZbhR5mz8E/G+Z/2Dy+n08VXXuVDPfxyPibuDAiPhSav89nivJ1y17RcTNLO0u+8PkpvWX1syn0XV7APnp02XtzPuysiyfKPm2q9F61IW62xfL9APytdLxkbvNv4583fZGYCs60WV+tXKOP4x8Xv9HRJxDfgK6Lvl1jdPJ18KQb759m6Xn9A2BT5ODrUY+SVBpSXJyRFxUyv8P8hPOmyLid+XvqeTj6ZGULuq7smzt6u5Irb/90IknVlXTrElu43tr2QgLyCerW8h3zzdqY7pR5JP8/eSL6krvNr+kfoTf5k9NvpUu3S9qoOxvIlfOW8h3FOeTL7jvIR8416gZf1Ny2+WXyBfBd5BPEBNo8IlVGTaEfOK/k6Vduv6LHCTtUTPuXuTvKVW66p1cJ7/KHej/6eS2/g35PYU55JP97eTAJmrGfUdZR3PJQc3ZZbsvc+eJ+h8Irnzg7kSW7Sp7M/LTqX+SD6Kzyr9PBEbUKe/HyTv19FKOx8knkv3rjHtAKe+Mkm/l5LZSI+uVpR8I/nepEy+S6+Wmbewv4zvYnybWG1413hvLeJd1MN4BZbyvdXYfJj9h/mVZF9PJ++mT5Iup5Z52sPSTCrc0UJdGk4OBG8u2nlfW+wPkd/82qBl/EPkipPJB3yXrkBywn0PeH+eSjw+HU//u3wTaf2L1BvJJbzp1jhUN7B+JPnhiVdKHkZ/23U/eP2eQ94+fU9WVexn38UaXjbY/0Fz5qVf2ncjB28xSjmupc8e9g3zrLePEdsZ9vBPbajD5IvbhUveeIV+ErNbG+NuRe7mdVurYPbVla2CeDZedHPAeTj6+ziTve48DPwHWbXB+Da/bqv2i0fJV6mC9bd9ePhOaWCfj6+VRho0iH6teLtvnb9Q5zlfX/TZ+avfNy8hPK+u2lKmT9xDyTbpKvXqR3ER04zbGH0++YTG3jHseVU+XWfrJjtM6mO9xZbwDGyjj6uQbnw+VMlaOmV+h/icoOly35OuSBcDIdua7Mvm4+nA31N8JVeN1qu721TKRm+F/nXyOm0s+ltwJfKZOHR/bXlqdvHcgN0d8uWzTJ8nXhptXjTOEfAP8uapl/iD1r0WXSyvpXyFf4yyobAfyzcszyD0gTyOfe6aQr5869XSy0Z9KMyL1YxHxOfJF25tSEz1RtZKI+Cn5icPolNLTHY0vdaTcOfw9uUnujX1dHknqqvJe4YvkZnOf6OvySMoMrFpAaVr075TSZ/u6LL0hclfET5GbPn6wr8ujFUNpXrWJdUpSqytNtm4if6jXm49SP2FgpX4jIt5E7njgE8Bu5A5Ebm1/KkmSJKnvNfKNIqm37Edu7701uV2vQZUkSZJagk+sJEmSJKlJPrGSJEmSpCYZWEmSJElSk1iO/CsAACAASURBVAysJEmSJKlJBlaSJEmS1CQDK0mSJElqkoGVJEmSJDXJwEqSJEmSmmRgJUmSJElNMrCSJEmSpCYZWEmSJElSkwysJEmSJKlJBlaSJEmS1CQDK0mSJElqkoGVJEmSJDXJwEqSJEmSmmRgJUmSJElNMrCSJEmSpCYZWEmSJElSkwysJEmSJKlJBlaSJEmS1CQDK0mSJElqkoGVJEmSJDXJwEqSJEmSmmRgJUmSJElNMrCSJEmSpCYZWEmSJElSkwysJEmSJKlJBlaSJEmS1CQDK0mSJElqkoGVJEmSJDXJwEqSJEmSmjSkrwvQn6yzzjpp9OjRfV0MAGbNmsXw4cP7uhgaYKx36gvWO/UF6516m3VuxXH33Xe/nFJatzbdwKrK6NGjueuuu/q6GABMnjyZsWPH9nUxNMBY79QXrHfqC9Y79Tbr3IojIp6ol25TQEmSJElqkoGVJEmSJDXJwEqSJEmSmmRgJUmSJElNMrCSJEmSpCYZWEmSJElSkwysJEmSJKlJBlaSJEmS1CQDK0mSJElqkoGVJEmSJDXJwEqSJEmSmmRgJUmSJElNMrCSJEmSpCYZWEmSJElSkwysWtGihTBvZl+XQpIkSVLR64FVRGwbEX+KiNkR8WxEnBgRgzuYZqWIODUi/hwRcyIitTPu3hFxf0TMjYgHI2L/7l+KvjX2vMPZ6bwd2fW8I/q6KJIkSZKAIb05s4gYCUwCHgT2BrYATiMHeMe3M+kw4JPAHcBfgd3ayP9dwGXAT4HPAXsBv46IqSml67ppMfrcjx56LyOGHsyrC17p66JIkiRJovefWH0aWBX4cErp+pTSWcAJwBcjYo22JkopTQPWSintCfyunfz/B7g5pfS5lNKNKaUvA9cA3+i+Reh7T+9yKv/a45M8td1vAFgwfxHz5ixsOt+UEosWLmg6n7YsXLCABXPnsnjxoiVpV/3o+5x+wIeYdO6ZkFL+6S8WL26oPHNnzWTRwubX/5LZLlrEjFdeXvL3ooV5vXXWvMWLeXXePGbPnsHs6a/lxMuPgBPWgqu+lJdt5osd5vN/p3936TZqx5yZM5g/Z3any9kpixbmny5YnBYzZ94c0oLFzFk4h8VpMZDr/RWnfKuhZQRYtGgeKS2tw1f+8JSGp23E1T85o6n8rv3ZD7u1PHWlBAvmNJfF4sUsXrRoufRFCxeSuvE48Mcfn9bz66OYPf01Fi7o3mPo1T85fbnyz57+2jLHUQAWzIVFHc97/pzZzJvd2H6aFi/u1m0hSSu66M2DZkTcDDybUvpoVdomwBPAh1JKf2ggj6OAH6WUoiZ9ZWAG8LkSsFXSDwbOJwdmr7WX95gxY9Jdd93VmUXqMZMnT2bs2LF1h4254QqejtGMS1fzicXnEAGDZ27M0at+g+eHrrVMMLAr1/Ox9At+FQczmffwgWfmcuDIz7Fw1anMZyjTWIt1eYFFC4fy80Gf4dbB72Q9nud5NswZREBKvGf+Xxk/9AxIQCRqa82JC07lkZU2WyZt8xmLOHnON5i/7r9YOHcYg1eZxbx5q7DyynN48cVNuWy9D3FL7LJk/GFpFifwNTZc+DIMmcciggdeeAdbrnkvK688h6mz1+aRe3dl07feyuqrTGUYcxnEYn4YX+R2/l9NiRLjuJbx6ZxSZkiL8+LMnD+Kb6xyHC+ywTJTjF10A4cP+iksHgSDFi8dsHAVfjz0U9zKzsuMvzvXcsDcXxMrL2AV5uXVHrBwwVAufumnXDNq5HLbbneu4VBKmZaUNPsSP+KFQRvm7VfWO8BuXMeBsy9i1VVnlW2SJzo3HckNg3ZfZjtVFnbDxU9zSnyB6p0kAWfG57iFdy+T/+5cy0Hzf8Fmt32Th7b7KWnEDBbPXokRw15mAUP4GUdxW7wTYtCSacZxDePTOcT0UaQ1nqmaR3D6ouO4Z8jblp3Hwhs4dPBPl4wXC1cmDZnHkJkb8txKKzF/pfl8JX5QFg7ezQ0cns5kUFk7ixaszKCh8wCYPXNNVpqxLYdv+N8siFXKjBO7cS0HpF+yKnNZOGcNhqw6g1ef3ZJBq05jtZGv8CO+wN2x4zLlGsc1HPDqpcyYOYJ1Nn6ykhURcE76NJMHjVtm+w1nBmenQxg8e10WDnuZxYth0KCc1/lxOH9iz+W2efX6evXZbdhoyFBmr3cfAZzHEfwp3rNkuQE2WPwsmw96lNt4J2MX/YlDB53NnGfezForLWbuug/ys0Wf5eYh71pmmkr+c+cOY5VV5rD60+9i9rr3sXjl1zgzjuIWdmEtXuIV1gNgFE9xcjoagBFPj+X51aZz0cgduInd2HPmP3hx5mrcs8FmjOQVXmXtXA8XX8++cQm/joP5a1UdGsZMzlrw3wweMosEzGZVhpGDrnPTp7hx0HuWWx8b8jSnpC8s+Xvx4uCl59/Aehs+wlnxWW5hl2XHX/w0H7nlTuYtDrbc6hbWW/+xpZtx0VDOHXIoN7J0Pqsyi5/M/hwrrbrsIX/4szvyi3QkV2w0HIC1ebGsk3y8OGjBLzhu6Kk8x0ZLp0mzOZtPwKIhpMELmL9gVVYampcvgI/FpUv3jVKo4WkWZ/MJUlm2QYNgyJyRLFz1VQBOT8fyt0FvX6YubsSTfC99cZnyRsDiBM89vzNrrXc3xw7+Pq+w3jLbb86c4Vw87EBuYA9251oOSeewkCHMe+ItnPO6Pbhj5bcCsHu6ln35LRfGeG6j7M+Q952Fk9l38IWMZBqvPLsVg1aZzsi1ngNgPkP5TJzLXIYtKddG6SlO5mhIQYrE7FlrMHPmOqy3/r9JwFf4Ic/FhkuXA3j3M/P4zcd3XK4u9KX2zrNST7DOrTgi4u6U0pjl0ns5sHoR+GlKaUJN+ixgQkrp1AbyaCuw2hZ4ANg1pTS5Kv3t5CaEO6SU7mwv71YJrDa48e/5H5UTubpXZZ/o7Lp1eww8XdnmnZlmINSpgbKM0DrL2RPbJCWe3+2t3Ztnk7zIVW+zzq042gqsevUdK2AkMK1O+tQyrNm8qZP/1Jrhy4iII4AjANZff30mT57cZDG6x8yZM9spy5r5V6ucpFtNV9er22Pg6co278w0A6FOuYz9Tw+Vt7+cXyvaP89K3c86t+Lr7cCq30kpnQ2cDfmJVX+5k9DuXY3KE6tatU8fK81MunKSrGmOtiS/jqapnX+j82nr70ZUl7W6zO3l09Wy9uQ0tcvRiNrt0+iyd2Ydd6YO1M6jM8vU1TpXGaejeXR1XdXq7H7Q3jRdyb/edI1u70a3Q6Pl6IzO5NvZ9dLV7VQ7Tlvrp7PrrTPjd6a8jYzb2e3XlbI2kn+d8vaX82uFTw/U26xzK77e7rxiKjCiTvpIlj5ZaiZv6uQ/smZ4yxu+ePrSjh6qfjbiSS5M+3Fh2o+NeBJSIlhcd9yOfjbiSQalRYzjmmXya++nMu6FaT/GcU0D81m8XL6NzKf2ZwgLlvm9EU8u+XdbP8OZsaSsw5nR8Drp3PJ1bppgMYPSorIOGttulfwr620jnuxwHTa6vLXratl82y9fZR7DmVG1TB3Pp3qZOi7n4qp1tbjDul5ZjnFcs6RudzSP6nrS6Hav3uYXpv3arYtDWNDp/LtSrzqz7RvZf7ryM45rSlk7rtu167CjcteO39BxhPr5tLWdOqqLleUblBY1tP6qj5edOb42sn9fmPZreLvkddv+NunK+q2Ud3Xy+er/zbytr0+dktTjevuJ1UPA1tUJEbExuTv1h5rM+1FgQcn/pqr0rYHFwCNN5t9v7DT9H9w84m08uVt+EXjSuWfys2d+yUObzOCLMZwt1tyCBVP/h52fXI1Pjfo44w47kq8+8hS/fOYVfvvsmew05VIYcwiTnn899153Vc40gu3fsxfP3DmXmelNrDz/Qcas8VW2G/kcg95+GHe9f+8l8z/4yvu5ftUFfOeOu9nttTfwl5F/53sbnMt9BLdvdSjveGAt3jbpasZt+DSvPP0EG7/8GqvPnc/QQ8cz7rAjl5T3kU1msu/W+/OOB55dUo7d1p/C9ms9z6C3H8bcf7/Gyi9fxjNzxvDQVh9m3VEP8/KQq1hn4fvZ/r3/y9QrpjDr9ucY/o7Xcfcr13PfpKvZbtz7lszj3uuuWrJc4w47ss6afJQfH/pRPjPrFFYevhpHnXfxMnmO3Of1PH/G3Sx8YTYzFk/lj0/8nJtGf5r1XnsLI9e/nXU3O5g1Zwzlm8MOZ9xhRzL1iinMvO0Zhg/6I0/M/D3rbLwpF6zyCEevsRoB7D/9bLZZ72YumfMMW1Ztm4rKvIestxELX5y1ZLkq6+q/tt6fg/98M0NuepCpjw5n1vbb8faLL2Hil67jgKd/DsD2e7x/SZ4Tv/TfvPL0E+y1xQtss/KjMOYQeP9pTL1iCrfe8BSPL0iMWHcqL/zrF2w37n1s/K7nefqZX7HRqAPZaqsTOOm2k7j0kUv5yJYfYdyOj3IXcMV5Y1ltk6eY+eTG7HPo5Fzwq74Ed53PSVu/g0vnPccZj32HLWavxt8GP8QDH/o3H7zxjYx4bU3+uOZV/Gr4ZXzz8aPYcujruWudR/jmuj/M1Y9g/6325+s7fp37vvsEa047j9+t+SrbHfdunjp1T0bNvI17p76OV7b/POMOO5KHH/4mTz19ES8/MIJn/roh72ZVVrv/QVbafHPmTZnCk2uvwZBDPgHAK7PPZe1tp7Hugg+w1k3nceyoGzlqzPHMmv0o/zNqLlttdcKSbTDp3DOX1qMNpsBd5/PUsLdzyV1D8wg73Mi6a/+Kzzy/P3tN25k1dhzFyH1ev2S6tTbcmFeffQrGHbNkO2wzcRee5xVeP38BX3j1WB54cjRv3HkUC2bfwH2TroZxxzBx7c340+rrsf0Dd3DhsNuW1OHBd81jizXeyrQ1p7LxNm9i1u3PkVa6i1FM4JnVdmTjbd/EuLtOhTEvM/GGuWw6+w1sscZbWX2nUfz+z2fwytNPLFcvaut4RWV777vlRzjgt48xdPBbgeDKkTdz7/oPcNYhvwbgpl8/TNz5HJutNJjVdnzdMsu/3bj38dIzb+XVZ2ez0qpzmfH8WUv2SXjrMuv4I2+bx5CbH2LOqocxdLN3M2X631k0ZuWy7Ldx36Q3Lpn2UeC5E05k2iWXsOZ//RevG/Ma3HU+jDmET7/4LH/lH5z11Pp8uuxT3zv3TO6bdO6S7fG3/T/DDWusz/YP3sGXVl28ZNtW9omrfvo17npxCDu+6XaGrPUYG406gK22OmG5dVXZp97xnoeYt9liNlq4OfOue4E3rfYk/5i5Cduddv+ydais8w9c81Uef+EqguCjpZ7n9XEcJ912EgseOp6jps/gE/O24uG19mHw3fPZYvW38OiMv/PamN+x2iZP8fKDa3LvX7dlzJ4Xs3DwP9lx0TZ8YLW/s8pa81lt+JbsuOPVSw9tV+3D83ftzqwhH2DqjMMBGL7j8sfJ+757BWtOG8m0NZ9ku+P24bkTTmTqxRfzxFqr8+DG67H9e/bi9je+ysUPX8zRaRhfm3IQ71q4E9fvuCF3v3I9C8//BZu8Mp2RH/0o0z+6iKeeuYhbZg7h72kb7p/6KGc9sR4j3zmN0Quf5vIP1TsGS9KKpbc7rzgO+DKwaUppRkk7BjgR2CClNL2BPOp2XlGGXQsMTimNq0q7ElgzpfSujvJulc4rPva7n/LnEW/jpGum8/FT9ujdgmmFZjMF9QXr3Yprh0m/Z8TCmVz/3o/1dVGWY71Tb7POrTj6S+cVZ5E/3Ht5RJwMbA5MAE6vDqoiYgpwU0rpsKq09wHDgbeUv/crg+5MKT1R/v0tYHJE/C9wBfkDwXsB7+3JheoLAWy6YGhfF0OSpDZF7927laQ+16uBVUppakTsDvwY+AO5B78zyMFVbbkG16SdCWxa9fel5fchwMSS/19KwPVt4EjgMeDAlNJ13bcU/cfolWtXkSRJkqS+0Ou9AqaUHgR262Cc0Y2ktTHtFeSnVSu8G9b4G+N5d18XQ5KkNiWCm379MLscsFVfF0WSelRv9wqobrTyhv3jfTBJkurLbQFn3PtAH5dDknqegVVLyv12HDD+wj4uhyRJHdsurdPXRZCkHmdg1aIC3wiWJLWGe+Olvi6CJPU4AytJktQjKt9F+eDOf+3TckhSbzCwkiRJPeuu8/u6BJLU4wysJElSzxpzSF+XQJJ6nIFVK/KLi5KkFpEi4P2n9XUxJKnHGVi1oLSk1bokSf2XHS1JGkgMrFqWJytJkiSpvzCwkiRJPcbbgJIGCgOrFjSobLbHJv6qj0siSZIkCQysWtLgVWYA8Ao39nFJJEmSJIGBVUuKleYA8NpGk/u2IJIkSZIAA6uWtGj+KgSJKc+9vq+LIklSm+wVUNJAYmDVgubNGwYET92/SV8XRZIkSRIGVi3pkVU2Zw6rcuub9+zrokiSJEnCwKolPT90A4jgwQ1H93VRJElqlx+1lzRQGFi1oFHzX4CUeN8//tzXRZEkqU2GVJIGEgOrFrTl3MdYlTmc9/nP93VRJEmSJGFg1bLsaUmSJEnqPwysJElSD/EmoKSBw8BKkiRJkppkYCVJknqMvQJKGigMrFqQJylJUivwfWBJA4mBVcvyZCVJ6t+8EShpIDGwkiRJkqQmGVhJkqQeEUv+J0krPgMrSZLUM5LN1iUNHAZWrci7f5IkSVK/YmAlSZJ6jB1YSBooDKxalKcpSVJ/57lK0kBiYCVJkiRJTTKwkiRJkqQmGVhJkqQeY7+AkgYKAytJktRDDKskDRwGVi3I05QkSZLUvxhYtSzDK0lSK7BvQEkDg4GVJEnqEYZUkgYSA6uW5KlKkiRJ6k8MrFqSzQAlSa3BM5akgcLAqiX5xEqS1AoMqyQNHAZWLcrQSpIkSeo/DKwkSZIkqUkGVpIkqQfZxkLSwGBg1ZJssy5J6v8MqSQNJAZWkiRJktQkA6sWlMJ7gJKk1mAbC0kDhYFViwpPVZKkfs5zlaSBxMBKkiRJkppkYCVJknqMzdclDRQGVpIkqWfYElDSAGJg1YI8T0mSJEn9i4FVyzK8kiS1As9XkgaGXg+sImLbiPhTRMyOiGcj4sSIGNzAdCMi4vyImBoRr0XERRGxds04K0XENyJiSkTMKb9PiIiVe26JJElS23zHStLAMKQ3ZxYRI4FJwIPA3sAWwGnkAO/4Dia/BNgS+CSwGDgZuALYuWqc7wGfLnndA7wN+DawJvD57loOSZLUMbtblzSQ9GpgRQ56VgU+nFKaDlwfEWsAEyLilJK2nIjYCdgD2CWldHNJewa4PSLGpZQmlVEPBM5MKZ1e/r4xIkYBH8PASpIkSVIP6e2mgO8Drq0JoC4mB1u7dDDdC5WgCiCldAfwWBlWMRR4rWbaaaxg7RBWqIWRJK3gPGtJGhh6O7DaGnioOiGl9CQwuwxreLrinzXTnQN8KiLeGRGrRcTOwJHAj5sqdT+TPElJkiRJ/UpvB1YjyU+Qak0tw5qd7qvAZcBfgBnAzcDlKaUTu1TafszQSpLU36Xy35kTVrjTsCQtp7ffseppXwYOAj4L3AdsD3wrIl5JKX2j3gQRcQRwBMD666/P5MmTe6mo7Zs5c2aHZekvZdWKo5F6J3U3692K64Uh6zE11uK6/3iRbfrZNrbeqbdZ51Z8vR1YTQVG1EkfWYa1N9267U0XEeuQewD875TSz8vwmyNiPvDjiPhxSunF2gxSSmcDZwOMGTMmjR07tsFF6VmTJ0+mrbL85P8eAWhzuNRV7dU7qadY71ZcU2+4ByK4ffgOjB37H31dnGVY79TbrHMrvt5uCvgQNe9SRcTGwDDqv0PV5nRF9btXm5M7r/h7zTj3kAPITbtQXkmS1EVrpVchJXZ77c6+Look9bjeDqyuBvaMiNWr0vYH5gA3dTDdBhHxrkpCRIwhB1NXl6Qnyu+31UxbuUX2eBfL3O/4VRBJUivYYOGLbL7oMbZ53St9XRRJ6nG93RTwLOBzwOURcTI5MJoAnF7dBXtETAFuSikdBpBSujUirgMuiIhjWPqB4L9UvmGVUnohIq4ATo6IVcjvWL2l5H9pSumlXlrGXmJ4JUlqDV/f8et9XQRJ6nG9GlillKZGxO7k7s//QO7p7wxy8FNbrsE1afuXcc8jP2m7khykVfsE8I2SviHwDPAz4FvdthCSJEmSVKPXewVMKT0I7NbBOKPrpE0DDik/bU03HTim/EiSJElSr+jtd6zUDfyGlSSpVfhRe0kDhYFVC/LtKkmSJKl/MbBqSd79kyRJkvoTA6sWZWglSZIk9R8GVpIkSZLUJAMrSZIkSWqSgZUkSZIkNcnAqhX5gpUkSZLUrxhYtaiw03VJUj/nfUBJA4mBlSRJkiQ1ycBKkiRJkppkYCVJkiRJTTKwkiRJkqQmGVi1ILutkCS1imQXFpIGCAOrlmV4JUnq3yJ5rpI0cBhYSZIkSVKTDKwkSZIkqUkGVpIkSZLUJAOrFuSLwJIkSVL/YmDVogytJEmSpP7DwEqSJPUY+wWUNFAYWEmSJElSkwysJEmSJKlJBlaSJEmS1CQDK0mSJElqkoFVq0q+DixJkiT1FwZWkiRJktQkAytJktSD/PKipIHBwKoVeY6SJLWA8CtWkgYQA6sW5GlKkiRJ6l8MrFqUD60kSZKk/sPASpIkSZKaZGAlSZIkSU0ysJIkST0mBexz4e/6uhiS1OMMrCRJUo9abfoZfV0ESepxBlYtya4rJEmt4x/DXu3rIkhSjzOwalF+G0SS1Cre/urwvi6CJPU4AytJktSjfv7F2/u6CJLU4wysJEmSJKlJBlYtyWaAkiRJUn9iYCVJknqQHS5JGhgMrFpQ8iQlSWoBdrQkaSAxsGpZnqwkSa3hn0d/oK+LIEk9zsBKkiT1qHTtlL4ugiT1OAMrSZLUo2LP1/d1ESSpxxlYSZKkHrXNGVf2dREkqccZWLWgFHZeIUlqDb4RLGmgMLBqUYZWkqT+znOVpIHEwEqSJPUIn1ZJGkgMrCRJkiSpSQZWkiRJktQkAytJkiRJapKBlSRJkiQ1qdcDq4jYNiL+FBGzI+LZiDgxIgY3MN2IiDg/IqZGxGsRcVFErF1nvLUj4mcR8XxEzImIhyLi4J5Zmr7kK8GSpP4tqv4vSSu6Ib05s4gYCUwCHgT2BrYATiMHeMd3MPklwJbAJ4HFwMnAFcDOVfmvAdwMzAQ+C7wMbAus1J3LIUmSJEnVejWwAj4NrAp8OKU0Hbi+BEMTIuKUkraciNgJ2APYJaV0c0l7Brg9IsallCaVUb8GrAyMSSnNKWk39uDySJKktti4QtIA0ttNAd8HXFsTQF1MDrZ26WC6FypBFUBK6Q7gsTKs4hDg3KqgSpIkSZJ6XG8HVlsDD1UnpJSeBGaXYQ1PV/yzMl1EbAasB0yLiD9GxPyIeCkiTo+IFaopoDcAJUmSpP6ltwOrkcC0OulTy7Bmptug/D4FeAZ4L/Ad4Ejg210pbH/mq8CSJElS/9Hb71j1pEqs8UBK6fDy7xsiYnXgaxExIaU0e7mJIo4AjgBYf/31mTx5cq8UtiMzZ87ssCz9paxacTRS76TuZr1b8fXH7Wu9U2+zzq34ejuwmgqMqJM+sgxrb7p1O5iu8ru2s4obgBPIPRDeX5tBSuls4GyAMWPGpLFjx7ZTjN4zefJk2irL6Vf9G6DN4VJXtVfvpJ5ivVtxfffqC0n0z/OV9U69zTq34uvtpoAPUfMuVURsDAyj/jtUbU5XVL979Sgwn+VbyVX+XtzZwvZXNgOUJLWC8K1gSQNIbwdWVwN7luZ5FfsDc4CbOphug4h4VyUhIsYAm5dhpJTmA9cDu9ZMuzu5c4wpTZdekiRJkuro7cDqLGAecHlEjCvvN00ATq/ugj0ipkTEuZW/U0q3AtcBF0TEhyNiH+Ai4C9V37ACOBF4a0ScHxF7RMQxwFeB76SU5vX40vWS5DMrSZIkqV/p1cAqpTSV/ARpMPAH8rtPZwDfrBl1SBmn2v7kp1rnARcAdwP71uR/B/BBYPuS/+eBk4Dvdudy9AdB4vxv/7iviyFJkiSJPugVMKX0ILBbB+OMrpM2jfwB4EM6mPZa4Nomitgydp+5XV8XQZIkSRK93xRQ3ejxeYv6ugiSJLXL5uuSBgoDq5aUe1n63Xr2tiRJ6s88T0kaOAysWlDl7t8Zx7XbolKSpD7m0ypJA4eBlSRJkiQ1ycBKkiRJkppkYCVJkiRJTTKwkiRJkqQmGVhJkiRJUpMMrCRJUo8Iu1uXNIAYWLUoT1aSJElS/2FgJUmSJElNMrCSJEmSpCYZWLUiP2QvSZIk9StD2hoQEZd0Mc+vpJQe7+K0akAyspIktQjPWZIGijYDK2A/4B5geoN5BbAz8D3g8eaKJUmSJEmto73ACuDIlNIdjWQUEUOA+c0XSZIkSZJaS3vvWJ0APN2JvBaVaZ5tqkSSJEmS1GLafGKVUjqhMxmllBI5sJIkSZKkAaWpXgEjYnhEHBQRV3VXgSRJkiSp1XT0jtVyImIl4P3AAeX3qsCD3VwuSZIkSWoZDQVWETEIGEcOpvYBRgAJ+CXwg5TSPT1WQtUVpL4ugiRJkqSi3cAqIt5JDqY+AqwDTAN+C/wRuAw4z6BKkiTV401ASQNJm+9YRcTjwM3AwcAkYG9gg5TS4cANvVI6SZLU8m471ssGSSu+9p5YbVJ+3w/cCNySUlrQ80WSJEkrkg07/0q3JLWc9noF3Bz4GrAacDbwXERcGREfA1bvjcKpvkT0dREkSWrY3wZ35rOYktSa2gysUkqPp5S+l1LaHngz8H1gK3KHFVPInVe8PSKG9kpJtQzbrUuSWsX3N7qsr4sgST2uoe9YpZQeSCkdn1J6A7AjcCbwHHAq8HxEnNmDZZQkSS3sL58xsJK04uv0B4JTSneklI4GNgZ2J/cO+JHuLpgkSWp9KWy+Lmlg6HRgVZGyG1NKRwAbdGOZJEnSYpEztgAAIABJREFUisBW65IGkPa6W/9QRIxoJJOU0sKqadborsKpLZ6pJEmSpP6kvSdWvwO2bDSjiBhcpnl9s4VS++wVUJIkSepf2vuwRACfi4jnGszLq31JkiRJA1J7gdWTwLs6md+TwLyuF0eSJEmSWk+bgVVKaXQvlkOSJK2orvoSvP+0vi6FJPWoLvcKKEmS1J4lH7O/6/y+LYgk9QIDq1bk22ySpJZQTlhjDunbYkhSLzCwkiRJPctmgJIGAAOrFhXJb1lJkiRJ/YWBlSRJkiQ1ycBKkiRJkprUdGAVEedFxHcjYtPuKJAkSVpxJHtckjRAdMcTq92AQ4EpEXFpN+SnDniSkiS1giXdrUvSANDmB4IbVfmQcERsBuzUbH6SJEmS1GqaDqwqUkqPAY91V36SJEmS1CrsvEKSJEmSmtTmE6uIeAkabxydUlqvW0okSZIkSS2mvaaAP6ETgZUkSZIkDVRtBlYppQm9WA5JkrQCsidbSQOF71i1KLuwlSRJkvoPAytJkiRJapKBlSRJkiQ1ycBKkiRJkppkYNWCfBFYkiRJ6l96PbCKiG0j4k8RMTsino2IEyNicAPTjYiI8yNiakS8FhEXRcTa7Yy/d0SkiLire5dAkiRJkpbV3nesul1EjAQmAQ8CewNbAKeRA7zjO5j8EmBL4JPAYuBk4Apg5zrzWQU4A3ihu8ouSZI6xx5sJQ0kvRpYAZ8GVgU+nFKaDlwfEWsAEyLilJK2nIjYCdgD2CWldHNJewa4PSLGpZQm1UzyZeAZ4FHgTT20LH1ut2vu5Yb3bt/XxZAkqT7jKkkDSG83BXwfcG1NAHUxOdjapYPpXqgEVQAppTuAx8qwJSJiE+ArwOe7q9D91SF/fKqviyBJkiSJ3g+stgYeqk5IKT0JzC7DGp6u+Ged6U4DLkkp/a2JcvZrg4fMZ9CgRYza/oq+LookSZIker8p4EhgWp30qWVYV6bbvPJHROxGbjK4ZRNl7P8GLwQgbXpTHxdEkiRJEvR+YNVjImII8EPgpJRSw51WRMQRwBEA66+/PpMnT+6ZAnbSzJkz2yxLWjSEGJyY8fwb+015tWJor95JPcV6t+Lrj9vXeqfeZp1b8fV2YDUVGFEnfWQZ1t5063Yw3eEl74kRsWZJWwkYXP6elVJaUJtBSuls4GyAMWPGpLFjxzawGD1v8uTJtFWW7139FItjMPscZFNAda/26p3UU6x3K67TrnqMRPTL7Wu9U2+zzq34ejuweoiad6IiYmNgGPXfoaqebrlu1UtelehiK2Aj6nexPhX4OHBhJ8srSZIkSR3q7c4rrgb2jIjVq9L2B+YA7b0wdDWwQUS8q5IQEWPI71ddXZJ+DOxa83Mt8Ej59/XdtAySJEmStIzefmJ1FvA54PKIOJkcGE0ATq/ugj0ipgA3pZQOA0gp3RoR1wEXRMQxLP1A8F8q37BKKU0BplTPLCLGA+uklCb38HL1qkT0dREkSZIkVenVJ1Yppanw/9u79zi5q/rg45/vzm6Szea2CZCQC4RLIIBAwURuIhECCrRKrUrtowWr0ovWPq21D9ZLg9LnQX2hPvVaqkgtWrHWxyoowQDhUpGb3CTcEiEhbC4QEshuNpu9nOePmd3MTnazm8zOzszO583rR3bP75zz+87s2Zn9zu/8zo9zgAzwU+AK4IvAPxRUrc/VyXcx2bNa1wLfAR4Efr+U8VYyUytJkiSpcoz6qoAppVXA2UPUmT9A2TbgvbltuMe6dB/DqxLZW9mv+OS7WfoZLxuTJEmSym20r7HSCEgBicS9r0weurIkSZKkkjOxqkLrMwezvm4ety1eWu5QJEkaVORmWEhSLTCxqkIvZ2ZABKtmH1buUCRJkiRhYlWVpne/DClxybyB7pksSVKlcKklSbVj1BevUPHmdm+gKdq46qiTyh2KJEmSJDxjJUmSJElFM7GSJEmSpCKZWFUhZ6xLkqpF8l1LUo0wsapCLl4rSaoGLrcuqZaYWFUpP/+TJFU60ypJtcTESpIkSZKKZGIlSZIkSUUysZIkSZKkIplYSZIkSVKRTKyqkEvXSpKqhQtYSKoVJlZVy7cqSVJl82NASbXExEqSJEmSimRiJUmSJElFMrGSJEmSpCKZWEmSJElSkUysqlS4doUkqSq4hIWk2mBiJUmSJElFMrGSJEmSpCKZWEmSJElSkUysJEmSJKlIJlZVKHkhsCRJklRRTKyqlssCSpIkSZXCxEqSJJWMHwNKqhUmVpIkqSQimVZJqh0mVlXJNypJkiSpkphYVSUXr5AkSZIqiYlVlTK1kiRJkiqHiZUkSZIkFcnESpIkSZKKZGIlSZJKyMnrkmqDiZUkSSqJcBVbSTXExKoKpfDTP0lSNfD9SlLtMLGqUn4KKEmSJFUOEytJkiRJKpKJlSRJkiQVycRKkiSVTPI6K0k1wsSqKnl9lSSpGvh+Jal2mFhVIT/9kyRJkiqLiZUkSZIkFcnESpIkSZKKZGIlSZIkSUUysZIkSZKkIplYSZKkknFdQEm1wsSqSoVvVZKkCucatpJqiYmVJEkqDT8DlFRDTKwkSZIkqUgmVpIkSZJUJBMrSZIkSSqSiVUVSl4OLEmqFuF7lqTaMOqJVUQcGxG3RsSOiGiJiE9HRGYY7aZGxLcjYmtEvBIR342IGXn7MxHxvyLirojYkttuiYjFpX1E5eHblCRJklQ5RjWxiohmYAXZdYLeCnwa+AhwxTCa/wBYArwfuBRYDPw4b38jcDlwP/Ae4N1AJ3B3RLx2RB6AJEmSJA2gfpSP92dkE6C3pZReBX4REVOAZRHxuVzZHiLiNOA84KyU0p25sheAeyNiaUppBdAOHJ5S2prX7lbgaeBDwHtL+cAkSZIk1a7Rngp4PrC8IIH6Ptlk66wh2m3qTaoAUkr3Ac/m9pFS6s5PqnJlu4DHgdkjE74kSZIk7Wm0E6uFwJP5BSmldcCO3L5ht8t5Ym/tImI8cDLZs1aSJEmSVBKjPRWwGdg2QPnW3L79aXf4Xtp9HJgOfGWwChFxGXAZwMyZM1m5cuVeuhs9ra2tQ8SSKiZWjR1Djztp5Dnuxr5K/Pk67jTaHHNj32gnVqMmIi4km1h9JKX01GD1UkrXANcALFq0KC1ZsmR0AhzCypUrGSyWK5Z/H2DQ/dL+2tu4k0rFcTd2/dNPV5OozPcrx51Gm2Nu7BvtqYBbgakDlDfn9o1Iu9wS6zcA30gpfWk/4pQkSUUKUrlDkKRRM9qJ1ZMUXBMVEfOAiQx8DdWg7XL2uPYqIo4CbgJuBT5cTLCSJEmSNByjnVj9HHhTREzOK7uY7FLpdwzRblZEvL63ICIWkb2+6ud5ZQcDy4E1wLtSSt0jGLskSZIkDWi0E6tvAB3AjyJiaW7hiGXAF/KXYI+I1RHxrd7vU0r3ALcA34mIt0XERcB3gbtz97AiIhrJJlnNwJXACRFxam47aZQe36hIRLlDkCRpSJlx7QSJm697T7lDkaSSG9XFK1JKWyPiHLKr9P2U7Ep/XySbXBXGlSkouzhX91qyCeGN9J/qNxM4Mff1jQVt1wLzi4tekiTti9UNh7GV6Vw/71jeXO5gJKnERn1VwJTSKuDsIerMH6BsG/De3DZQm+fAUzmSJFWKFuZCBLdxXrlDkaSSG+2pgJIkqUbM7NwMKXHis4+XOxRJKrkxex8rSZJUXgt2raOjYRwfmjWj3KFIUsl5xqoaOeFRklRFLrzwwnKHIEklZ2JVpSJ500VJkiSpUphYSZIkSVKRTKwkSZIkqUgmVpIkqWS8qb2kWmFiJUmSSsPLgSXVEBOrKuSnf5IkSVJlMbGqUqZWkiRJUuUwsZIkSZKkIplYSZIkSVKRTKwkSZIkqUgmVlXIRZYkSdXC9yxJtcLEqmr5ViVJqmzhe5WkGmJiJUmSJElFMrGSJEkl4fkqSbXExEqSJEmSimRiJUmSJElFMrGqSlHuACRJkiTlMbGqUqZWkqRKF3n/l6SxzsRKkiRJkopkYiVJkiRJRTKxkiRJJfWlt59X7hAkqeRMrKqQ9wWRJFWTh5fsKHcIklRyJlZVy/RKklQdHp60rdwhSFLJmVhJkqSSScDvtDaXOwxJKjkTK0mSVBKRm13xqdWbyhyJJJWeiZUkSSqpxuZ3lzsESSo5EytJklQSvVcDb7vh+2WNQ5JGg4lVVfIu9pKk6tH6+u5yhyBJJWdiVaVMrSRJ1WLKR/6w3CFIUsmZWEmSpJI6+ugryh2CJJWciZUkSSoh51hIqg0mVpIkqSRMqSTVEhOrKpSGriJJkiRpFJlYSZIkSVKRTKyqVHjeSpIkSaoYJlaSJEmSVCQTK0mSVDLJJSwk1QgTqyr2X5f/sNwhSJI0qEhOW5dUO0ysqlCK7Kd/J6WDyhyJJEmSJDCxql4JHo2Xyh2FJEl74TRASbXDxKqKjc9MLXcIkiRJkjCxqmrn/uM55Q5BkiRJEiZWVcl7WEmSqsm3rvxyuUOQpJIzsZIkSSWTgKWtx5c7DEkqOROrKuQ9QSRJ1SE7w+JRtpQ5DkkqPROrKuV0QElStXh+W3O5Q5CkkjOxkiRJJXXk+HXlDkGSSs7ESpIkldR55z1W7hAkqeTqyx2A9pfXWUmSqsSFV5c7AqlmvfwfT7Hj15uZ+LpZNL/1SLpeaufVW9fS/shL5Q5tn8296sxyh7BXJlZVyaRKkiRJkHoSGz57Hz2v7NprvR33bmTHvRtHKaraNOqJVUQcC3wZOA3YBnwTuCKl1D1Eu6nAl4CLyE5hvBH4cEppS0G9twJXAguA3+b6vmGkH0f5uXiFJKka+GGgNJK2XL+K9t+40mYlGtXEKiKagRXAKuCtwBHA1WQTpU8M0fwHwFHA+4Ee4LPAj4G+c4IR8XrgP4GvAR8GLgD+PSK2ppRuGdEHI0mS9sqUSipe6km8sOyXsKtnRPvtopt6MkMfn0QX3UTuv0Tq1+7W+sd4LrOZhd1zWdx1BL+qf5pnMhtY2D2H07uOJgi6yJ4/WVn/OGszL3J09xzO6DqantxNhOpyyz7cWb+KZzIbOLp7Dqd3HUUQdNMzrDgrwWifsfozoBF4W0rpVeAXETEFWBYRn8uV7SEiTgPOA85KKd2ZK3sBuDcilqaUVuSqfhK4M6X04dz3t0fEccCngDGVWAVw4+X/ye9e9QflDkWSpBHV2trKhAkTqK/3igXVrtSTeOGKe6Bj96SudnbRQIa26OCX9U+yqWETRx3+MNMPfqqgcaIOSHWl/3hjbm4DeBaYmdsAni6oOy+3DbSPgrbPFOxLCeayprhgS2y0X7HOB5YXJFDfJ3v26Szgp3tpt6k3qQJIKd0XEc/m9q2IiPHAG8meqcr3feDbETE1pfTKCD2Okko9PbS8vIUN1z/Kzse3MPWUuax78GGm7zqIWzK/hnPmUJfZybbj/hUwsZIkVa4ELLviCsaPG0dHRwd3HHkCT86ez7Etz3FpuoaDZ69mQ8sCVq8+hYjsp+ORO9f13cVL2d7YBMBxLc9y5jOPQsDE7nra67poYjy7GraR6ZxMO51A8MCRi3hgzpy+45+46j6uWX80GTLcnXmCJ+tbILppaNjFHXesIKX63YH2ZKCum2O65/Bi04s81bSF5w/6A+47sJELN7/Kaff9O6fXXUBTwzSeG9fCzzKPMC6No4tO6mmgvr6Drq4GoI5I0No4jua0nc6OcUypm0xH6yR2Nm6CyE7nzz7OxO1HncTTsw7lmJbfsmTNQ3T31NM2bgKTdu2kq66O9oZxNLVv5/gTV9LcvInJz59F272v4Zfj19A1dQYAtx19Mk/POiTbb08P1AXHtKzl3xuP5pbVd7NmRwsEJHqoz3TT3d1AIpGp6+YXCxbzzMxDCOBt63bxd6va+c7EO+mih+buicw58r9pnvs4LS1H8ts1p/ZdjdDU2c7RM6Zw4NqZzG1cwMM7H2NaXTMzmubxn/Ur6aYn+9dwZH+eEd2QIJGB1EPDuA46OxshwfLjFvPcjIM5tuU5PvDkFl7TcSRfabqTjceey30HNHLMhmc5c/Wjfcdu7G5k87ZDOGFGB0s65vO+17zK47PnkkhAHc1tr/Luh2/mnLaTmZ0OYs2rD3HwgXMZt2s6TN7K/I/9Pjtbt/PP3/wGr25vZeLEHtraGgC44ZTz2Dq+MXucnh1cctcv+o3phshwxNZFbOkYR9fOR5h/OvzF4afTXTcegOPXruWMtQ/v8YsQAQ9+42pueNMGPjA1w2FTt9DSsoB1a06hOyWmpAxvrD+eA9oPgJS4rf43rG/8Le8+8LvMe2kH7T2TeLnzUDJkyKTE++seg26I1cDqfk/1mJN6r4A5p6xhDClSGr1rdSJiM/C1lNKygvI2YFlK6fODtPsBcFBKaUlB+U0AKaULc9duPQ68MaW0Mq/OYuA+4HUppfv3Ft+iRYvSAw88sK8Pa8TNuu2hoX8zUmIpN3P92R8bnaBUE1auXMmSJUvKHYZqjONu7Dr4tgdJkZvCM9Rffb1/j0T0/3qwurl6TWxnGtt4IQ7ZezAD9Zkf0778VTrQ305DPrYEBI20UU8322Pq8I413BiG89wOt/6+xDCcfvYl1mH2M4sX2Bhz91J5gHb787MeoJ/ZrKcl5u29Xv6x8o89QN0MXXRHQ7+ypekW/v6D13Hf8YlLjt3Qt2usJk7DkRLEFZVxjiQiHkwpLSosH+0zVs1kF6wotDW3b3/aHZ5XhwHqbS3YX/mG81sTwYr05tLHIknSfupLqmDo97b8/cOtG0EbU2hjytDBDNTnvhxzqL6GrJ9t086kfWs7EjGU6q/x4fY7UsfP62cjw0yqBjr+/saTa9fCXpKqwv6HMZa7adij7DaW8pY5N3L8mjZ+/dShPDZ7BlumTARg7svbOWbjVn5z8HQ2NPcfT007d/H61S1kenp4dO4BrJ+e/d2o7+qhq37P29fWdffQNu+IvjOf9a9sYcLGdURPdvrhwVtbOa7lJRq6e/qumXxszgE8P6P/79yknbt4w9PrAeisq+ORQw7kxSlNzN7WRk8ELc2T6ThkIZ2NjUzZ9grj1j1BR0N9v3bdEWRSoqM+Q11KZLp76KkLHptzIBuaJzFvy6u8c+/PZtnV/OTliLgMuAxg5syZrFy5srwBAaSpw/6lr4h4NWa0trY6pjTqHHdj2bTyHXosz4vS2JYSZ3MLq848h1X9yrP/PBHwREFZAxk6o5vtwA9P7t+m97dgYfdcTuk6kuvH30lXDLwQRte0A2iddkDf99uBp3tPuuXKJqUJbI+duxtFtt4N+cfNGWjxhFebp0HzaX3933ASHN01m9d2Hc7EGM94utjJLn5d/yyrMxv7DrwqVf7fvaOdWG0FBjr33czuM0uDtTtwiHa9/xb231ywv5+U0jXANZCdClgJ01HOufX/cCtv7j8dolfBm0QlxKuxwylZKgfH3Rh2268h6gafcpc3pW/AKXp7u1xhoKQpr37QQ0p1A08tHO60w721K4y14Ph7xDpY2+E8rsGOXRjDSB5/H6ezDWqg4xXGWjgGBnve99bncI4/WP2hfn770tfe2gw1JTLvObg0fZOu0+qpr+8q3LWHDRsWkMl0cdBBz7JjxxQmTtwznenoaGT8+HZWA6cW7Nu8eT4bNxzF3HmPM336C/32dXfXk8l00dVVT319N5s3z2fcuB1Mm7ZpwFgKj79p0+E89+zJ9PRkOHLBrzjwwLV9+9rbJ9PY2Ep3dx2ZTDfrco9lwoRWmps3MAuYBexsb2JC4w42tCxgyZJlAz8JFWK0E6sngYX5BRExD5iY27e3dgPdankh2SXXAdYAnbmyOwrq9DDw4iMV6aJ7DmTXCffy35MWc0rbfVzW8H9paOikpyf4k8z36MqdMp7Q2VnmSCVJGtzSdAu3cS6zUwvrmQMEMzs3sakhu+5XE9tpT03MZj3r0+5rpJrYTluazMzOTVxd/yHa2qbQ1PQqKSUi4PL4Qr/6vZrbXuXvt13FwbOfYUPLAq7jA6yaM59zO+/mtoZT6UrZ98+l3MxjnSexqWEmc1kHMEB/iaUs50mO7du3lJvp6ZzAbQ1L+mrN7llPS112sYxz0nLeyzcBaGubSlPTK/xpfJu2NJnxnbu4cvMyls35GG1M7ov34gdu56TX/oSmple4Lt7PivQmBlqofik309Y2jXuaThlgf6Iu9XDMC2uzCzwAZ5z5b/2eq7msYyvNtKXJ/fr84+5vUVcHbW1T+Mykf+h7rPV09j1fc1nHQlYNeglCJnXxwTuXc9xrf0RTU/9rYN7ND/u+nkgrp3M3t6XzWNK9gqPubueRRTO5t+l1uTGQnWJ34fbf0LhtIT+c1wAkTmu7l7dt+wkHz3469xzlx9HDN1v/lAlN2c/PN7QcBcDBs7N/9r2HH5DYPQXuuBeyi2Ace8SDTJ/zBB/t+iobGg7qe5yfbL2Chx58C6eedgP1Dbvo7GzgpRcPY/mcN+zx+Oeyjiu3/28aml4m1p7FY4+cyUmZQ1h38ueYNfsZLuPb7Mib+nle511ckvkynW3T+eDkz/f7WQA0dHXS2TAOgK/HX/KehutoZAcZurk2/pTbOXfA55/Z7M66mnZfB9ZFPZuZlS2fAAezng0DTaGcCXNnrmMnF/ESB/Xb1VjfRjtN9M1WnNm/6Znczru4niZauYzr6GhqZCKtnMhD3MOZ9GZHc3ieuczhfk7lDdxOO43cO/F0IDGhvp2dTGQOz/Pi7APZFY19SWgjbbRPbOJg1vP52f9z4MdfQUZ78YqPAR8FDk0pbc+V/S3waWDWEMut/xI4M6V0d65sEXA/cG7vcusRsRzIpJSW5rW9EZiWUnr9UPFVyuIVkP0Et2vNEzy64uecsPR8lr7vz8sdkmqAZw5UDo67sevWWxdA9EBPHecs3b148k033cT992fXk2rYuplTTji+731uxbe+zqMrfk7ncYtp78pe57F48WIuvPDCfn331it8j7zuIx9ky/q1zJh7KJde/dVBY+t9n33klpu457iXeeaQVt658GI+furH9+h7uH0OFtdgsQ63/WD1Hrnlpuw3EZx47gUsfd+f7/X402fP4+WW55l48hlsbGvv6yt27uCMBYftV2wDPTe99Z4+r4lfZZ7gHUe9gxl31bOxdQcAjQ317OzuYdGiRYzfuG7QPgFOPO/CvvLecdM7ZoB+j+uEpefTMeuQbJ2XNzFh8/q+52VfHtf+/LzyY+jt495HH6Oz+aC+8fudT3+Cl554dI9+e/vYeuIi/uWUt+z1eDUtJTaefVK5owAGX7xitBOrZrI3B/4N2SXWDwe+AHwppfSJvHqrgTtSSu/LK1sOLAD+lt03CN6cUiq8QfBK4Ctkz2RdkKv/5uHcILjSEiv/0NBoc9ypHBx3Y9dt17yFdPgTxG+P4ezLflLucPpx3Gm0DTXmvnj9v/LZOSeOXkDVpgoSq1GdCphS2hoR55BNfH5KdgW/LwLLBoir8BbLF+fqXgvUATdScM+qlNLdEfF24Ergz8nep+yPhpNUSZKkkfXYrXPoujVRzxzOvqzc0UiVLdVPKCjYx2u+Bm0bA80u3ftxBluafm/X6g11PV32RnXZWAa7vrLwmPlfV8FiNKO+KmBKaRVw9hB15g9Qtg14b27bW9sfs/u6K0mSVCZ/dcPXyx2CVDXqZ+ZubJ1LRJam5Vx/zuUD1r386ee57oUtg/Z1dNME7jjlmGG1Lax71r1P8NSOjr59vV/3fn9a86S+9gFcMje7imBh2T1bW3lqR0dfm397YQtHNo1n9Y4OJjdk2NbVw7Tcv70unTOjr13+8QO4ZM6MQR9vpaj55dYlSZKkcuscPx466DuT846N9w1a96qj5nHVUUPcT2s/2w6WkBX2MZyyfdk/Fux5pzBJkiRJo+qIww7r9/0bmj5Xpki0v0ysJEmSpDI7YtJEGjvaISWmdXbQfNGR5Q5J+8ipgJIkSVKZHT95Ih3jGwHYPm7CELVViTxjJUmSJFWAP54zgwzwnipYqEF78oyVJEmSVAGKWZRC5ecZK0mSJEkqkomVJEmSJBXJxEqSJEmSimRiJUmSJElFMrGSJEmSpCKZWEmSJElSkUysJEmSJKlIJlaSJEmSVCQTK0mSJEkqkomVJEmSJBXJxEqSJEmSimRiJUmSJElFMrGSJEmSpCKZWEmSJElSkSKlVO4YKkZEvAisLXccOQcAL5U7CNUcx53KwXGncnDcabQ55saOQ1NKBxYWmlhVqIh4IKW0qNxxqLY47lQOjjuVg+NOo80xN/Y5FVCSJEmSimRiJUmSJElFMrGqXNeUOwDVJMedysFxp3Jw3Gm0OebGOK+xkiRJkqQiecZKkiRJkopkYlVBIuLYiLg1InZEREtEfDoiMuWOS9UhIo6MiH+OiEcjojsiVg5QJyLi7yPi+Yhoj4g7I+J3Bqg35Fgcbl8auyLiHRHxk4h4ISJaI+LBiHjXAPU+EBHPRMTOXJ1zBqgzJyL+X0Rsj4iXIuIrETFxf/rS2BYRb4+IX0bEltw4eCoiPhER4/Lq+Fqnksm9XrVGRIqISXnljrsaZ2JVISKiGVgBJOCtwKeBjwBXlDMuVZXjgAuAp4CnB6lzOfBJ4LPA7wGtwIqImNVbYR/G4pB9acz7G7I/978G3gLcDnwvIv6yt0Iu0foG8B3gfOBx4MaIeE1enQZgOXAo8IfAXwHvoOB6hOH0pZowA7gNeD/ZcXAt8HHgC3l1fK1TKX2e7Dgo5LirdSkltwrYgI8BW4EpeWV/B+zIL3NzG2wD6vK+/iGwsmD/BOAV4FN5ZU3Ai8CVeWVDjsXh9uU2tjfggAHKvgc8m/f9U8C1ed/XAY8B1+eVvQvoBg7LK3sn0AMs2Je+3GpzA/4R2AaEr3VupdyANwAvA39LNjmatC9jxXE3tjfPWFWO84HlKaVX88q+DzQCZ5UnJFWTlFLPEFVOB6YAP8hr0wb8lOz46zWcsTjcvjSGpZRSiBAnAAAGKElEQVReGqD4IWA2QEQcDhxF/3HSA/wHe465+1NKz+aV/RjYBbx5H/tSbdoC9E4F9LVOJZGbrvdlsmeZCl//HHcysaogC4En8wtSSuvIfoKxsCwRaaxZSPaswDMF5U/Qf4wNZywOty/VntPYPRW1dyw8WVDnCWB6RByYV69wzO0C1tB/zA2nL9WIiMhExMSIeD3wYeDrKfvRvq91KpU/A8YDXx1gn+NOJlYVpJnsNIZCW3P7pGI1A60ppe6C8q3AxLwLv4czFofbl2pIbiGJi4Crc0W946VwPG0t2D/cMTecvlQ72nLbXcAdwEdz5b7WacRFxAzgM8DfpJQ6B6jiuJOJlSSpeBExn+z1Vf+VUrqurMGoVpwOnEn2wv+3Al8pbzga4/4R+FVK6WflDkSVq77cAajPVmDqAOXN7P5EVirGVmBSRGQKPgVrBnbkpl711htqLA63L9WAiJgO/BxYC/yPvF2942Uq/T+hbS7Yv7cx98g+9qUakVL6de7LuyPiJeBfI+JqfK3TCIuI44A/Ad4QEdNyxb23g5gaEd047oRnrCrJkxTMm42IeWR/cQuvKZD2x5NABjiyoLxwvvdwxuJw+9IYl7vX1I1kFw743ZTSjrzdvWOh8JqAhcDLKaUX8+oVjrlxwOH0H3PD6Uu1qTfJOgxf6zTyFgANwD1kk56t7L7Oaj3ZBS0cdzKxqiA/B94UEZPzyi4G2snOHZeK9UvgVbL3BwL6/ij+PbLjr9dwxuJw+9IYFhH1ZFflWwC8OaW0OX9/Sum3ZBeyyB8ndbnvC8fc4og4NK/sLWQvEr95H/tSbToj9++z+FqnkXc38MaC7bO5fReQva+V405OBawg3yC7qtGPIuKzZD+pXQZ8oWBJTmlAuRfdC3LfzgGmRMTbc9//LKW0IyKuAj4ZEVvJfur1N2Q/YPlyXldDjsWU0s5h9qWx7Wtkx9xfATNyF3f3eiil1EF27FwfEc8B/w1cQjYR+6O8uj8ke4PXH0XEJ8lOk/ki8L2UUv6qWMPpS2NcRNxM9garj5NdOe0MstdZ3ZBSWpOr42udRkzu1hIr88ty15UC3JVSas2VOe5qXblvpOW2ewOOJXs3+XZgA9nVZzLljsutOjZgPtmbFQ60zc/VCbJ/wK7PjbO7gJMG6GvIsTjcvtzG7gY8N9SYy9X7ALAa6CA7ZeucAfqaS/beVa1k70n0VWDiAPWG7MttbG+516Pf5MbKttw4+EugIa+Or3VuJd2AS8m7QXCuzHFX41vkfniSJEmSpP3kNVaSJEmSVCQTK0mSJEkqkomVJEmSJBXJxEqSJEmSimRiJUmSJElFMrGSJEmSpCKZWEmSxqyIeGdEXLqfbS+NiJTbHt7Pdg/sz7ElSdXHxEqSNJa9k+yNPItxNvCefah/E3Aa8LMijytJqiL15Q5AkqQKd39KqXW4lVNKLwIvRsSLwMzShSVJqiSesZIkjUkRcR3wB8BZeVPzlo1Av9Mi4psR0RIROyNiXUT8S7H9SpKqm2esJElj1WeAQ4BpwF/kytaPQL9fAE4H/hrYCMwD3jAC/UqSqpiJlSRpTEoprYmIl4G6lNKvRrDr1wFfTSndkFd2/Qj2L0mqQiZWkiTtm4eBj0ZEN7AipfR0uQOSJJWf11hJkrRvPgT8GPgU8FREPBMRf1jmmCRJZWZiJUnSPkgpbUspfTilNAs4EbgX+G5EHFvm0CRJZWRiJUkay3YBE0rVeUrpUeCjZN9PF5bqOJKkymdiJUkay54Ejo+IiyJiUUTMBoiIS3PLr8/f1w4j4u6I+EhEvCkizgP+CWgD7hvJwCVJ1cXFKyRJY9nXgJOAa4Fm4ApgGTCR7NmsbfvR5z3ApcB8oBt4CDg/pTQSS7lLkqqUiZUkacxKKb0E/P4Au04BvpdSGk5ilYmITEqpO9fnR8lO/xtQRASQAWI/QpYkVSmnAkqSatFpZG/0OxzbgAf3oe9LgE7gj/c1KElS9YqUUrljkCSp4kTEDOCw3Lc7Ukqr9qNdW0rpiVLEJ0mqLCZWkiRJklQkpwJKkiRJUpFMrCRJkiSpSCZWkiRJklQkEytJkiRJKpKJlSRJkiQVycRKkiRJkor0/wEj2/7BCZ27ugAAAABJRU5ErkJggg==\n",
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R+9aMv/wJUEQML73UDCdfyO9YrxeeOg4DHiDfNd2g8kO++LoW2L2Bu/6QOxiZQ777UilTkLfVvSml29qasHi5/D6gPEnsTtemlP5W+SflPfaU8u97aua/V0Rs1E5eh5GbhF1Ws75GkU9oY4FXlnE/UH5/OeU71sulooGyv4d8Ylrp7m1K6QryHfADIqL2WHBBSum52oxSSlNTSpFSmtjAfCuOIN9Je6QqbTLwxoh4VfWI5enaT8nr+1cdZZxSOi6l9LmU0kUppctSSieQg9HF5BN9l6SUFgF7AseTm7PsTz6GXAs8GREfaGfy2ryq97G1yj62HnAN+fixQ53J/jeltKSr5e8BN6eUKk8tK+vnNnJw//2acStP714Jy/fhD5DvRD9VU+fnku9m1h6XxqaUoisFLU+8LwS2Ao5JKb1UNXh4+b2wzqQLasapl/eG5Lug88nNpXrCcOqXD1Yt4zrl93rAPimlM1NKl6SUDiAH5x+KiB17oIxLyc2sp5DXw3vJT6smABdHG70xtqez6zYiPk9uHXB2Sum66mFdPE41JaU0ucxzUlVyU/Wtm61T5vW7lNLElNKlKaXTyOeH4eQbRxWdKnc5vx9CbpI6ByCltJj85P2AiFivE+VcSL65eEHJ8xDy6xbHk1836FIZi4nkm1rVT9QvIp8veu2pVTt1t6+W6QPkAPvE2gEppWUN5nFmSmleTdp+5MDztJTSU03k3Yz55PX5puil7tl7qplAf3Q2+XFgIp/MH6o54VYCo3qBxC3AW8vf+5Kb89ROtw5dFBH7k3eEO8l36Ru5WG5TSul5cjOu48pF3G7ku5iHAb+LiF1SStPKvDcit+k/gPxya61RdBw07khuG/18O+NsQG5X216550TEL4GJEbFhWY7xwNbkpmkduZi8jF8BPhsRt5Afb1+cUnqsgenbU69Z0v3l99al/I+VZntfBqaX5hZ/An6dUrq9arod6bjJ58bkJoSvpDxJbaLsWwFPl6C71n3Aa8nbpzqQeqiJ+S1Xun3dDrgwIratGnQrOdg7ktxTUsWx5Ca6DXUpXk9K6V8RcQm5Hm2XUurSspQLhJOAk8oNhjeWch0NXBARj6aUbuoon9JkZhJ5H6z3OYXRddK6Zf13o3/XSavUp0faSK90Jbxh+Xtf2j5GdMsJttwgOI98PPtqSumXNaNUTvxr1pl8rZpxavNejxxYbwq8o6v1quQ1knzMrPZ8SmlpmX9bN2Zqyzi//L4lpfRgzbgXkI+f44F/lnq4ds04L5UgubMmk99nfVXKzbcgn1umkW9ofJjcS2NDOrtuI3825FTyE7JPtDduH+tyfesB88nbf3J1YkppakQ8zsrNoqrLPZ+V1Sv3QeQnAzfUHOdvJJ+7D6PcgClB2MiaPF9OKc2PiOHkJsN/SylVNxW/OCIuBk6MiN+Uut6pdVt1k/YeYFBNOW8CPhgRX67c0CqBfvVrCUvLNUlTOqi7PbpM7Xgl8Pfam7edVG+frdwgvquJfJuSUloUEZ8ht5p4JCLuJz84uCyl1KVPAnRkIAVW/0opTWlrYEppdjm4bB8Ra1VXsJTSC+Q7c9R5H+Vf5Gi4S98PivzNjt+SL3D3TSk19eSrVkrpRXIThssj4gly0PF+4Jtlp7yGfKH/PXIztJfJdyMPBw6lsW+dBbn5yufaGafRA9LZ5KZrHyLfAT2SBt97SyktBN4aEW8k3yl5C/kOzKSIODSlVGmDWzdw7Y73EVJKx0fEeeRmdnuQ77x+MSJOSSlVvn0U5PVxaBvZQO4Od3m2bZW5B3XXyb7y9PFE6twNI7/DdGxKaXFpX/5VcjvsqDpJjCm/1y9p01M779oVj5bfG9ANQUrZL6cAUyLibnI9PZx88urIL4B3lmluJL84u5T8FOyz1N/Heutiq1FL2xpQgoF6oub3FPKT9B5RgqpzyMeOE1JK36oz2tPl95g6wyppq9xZLRf+U8hPFw+ofULSBd8jBx/VtiLX26eBnSJizXJMqy3jC1XB0JPl9zN15jG9/K4E7l8gN5Wtthf5yVbDImIL8h3uH1YFVRW/JgdWe9JgYNXZdRsRR5D3pWuA/yxPRvqrLtW3HvIkeR23VVdeX/V/dbmn1Yw7hnw+eroqrXKcP7eNeR/BiifbB7Nqq5zDyQHfQeSL8Xrvnv66TLs7udlZZ9ftnuROcSBft9XzTvL7ywC3k5sqVzxGbk3SZQ3U3Z5epp7UzDmrveub7rguOysifk++LtuTXM8+ERG/qgngu8VACqwa8RtycPBBqjolaE9KaUFE/BF4T0Tsm1K6ptGZlaDqMnIzugltPFHoTpWXHys76M7kNu0nppRWOuFG5z4k/C/yXenrGni0226AkFK6IyLuAo6MiHPJTRkvq3m62P4McpPB2wAif3D5LvJTuUpg9VIZtl5Nvu192LJec5qdyu+V7uanlP4N/AD4QWmSeDXwpYg4rTSv+xf5Kc4tlWYT7XiI3PHDLtS8zF6jvfX6b/LLwKNSSjPrLMMsVnTg0m0iYh3yAexaVnR8Um1nckcO7yY39diYfFfuo+Wn1nHl533kfbU9lTtlPdG5QO1+BG0H66PIJ7afp5Q+VjOs4Ze6W9zz5Hed1m3v5lYzqoKqw4Fv1jTHqlZ5crwbq17470rejnfW5F258N+J3Fvq1d1Q5FPIzRWrVS54byc/3XsjK5pVVjpKei0rf5S9ckyo1wFNJa3yJPoC4C8143TlSXil3g+uM2xIze92dXbdlgvTc8o0B9YJPPuVlNL0iHiKXLdqVdLu6KXi3EYOrDZj5Rt3lLTqFgu3k5/M78aqgdWuwIOVc1dEbEO+iXkR9S/g9wE+FhH/kVK6k3w+fGvNOPeV3w3XrS6s2yPIN2k/RP0n5D8hB4iVZfgAKz9Vrr2J0CmN1N1eWKa2PETukKTezZxmVG5qvpYcTLalch1Wr8loQx8cp+Nry+nk9X9OaS7+c+CQcl12e3vTdlrqpZe5+uqHdl58rzPuJuQLsZnAm9sY5/CS30FVaa8mR+uPU/XCds10h7LyS4r7knfUu4H1u3F5dwNGtTHs3FL2T1aVO5EDq+rxXk3eWWtfDpxI/c4rvtDeOqZ8J6z8XXk583PtLMMxZZyfl98NdUJATTe3JS3IzfimV6V9tOT7XzXj/oSudV5R6a5/JPU7Nqh0gb99+f+g8v8PGlhflc4rplBeWK9dvo7WKys6r/hOTfrbK+u5zv4ysY2yNdzdetV8635QuuQ1l9K1bll/B9X5+UbJ52fl/zFl/BHU/37R60r9rdslcIN16bVtLSM5GExUfc+OHEgnqjpKKOnrkE94F9Skv4IczNa+CDyJOi/gVg2fTRc7yqHJ7tbrjDuZOi/z16tDrOid86A25rtRzf8Nd7dO3hcrx7a6n2uoGf928s2ETavSNi1pU2rGHU0OtBaSm6h1Zn13tfOK19D+d6wOq0n/Sxm/+vg0mNzcdjFd+FB2e2UnX/wsId9dH1Uz7Fg6OL53dd2Szz9LycfCVTpVqBm3P3W3fmqZT73vEs2gne7x6d7OKyrfybysJr3yWYKzq9I2JF/T3Er971gdX5VW+aDv69uY79gy/EcNlLHyvcN63a3/sXY+ja7bsm3m0c6xk/wUbUl7daar9aiTdbfXl4kV34r8nzrDomY5as9Zq6RVDat0XvFsvTLU5D2dHPBXp21dlnGlcyL1O6+odEz0+jplWOWbWqz4pMp+tcOa/fGJVZWU0jMR8Q5yj0o3lidRN5Cb7qxHPuEdRH6J8Jmq6f4REe8jd2F9d3m/41Zy4LQl+WCxC/lClsjdj/+efEFwPvD23CpvpbIsv5tZXrh7BLghpTS+g8X4ALmr9StY8UG59cnNjvYivxd0Xhn3n+Q7RV8qbZsfJD9J+Si5aV8j3Q5DbtbyVuDUiNib3H51Frk7zX3I62uvMu795IvDj0fEPHIQ+1xaufnHReSDy2FluRttB3t85M45Li/TBflEsAMrOpqAvJ2+BZwdETuQ75a8jXyAbMvdwHUR8SPyAeAA8onq5ymlSpe0e5U8LyWvyznkdfgRcg94DwKklH4TEeeTH0W/vpT3BfJdw93I7xhV3tu6LSJOJl+w/C0ifkWue1uR6+IbyeuwvfU6mdzs6NhSl24s8/g4+YBX/UJwR95I/t7Wz8gH1PYcST4o1v0MQUppXkRcCRwYEWNSfrl1lSdREVF5mnZvSql6+CuBKyPiMvJTwLnk/ewI8kns6Dp5JeCxlNLYDso+AfhWRFxDbu73DPlENp78hG06ufe7ilvI7eV/XPa9xeRt/kjJ47CImM+K5iUfJdfR9emcW4AJEXEspffPlFIzXVv3lq+SP+R7STk+3kLuuXFL8rHpTlauT38qwxrpwOJU8ja/m/wu0WE1wx+u2kch95h1PfDniPhBSfskuUnm52umvZbcROqXwOg6ef815SfUAETEu1jxaYdtS9rx5f+ZKaUfdrQwKaV7y3HmExHxW/IF5Y7kXk9vIDctrfZJ8pOtKRHxffIx/2DyvnpiSunxjubZmbKnlF6KiP+lfAYgIn5KPoa+mXz+eZjGmgE2vG4jf4LiXPJ55VfAf9acM+eklKrvyrd5nKpapkonADtXpd2YUrqxatzObM/3kM/nJ5Av/Cq+Q37K/ouIOJ3clOsQcrfZH0kpza4p3yfI7zZD7llvy6p53p1S+kPVuJPJx/a9UkpTaUdKaUrkd5gPKdc2l5P3sU+Sj2eTqsZ9PiK+Ru5CuzLdGPI2fwD43zL/weT1+2iq6typZr6PRsSdwKER8fnU/ns8l5OvW/aPiBtZ0V32e8lN639dM59G1+0h5KdPl7Yz70vLsny45NuuRutRF+puXyzT98jXSsdH7jb/GvJ126uA7elEl/nVyjn+SPJ5/R8RcQ75CeiG5Nc1TidfC0O++fZNVpzTNwU+Rg62GvkkQaUlyckRcVEp/z/ITzhviIjflf9nkI+nx1C6qO/KsrWruyO1/vZDJ55YVU0zitzG9+ayERaTT1Y3ke+eb9bGdGPIJ/l7yRfVld5tfk79CL/Nn5p8K126X9RA2V9Nrpw3ke8oLiJfcN9FPnCuWzP+luS2y8+TL4JvI58gJtHgE6sybAj5xH87K7p0/Rc5SNq3Ztz9yd9TqnTVO7VOfpU70F/r5Lb+Ffk9hfnkk/2t5MAmasZ9U1lHC8hBzdllu69054n6HwiufODuRFbuKnsr8tOpf5IPonPL3ycCI+uU94PknXpWKcej5BPJwXXGPaSUd3bJt3JyW6OR9cqKDwT/u9SJ58j1css29peJHexPk+sNrxrvVWW8SzsY75Ay3lc6uw+TnzD/vKyLWeT99HHyxdQqTztY8UmFmxqoS2PJwcD1ZVsvLOv9PvK7f5vUjD+IfBFS+aDv8nVIDtjPIe+PC8jHh6Oof/dvEu0/sXol+aQ3izrHigb2j0QfPLEq6cPJT/vuJe+fs8n7x0+p6sq9jPtoo8tG2x9orvzUK/tu5OBtTinH1dS5495BvvWWcXI74z7aiW01mHwR+2Cpe0+RL0LWbmP8ncm93M4sdeyu2rI1MM+Gy04OeI8iH1/nkPe9R4EfARs2OL+G123VftFo+Sp1sN62by+fSU2sk4n18ijDxpCPVS+U7fM36hznq+t+Gz+1++al5KeVdVvK1Ml7CPkmXaVePUduIrp5G+NPJN+wWFDGPY+qp8us+GTHaR3M98tlvEMbKOM65BufD5QyVo6ZX6L+Jyg6XLfk65LFwOh25rsm+bj6YDfU30lV43Wq7vbVMpGb4X+VfI5bQD6W3A58vE4dH99eWp2830hujvhC2aaPk68Nt64aZwj5Bvj0qmV+F/WvRVdJK+lfIl/jLK5sB/LNyzPIPSDPJJ97ppGvnzr1dLLRn0ozIvVjEfEp8kXbq1MTPVG1koj4MfmJw9iU0pMdjS91pNw5/D25Se71fV0eSeqq8l7hc+Rmcx/u6/JIygysWkBpWvTvlNIn+7osvSFyV8RPkJs+vquvy6PVQ2letYV1SlKrK022biB/qNebj1I/YWClfiMiXk3ueODDwN7kDkRubn8qSZIkqe818o0iqbccRG7vvQO5Xa9BlSRJklqCT6wkSZIkqUk+sZIkSZKkJhlYSZIkSduDBPAAACAASURBVFKTDKwkSZIkqUkGVpIkSZLUJAMrSZIkSWqSgZUkSZIkNcnASpIkSZKaZGAlSZIkSU0ysJIkSZKkJhlYSZIkSVKTDKwkSZIkqUkGVpIkSZLUJAMrSZIkSWqSgZUkSZIkNcnASpIkSZKaZGAlSZIkSU0ysJIkSZKkJhlYSZIkSVKTDKwkSZIkqUkGVpIkSZLUJAMrSZIkSWqSgZUkSZIkNcnASpIkSZKaZGAlSZIkSU0ysJIkSZKkJhlYSZIkSVKTDKwkSZIkqUkGVpIkSZLUJAMrSZIkSWqSgZUkSZIkNcnASpIkSZKaNKSvC9CfbLDBBmns2LF9XQwA5s6dy4gRI/q6GBpgrHfqC9Y79QXrnXqbdW71ceedd76QUtqwNt3AqsrYsWO54447+roYAEydOpXx48f3dTE0wFjv1Besd+oL1jv1Nuvc6iMiHquXblNASZIkSWqSgZUkSZIkNcnASpIkSZKaZGAlSZIkSU0ysJIkSZKkJhlYSZIkSVKTDKwkSZIkqUkGVpIkSZLUJAMrSZIkSWqSgZUkSZIkNcnASpIkSZKaZGAlSZIkSU0ysJIkSZKkJhlYSZIkSVKTDKxa0dIlsHBOX5dCkiRJUtHrgVVE7BQRf4qIeRHxdEScGBGDO5hmjYg4NSL+HBHzIyK1M+4BEXFvRCyIiPsj4uDuX4q+Nf68o9jtvF3Z67yj+7ookiRJkoAhvTmziBgNTAHuBw4AtgFOIwd4x7cz6XDgI8BtwF+BvdvIf3fgUuDHwKeA/YFfRsSMlNI13bQYfe4HD7yNkUM/xEuLX+zrokiSJEmi959YfQwYBrw3pXRtSuks4ATgcxGxblsTpZRmAuullPYDftdO/l8DbkwpfSqldH1K6YvAVcDXu28R+t6Te57Kv/b9CE/s/CsAFi9aysL5S5rON6XE0iWLm86nLUsWL2bxggWkZcuWp13xg+9y+iHvZsq5Z0JK+ae/WLasofIsmDuHpUuaX//LZ7t0KbNffGH5/0uX5PXWWQuXLeOlhQuZN28282a9nBMvPQpOWA+u+HxevjnPdZjP/53+7RXbqB3z58xm0fx5nS5npyxdkn+6YFlaxvyF80mLlzF/yXyWpVwPp5z7Y05//7uYcu6PGyvC0oWktHT5/5d//5SG1k+jrvzRGU3ld/VPvt+t5akrJVg8v7ksli1j2dKlq6QvXbKE1I3HgT/+8LSeXx/FvFkvs2Rx9x5Dr/zR6auUf96sl1m2rGbdLV4ASzue98J581g4r7H9NC1b1q3bQpJWd9GbB82IuBF4OqX0/qq0LYDHgHenlP7QQB6fAH6QUoqa9DWB2cCnSsBWSf8QcD45MHu5vbzHjRuX7rjjjs4sUo+ZOnUq48ePrzts3HWX8WSMZUK6kg8vO4cIGDxncz477Os8M3S9lYKBvbiWD6Sf8Yv4EFN5K+98agGHjv4US4bNYBFDmcl6bMizLF0ylJ8O+jg3D34zG/EMz7BpziACUuKti/7KxKFnQAIiUVtrTlx8Kg+tsdVKaVvPXsrJ87/Oog3/xZIFwxm81lwWLlyLNdecz3PPbcmlG72bm2LP5eMPT3M5ga+w6ZIXYMhClhLc9+yb2G7U3ay55nxmzFufh+7eiy1edzPrrjWD4SxgEMv4fnyOW/l/NSVKTOBqJqZzSpkhLcuLM3vRZnxjreN4jk1WmmL80us4atCPYdkgGLQi+GPJWvxw6Ee5mT1WGn8fruaQBb8k1lzMWizMqz1gyeKhXPz8j7lqzOhVtt0+XMURlDItL2n2eX7As4M2zduvrHeAvbmGQ+ddxLBhc8s2yROdm47hukH7rLSdKgu76bInOSU+Q/VOkoAz41PcxFtWyn8fruawRT9jq1u+wQM7/5g0chbL5q3JyOEvsJgh/IRPcEu8GWLQ8mkmcBUT0znErDGkdZ+qmkdw+tKvcNeQ1608jyXXccTgFYFLLFmTNGQhQ+ZsyvQ11mDRGov4UnyvLBzsyZ/4SDqLQWXtLF28JoOGLgRg3pxRrDF7J47a9L9ZHGuVGSf25moOST9nGAtYMn9dhgybzUtPb8egYTNZe/SLfDG+x/NsvFK5JnAV73/xF8yZuwEbbP74StvqJ0s+wZ+Hjl8pbQSzOTsdzuB5G7Jk+AssWwaDBuW8zo+j+BP7rbLNq9fXS0/vyGZDhjJvo3sI4Fw+ynUxYflyA2yy7Gm2GvQwt/Jmxi/9E0cMOpv5T72G9dZYxoIN7+cnSz/FjUPevNI0lfwXLhjOmmvNZ50nd2fehvewbM2XOTM+yU28hfV4nhfZCIAxPMHJ6bMAjHxyPM+sPYuLRr+RG9ib/eb8g+fmrM3fNtkagI14hhfYiL25hgPSb/hlfIi/VtWh4czhrMX/zeAhc0nAPIYxnBx0nZM+xtRBE1ZZH5vyJKekzyz/f9my4PlnXslGmz7EWZU6Wj3+sid53023s3BZsN32N7HxJo9UNjssHcq5Q47get66fPxhzOVH8z7FGsNWPuSPeHpXfpaO4bLNRgCwPs+VdZKPF4ct/hlfHnoq09lsxTRpHmfzYVg6hDR4MYsWD2ONoXn5AvhA/HrFvlHWyYg0l7P5MKks26BBMGT+aJYMewmA09Nx/G3QuJXq4mY8znfS51YqbwQsSzD9md1Zb6O/cezg7/IiG620/ebPH8HFww/lOvZlH67m8HQOixnCosdeyzmb7stta7wOgH3S1byH33BhHM4t/L9c5rIS914ylfcOvpBRzOTFp7dn0LBZjB49HYBFDOXjcS4LGL68XJvxOCenz8HSoaTBi5k3d13mzNmAjTb+Nwn4Et9nemy6YjmAtzy1kF99cNdV6kJfau88K/UE69zqIyLuTCmNWyW9lwOr54Afp5Qm1aTPBSallE5tII+2AqudgPuAvVJKU6vS30BuQvjGlNLt7eXdKoHVJtf/Pf9ROZGre1X2ic6uW7fHwNOVbd6ZaQZCnRooywits5w9sU1S4pm9X9e9eTbJi1z1Nuvc6qOtwKpX37ECRgMz66TPKMOazZs6+c+oGb6SiDgaOBpg4403ZurUqU0Wo3vMmTOnnbKMyr9a5STdarq6Xt0eA09XtnlnphkIdcpl7H96qLz95fxa0f55Vup+1rnVX28HVv1OSuls4GzIT6z6y52Edu9qVJ5Y1ap9+lhpZtKVk2RNc7Tl+XU0Te38G51PW/83orqs1WVuL5+ulrUnp6ldjkbUbp9Gl70z67gzdaB2Hp1Zpq7Wuco4Hc2jq+uqVmf3g/am6Ur+9aZrdHs3uh0aLUdndCbfzq6Xrm6n2nHaWj+dXW+dGb8z5W1k3M5uv66UtZH865S3v5xfK3x6oN5mnVv99XbnFTOAkXXSR7PiyVIzeVMn/9E1w1veiGWzV3T0UPWzGY9zYTqIC9NBbMbjkBLBsrrjdvSzGY8zKC1lAletlF97P5VxL0wHMYGrGpjPslXybWQ+tT9DWLzS7814fPnfbf2MYPbyso6g/vpsb/02tnydmyZYxqC0tKyDxrZbJf/KetuMxztch40ub+26Wjnf9stXmccIZlctU8fzqV6mjsu5rGpdLeuwrlfyncBVy+t2R/OorieNbvfqbX5hOqjdujiExZ3Ovyv1qjPbvpH9pys/E7iqlLXjul27Djsqd+34DR1HqJ9PR+uwrbpYWb5BaWlD66/6eNmZ42sj+/eF6aCGt0tet43tO10p79pl2/2/Obf09alTknpcbz+xegDYoTohIjYnd6f+QJN5PwwsLvnfUJW+A7AMeKjJ/PuNXWfdy59Hvp7H984vAk8590x+8tTPeWCL2XwuRrDNqG1YPONr7PH42nx0zAeZcOQxHPfQE/z8qRf5zdNnstu0X8O4w5nyzLbcfc0VOdMIdnnr/jx1+wLmpFez5qL7Gbfucew8ejqD3nAkd7zjgOXz/9Dl93LtsMV867Y72fvlV/KX0X/nO5ucyz0Et25/BG+6bz1eP+VKJmz6JC8++Ribv/Ay6yxYxNAjJjLhyGOWl/ehLebwnh0O5k33Pb28HHtvPI1d1nuGQW84kgX/fpk1X7iUp+aP44Ht38uGYx7khSFXsMGSd7DL2/6XGZdNY+6t0xnxpldw54vXcs+UK9l5wtuXz+Pua65YvlwTjjymzpp8mB8e8X4+PvcU1hyxNp847+KV8hx94LY8c8adLHl2HrOXzeCPj/2UG8Z+jI1efi2jN76VDbf6EKNmD+Ubw49iwpHHMOOyacy55SlGDPojj835PRtsviUXrPUQn113bQI4eNbZ7LjRjVwy/ym2q9o2FZV5D9loM5Y8N3f5clXW1X/tcDAf+vONDLnhfmY8PIK5u+zMGy6+hMmfv4ZDnvwpALvs+47leU7+/H/z4pOPsf82z7Ljmg/DuMPhHacx47Jp3HzdEzy6ODFywxk8+6+fsfOEt7P57s/w5FO/YLMxh7L99idw0i0n8euHfs37tnsfE3Z9mDuAy84bz9pbPMGcxzfnwCOm5oJf8Xm443xO2uFN/HrhdM545FtsM29t/jb4Ae5797951/WvYuTLo/jjqCv4xYhL+cajn2C7odtyxwYP8Y0Nv5+rH8HB2x/MV3f9Kvd8+zFGzTyP3416iZ2//BaeOHU/xsy5hbtnvIIXd/k0E448hgcf/AZPPHkRL9w3kqf+uilvYRhr33s/a2y9NQunTePx9ddlyOEfBuDFeeey/k4z2XDxO1nvhvM4dsz1fGLc8cyd9zBfG7OA7bc/Yfk2mHLumSvq0SbT4I7zeWL4G7jkjqF5hDdez4br/4KPP3Mw+8/cg3V3HcPoA7ddPt16m27OS08/ARO+sHw77Dh5T57hRbZdtJjPvHQs9z0+llftMYbF867jnilXwoQvMHn9rfjTOhuxy323ceHwW5bX4cF3LGSbdV/HzFEz2HzHVzP31umkNe5gDJN4au1d2XynVzPhjlNh3AtMvm4BW857Jdus+zrW2W0Mv//zGbz45GOr1IvaOl5R2d7v2e59HPKbRxg6+HVAcPnoG7l74/s46/BfAnDDLx8kbp/OVmsMZu1dX7HS8u884e08/9TreOnpeawxbAGznzlr+T4Jr1tpHb/v9QsZcuMDzB92JEO3egvTZv2dpePWLMt+C/dMedXyaR8Gpp9wIjMvuYRR//VfvGLcy3DH+TDucD723NP8lX9w1hMb87GyT33n3DO5Z8q5y7fH3w7+ONetuzG73H8bnx+2bPm2ZdzhuQrf/m/uYGd23e0xhgz9K5uNOYTttz9hlXVV2afe9NYHWLjVMkY+P5LBf53PLqOn8+Di7djxW7evXIfKOn/nVcfx6LNXEATvL/U8r48vc9ItJ7H4geP5xKzZfHjh9jy43oEMvnMR26zzWh6e/XdeHvc71t7iCV64fxR3/3Unxu13MUsG/5Ndl+7IO9f+O2utt4i1R2zHrrteueLQdsWBPHPHPswd8k5mzD4KgBG7rnqcvOfblzFq5mhmjnqcnb98INNPOJEZF1/MY+utw/2bb8Qub92fW1/1Ehc/eDGfTcP5yrTD2H3Jbly766bc+eK1LDn/Z2zx4ixGv//9zHr/Up546iJumjOEv6cduXfGw5z12EaMevPLbLv4MX777nrHYElavfR25xVfBr4IbJlSml3SvgCcCGySUprVQB51O68ow64GBqeUJlSlXQ6MSint3lHerdJ5xQd+92P+PPL1nHTVLD54yr69WzCt1mymoL5gvVt9jZvyB9Zf8jJXv+2wvi7KKqx36m3WudVHf+m84izyh3t/GxEnA1sDk4DTq4OqiJgG3JBSOrIq7e3ACOC15f+DyqDbU0qPlb//B5gaEf8LXEb+QPD+wNt6cqH6QgBbLh7a18WQJKlNLdZthyQ1pVcDq5TSjIjYB/gh8AdyD35nkIOr2nINrkk7E9iy6v9fl9+HA5NL/n8pAdc3gWOAR4BDU0rXdN9S9B9j16xdRZIkSZL6Qq/3CphSuh/Yu4NxxjaS1sa0l5GfVq32rlv3b0ys+ZCmJEn9zQ2/fJA9D9m+r4shST2qt3sFVDdac9P+8T6YJEn15fe4Z999Xx+XQ5J6noFVS8qt1g+ZeGEfl0OSpI7tnDbo6yJIUo8zsGpRQe/15ihJUlcl4O54vq+LIUk9zsBKkiT1iEqvgO/a4699Wg5J6g0GVpIkqWfdcX5fl0CSepyBlSRJ6lnjDu/rEkhSjzOwakG+XSVJahWJgHec1tfFkKQeZ2AlSZJ6iLcCJQ0cBlYty5OVJEmS1F8YWEmSJElSkwysWtCgyJvtkcm/6OOSSJLUtrBxhaQBxMCqBQ1eazYAL3J9H5dEkiRJEhhYtaRYYz4AL282tW8LIklSB9LyzwRL0urNwKoFLV00jCAxbfq2fV0USZLakbCzJUkDhYFVC1q4cDgQPHHvFn1dFEmSJEkYWLWkh9baivkM4+bX7NfXRZEkSZKEgVVLemboJhDB/ZuO7euiSJLUAd+xkjQwGFi1oDGLnoWUePs//tzXRZEkqU2GVJIGEgOrFrTdgkcZxnzO+/Sn+7ookiRJkjCwallhL0uSpBaQwudWkgYGAytJktQjvAkoaSAxsJIkSZKkJhlYtSTvAEqSWoNnLEkDhYFVC0r2syRJkiT1KwZWLct7gJIkSVJ/YWAlSZIkSU0ysJIkSZKkJhlYSZKkHmF365IGEgMrSZIkSWqSgZUkSeox9mQraaAwsGpRnqYkSf2d5ypJA4mBlSRJkiQ1ycBKkiRJkppkYNWKbFshSZIk9SsGVpIkqYfY3bqkgcPAqgXZw5IkSZLUvxhYtSzvAkqS+j9vBkoaKAysJEmSJKlJBlaSJEmS1CQDq5ZkM0BJUouwJaCkAcLAqiV5lpIk9X+RvBEoaeAwsGpRhlaSJElS/2FgJUmSJElNMrCSJEk9xu7WJQ0UBlaSJKlHGFJJGkgMrCRJkiSpSQZWLSh5C1CS1CLsF1DSQGFg1aLCU5Ukqd/zXCVp4DCwkiRJkqQmGVhJkqQeZPt1SQODgZUkSeoRhlSSBhIDqxZki3VJkiSpfzGwalmGV5IkSVJ/0euBVUTsFBF/ioh5EfF0RJwYEYMbmG5kRJwfETMi4uWIuCgi1q8ZZ42I+HpETIuI+eX3CRGxZs8tkSRJaou3ASUNFEN6c2YRMRqYAtwPHABsA5xGDvCO72DyS4DtgI8Ay4CTgcuAParG+Q7wsZLXXcDrgW8Co4BPd9dySJKkRiR800rSQNGrgRU56BkGvDelNAu4NiLWBSZFxCklbRURsRuwL7BnSunGkvYUcGtETEgpTSmjHgqcmVI6vfx/fUSMAT6AgZUkSZKkHtLbTQHfDlxdE0BdTA629uxgumcrQRVASuk24JEyrGIo8HLNtDPxdpkkSX3EU7CkgaG3A6sdgAeqE1JKjwPzyrCGpyv+WTPdOcBHI+LNEbF2ROwBHAP8sKlS9zuepCRJ/Z9nK0kDSW8HVqPJT5BqzSjDmp3uOOBS4C/AbOBG4LcppRO7VNp+zJOVJKm/SyRSJM6ctNqdhiVpFb39jlVP+yJwGPBJ4B5gF+B/IuLFlNLX600QEUcDRwNsvPHGTJ06tZeK2r45c+Z0WJb+UlatPhqpd1J3s96tvp4bvAEzYz2u+Y8X2LGfbWPrnXqbdW7119uB1QxgZJ300WVYe9Nt2N50EbEBuQfA/04p/bQMvzEiFgE/jIgfppSeq80gpXQ2cDbAuHHj0vjx4xtclJ41depU2irLj/7vIYA2h0td1V69k3qK9W71NfO6uyCCW0e8kfHj/6Ovi7MS6516m3Vu9dfbTQEfoOZdqojYHBhO/Xeo2pyuqH73amty5xV/rxnnLnIAuWUXyitJkrpoVHoJUmLvl2/v66JIUo/r7cDqSmC/iFinKu1gYD5wQwfTbRIRu1cSImIcOZi6siQ9Vn6/vmbayi2yR7tY5n7Hjy1KklrBJktfYNslD7PjK17s66JIUo/r7aaAZwGfAn4bESeTA6NJwOnVXbBHxDTghpTSkQAppZsj4hrggoj4Ais+EPyXyjesUkrPRsRlwMkRsRb5HavXlvx/nVJ6vpeWsZcYXkmSWsNXd/1qXxdBknpcrwZWKaUZEbEPufvzP5B7+juDHPzUlmtwTdrBZdzzyE/aLicHadU+DHy9pG8KPAX8BPifblsISZIkSarR670CppTuB/buYJyxddJmAoeXn7ammwV8ofxIkiRJUq/o7Xes1A38hpUkqWV40pI0QBhYtSDfrpIktQRPWJIGEAOrluTtP0mSJKk/MbBqUYZWkiRJUv9hYCVJkiRJTTKwkiRJkqQmGVhJkqQek2y8LmmAMLBqQclzlCSpBYTdAkoaQAysWpQnK0lS/+edQEkDh4GVJEmSJDXJwEqSJEmSmmRgJUmSJElNMrBqQbZYlyRJkvoXA6sWZNe1kqTW4TlL0sBgYNWy7BVQktTfJTxfSRooDKwkSZIkqUkGVpIkSZLUJAOrlmSzCkmSJKk/MbBqQXZeIUmSJPUvBlYtytBKktQKvBkoaaAwsJIkST0ibLouaQAxsJIkSZKkJhlYSZIkSVKTDKwkSZIkqUkGVpIkSZLUJAOrluULwZIkSVJ/YWAlSZJ6jN2tSxooDKwkSVIPsoWFpIHBwEqSJEmSmmRg1YIS4Q1ASZIkqR8xsGpRtliXJEmS+g8DK0mSJElqkoGVJEnqQbaxkDQwGFhJkqQeUQmpDrzwd31aDknqDQZWrSjsuUKS1DrWnnVGXxdBknqcgVVLslmFJKl1/GP4S31dBEnqcQZWLSrsb12S1CLe8NKIvi6CJPU4AytJktSjfvq5W/u6CJLU4wysJEmSJKlJBlaSJKnHJN8LljRAGFhJkqQeEcn3gSUNHAZWLcjTlCRJktS/GFi1LMMrSVJr+Odn39nXRZCkHmdgJUmSelS6elpfF0GSepyBlSRJ6lGx37Z9XQRJ6nEGVpIkqcckYMczLu/rYkhSjzOwakF2XStJkiT1LwZWLcrQSpIkSeo/DKwkSZIkqUkGVpIkSZLUJAOrVmQ7QEmSJKlfMbCSJEmSpCYZWEmSpB5kMwtJA0OvB1YRsVNE/Cki5kXE0xFxYkQMbmC6kRFxfkTMiIiXI+KiiFi/znjrR8RPIuKZiJgfEQ9ExId6Zmn6UurrAkiS1K7wXCVpABnSmzOLiNHAFOB+4ABgG+A0coB3fAeTXwJsB3wEWAacDFwG7FGV/7rAjcAc4JPAC8BOwBrduRySJEmSVK1XAyvgY8Aw4L0ppVnAtSUYmhQRp5S0VUTEbsC+wJ4ppRtL2lPArRExIaU0pYz6FWBNYFxKaX5Ju74Hl0eSJEmSer0p4NuBq2sCqIvJwdaeHUz3bCWoAkgp3QY8UoZVHA6cWxVUSZIkSVKP6+3AagfggeqElNLjwLwyrOHpin9WpouIrYCNgJkR8ceIWBQRz0fE6RGxWjUFTL4ILElqFZ6yJA0QvR1YjQZm1kmfUYY1M90m5fcpwFPA24BvAccA3+xKYfszz1OSpFZg9xWSBorefseqJ1VijftSSkeVv6+LiHWAr0TEpJTSvFUmijgaOBpg4403ZurUqb1S2I7MmTOnw7L0l7Jq9dFIvZO6m/Vu9dcft6/1Tr3NOrf66+3AagYwsk766DKsvek27GC6yu/aziquA04g90B4b20GKaWzgbMBxo0bl8aPH99OMXrP1KlTaassp1/xCECbw6Wuaq/eST3Ferf6Oumqi4D+eb6y3qm3WedWf73dFPABat6liojNgeHUf4eqzemK6nevHgYWsWorucr/yzpb2P7LhhWSJElSf9LbgdWVwH6leV7FwcB84IYOptskInavJETEOGDrMoyU0iLgWmCvmmn3IXeOMa3p0kuSJElSHb0dWJ0FLAR+GxETyvtNk4DTq7tgj4hpEXFu5f+U0s3ANcAFEfHeiDgQuAj4S9U3rABOBF4XEedHxL4R8QXgOOBbKaWFPb50vcauKyRJkqT+pFcDq5TSDPITpMHAH8jvPp0BfKNm1CFlnGoHk59qnQdcANwJvKcm/9uAdwG7lPw/DZwEfLs7l6M/CBLnf/OHfV0MSZI64M1ASQNDr/cKmFK6H9i7g3HG1kmbSf4A8OEdTHs1cHUTRWwZ+8zZua+LIElSm8J3giUNIL3dFFDd6NGFS/u6CJIkSZIwsGppv9vIO4GSJElSf2Bg1YIq4dQZX263RaUkSZKkXmJgJUmSJElNMrCSJEmSpCYZWEmSpB5iv4CSBg4DK0mS1EMMqyQNHAZWkiRJktQkA6sW5P0/SZIkqX8xsGpRtlqXJPV7nqokDSAGVpIkSZLUJAMrSZLUg6KvCyBJvcLAqgV5ipIktQLPV5IGkiFtDYiIS7qY55dSSo92cVo1IHmqkiRJkvqVNgMr4CDgLmBWg3kFsAfwHeDR5oqljvlGsCRJktRftBdYARyTUrqtkYwiYgiwqPkiSZIkSVJrae8dqxOAJzuR19IyzdNNlUiSJEmSWkybT6xSSid0JqOUUiIHVpIkSZI0oDTVK2BEjIiIwyLiiu4qkBpg3xWSpBbhG8GSBoqO3rFaRUSsAbwDOKT8Hgbc383lUrsCoytJUn8XhlWSBpCGAquIGARMIAdTBwIjyTehfg58L6V0V4+VUHV5spIkSZL6j3YDq4h4MzmYeh+wATAT+A3wR+BS4DyDKkmSJEkDXZvvWEXEo8CNwIeAKcABwCYppaOA63qldJIkqWVV2lbccqyXDZJWf+09sdqi/L4XuB64KaW0uOeLpI7ZDFCS1Do27fwr3ZLUctrrFXBr4CvA2sDZwPSIuDwiPgCs0xuFU33JjiskSS0iEfxtcGc+iylJranNwCql9GhK6TsppV2A1wDfBbYnd1gxjfzY5A0RMbRXSqqV2HmFJKm/q9wG/O5ml/ZpOSSpNzT0HauU0n0ppeNTSq8EdgXOBKYDpwLPRMSZPVhGSZLUwv7ycQMrSau/Tn8gOKV0W0rpwYu+TwAAIABJREFUs8DmwD7k3gHf190FkyRJkqRW0enAqiJl16eUjgY26cYySZIkSVJLaa+79XdHxMhGMkkpLamaZt3uKpwkSZIktYL2nlj9Dtiu0YwiYnCZZttmC6X22W2FJEmS1L+092GJAD4VEdMbzMs+wCVJkiQNSO0FVo8Du3cyv8eBhV0vjiRJWl34aRBJA0mbgVVKaWwvlkOSJK2urvg8vOO0vi6FJPWoLvcKKEmS1JA7zu/rEkhSjzOwkiRJPWvc4X1dAknqcQZWkiSpZ9kMUNIAYGDVoiL5QrAkqf9LdhosaYAwsJIkSZKkJhlYSZIkSVKTmg6sIuK8iPh2RGzZHQVSA2xVIUmSJPUr3fHEam/gCGBaRPy6G/JTB2yvLkmSJPUvbX4guFGVDwlHxFbAbs3mJ0mSJEmtpunAqiKl9AjwSHflJ0mSJEmtws4rJEmSJKlJbT6xiojngYY/lpRS2qhbSiRJklYL0fhlhCS1vPaaAv6ITgRWkiRJkjRQtRlYpZQm9WI5JEmSJKll+Y5Vi7J5hSRJktR/GFhJkqSe4T1ASQOIgVVL8gPBkqTWkMJzlqSBwcCqJXkLUJIkSepPDKxaUPKJlSRJktSv9HpgFRE7RcSfImJeRDwdESdGxOAGphsZEedHxIyIeDkiLoqI9dsZ/4CISBFxR/cugSRJkiStrL3vWHW7iBgNTAHuBw4AtgFOIwd4x3cw+SXAdsBHgGXAycBlwB515rMWcAbwbHeVXZIkSZLa0quBFfAxYBjw3pTSLODaiFgXmBQRp5S0VUTEbsC+wJ4ppRtL2lPArRExIaU0pWaSLwJPAQ8Dr+6hZelze191N9e9bZe+LoYkSZI04PV2U8C3A1fXBFAXk4OtPTuY7tlKUAWQUroNeKQMWy4itgC+BHy6uwrdXx3+xyf6ugiSJEmS6P3AagfggeqElNLjwLwyrOHpin/Wme404JKU0t+aKGe/NnjIIgYNWsqYXS7r66JIkiRJovebAo4GZtZJn1GGdWW6rSv/RMTe5CaD2zVRxv5v8BIA0pY39HFBJElqm33YShpIejuw6jERMQT4PnBSSqnhTisi4mjgaICNN96YqVOn9kwBO2nOnDltliUtHUIMTsx+5lX9prxaPbRX76SeYr1b/fXH7Wu9U2+zzq3+ejuwmgGMrJM+ugxrb7oNO5juqJL35IgYVdLWAAaX/+emlBbXZpBSOhs4G2DcuHFp/PjxDSxGz5s6dSptleXbVz7BshjMgYfZFFDdq716J/UU693q69Q//gygX25f6516m3Vu9dfbgdUD1LwTFRGbA8Op/w5V9XSrdKte8qpEF9sDm1G/i/UZwAeBCztZXkmSJEnqUG93XnElsF9ErFOVdjAwH2jvhaErgU0iYvdKQkSMI79fdWVJ+iGwV83P1cBD5e9ru2kZ+pxt1iVJkqT+pbefWJ0FfAr4bUScTA6MJgGnV3fBHhHTgBtSSkcCpJRujohrgAsi4gus+EDwXyrfsEopTQOmVc8sIiYCG6SUpvbwcvWqZGglSWoRnrMkDRS9+sQq/f/27j1O7qo++Pjnu7ObZLO5LQFyh3BJCEGg0ERABCKJKNKKWpXaSsGq1LZqn9b6FB8vDUqfB+0LtY/XUkFq0YpaH6tQCQYMl4qAyE3uiZAQNiSQC8luNslezvPHzG4mk93sbmZnZ2bn8369fpA5v3PO7zu7Z2fmO7/zO7+UtgJLgQzwE+AK4AvA3xdUrc/VyXcR2bNa1wHfAh4A3lrKeCuZb1OSpEoXpHKHIEkjZsRXBUwpPQ6cO0CduX2UbQPek9sGe6xLhxheVVn5yXez7DNeNiZJkiSV20hfY6VhkCKRSNz7ysSBK0uSJEkqOROrKrQ+M4P1dXO4ffGycociSZIkCROrqrQlMxUieHzmUeUORZIkSRImVlXpkK4tkBKXzOnrnsmSJFUKl1qSVDtGfPEKFW925waaoo2r5p9S7lAkSTogl1uXVCs8YyVJkkrE5dYl1Q4TK0mSJEkqkolVNXJWhSRJklRRTKwkSVIJOR1QUm0wsapSnrSSJFU8cypJNcTESpIklZBfBUqqDSZWkiSpJMJTVpJqiImVJEmSJBXJxEqSJEmSimRiVYW8i70kSZJUWUysqpbz1iVJkqRKYWIlSZJKIuEsC0m1w8RKkiSVhCmVpFpiYiVJkiRJRTKxkiRJkqQimVhVqXDtCkmSJKlimFhJkiRJUpFMrCRJkiSpSCZWkiRJklQkEytJklQSLrcuqZaYWFUhb7YoSZIkVRYTq6rlsoCSJElSpTCxkiRJkqQimVhJkiRJUpFMrCRJUsl4XbCkWmFiJUmSSsTrgSXVDhOrKuX3f5IkSVLlMLGSJEmSpCKZWEmSJElSkUysJEmSJKlIJlaSJEmSVCQTqyqUwqUrJEnVIFwXUFLNMLGqUr5VSZIqne9VkmqJiZUkSZIkFcnESpIkSZKKZGIlSZIkSUUysZIkSZKkIplYVSEvBZYkVQ9XspVUG0ysqpbplSRJklQpTKwkSZIkqUgmVpIkSZJUJBMrSZIkSSqSiVXV8mJgSZIkqVKYWFWpcPEKSZIkqWKYWEmSpNJIrmErqXaYWEmSpJJwdoWkWmJiJUmSJElFMrGSJEmSpCKZWFWh5IqAkiRJUkUZ8cQqIhZGxG0RsTMiWiLi0xGRGUS7yRHxzYjYGhGvRMS3I2Jq3v5MRPxdRNwVEZtz260Rsbi0z6g8nLcuSZIkVY4RTawiohlYSXaRoAuBTwMfAa4YRPPvAUuA9wGXAouBH+XtbwQuB+4HLgbeDXQAd0fE7w7LE5AkSUPkLAtJtaF+hI/3AbIJ0NtSStuBn0XEJGB5RHwuV7afiDgDOA84J6V0Z67sBeDeiFiWUloJtANHp5S25rW7DXga+CDwnlI+MUmStC9TKkm1ZKSnAp4PrChIoL5LNtk6Z4B2G3uSKoCU0n3As7l9pJS68pOqXNke4DFg5vCEL0mSJEn7G+nEagHwZH5BSmkdsDO3b9Dtcp44ULuIGAucSvas1SgS+D2gJEmSVDlGeipgM7Ctj/KtuX0H0+7oA7T7OHAI8OX+KkTEZcBlANOmTWPVqlUH6G7ktLa2DhBLqphYNXoMPO6k4ee4G/0q8ffruNNIc8yNfiOdWI2YiLiAbGL1kZTSU/3VSyldA1wDsGjRorRkyZKRCXAAq1ator9YrlhxI0C/+6WDdaBxJ5WK4270+qeb1gCV+X7luNNIc8yNfiM9FXArMLmP8ubcvmFpl1ti/Ubg6ymlLx5EnJIkSZI0aCOdWD1JwTVRETEHGE/f11D12y5nv2uvImI+cDNwG/DhYoKtXN7DSpJUHbypvaRaMdKJ1U+BN0TExLyyi8gulX7HAO2mR8RrewoiYhHZ66t+mlc2A1gBrAHelVLqGsbYJUnSkPhFoKTaMdKJ1deB3cAPI2JZbuGI5cDn85dgj4jVEXFtz+OU0j3ArcC3IuJtEfEW4NvA3bl7WBERjWSTrGbgSuCkiDg9t50yQs9vRPjtnySpGmTG7CKim1uuv7jcoUhSyY3o4hUppa0RsZTsKn0/IbvS3xfIJleFcWUKyi7K1b2ObEJ4E/tO9ZsGnJz7900FbdcCc4uLvrKE3wJKkircmvoj2cyh3DBnIW8sdzCSVGIjvipgSulx4NwB6szto2wb8J7c1leb5/DmTpIkVYwNzIYIbue8cociSSU30lMBJUlSjTi8cxOkxMnPPlbuUCSp5EbtfawkSVJ5HbPneToy9Xxw+tRyhyJJJecZq2oULmAhSap8kbsc+IILLihvIJI0AkysqlQkF6+QJEmSKoWJlSRJkiQVycRKkiRJkopkYiVJkiRJRTKxkiRJkqQimVhVIVcElCRVjfA9S1JtMLGqUr5NSZIkSZXDxEqSJEmSimRiJUmSJElFMrGSJEmSpCKZWFWhVO4AJEmSJO3DxKpqmV5Jkiqf71aSaoWJlSRJKokwrZJUQ0ysJEmSJKlIJlaSJEmSVCQTK0mSJEkqkolVVYpyByBJkiQpj4lVlTK1kiRJkiqHiZUkSSohvwqUVBtMrCRJUkmYUkmqJSZWkiSppL749vPKHYIklZyJVRXydouSpGry0JKd5Q5BkkrOxKpqmV5JkqrDQxO2lTsESSo5EytJklRSv9PaXO4QJKnkTKwkSVLJJIJPrd5Y7jAkqeRMrCRJUmnkZq03Nr+7vHFI0ggwsZIkSSW17cbvljsESSo5E6uq5J1BJEnVo/W1XeUOQZJKzsSqSplaSZKqxaSP/GG5Q5CkkjOxkiRJJXXccVeUOwRJKjkTK0mSVDLedVFSrTCxkiRJJRGmVZJqiIlVFfJtSpIkSaosJlaSJKkk/CJQUi0xsapSTq+QJEmSKoeJlSRJkiQVycRKkiRJkopkYlXF/vPyH5Q7BEmS+hV5/5Wk0c7EqgqlyL5JnZIOL3MkkiRJksDEqnoleCReLncUkiRJkjCxqmpjM5PLHYIkSZIkTKyq2uv/YWm5Q5AkSZKEiZUkSSqxa6/8UrlDkKSSM7GqSt4cWJJUHRKwrPXEcochSSVnYlWVXLpWklT5IvdF4CNsLnMkklR6JlZVKjxrJUmqEs9vay53CJJUciZWkiSpJHq+Ajx27LqyxiFJI8HESpIkldR55z1a7hAkqeTqyx2AJEka5S64utwRSDVry/efYuevNzH+1dNpvvBYOl9uZ/tta2l/+OVyhzZks686q9whHJCJVVVy8QpJkiRB6k5s+Ox9dL+y54D1dt77IjvvfXGEoqpNI55YRcRC4EvAGcA24BvAFSmlrgHaTQa+CLyF7BTGm4APp5Q2F9S7ELgSmAf8Ntf3jcP9PCRJ0mD4ZaA0nDZ/+wnaH62+s021YEQTq4hoBlYCjwMXAscAV5NNlD4xQPPvAfOB9wHdwGeBHwG95wQj4rXAfwBfBT4MvAn494jYmlK6dVifjCRJOiBTKql4qTvxwvJfwJ7uYe23ky7qyQx8fBKddFGXW5ohkfZpt7L+EdZmXmJB12wWdx7DL+uf5pnMBhZ0zeI1nccRBJ1kz5+sqn+MtZmXOK5rFmd2Hkc3iYDevu+sf5xnMhs4rrctdNE9qDgrwUifsfoA0Ai8LaW0HfhZREwClkfE53Jl+4mIM4DzgHNSSnfmyl4A7o2IZSmllbmqnwTuTCl9OPf45xFxAvApYFQlVgHcdPl/8HtX/UG5Q5EkaVi1trbS2NhIJlMdH6akUkjdiReuuAd2753U1c4eGsjQFrv57/on2dSwkflHP8QhM54qaJyoA1Jd6b/emJPbAJ4FpuU2gKcPULdwHwVtnynYlxLMZk1xwZbYSCdW5wMrChKo75I9+3QO8JMDtNvYk1QBpJTui4hnc/tWRsRY4HVkz1Tl+y7wzYiYnFJ6ZZieR0ml7m5atmxmww2PsOuxzUw+bTbrHniIQ/Yczq2ZX8PSWdRldrHthH8FTKwkSZUrESy/4grGjhnD7t27uePYk3hy5lwWtjzHpekaZsxczYaWeaxefRoR2W/DI3eu69uLl7GjsQmAE1qe5axnHoGA8V31tNd10sRY9jRsI9MxkXY6gOD+YxfxwKxZvcc/+fH7uGb9cWTIcHfmCZ6sb4HooqFhD3fcsZKU6nsChe4M1HVxfNcsNjVt4ummLTx/+B9w32GNXLBpO+954BnmZOZDwE1T7mTd7jbGpDF0000ddaT6VqKzCQgiQev4MRzSvZ09u8cyqW4Su1ub2NW4ESK7EH32eSZ+Pv8Unp5+JMe3/JYlax6kq7uenWPG0bRnFx11GXY1NNDUvoMTT15Fc/NGJj5/Dm33vopfjF1D5+SpANy+4FSennZEtt/ubqgLjm9Zy3cbF7Bi9V2s2dkCAYlu6jNddHU1kEhk6rr42bzFPDPtCAJ427o9/N0Tu/jXxjvopJux3fUcMf8ups9YQ0vLsfx2zem96+g3dbQzf+pEpq2dwazGY3lw16McUtdMc9Nsflh/B110Zz8NR/b3GdEFCRIZSN00jNlDR8c4SLDihMU8N3UGC1ue4/1PbuZVu4/lS013s3HhUu47tJHjNzzLWasf6T12Y1cjm7YdwUlTd7Nk91ze+6rtPDZzNokE1NHctp13P3QLS9tOZWY6nDXbH2TGobMZ03EITNzK3I+9lfYd2/nna7/Ojh1tjB/fTVtbAwDXnXkBezLZcTGtYyNv/cUv9xnTDZHhmK2L2Lx7DJ27HmbumfAXR72GrrqxAJy4di1nrn2o8A+BCHjgn6/mxvM2cNnkDHMnb6alZR5r17ya7gTT2sdw+oSFHNp+KKTE7fWPsr7xWS6e9m/M3rSL9u4JbNlzJJmoJ5O6eX/do9AFsRpYvc+PetRJPfduWFrWMAYUKY3cjWYjYhPw1ZTS8oLyNmB5Sukf+2n3PeDwlNKSgvKbAVJKF+Su3XoMeF1KaVVencXAfcCrU0r3Hyi+RYsWpV/96ldDfVrDbvrtDw78l5ESy7iFG8792MgEpZqwatUqlixZUu4wVGMcd6PX9NsfgMiddRroU1/P55GIff/dX91cvSZ2MIVtvBBHHDiYvvrMj2kon0r7+uw04HPrBupopI0MXbTG5MEda7AxDOZnO9j6Qzn+YPrJ+30Vdey85zGdF3gxZg+pzUH9rvvoaybraYk5B66Xf6z8Y/dRN0MnXdGQV9bFt7v+iBkfquO+ExOXLNyw31OoRSlBXFEZ50gi4oGU0qLC8pE+Y9VMdsGKQltz+w6m3dF5deij3taC/ZVvMH81EaxMbyx9LJIkHazIm8o30Htb/v7B1o2gjUm0MWkQsfTR51COOVBfA9bP/izamTC0tsMRQyk+jR/M8YuNI6/9iwwiqervmAcbR65dCwdIqgr7H8RY7qKhoLAO6jr5zayZnLimjQeeOpLfzJrK5onjAZi9ZQcLN2zh0ZlT2dC873hq2rWH165uIdPdzSOzD2X9Idm/jfrObjrr9799bV1XN21zjuk981n/ymbGvbiO6M5OP5yxtZUTWl6moau795rJR2cdyvNT9/2bm7BrD2c/vR6Ajro6Hj7iMF6a1MTMbW101wUtUyay+4gFdDQ2MqatlbHrngTgiM3bedULL2dPGEeQSYnd9RnqUiLT1U13XfDorMPY0DyBOZu3884D/zTLruaXW4+Iy4DLAKZNm8aqVavKGxBAmjzoP/qKiFejRmtrq2NKI85xN5pNKd+hR/O8KI16CXj8rKU8XlgIPBHwREFZAxk6oosdwA9O3bdNz1/Bgq7ZnNZ5LDeMvZPO6HshjM4ph9I65dDexzuAp3tOuuXKJqRx7IhdextFtt6N+cfN6WvxhD0TJrJn4WIgO9XssQQLOmdyaufRjI+xjKWTXezh1/XPsjrzYu+BH0+V/7l3pBOrrUBf576b2Xtmqb92hw3Qruf/hf03F+zfR0rpGuAayE4FrITpKEtv+z/cxhv3PW3eo+BNohLi1ejhlCyVg+NuFLv91xB1/U+5y58i1tcUvQNdrtBX0pRXP+gmpbq+p6ANdtrhgdoVxlpw/P1i7a/tYJ5Xf8cujGE4jz/E6Wz96ut4hbEWjoH+fu4H6nMwx++v/kC/v6H0daA2fU1LLNyXV376Gf9OfX1n7+7+fvwbNswjk+nk8MOfZefOSYwfv386s3t3I2PHtrMaOL1g36ZNc3lxw3HMnvMohxzS0lu+c+ckMplOxo7dSWdnPfX1XWzaNJcxY3YyZcrGPmMpPP7GjUfz3LOn0t1dz7Hz7uGww9b27mtvn0hjYytdXXVkMl2syz2XceNaaW7ewHRgOrBrVxPjxu1kQ8s8lixZ3vcPoUKMdGL1JLAgvyAi5gDjc/sO1K6vWy0vILvkOsAaoCNXdkdBnW76XnykIr3lnsPYc9K9/PeExZzWdh+XNfwTDQ0ddHcHf5r5Dp25U8bjOjrKHKkkSf1blm7ldl7PzNTCemYBwbSOjWxsyK771cQO2lMTM1nP+rT3GqkmdtCWJjKtYyNX13+QtrZJNDVtJ6VEBFwen9+nfo/mtu38r21XMWPmM2xomcf1vJ/HZ83l9R13c3vD6XSm7PvnMm7h0Y5T2NgwjdmsA+ijv8QyVvAkC3v3LeMWujvGcXvDkt5aM7vX01KXXSxjaVrBe/gGAG1tk2lqeoU/i2/SliYytmMPV25azvJZH6ONib3xXvSrn3PK7/6YpqZXuD7ex8r0BvpaqH4Zt9DWNoV7mk7rY3+iLnVz/Atrsws8AGee9W/7/Kxms46tNNOWJu7T5590XUtdHbS1TeIzE/6+97nW09H785rNOhbweL+XIGRSJ3955wpO+N0f0tS09xqY7PPZ22Y8rbyGu7k9nceSrpXMv7udhxdN496mV+fGQHaK3QU7fkPjtgX8YE4DkDij7V7etu3HzJj59H59QjffaP0zxjVlvz/f0DIfgBkzsx/7LuZ7JPZOgTvhhewiGAuPeYBDZj3BRzu/woaGw3uf5ydbr+DBB97M6WfcSH3DHjo6Gnj5paNYMevs/Z7/bNZx5Y7/TUPTFmLtOTz68FmckjmCdad+jukzn+EyvsnOvKmf53XcxSWZL3Ft11/sM4Z6nsfE9nZ2jM/W/1p8iIsbrqeRnWTo4tr4AKtY1ufPn5nszbqasgnaDNbTRT2bmJ4tH5e7Lo1Z+7efBrOnraOdC9nM4XvLm6CRNtppone24rS8MuAsfs67uIEmWrmM69nd1Mh4WjmJB/klZ9GTHc3ieVp4G2fzc/6Yb/ENPsB948/I9pnLRl7Hz7h75tl0xLjeRLORNtobm5jBev5x5v/o+/lXkJFevOJjwEeBI1NKO3Jlfwt8Gpg+wHLrvwDOSindnStbBNwPvL5nufWIWAFkUkrL8treBExJKb12oPgqZfEKyH6D27nmCR5Z+VNOWnY+y9775+UOSTXAMwcqB8fd6HXbbfMguqG7jqXL9i6efPPNN3P//dn1pBq2buK0k07sfZ9bee3XeGTlT+k4YTHtndnrPBYvXswFF1ywT9899QrfI6//yF+yef1aps4+kkuv/kq/sfW8zz58683cc8IWnjmilXcuuIiPn/7x/foebJ/9xdVfrINt31+9h2+9OfsggpNf/yaWvffPD3j8Q2bOYUvL84w/9UxebGvv7St27eTMeUcdVGyFP5v8OveesIXvP/193jH/HUy9q54XW3cC0NhQz66ubhYtWsTYF9f12yfAyedd0FveM256xgywz/M6adn57J5+RLbOlo2M27S+9+cylOc11N/Xw7fevM/voKf83kcepaP58N7x+61Pf4KXn3hkv357jvfSyYv45mlvPuDxalpKvHjuKeWOAuh/8YqRTqyayd4c+Ddkl1g/Gvg88MWU0ify6q0G7kgpvTevbAUwD/hb9t4geFNKqfAGwauAL5M9k/WmXP03DuYGwZWWWPlBQyPNcadycNyNXrdf82bS0U8Qvz2ecy/7cbnD2YfjTiNtoDF31XX/whePWjxyAVWbKkisRnQqYEppa0QsJZv4/ITsCn5fAJb3EVfhXQEvytW9DqgDbqLgnlUppbsj4u3AlcCfk71P2R8NJqmSJEnD69HbZtF5W6KeWZx7WbmjkSpbd13B6oBDvear37bR1+zSAx+nv6XpD3St3kDX02VvVJeNpb/rKwuPmf/vKliMZsRXBUwpPQ6cO0CduX2UbQPek9sO1PZH7L3uSpIklclf3fi1cocgVY26mUdm/5FLRJalFdyw9PI+617+9PNc/8Lmfvs6rmkcd5x2/KDaFtY9594neGrn7t59Pf/ueXxG84Te9gFcMju7imBh2T1bW3lq5+7eNv/2wmaObRrL6p27mdiQYVtnN1Ny/+9x6aypve3yjx/AJbOm9vt8K0XNL7cuSZIklduuMeNyZ3SyZ3Le8eJ9/da9av4crpo/wP20DrJtfwlZYR+DKRvK/tFg/zuFSZIkSRpR8445ep/HZzd9rkyR6GCZWEmSJElldvykCTTuboeUmNKxm+a3HFvukDRETgWUJEmSyuzUyU3sHtsIwI4x48ocjQ6GZ6wkSZKkCvAns6aSAS6ugoUatD/PWEmSJEkVoJhFKVR+nrGSJEmSpCKZWEmSJElSkUysJEmSJKlIJlaSJEmSVCQTK0mSJEkqkomVJEmSJBXJxEqSJEmSimRiJUmSJElFMrGSJEmSpCKZWEmSJElSkUysJEmSJKlIJlaSJEmSVCQTK0mSJEkqkomVJEmSJBUpUkrljqFiRMRLwNpyx5FzKPByuYNQzXHcqRwcdyoHx51GmmNu9DgypXRYYaGJVYWKiF+llBaVOw7VFsedysFxp3Jw3GmkOeZGP6cCSpIkSVKRTKwkSZIkqUgmVpXrmnIHoJrkuFM5OO5UDo47jTTH3CjnNVaSJEmSVCTPWEmSJElSkUysKkhELIyI2yJiZ0S0RMSnIyJT7rhUHSLi2Ij454h4JCK6ImJVH3UiIv5XRDwfEe0RcWdE/E4f9QYci4PtS6NXRLwjIn4cES9ERGtEPBAR7+qj3vsj4pmI2JWrs7SPOrMi4v9FxI6IeDkivhwR4w+mL41uEfH2iPhFRGzOjYOnIuITETEmr46vdSqZ3OtVa0SkiJiQV+64q3EmVhUiIpqBlUACLgQ+DXwEuKKccamqnAC8CXgKeLqfOpcDnwQ+C/w+0AqsjIjpPRWGMBYH7Euj3t+Q/b3/NfBm4OfAdyLiQz0VconW14FvAecDjwE3RcSr8uo0ACuAI4E/BP4KeAcF1yMMpi/VhKnA7cD7yI6D64CPA5/Pq+NrnUrpH8mOg0KOu1qXUnKrgA34GLAVmJRX9j+Bnfllbm79bUBd3r9/AKwq2D8OeAX4VF5ZE/AScGVe2YBjcbB9uY3uDTi0j7LvAM/mPX4KuC7vcR3wKHBDXtm7gC7gqLyydwLdwLyh9OVWmxvwD8A2IHytcyvlBpwNbAH+lmxyNGEoY8VxN7o3z1hVjvOBFSml7Xll3wXQV8SHAAAGTElEQVQagXPKE5KqSUqpe4AqrwEmAd/La9MG/ITs+OsxmLE42L40iqWUXu6j+EFgJkBEHA3MZ99x0g18n/3H3P0ppWfzyn4E7AHeOMS+VJs2Az1TAX2tU0nkput9iexZpsLXP8edTKwqyALgyfyClNI6st9gLChLRBptFpA9K/BMQfkT7DvGBjMWB9uXas8Z7J2K2jMWniyo8wRwSEQcllevcMztAdaw75gbTF+qERGRiYjxEfFa4MPA11L2q31f61QqHwDGAl/pY5/jTiZWFaSZ7DSGQltz+6RiNQOtKaWugvKtwPi8C78HMxYH25dqSG4hibcAV+eKesZL4XjaWrB/sGNuMH2pdrTltruAO4CP5sp9rdOwi4ipwGeAv0kpdfRRxXEnEytJUvEiYi7Z66v+M6V0fVmDUa14DXAW2Qv/LwS+XN5wNMr9A/DLlNJ/lTsQVa76cgegXluByX2UN7P3G1mpGFuBCRGRKfgWrBnYmZt61VNvoLE42L5UAyLiEOCnwFrgj/N29YyXyez7DW1zwf4DjbmHh9iXakRK6de5f94dES8D/xoRV+NrnYZZRJwA/ClwdkRMyRX33A5ickR04bgTnrGqJE9SMG82IuaQ/cMtvKZAOhhPAhng2ILywvnegxmLg+1Lo1zuXlM3kV044PdSSjvzdveMhcJrAhYAW1JKL+XVKxxzY4Cj2XfMDaYv1aaeJOsofK3T8JsHNAD3kE16trL3Oqv1ZBe0cNzJxKqC/BR4Q0RMzCu7CGgnO3dcKtYvgO1k7w8E9H4o/n2y46/HYMbiYPvSKBYR9WRX5ZsHvDGltCl/f0rpt2QXssgfJ3W5x4VjbnFEHJlX9mayF4nfMsS+VJvOzP3/WXyt0/C7G3hdwfbZ3L43kb2vleNOTgWsIF8nu6rRDyPis2S/qV0OfL5gSU6pT7kX3TflHs4CJkXE23OP/yultDMirgI+GRFbyX7r9Tdkv2D5Ul5XA47FlNKuQfal0e2rZMfcXwFTcxd393gwpbSb7Ni5ISKeA/4buIRsIvZHeXV/QPYGrz+MiE+SnSbzBeA7KaX8VbEG05dGuYi4hewNVh8ju3LamWSvs7oxpbQmV8fXOg2b3K0lVuWX5a4rBbgrpdSaK3Pc1bpy30jLbe8GLCR7N/l2YAPZ1Wcy5Y7LrTo2YC7ZmxX2tc3N1QmyH2DX58bZXcApffQ14FgcbF9uo3cDnhtozOXqvR9YDewmO2VraR99zSZ776pWsvck+gowvo96A/blNrq33OvRb3JjZVtuHHwIaMir42udW0k34FLybhCcK3Pc1fgWuV+eJEmSJOkgeY2VJEmSJBXJxEqSJEmSimRiJUmSJElFMrGSJEmSpCKZWEmSJElSkUysJEmSJKlIJlaSpFErIt4ZEZceZNtLIyLltocOst2vDubYkqTqY2IlSRrN3kn2Rp7FOBe4eAj1bwbOAP6ryONKkqpIfbkDkCSpwt2fUmodbOWU0kvASxHxEjCtdGFJkiqJZ6wkSaNSRFwP/AFwTt7UvOXD0O+UiPhGRLRExK6IWBcR/1Jsv5Kk6uYZK0nSaPUZ4AhgCvAXubL1w9Dv54HXAH8NvAjMAc4ehn4lSVXMxEqSNCqllNZExBagLqX0y2Hs+tXAV1JKN+aV3TCM/UuSqpCJlSRJQ/MQ8NGI6AJWppSeLndAkqTy8xorSZKG5oPAj4BPAU9FxDMR8YdljkmSVGYmVpIkDUFKaVtK6cMppenAycC9wLcjYmGZQ5MklZGJlSRpNNsDjCtV5ymlR4CPkn0/XVCq40iSKp+JlSRpNHsSODEi3hIRiyJiJkBEXJpbfn3uUDuMiLsj4iMR8YaIOA/4v0AbcN9wBi5Jqi4uXiFJGs2+CpwCXAc0A1cAy4HxZM9mbTuIPu8BLgXmAl3Ag8D5KaXhWMpdklSlTKwkSaNWSull4K197DoN+E5KaTCJVSYiMimlrlyfHyU7/a9PERFABoiDCFmSVKWcCihJqkVnkL3R72BsAx4YQt+XAB3Anww1KElS9YqUUrljkCSp4kTEVOCo3MOdKaXHD6JdW0rpiVLEJ0mqLCZWkiRJklQkpwJKkiRJUpFMrCRJkiSpSCZWkiRJklQkEytJkiRJKpKJlSRJkiQVycRKkiRJkor0/wFyUvaZDp3jkQAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<Figure size 1008x504 with 1 Axes>"
       ]
@@ -3910,10 +3903,10 @@
    "id": "c2ccba46",
    "metadata": {
     "papermill": {
-     "duration": 0.12968,
-     "end_time": "2022-01-11T13:57:06.858546",
+     "duration": 0.132372,
+     "end_time": "2022-02-21T13:10:24.469862",
      "exception": false,
-     "start_time": "2022-01-11T13:57:06.728866",
+     "start_time": "2022-02-21T13:10:24.337490",
      "status": "completed"
     },
     "tags": []
@@ -3928,16 +3921,16 @@
    "id": "c751fd1a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:57:07.125790Z",
-     "iopub.status.busy": "2022-01-11T13:57:07.125068Z",
-     "iopub.status.idle": "2022-01-11T13:57:07.127815Z",
-     "shell.execute_reply": "2022-01-11T13:57:07.128306Z"
+     "iopub.execute_input": "2022-02-21T13:10:24.749681Z",
+     "iopub.status.busy": "2022-02-21T13:10:24.749342Z",
+     "iopub.status.idle": "2022-02-21T13:10:24.756500Z",
+     "shell.execute_reply": "2022-02-21T13:10:24.755743Z"
     },
     "papermill": {
-     "duration": 0.139347,
-     "end_time": "2022-01-11T13:57:07.128511",
+     "duration": 0.156677,
+     "end_time": "2022-02-21T13:10:24.758882",
      "exception": false,
-     "start_time": "2022-01-11T13:57:06.989164",
+     "start_time": "2022-02-21T13:10:24.602205",
      "status": "completed"
     },
     "scrolled": false,
@@ -3967,10 +3960,10 @@
    "id": "a0739d83",
    "metadata": {
     "papermill": {
-     "duration": 0.127395,
-     "end_time": "2022-01-11T13:57:07.383953",
+     "duration": 0.132202,
+     "end_time": "2022-02-21T13:10:25.030105",
      "exception": false,
-     "start_time": "2022-01-11T13:57:07.256558",
+     "start_time": "2022-02-21T13:10:24.897903",
      "status": "completed"
     },
     "tags": []
@@ -3985,16 +3978,16 @@
    "id": "01bd2d08",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:57:07.646990Z",
-     "iopub.status.busy": "2022-01-11T13:57:07.646328Z",
-     "iopub.status.idle": "2022-01-11T13:57:07.648195Z",
-     "shell.execute_reply": "2022-01-11T13:57:07.648812Z"
+     "iopub.execute_input": "2022-02-21T13:10:25.291587Z",
+     "iopub.status.busy": "2022-02-21T13:10:25.291232Z",
+     "iopub.status.idle": "2022-02-21T13:10:25.294966Z",
+     "shell.execute_reply": "2022-02-21T13:10:25.294325Z"
     },
     "papermill": {
-     "duration": 0.135291,
-     "end_time": "2022-01-11T13:57:07.648985",
+     "duration": 0.136646,
+     "end_time": "2022-02-21T13:10:25.296727",
      "exception": false,
-     "start_time": "2022-01-11T13:57:07.513694",
+     "start_time": "2022-02-21T13:10:25.160081",
      "status": "completed"
     },
     "tags": []
@@ -4011,16 +4004,16 @@
    "id": "50892deb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:57:07.922759Z",
-     "iopub.status.busy": "2022-01-11T13:57:07.921999Z",
-     "iopub.status.idle": "2022-01-11T13:57:18.044711Z",
-     "shell.execute_reply": "2022-01-11T13:57:18.044093Z"
+     "iopub.execute_input": "2022-02-21T13:10:25.557866Z",
+     "iopub.status.busy": "2022-02-21T13:10:25.557564Z",
+     "iopub.status.idle": "2022-02-21T13:10:35.514395Z",
+     "shell.execute_reply": "2022-02-21T13:10:35.513442Z"
     },
     "papermill": {
-     "duration": 10.267254,
-     "end_time": "2022-01-11T13:57:18.044880",
+     "duration": 10.091075,
+     "end_time": "2022-02-21T13:10:35.517267",
      "exception": false,
-     "start_time": "2022-01-11T13:57:07.777626",
+     "start_time": "2022-02-21T13:10:25.426192",
      "status": "completed"
     },
     "scrolled": false,
@@ -4081,7 +4074,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[NbConvertApp] Writing 519292 bytes to ./results/reports/AN_PGC4.html\r\n"
+      "[NbConvertApp] Writing 519328 bytes to ./results/reports/AN_PGC4.html\r\n"
      ]
     }
    ],
@@ -4100,6 +4093,23 @@
     "Time.sleep(5)\n",
     "!{sys.executable} -m jupyter nbconvert --to html $path_to_notebook --output-dir $report_destination_path --output $html_filename --TemplateExporter.exclude_input=True --TagRemovePreprocessor.remove_all_outputs_tags skip_output --TagRemovePreprocessor.remove_cell_tags skip_cell"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "890234d5",
+   "metadata": {
+    "papermill": {
+     "duration": 0.133748,
+     "end_time": "2022-02-21T13:10:35.786476",
+     "exception": false,
+     "start_time": "2022-02-21T13:10:35.652728",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -4122,8 +4132,8 @@
   },
   "papermill": {
    "default_parameters": {},
-   "duration": 1747.813625,
-   "end_time": "2022-01-11T13:57:18.793722",
+   "duration": 849.880675,
+   "end_time": "2022-02-21T13:10:36.748253",
    "environment_variables": {},
    "exception": null,
    "input_path": "/builds/LHCData/lhc-sm-hwc/test/../pgc/AN_PGC4.ipynb",
@@ -4140,8 +4150,8 @@
     "t_end": "2021-06-18 22:11:01.936000000",
     "t_start": "2021-06-18 22:11:01.925000000"
    },
-   "start_time": "2022-01-11T13:28:10.980097",
-   "version": "2.3.3"
+   "start_time": "2022-02-21T12:56:26.867578",
+   "version": "2.3.4"
   },
   "sparkconnect": {
    "bundled_options": [
diff --git a/test/resources/reports/AN_PGC1.html b/test/resources/reports/AN_PGC1.html
index 8c819bee..c285b686 100644
--- a/test/resources/reports/AN_PGC1.html
+++ b/test/resources/reports/AN_PGC1.html
@@ -13163,8 +13163,8 @@ Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdo
 
 
 <div class="output_subarea output_stream output_stdout output_text">
-<pre>Analysis executed with lhc-sm-api version: 1.5.18
-Analysis executed with lhc-sm-hwc notebooks version: 1.5.66
+<pre>Analysis executed with lhc-sm-api version: 1.5.19
+Analysis executed with lhc-sm-hwc notebooks version: 1.5.67
 user = root
 </pre>
 </div>
@@ -13467,9 +13467,11 @@ Name: Circuit name, dtype: int64
 
 
 <div class="output_subarea output_stream output_stdout output_text">
-<pre>1 type = RB , name = RB.A12 , Imax = 11500
+<pre>Main circuits (RB, RQ, IT)
+1 type = RB , name = RB.A12 , Imax = 11500
 2 type = RQ , name = RQD.A12 , Imax = 11200
 3 type = RQ , name = RQF.A12 , Imax = 11200
+Individualy powered circuits (IPQ, IPD)
 1 type = IPQ2 , name = RQ8.L2 , Imax = 5390
 2 type = IPQ2 , name = RQ8.R1 , Imax = 5390
 3 type = IPQ2 , name = RQ10.L2 , Imax = 5390
@@ -13479,6 +13481,7 @@ Name: Circuit name, dtype: int64
 7 type = IPQ4 , name = RQ7.R1 , Imax = 5390
 8 type = IPQ4 , name = RQ9.L2 , Imax = 5390
 9 type = IPQ4 , name = RQ9.R1 , Imax = 5390
+600A-circuits
 1 type = 600A , name = RCD.A12B1 , Imax = 450 , Imin = 0
 2 type = 600A , name = RCD.A12B2 , Imax = 350 , Imin = 0
 3 type = 600A , name = RCO.A12B2 , Imax = 0 , Imin = -100
@@ -13520,6 +13523,7 @@ Powering current is too low
 36 type = 600A , name = RSF2.A12B2 , Imax = 550 , Imin = -550
 37 type = 600A , name = RSS.A12B1 , Imax = 200 , Imin = -200
 38 type = 600A , name = RSS.A12B2 , Imax = 200 , Imin = -200
+60A, 80A, 120A circuits
 1 type = 60A , name = RCBH11.L2B1 , Imax = 55 , Imin = -55
 2 type = 60A , name = RCBH12.L2B2 , Imax = 55 , Imin = -55
 3 type = 60A , name = RCBH12.R1B2 , Imax = 55 , Imin = -55
@@ -13631,7 +13635,7 @@ Powering current is too low
 109 type = 80-120A , name = RCBCV8.R1B1 , Imax = 100 , Imin = -100
 110 type = 80-120A , name = RCBCV9.L2B2 , Imax = 100 , Imin = -100
 111 type = 80-120A , name = RCBCV9.R1B2 , Imax = 100 , Imin = -100
-Elapsed: 1394.826 s.
+Elapsed: 1711.256 s.
 </pre>
 </div>
 </div>
@@ -13932,7 +13936,7 @@ Elapsed: 1394.826 s.
 <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
 </div><div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
-<h2 id="8.-60A-80A-120A-circuits-(metadata-to-be-updated)">8. 60A-80A-120A circuits (metadata to be updated)<a class="anchor-link" href="#8.-60A-80A-120A-circuits-(metadata-to-be-updated)">&#182;</a></h2>
+<h2 id="8.-60A-80A-120A-circuits">8. 60A-80A-120A circuits<a class="anchor-link" href="#8.-60A-80A-120A-circuits">&#182;</a></h2>
 </div>
 </div>
 </div>
@@ -13950,7 +13954,7 @@ Elapsed: 1394.826 s.
 
 
 <div class="output_png output_subarea ">
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
 "
 >
 </div>
@@ -14001,6 +14005,9 @@ Elapsed: 1394.826 s.
 </div>
 <div class="cell border-box-sizing code_cell rendered">
 
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
 </div>
     </div>
   </div>
diff --git a/test/resources/reports/AN_PGC3.html b/test/resources/reports/AN_PGC3.html
index f56c4ace..01ac846d 100644
--- a/test/resources/reports/AN_PGC3.html
+++ b/test/resources/reports/AN_PGC3.html
@@ -13178,8 +13178,8 @@ Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdo
 
 
 <div class="output_subarea output_stream output_stdout output_text">
-<pre>Analysis executed with lhc-sm-api version: 1.5.18
-Analysis executed with lhc-sm-hwc notebooks version: 1.5.66
+<pre>Analysis executed with lhc-sm-api version: 1.5.19
+Analysis executed with lhc-sm-hwc notebooks version: 1.5.67
 user = root
 </pre>
 </div>
@@ -13360,9 +13360,9 @@ See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stab
 
 <div class="output_subarea output_stream output_stdout output_text">
 <pre>Circuit type SIGMON
-600A       47
+600A       49
 60A        94
-80-120A    16
+80-120A    18
 IPQ2        3
 IPQ4        1
 RB          1
@@ -13396,9 +13396,9 @@ Name: Circuit name, dtype: int64
 
 <div class="output_subarea output_stream output_stdout output_text">
 <pre>pgc_group
-pgc_120A    110
+pgc_120A    112
 pgc_13kA      3
-pgc_600A     47
+pgc_600A     49
 pgc_6kA       4
 Name: Circuit name, dtype: int64
 </pre>
@@ -13503,42 +13503,44 @@ Individualy powered circuits (IPQ, IPD)
 8 type = 600A , name = ROD.A34B2 , Imax = 590 , Imin = 0
 9 type = 600A , name = ROF.A34B1 , Imax = 590 , Imin = -39
 10 type = 600A , name = ROF.A34B2 , Imax = 590 , Imin = 0
-11 type = 600A , name = RQS.A34B2 , Imax = 550 , Imin = 0
-12 type = 600A , name = RQS.L4B1 , Imax = 550 , Imin = 0
-13 type = 600A , name = RQS.R3B1 , Imax = 550 , Imin = 0
-14 type = 600A , name = RQT12.L4B1 , Imax = 550 , Imin = 0
-15 type = 600A , name = RQT12.L4B2 , Imax = 550 , Imin = 0
-16 type = 600A , name = RQT12.R3B1 , Imax = 550 , Imin = 0
-17 type = 600A , name = RQT12.R3B2 , Imax = 550 , Imin = 0
-18 type = 600A , name = RQT13.L4B1 , Imax = 550 , Imin = 0
-19 type = 600A , name = RQT13.L4B2 , Imax = 550 , Imin = 0
-20 type = 600A , name = RQT13.R3B1 , Imax = 550 , Imin = 0
-21 type = 600A , name = RQT13.R3B2 , Imax = 550 , Imin = 0
-22 type = 600A , name = RQTD.A34B1 , Imax = 550 , Imin = 0
-23 type = 600A , name = RQTD.A34B2 , Imax = 550 , Imin = 0
-24 type = 600A , name = RQTF.A34B1 , Imax = 550 , Imin = 0
-25 type = 600A , name = RQTF.A34B2 , Imax = 550 , Imin = 0
-26 type = 600A , name = RQTL10.R3B1 , Imax = 450 , Imin = 0
-27 type = 600A , name = RQTL10.R3B2 , Imax = 450 , Imin = 0
-28 type = 600A , name = RQTL11.L4B1 , Imax = 550 , Imin = 0
-29 type = 600A , name = RQTL11.L4B2 , Imax = 550 , Imin = 0
-30 type = 600A , name = RQTL11.R3B1 , Imax = 500 , Imin = 0
-31 type = 600A , name = RQTL11.R3B2 , Imax = 500 , Imin = 0
-32 type = 600A , name = RQTL7.R3B1 , Imax = 550 , Imin = 0
-33 type = 600A , name = RQTL7.R3B2 , Imax = 550 , Imin = -1
-34 type = 600A , name = RQTL8.R3B1 , Imax = 550 , Imin = 0
-35 type = 600A , name = RQTL8.R3B2 , Imax = 550 , Imin = 0
-36 type = 600A , name = RQTL9.R3B1 , Imax = 450 , Imin = 0
-37 type = 600A , name = RQTL9.R3B2 , Imax = 425 , Imin = 0
-38 type = 600A , name = RSD1.A34B1 , Imax = 550 , Imin = 0
-39 type = 600A , name = RSD1.A34B2 , Imax = 550 , Imin = 0
-40 type = 600A , name = RSD2.A34B1 , Imax = 550 , Imin = 0
-41 type = 600A , name = RSD2.A34B2 , Imax = 550 , Imin = 0
-42 type = 600A , name = RSF1.A34B1 , Imax = 550 , Imin = 0
-43 type = 600A , name = RSF1.A34B2 , Imax = 550 , Imin = 0
-44 type = 600A , name = RSF2.A34B1 , Imax = 550 , Imin = 0
-45 type = 600A , name = RSF2.A34B2 , Imax = 550 , Imin = 0
-46 type = 600A , name = RSS.A34B2 , Imax = 200 , Imin = 0
+11 type = 600A , name = RQ6.R3B1 , Imax = 400 , Imin = 0
+12 type = 600A , name = RQ6.R3B2 , Imax = 400 , Imin = 0
+13 type = 600A , name = RQS.A34B2 , Imax = 550 , Imin = 0
+14 type = 600A , name = RQS.L4B1 , Imax = 550 , Imin = 0
+15 type = 600A , name = RQS.R3B1 , Imax = 550 , Imin = 0
+16 type = 600A , name = RQT12.L4B1 , Imax = 550 , Imin = 0
+17 type = 600A , name = RQT12.L4B2 , Imax = 550 , Imin = 0
+18 type = 600A , name = RQT12.R3B1 , Imax = 550 , Imin = 0
+19 type = 600A , name = RQT12.R3B2 , Imax = 550 , Imin = 0
+20 type = 600A , name = RQT13.L4B1 , Imax = 550 , Imin = 0
+21 type = 600A , name = RQT13.L4B2 , Imax = 550 , Imin = 0
+22 type = 600A , name = RQT13.R3B1 , Imax = 550 , Imin = 0
+23 type = 600A , name = RQT13.R3B2 , Imax = 550 , Imin = 0
+24 type = 600A , name = RQTD.A34B1 , Imax = 550 , Imin = 0
+25 type = 600A , name = RQTD.A34B2 , Imax = 550 , Imin = 0
+26 type = 600A , name = RQTF.A34B1 , Imax = 550 , Imin = 0
+27 type = 600A , name = RQTF.A34B2 , Imax = 550 , Imin = 0
+28 type = 600A , name = RQTL10.R3B1 , Imax = 450 , Imin = 0
+29 type = 600A , name = RQTL10.R3B2 , Imax = 450 , Imin = 0
+30 type = 600A , name = RQTL11.L4B1 , Imax = 550 , Imin = 0
+31 type = 600A , name = RQTL11.L4B2 , Imax = 550 , Imin = 0
+32 type = 600A , name = RQTL11.R3B1 , Imax = 500 , Imin = 0
+33 type = 600A , name = RQTL11.R3B2 , Imax = 500 , Imin = 0
+34 type = 600A , name = RQTL7.R3B1 , Imax = 550 , Imin = 0
+35 type = 600A , name = RQTL7.R3B2 , Imax = 550 , Imin = -1
+36 type = 600A , name = RQTL8.R3B1 , Imax = 550 , Imin = 0
+37 type = 600A , name = RQTL8.R3B2 , Imax = 550 , Imin = 0
+38 type = 600A , name = RQTL9.R3B1 , Imax = 450 , Imin = 0
+39 type = 600A , name = RQTL9.R3B2 , Imax = 425 , Imin = 0
+40 type = 600A , name = RSD1.A34B1 , Imax = 550 , Imin = 0
+41 type = 600A , name = RSD1.A34B2 , Imax = 550 , Imin = 0
+42 type = 600A , name = RSD2.A34B1 , Imax = 550 , Imin = 0
+43 type = 600A , name = RSD2.A34B2 , Imax = 550 , Imin = 0
+44 type = 600A , name = RSF1.A34B1 , Imax = 550 , Imin = 0
+45 type = 600A , name = RSF1.A34B2 , Imax = 550 , Imin = 0
+46 type = 600A , name = RSF2.A34B1 , Imax = 550 , Imin = 0
+47 type = 600A , name = RSF2.A34B2 , Imax = 550 , Imin = 0
+48 type = 600A , name = RSS.A34B2 , Imax = 200 , Imin = 0
 60A, 80A, 120A circuits
 1 type = 60A , name = RCBH11.L4B1 , Imax = 55 , Imin = 0
 2 type = 60A , name = RCBH11.R3B1 , Imax = 55 , Imin = 0
@@ -13636,21 +13638,23 @@ Individualy powered circuits (IPQ, IPD)
 94 type = 60A , name = RCBV34.L4B1 , Imax = 55 , Imin = 0
 95 type = 80-120A , name = RCBCH10.L4B2 , Imax = 100 , Imin = 0
 96 type = 80-120A , name = RCBCH10.R3B2 , Imax = 100 , Imin = 0
-97 type = 80-120A , name = RCBCH7.L4B1 , Imax = 100 , Imin = 0
-98 type = 80-120A , name = RCBCH7.R3B1 , Imax = 100 , Imin = 0
-99 type = 80-120A , name = RCBCH8.L4B2 , Imax = 100 , Imin = 0
-100 type = 80-120A , name = RCBCH8.R3B2 , Imax = 100 , Imin = 0
-101 type = 80-120A , name = RCBCH9.L4B1 , Imax = 100 , Imin = 0
-102 type = 80-120A , name = RCBCH9.R3B1 , Imax = 100 , Imin = 0
-103 type = 80-120A , name = RCBCV10.L4B1 , Imax = 100 , Imin = 0
-104 type = 80-120A , name = RCBCV10.R3B1 , Imax = 100 , Imin = 0
-105 type = 80-120A , name = RCBCV7.L4B2 , Imax = 100 , Imin = 0
-106 type = 80-120A , name = RCBCV7.R3B2 , Imax = 100 , Imin = 0
-107 type = 80-120A , name = RCBCV8.L4B1 , Imax = 100 , Imin = 0
-108 type = 80-120A , name = RCBCV8.R3B1 , Imax = 100 , Imin = 0
-109 type = 80-120A , name = RCBCV9.L4B2 , Imax = 100 , Imin = 0
-110 type = 80-120A , name = RCBCV9.R3B2 , Imax = 100 , Imin = 0
-Elapsed: 535.288 s.
+97 type = 80-120A , name = RCBCH6.R3B2 , Imax = 80 , Imin = 0
+98 type = 80-120A , name = RCBCH7.L4B1 , Imax = 100 , Imin = 0
+99 type = 80-120A , name = RCBCH7.R3B1 , Imax = 100 , Imin = 0
+100 type = 80-120A , name = RCBCH8.L4B2 , Imax = 100 , Imin = 0
+101 type = 80-120A , name = RCBCH8.R3B2 , Imax = 100 , Imin = 0
+102 type = 80-120A , name = RCBCH9.L4B1 , Imax = 100 , Imin = 0
+103 type = 80-120A , name = RCBCH9.R3B1 , Imax = 100 , Imin = 0
+104 type = 80-120A , name = RCBCV10.L4B1 , Imax = 100 , Imin = 0
+105 type = 80-120A , name = RCBCV10.R3B1 , Imax = 100 , Imin = 0
+106 type = 80-120A , name = RCBCV6.R3B1 , Imax = 80 , Imin = 0
+107 type = 80-120A , name = RCBCV7.L4B2 , Imax = 100 , Imin = 0
+108 type = 80-120A , name = RCBCV7.R3B2 , Imax = 100 , Imin = 0
+109 type = 80-120A , name = RCBCV8.L4B1 , Imax = 100 , Imin = 0
+110 type = 80-120A , name = RCBCV8.R3B1 , Imax = 100 , Imin = 0
+111 type = 80-120A , name = RCBCV9.L4B2 , Imax = 100 , Imin = 0
+112 type = 80-120A , name = RCBCV9.R3B2 , Imax = 100 , Imin = 0
+Elapsed: 1160.752 s.
 </pre>
 </div>
 </div>
@@ -13835,7 +13839,7 @@ Elapsed: 535.288 s.
 
 
 <div class="output_png output_subarea ">
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 >
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diff --git a/test/resources/reports/AN_PGC4.html b/test/resources/reports/AN_PGC4.html
index 69e5e84e..d21dcffa 100644
--- a/test/resources/reports/AN_PGC4.html
+++ b/test/resources/reports/AN_PGC4.html
@@ -13178,8 +13178,8 @@ Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdo
 
 
 <div class="output_subarea output_stream output_stdout output_text">
-<pre>Analysis executed with lhc-sm-api version: 1.5.18
-Analysis executed with lhc-sm-hwc notebooks version: 1.5.66
+<pre>Analysis executed with lhc-sm-api version: 1.5.19
+Analysis executed with lhc-sm-hwc notebooks version: 1.5.67
 user = root
 </pre>
 </div>
@@ -13756,7 +13756,7 @@ Powering current is too low
 Powering current is too low
 110 type = 80-120A , name = RCBCV9.R4B1 , Imax = 0 , Imin = 0
 Powering current is too low
-Elapsed: 1679.096 s.
+Elapsed: 780.004 s.
 </pre>
 </div>
 </div>
@@ -14852,7 +14852,7 @@ Elapsed: 1679.096 s.
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 </div><div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
-<h2 id="8.-60A-80A-120A-circuits-(metadata-to-be-updated)">8. 60A-80A-120A circuits (metadata to be updated)<a class="anchor-link" href="#8.-60A-80A-120A-circuits-(metadata-to-be-updated)">&#182;</a></h2>
+<h2 id="8.-60A-80A-120A-circuits">8. 60A-80A-120A circuits<a class="anchor-link" href="#8.-60A-80A-120A-circuits">&#182;</a></h2>
 </div>
 </div>
 </div>
@@ -14870,7 +14870,7 @@ Elapsed: 1679.096 s.
 
 
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
 "
 >
 </div>
@@ -14921,6 +14921,9 @@ Elapsed: 1679.096 s.
 </div>
 <div class="cell border-box-sizing code_cell rendered">
 
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
 </div>
     </div>
   </div>
-- 
GitLab


From af754666ffac1c70148d055fee2ad14dee9c6735 Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Mon, 21 Feb 2022 15:23:07 +0100
Subject: [PATCH 37/44] [SIGMON-315] value_max instead of max_value

---
 rq/AN_RQ_PNO.b3.ipynb | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/rq/AN_RQ_PNO.b3.ipynb b/rq/AN_RQ_PNO.b3.ipynb
index 483bbd07..47fb6cfb 100644
--- a/rq/AN_RQ_PNO.b3.ipynb
+++ b/rq/AN_RQ_PNO.b3.ipynb
@@ -679,7 +679,7 @@
    "source": [
     "if t_pnob3 > 1800 and not res_busbar_rqd_df.empty:\n",
     "    title = '%s, %s: %s-%s' % (circuit_names[0], hwc_test, Time.to_string(t_start).split('.')[0], Time.to_string(t_end).split('.')[0])\n",
-    "    res_busbar_rqd_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_busbar_rqd_df, signal_name='R_RES', max_value=10e-9, title=title)"
+    "    res_busbar_rqd_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_busbar_rqd_df, signal_name='R_RES', value_max=10e-9, title=title)"
    ]
   },
   {
@@ -722,7 +722,7 @@
    "source": [
     "if t_pnob3 > 1800 and not res_busbar_rqf_df.empty:\n",
     "    title = '%s, %s: %s-%s' % (circuit_names[1], hwc_test, Time.to_string(t_start).split('.')[0], Time.to_string(t_end).split('.')[0])\n",
-    "    res_busbar_rqf_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_busbar_rqf_df, signal_name='R_RES', max_value=10e-9, title=title)"
+    "    res_busbar_rqf_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_busbar_rqf_df, signal_name='R_RES', value_max=10e-9, title=title)"
    ]
   },
   {
@@ -787,7 +787,7 @@
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqd_df.empty:\n",
     "    title = '%s, %s: %s-%s' % (circuit_names[0], hwc_test, Time.to_string(t_start).split('.')[0], Time.to_string(t_end).split('.')[0])\n",
-    "    res_magnet_rqd_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_magnet_rqd_df, signal_name='R_MAG', max_value=50e-9, title=title)"
+    "    res_magnet_rqd_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_magnet_rqd_df, signal_name='R_MAG', value_max=50e-9, title=title)"
    ]
   },
   {
@@ -829,7 +829,7 @@
    "outputs": [],
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqf_df.empty:\n",
-    "    res_magnet_rqf_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_magnet_rqf_df, signal_name='R_MAG', max_value=50e-9)"
+    "    res_magnet_rqf_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_magnet_rqf_df, signal_name='R_MAG', value_max=50e-9)"
    ]
   },
   {
-- 
GitLab


From 873633ddf85bb8dd54cc14a417435ebdd6f19eb1 Mon Sep 17 00:00:00 2001
From: agchadaj <agata.chadaj@cern.ch>
Date: Mon, 21 Feb 2022 16:12:53 +0100
Subject: [PATCH 38/44] updated reference notebook

---
 test/resources/notebooks/result_AN_PGC2.ipynb | 613 +++++++++---------
 test/resources/reports/AN_PGC2.html           |  13 +-
 2 files changed, 319 insertions(+), 307 deletions(-)

diff --git a/test/resources/notebooks/result_AN_PGC2.ipynb b/test/resources/notebooks/result_AN_PGC2.ipynb
index 83e58625..def5e2d9 100644
--- a/test/resources/notebooks/result_AN_PGC2.ipynb
+++ b/test/resources/notebooks/result_AN_PGC2.ipynb
@@ -3,19 +3,19 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "1acbdec7",
+   "id": "f2d90039",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:01.433663Z",
-     "iopub.status.busy": "2022-01-11T13:21:01.432937Z",
-     "iopub.status.idle": "2022-01-11T13:21:37.297625Z",
-     "shell.execute_reply": "2022-01-11T13:21:37.296840Z"
+     "iopub.execute_input": "2022-02-21T14:28:29.053252Z",
+     "iopub.status.busy": "2022-02-21T14:28:29.052844Z",
+     "iopub.status.idle": "2022-02-21T14:29:43.618800Z",
+     "shell.execute_reply": "2022-02-21T14:29:43.617715Z"
     },
     "papermill": {
-     "duration": 35.919509,
-     "end_time": "2022-01-11T13:21:37.297858",
+     "duration": 74.628722,
+     "end_time": "2022-02-21T14:29:43.622644",
      "exception": false,
-     "start_time": "2022-01-11T13:21:01.378349",
+     "start_time": "2022-02-21T14:28:28.993922",
      "status": "completed"
     }
    },
@@ -73,10 +73,10 @@
    "id": "d4fa8158",
    "metadata": {
     "papermill": {
-     "duration": 0.042539,
-     "end_time": "2022-01-11T13:21:37.383334",
+     "duration": 0.042741,
+     "end_time": "2022-02-21T14:29:43.710319",
      "exception": false,
-     "start_time": "2022-01-11T13:21:37.340795",
+     "start_time": "2022-02-21T14:29:43.667578",
      "status": "completed"
     },
     "tags": []
@@ -90,10 +90,10 @@
    "id": "be33bf4d",
    "metadata": {
     "papermill": {
-     "duration": 0.041248,
-     "end_time": "2022-01-11T13:21:37.466274",
+     "duration": 0.041436,
+     "end_time": "2022-02-21T14:29:43.793202",
      "exception": false,
-     "start_time": "2022-01-11T13:21:37.425026",
+     "start_time": "2022-02-21T14:29:43.751766",
      "status": "completed"
     },
     "tags": []
@@ -145,10 +145,10 @@
    "id": "d26587dd",
    "metadata": {
     "papermill": {
-     "duration": 0.040496,
-     "end_time": "2022-01-11T13:21:37.547783",
+     "duration": 0.041536,
+     "end_time": "2022-02-21T14:29:43.876589",
      "exception": false,
-     "start_time": "2022-01-11T13:21:37.507287",
+     "start_time": "2022-02-21T14:29:43.835053",
      "status": "completed"
     },
     "tags": []
@@ -163,16 +163,16 @@
    "id": "fde333a7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:37.636790Z",
-     "iopub.status.busy": "2022-01-11T13:21:37.636104Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.108523Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.107809Z"
+     "iopub.execute_input": "2022-02-21T14:29:43.963759Z",
+     "iopub.status.busy": "2022-02-21T14:29:43.963422Z",
+     "iopub.status.idle": "2022-02-21T14:29:47.661995Z",
+     "shell.execute_reply": "2022-02-21T14:29:47.661036Z"
     },
     "papermill": {
-     "duration": 2.520429,
-     "end_time": "2022-01-11T13:21:40.108682",
+     "duration": 3.745987,
+     "end_time": "2022-02-21T14:29:47.664247",
      "exception": false,
-     "start_time": "2022-01-11T13:21:37.588253",
+     "start_time": "2022-02-21T14:29:43.918260",
      "status": "completed"
     },
     "tags": []
@@ -224,16 +224,16 @@
    "id": "26e33716",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.198879Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.198211Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.202524Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.201633Z"
+     "iopub.execute_input": "2022-02-21T14:29:47.754469Z",
+     "iopub.status.busy": "2022-02-21T14:29:47.754127Z",
+     "iopub.status.idle": "2022-02-21T14:29:47.760005Z",
+     "shell.execute_reply": "2022-02-21T14:29:47.759020Z"
     },
     "papermill": {
-     "duration": 0.052074,
-     "end_time": "2022-01-11T13:21:40.202678",
+     "duration": 0.054009,
+     "end_time": "2022-02-21T14:29:47.762128",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.150604",
+     "start_time": "2022-02-21T14:29:47.708119",
      "status": "completed"
     },
     "tags": []
@@ -243,8 +243,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Analysis executed with lhc-sm-api version: 1.5.18\n",
-      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.66\n",
+      "Analysis executed with lhc-sm-api version: 1.5.19\n",
+      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.67\n",
       "user = root\n"
      ]
     }
@@ -263,16 +263,16 @@
    "id": "dbccfe24",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.295503Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.294785Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.300948Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.300347Z"
+     "iopub.execute_input": "2022-02-21T14:29:47.851003Z",
+     "iopub.status.busy": "2022-02-21T14:29:47.850664Z",
+     "iopub.status.idle": "2022-02-21T14:29:47.859107Z",
+     "shell.execute_reply": "2022-02-21T14:29:47.858271Z"
     },
     "papermill": {
-     "duration": 0.05627,
-     "end_time": "2022-01-11T13:21:40.301111",
+     "duration": 0.056114,
+     "end_time": "2022-02-21T14:29:47.861337",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.244841",
+     "start_time": "2022-02-21T14:29:47.805223",
      "status": "completed"
     },
     "tags": []
@@ -289,10 +289,10 @@
    "id": "934f6604",
    "metadata": {
     "papermill": {
-     "duration": 0.043177,
-     "end_time": "2022-01-11T13:21:40.386618",
+     "duration": 0.042972,
+     "end_time": "2022-02-21T14:29:47.948059",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.343441",
+     "start_time": "2022-02-21T14:29:47.905087",
      "status": "completed"
     },
     "tags": []
@@ -306,10 +306,10 @@
    "id": "71f0b615",
    "metadata": {
     "papermill": {
-     "duration": 0.04275,
-     "end_time": "2022-01-11T13:21:40.472164",
+     "duration": 0.042977,
+     "end_time": "2022-02-21T14:29:48.034988",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.429414",
+     "start_time": "2022-02-21T14:29:47.992011",
      "status": "completed"
     },
     "tags": []
@@ -325,16 +325,16 @@
    "id": "0aebdd20",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.564815Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.564101Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.570036Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.569261Z"
+     "iopub.execute_input": "2022-02-21T14:29:48.123277Z",
+     "iopub.status.busy": "2022-02-21T14:29:48.122949Z",
+     "iopub.status.idle": "2022-02-21T14:29:48.127193Z",
+     "shell.execute_reply": "2022-02-21T14:29:48.126461Z"
     },
     "papermill": {
-     "duration": 0.055293,
-     "end_time": "2022-01-11T13:21:40.570201",
+     "duration": 0.051207,
+     "end_time": "2022-02-21T14:29:48.129250",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.514908",
+     "start_time": "2022-02-21T14:29:48.078043",
      "status": "completed"
     },
     "tags": [
@@ -343,25 +343,30 @@
    },
    "outputs": [],
    "source": [
-    "#User input from ACCTESTING\n"
+    "#User input from ACCTESTING\n",
+    "hwc_test = 'PGC.2'\n",
+    "circuit_name = 'RB.A78'\n",
+    "campaign = 'Recommissioning post LS2 - YETS'\n",
+    "t_start = '2021-11-24 07:10:00.628000000'\n",
+    "t_end = '2021-11-24 08:18:00.640000000'"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "d50e8efa",
+   "id": "f03a5714",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.668153Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.667376Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.670983Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.670184Z"
+     "iopub.execute_input": "2022-02-21T14:29:48.368457Z",
+     "iopub.status.busy": "2022-02-21T14:29:48.368121Z",
+     "iopub.status.idle": "2022-02-21T14:29:48.377394Z",
+     "shell.execute_reply": "2022-02-21T14:29:48.376417Z"
     },
     "papermill": {
-     "duration": 0.056984,
-     "end_time": "2022-01-11T13:21:40.671164",
+     "duration": 0.058471,
+     "end_time": "2022-02-21T14:29:48.380204",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.614180",
+     "start_time": "2022-02-21T14:29:48.321733",
      "status": "completed"
     },
     "tags": [
@@ -389,16 +394,16 @@
    "id": "82eacd19",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.766961Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.766245Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.770842Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.770141Z"
+     "iopub.execute_input": "2022-02-21T14:29:48.471764Z",
+     "iopub.status.busy": "2022-02-21T14:29:48.471449Z",
+     "iopub.status.idle": "2022-02-21T14:29:48.483248Z",
+     "shell.execute_reply": "2022-02-21T14:29:48.479114Z"
     },
     "papermill": {
-     "duration": 0.054755,
-     "end_time": "2022-01-11T13:21:40.771010",
+     "duration": 0.061208,
+     "end_time": "2022-02-21T14:29:48.485560",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.716255",
+     "start_time": "2022-02-21T14:29:48.424352",
      "status": "completed"
     },
     "tags": []
@@ -425,10 +430,10 @@
    "id": "43db2efd",
    "metadata": {
     "papermill": {
-     "duration": 0.044899,
-     "end_time": "2022-01-11T13:21:40.861412",
+     "duration": 0.057988,
+     "end_time": "2022-02-21T14:29:48.589814",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.816513",
+     "start_time": "2022-02-21T14:29:48.531826",
      "status": "completed"
     },
     "tags": []
@@ -443,18 +448,19 @@
    "id": "a53cd810",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:40.958245Z",
-     "iopub.status.busy": "2022-01-11T13:21:40.957537Z",
-     "iopub.status.idle": "2022-01-11T13:21:40.984196Z",
-     "shell.execute_reply": "2022-01-11T13:21:40.983440Z"
+     "iopub.execute_input": "2022-02-21T14:29:48.687423Z",
+     "iopub.status.busy": "2022-02-21T14:29:48.687031Z",
+     "iopub.status.idle": "2022-02-21T14:29:48.721241Z",
+     "shell.execute_reply": "2022-02-21T14:29:48.711339Z"
     },
     "papermill": {
-     "duration": 0.07859,
-     "end_time": "2022-01-11T13:21:40.984356",
+     "duration": 0.086904,
+     "end_time": "2022-02-21T14:29:48.724837",
      "exception": false,
-     "start_time": "2022-01-11T13:21:40.905766",
+     "start_time": "2022-02-21T14:29:48.637933",
      "status": "completed"
     },
+    "scrolled": false,
     "tags": []
    },
    "outputs": [
@@ -472,9 +478,9 @@
     "lhc_circuit = meta_df[lambda x: x['Circuit name'] == circuit_name]\n",
     "\n",
     "safety_subsector = lhc_circuit.iloc[0]['Safety subsector name']\n",
-    "lhc_circuits = meta_df[lambda x: x['Safety subsector name'] == safety_subsector]\n",
+    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))\n",
     "\n",
-    "print('Safety subsector name = \\'%s\\'' % (safety_subsector))"
+    "lhc_circuits = meta_df[meta_df['Safety subsector name'].str.contains(safety_subsector)]"
    ]
   },
   {
@@ -482,10 +488,10 @@
    "id": "9e8d59de",
    "metadata": {
     "papermill": {
-     "duration": 0.045425,
-     "end_time": "2022-01-11T13:21:41.075119",
+     "duration": 0.047239,
+     "end_time": "2022-02-21T14:29:48.818910",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.029694",
+     "start_time": "2022-02-21T14:29:48.771671",
      "status": "completed"
     },
     "tags": []
@@ -501,16 +507,16 @@
    "id": "9a02e5a1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.185245Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.184520Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.196617Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.197133Z"
+     "iopub.execute_input": "2022-02-21T14:29:48.913835Z",
+     "iopub.status.busy": "2022-02-21T14:29:48.913505Z",
+     "iopub.status.idle": "2022-02-21T14:29:48.930211Z",
+     "shell.execute_reply": "2022-02-21T14:29:48.929246Z"
     },
     "papermill": {
-     "duration": 0.076538,
-     "end_time": "2022-01-11T13:21:41.197318",
+     "duration": 0.066762,
+     "end_time": "2022-02-21T14:29:48.932229",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.120780",
+     "start_time": "2022-02-21T14:29:48.865467",
      "status": "completed"
     },
     "tags": []
@@ -540,8 +546,8 @@
     "    t_end = Time.to_string_short((Time.to_unix_timestamp(t_start) + (5 * 60) * 1e9))\n",
     "t_end_sec = int((Time.to_unix_timestamp(t_end) - Time.to_unix_timestamp(t_start))*1e-9)\n",
     "#\n",
-    "t_start_utc = Time.to_string_short((Time.to_unix_timestamp(t_start) - 2 * 3600 * 1e9))\n",
-    "t_end_utc = Time.to_string_short((Time.to_unix_timestamp(t_end) - 2 * 3600 * 1e9))\n",
+    "t_start_timestamp = Time.to_unix_timestamp(t_start)\n",
+    "t_end_timestamp = Time.to_unix_timestamp(t_end)\n",
     "#\n",
     "print('hwc_test = \\'%s\\'\\ncircuit_name = \\'%s\\'\\ncampaign = \\'%s\\'\\nt_start = \\'%s\\'\\nt_end = \\'%s\\'\\nt_end_sec = \\'%s\\'' % (hwc_test, circuit_name, campaign, t_start, t_end, t_end_sec))"
    ]
@@ -551,10 +557,10 @@
    "id": "89e0a93f",
    "metadata": {
     "papermill": {
-     "duration": 0.044401,
-     "end_time": "2022-01-11T13:21:41.286801",
+     "duration": 0.046839,
+     "end_time": "2022-02-21T14:29:49.033024",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.242400",
+     "start_time": "2022-02-21T14:29:48.986185",
      "status": "completed"
     },
     "tags": []
@@ -569,16 +575,16 @@
    "id": "3f1c0a0c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.382568Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.381889Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.383878Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.384503Z"
+     "iopub.execute_input": "2022-02-21T14:29:49.128773Z",
+     "iopub.status.busy": "2022-02-21T14:29:49.128444Z",
+     "iopub.status.idle": "2022-02-21T14:29:49.134047Z",
+     "shell.execute_reply": "2022-02-21T14:29:49.133183Z"
     },
     "papermill": {
-     "duration": 0.052671,
-     "end_time": "2022-01-11T13:21:41.384678",
+     "duration": 0.057054,
+     "end_time": "2022-02-21T14:29:49.136741",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.332007",
+     "start_time": "2022-02-21T14:29:49.079687",
      "status": "completed"
     },
     "tags": []
@@ -597,16 +603,16 @@
    "id": "0046420e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.481135Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.480439Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.482321Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.482958Z"
+     "iopub.execute_input": "2022-02-21T14:29:49.232491Z",
+     "iopub.status.busy": "2022-02-21T14:29:49.232162Z",
+     "iopub.status.idle": "2022-02-21T14:29:49.239180Z",
+     "shell.execute_reply": "2022-02-21T14:29:49.238363Z"
     },
     "papermill": {
-     "duration": 0.053824,
-     "end_time": "2022-01-11T13:21:41.483148",
+     "duration": 0.057005,
+     "end_time": "2022-02-21T14:29:49.241190",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.429324",
+     "start_time": "2022-02-21T14:29:49.184185",
      "status": "completed"
     },
     "tags": []
@@ -633,16 +639,16 @@
    "id": "861b26fd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.587115Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.586435Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.612663Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.614424Z"
+     "iopub.execute_input": "2022-02-21T14:29:49.339884Z",
+     "iopub.status.busy": "2022-02-21T14:29:49.339565Z",
+     "iopub.status.idle": "2022-02-21T14:29:49.375548Z",
+     "shell.execute_reply": "2022-02-21T14:29:49.361449Z"
     },
     "papermill": {
-     "duration": 0.086626,
-     "end_time": "2022-01-11T13:21:41.614617",
+     "duration": 0.092374,
+     "end_time": "2022-02-21T14:29:49.381657",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.527991",
+     "start_time": "2022-02-21T14:29:49.289283",
      "status": "completed"
     },
     "scrolled": false,
@@ -662,8 +668,7 @@
     }
    ],
    "source": [
-    "lhc_circuits['pgc_group'] = lhc_circuits.apply(f, axis=1)\n",
-    "#display(lhc_circuits)"
+    "lhc_circuits['pgc_group'] = lhc_circuits.apply(f, axis=1)"
    ]
   },
   {
@@ -671,10 +676,10 @@
    "id": "b4b1b07b",
    "metadata": {
     "papermill": {
-     "duration": 0.045646,
-     "end_time": "2022-01-11T13:21:41.705949",
+     "duration": 0.046826,
+     "end_time": "2022-02-21T14:29:49.475676",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.660303",
+     "start_time": "2022-02-21T14:29:49.428850",
      "status": "completed"
     },
     "tags": []
@@ -689,16 +694,16 @@
    "id": "e9c0a0c7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:41.814240Z",
-     "iopub.status.busy": "2022-01-11T13:21:41.813554Z",
-     "iopub.status.idle": "2022-01-11T13:21:41.828125Z",
-     "shell.execute_reply": "2022-01-11T13:21:41.827210Z"
+     "iopub.execute_input": "2022-02-21T14:29:49.572328Z",
+     "iopub.status.busy": "2022-02-21T14:29:49.571982Z",
+     "iopub.status.idle": "2022-02-21T14:29:49.590545Z",
+     "shell.execute_reply": "2022-02-21T14:29:49.588441Z"
     },
     "papermill": {
-     "duration": 0.075654,
-     "end_time": "2022-01-11T13:21:41.828283",
+     "duration": 0.070881,
+     "end_time": "2022-02-21T14:29:49.593325",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.752629",
+     "start_time": "2022-02-21T14:29:49.522444",
      "status": "completed"
     },
     "tags": []
@@ -729,10 +734,10 @@
    "id": "06be7d04",
    "metadata": {
     "papermill": {
-     "duration": 0.046199,
-     "end_time": "2022-01-11T13:21:41.921115",
+     "duration": 0.048897,
+     "end_time": "2022-02-21T14:29:49.689813",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.874916",
+     "start_time": "2022-02-21T14:29:49.640916",
      "status": "completed"
     },
     "tags": []
@@ -747,16 +752,16 @@
    "id": "26b23285",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:42.021321Z",
-     "iopub.status.busy": "2022-01-11T13:21:42.020044Z",
-     "iopub.status.idle": "2022-01-11T13:21:42.024178Z",
-     "shell.execute_reply": "2022-01-11T13:21:42.024670Z"
+     "iopub.execute_input": "2022-02-21T14:29:49.788545Z",
+     "iopub.status.busy": "2022-02-21T14:29:49.788179Z",
+     "iopub.status.idle": "2022-02-21T14:29:49.795804Z",
+     "shell.execute_reply": "2022-02-21T14:29:49.794876Z"
     },
     "papermill": {
-     "duration": 0.057636,
-     "end_time": "2022-01-11T13:21:42.024858",
+     "duration": 0.059413,
+     "end_time": "2022-02-21T14:29:49.797890",
      "exception": false,
-     "start_time": "2022-01-11T13:21:41.967222",
+     "start_time": "2022-02-21T14:29:49.738477",
      "status": "completed"
     },
     "tags": []
@@ -784,10 +789,10 @@
    "id": "da308838",
    "metadata": {
     "papermill": {
-     "duration": 0.047128,
-     "end_time": "2022-01-11T13:21:42.118606",
+     "duration": 0.047685,
+     "end_time": "2022-02-21T14:29:49.893597",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.071478",
+     "start_time": "2022-02-21T14:29:49.845912",
      "status": "completed"
     },
     "tags": []
@@ -801,10 +806,10 @@
    "id": "a8fd31e4",
    "metadata": {
     "papermill": {
-     "duration": 0.047327,
-     "end_time": "2022-01-11T13:21:42.212901",
+     "duration": 0.048207,
+     "end_time": "2022-02-21T14:29:49.989511",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.165574",
+     "start_time": "2022-02-21T14:29:49.941304",
      "status": "completed"
     },
     "tags": []
@@ -822,16 +827,16 @@
    "id": "0144af59",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:42.316506Z",
-     "iopub.status.busy": "2022-01-11T13:21:42.315795Z",
-     "iopub.status.idle": "2022-01-11T13:21:42.319856Z",
-     "shell.execute_reply": "2022-01-11T13:21:42.319187Z"
+     "iopub.execute_input": "2022-02-21T14:29:50.087634Z",
+     "iopub.status.busy": "2022-02-21T14:29:50.087259Z",
+     "iopub.status.idle": "2022-02-21T14:29:50.097362Z",
+     "shell.execute_reply": "2022-02-21T14:29:50.096502Z"
     },
     "papermill": {
-     "duration": 0.060124,
-     "end_time": "2022-01-11T13:21:42.320012",
+     "duration": 0.061671,
+     "end_time": "2022-02-21T14:29:50.099354",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.259888",
+     "start_time": "2022-02-21T14:29:50.037683",
      "status": "completed"
     },
     "tags": []
@@ -860,7 +865,6 @@
     }
    ],
    "source": [
-    "#condemned_circuits = ['RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCSX3.L2', 'RCTX3.L2', 'RSS.A34B1']\n",
     "condemned_circuits = ['RCO.A78B1', 'RCO.A78B2', 'RCO.A12B1', 'RCO.A45B1', 'RSS.A34B1', 'RCBXH1.L2', 'RCOSX3.L2', 'RCOX3.L2', 'RCSSX3.L2', 'RCOSX3.L1', 'RCBH31.R7B1', 'RCBV26.R5B1', 'RCBH11.R1B1']\n",
     "display(condemned_circuits)"
    ]
@@ -870,10 +874,10 @@
    "id": "53a76bfc",
    "metadata": {
     "papermill": {
-     "duration": 0.047494,
-     "end_time": "2022-01-11T13:21:42.546681",
+     "duration": 0.048703,
+     "end_time": "2022-02-21T14:29:50.196753",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.499187",
+     "start_time": "2022-02-21T14:29:50.148050",
      "status": "completed"
     },
     "tags": []
@@ -888,16 +892,16 @@
    "id": "86df2e5a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:21:42.692023Z",
-     "iopub.status.busy": "2022-01-11T13:21:42.689200Z",
-     "iopub.status.idle": "2022-01-11T13:27:49.226183Z",
-     "shell.execute_reply": "2022-01-11T13:27:49.226777Z"
+     "iopub.execute_input": "2022-02-21T14:29:50.297908Z",
+     "iopub.status.busy": "2022-02-21T14:29:50.297562Z",
+     "iopub.status.idle": "2022-02-21T14:35:05.181265Z",
+     "shell.execute_reply": "2022-02-21T14:35:05.180334Z"
     },
     "papermill": {
-     "duration": 366.632603,
-     "end_time": "2022-01-11T13:27:49.227118",
+     "duration": 314.938554,
+     "end_time": "2022-02-21T14:35:05.183739",
      "exception": false,
-     "start_time": "2022-01-11T13:21:42.594515",
+     "start_time": "2022-02-21T14:29:50.245185",
      "status": "completed"
     },
     "scrolled": false,
@@ -2010,7 +2014,7 @@
      "output_type": "stream",
      "text": [
       "107 type = 80-120A , name = RCBCV9.R5B2 , Imax = 100 , Imin = 0\n",
-      "Elapsed: 366.528 s.\n"
+      "Elapsed: 314.832 s.\n"
      ]
     }
    ],
@@ -2126,11 +2130,9 @@
     "                    .with_metadata(circuit_name=circuit_name, system='PC', source='*') \\\n",
     "                    .event_query().df\n",
     "                if source_timestamp_fgc_df_i.empty == False: source_timestamp_fgc_600A_df = pd.concat([source_timestamp_fgc_600A_df, source_timestamp_fgc_df_i], ignore_index=True)                                            \n",
-    "                #j = j + 1\n",
     "        i = i + 1\n",
     "    #\n",
     "    print('60A, 80A, 120A circuits')\n",
-    "    # to be updated to metadata\n",
     "    i = j = 0\n",
     "    i_meas_120A_dfs = []\n",
     "    source_timestamp_fgc_120A_df = pd.DataFrame()\n",
@@ -2140,29 +2142,19 @@
     "            if circuit_type in pgc_120A:\n",
     "                j = j + 1\n",
     "                #print(j, circuit_type, circuit_name)\n",
-    "                df1 = DataQuery.builder(spark).byVariables() \\\n",
-    "                    .system('CMW') \\\n",
-    "                    .startTime(t_start_utc).endTime(t_end_utc) \\\n",
-    "                    .variableLike('%' + circuit_name + ':I_MEAS') \\\n",
-    "                    .buildDataset()\n",
-    "                i_meas_df = df1.select('nxcals_timestamp', 'nxcals_value').sort('nxcals_timestamp').toPandas()\n",
-    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['nxcals_value'].max()), ', Imin =', int(i_meas_df['nxcals_value'].min()))\n",
-    "                if (int(i_meas_df['nxcals_value'].max()) - int(i_meas_df['nxcals_value'].min())) < 10:\n",
-    "                    print('Powering current is too low')\n",
-    "                i_meas_df.rename(columns={'nxcals_timestamp': 'timestamp', 'nxcals_value': circuit_name + ':I_MEAS'}, inplace=True)\n",
-    "                t0 = i_meas_df['timestamp'].loc[0]\n",
-    "                i_meas_df['time'] = (i_meas_df['timestamp'] - t0)*1e-9\n",
-    "                i_meas_df.set_index('time', inplace = True)\n",
-    "                i_meas_df = i_meas_df.drop('timestamp', 1)\n",
-    "#                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
-    "#                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
-    "#                    .with_circuit_type(circuit_type) \\\n",
-    "#                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
-    "#                    .signal_query() \\\n",
-    "#                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
-    "#                    .convert_index_to_sec().dfs[0]\n",
-    "#                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
+    "                i_meas_df = QueryBuilder().with_nxcals(spark) \\\n",
+    "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
+    "                    .with_circuit_type(circuit_type) \\\n",
+    "                    .with_metadata(circuit_name=circuit_name, system='PC', signal='I_MEAS') \\\n",
+    "                    .signal_query() \\\n",
+    "                    .synchronize_time(Time.to_unix_timestamp(t_start)) \\\n",
+    "                    .convert_index_to_sec().dfs[0]\n",
+    "                print(j, 'type =', circuit_type, ', name =', circuit_name, ', Imax =', int(i_meas_df['I_MEAS'].max()), ', Imin =', int(i_meas_df['I_MEAS'].min()))\n",
+    "                if (int(i_meas_df['I_MEAS'].max()) - int(i_meas_df['I_MEAS'].min())) < 10:\n",
+    "                     print('Powering current is too low')\n",
+    "                i_meas_df.rename(columns = {'I_MEAS': circuit_name + ':I_MEAS'}, inplace = True)\n",
     "                i_meas_120A_dfs.append(i_meas_df)\n",
+    "\n",
     "                source_timestamp_fgc_df_i = QueryBuilder().with_pm() \\\n",
     "                    .with_duration(t_start=t_start, t_end=t_end) \\\n",
     "                    .with_circuit_type(circuit_type) \\\n",
@@ -2178,10 +2170,10 @@
    "id": "47dfeb05",
    "metadata": {
     "papermill": {
-     "duration": 0.113408,
-     "end_time": "2022-01-11T13:27:49.457461",
+     "duration": 0.127494,
+     "end_time": "2022-02-21T14:35:05.436653",
      "exception": false,
-     "start_time": "2022-01-11T13:27:49.344053",
+     "start_time": "2022-02-21T14:35:05.309159",
      "status": "completed"
     },
     "tags": []
@@ -2196,16 +2188,16 @@
    "id": "03ee8447",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:49.698320Z",
-     "iopub.status.busy": "2022-01-11T13:27:49.697655Z",
-     "iopub.status.idle": "2022-01-11T13:27:50.167412Z",
-     "shell.execute_reply": "2022-01-11T13:27:50.163813Z"
+     "iopub.execute_input": "2022-02-21T14:35:05.697697Z",
+     "iopub.status.busy": "2022-02-21T14:35:05.697348Z",
+     "iopub.status.idle": "2022-02-21T14:35:06.194932Z",
+     "shell.execute_reply": "2022-02-21T14:35:06.193953Z"
     },
     "papermill": {
-     "duration": 0.596079,
-     "end_time": "2022-01-11T13:27:50.167577",
+     "duration": 0.630463,
+     "end_time": "2022-02-21T14:35:06.197418",
      "exception": false,
-     "start_time": "2022-01-11T13:27:49.571498",
+     "start_time": "2022-02-21T14:35:05.566955",
      "status": "completed"
     },
     "scrolled": false,
@@ -2254,10 +2246,10 @@
    "id": "9afe590a",
    "metadata": {
     "papermill": {
-     "duration": 0.113325,
-     "end_time": "2022-01-11T13:27:50.395361",
+     "duration": 0.12242,
+     "end_time": "2022-02-21T14:35:06.438909",
      "exception": false,
-     "start_time": "2022-01-11T13:27:50.282036",
+     "start_time": "2022-02-21T14:35:06.316489",
      "status": "completed"
     },
     "tags": []
@@ -2272,16 +2264,16 @@
    "id": "b7a1e51a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:50.644789Z",
-     "iopub.status.busy": "2022-01-11T13:27:50.642880Z",
-     "iopub.status.idle": "2022-01-11T13:27:51.281196Z",
-     "shell.execute_reply": "2022-01-11T13:27:51.281728Z"
+     "iopub.execute_input": "2022-02-21T14:35:06.682601Z",
+     "iopub.status.busy": "2022-02-21T14:35:06.682122Z",
+     "iopub.status.idle": "2022-02-21T14:35:07.361794Z",
+     "shell.execute_reply": "2022-02-21T14:35:07.360495Z"
     },
     "papermill": {
-     "duration": 0.772608,
-     "end_time": "2022-01-11T13:27:51.281917",
+     "duration": 0.805659,
+     "end_time": "2022-02-21T14:35:07.364571",
      "exception": false,
-     "start_time": "2022-01-11T13:27:50.509309",
+     "start_time": "2022-02-21T14:35:06.558912",
      "status": "completed"
     },
     "scrolled": false,
@@ -2325,10 +2317,10 @@
    "id": "e450dde9",
    "metadata": {
     "papermill": {
-     "duration": 0.116545,
-     "end_time": "2022-01-11T13:27:51.515923",
+     "duration": 0.120362,
+     "end_time": "2022-02-21T14:35:07.608551",
      "exception": false,
-     "start_time": "2022-01-11T13:27:51.399378",
+     "start_time": "2022-02-21T14:35:07.488189",
      "status": "completed"
     },
     "tags": []
@@ -2343,16 +2335,16 @@
    "id": "06b83623",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:51.757688Z",
-     "iopub.status.busy": "2022-01-11T13:27:51.756983Z",
-     "iopub.status.idle": "2022-01-11T13:27:51.764973Z",
-     "shell.execute_reply": "2022-01-11T13:27:51.765505Z"
+     "iopub.execute_input": "2022-02-21T14:35:07.852481Z",
+     "iopub.status.busy": "2022-02-21T14:35:07.852140Z",
+     "iopub.status.idle": "2022-02-21T14:35:07.867272Z",
+     "shell.execute_reply": "2022-02-21T14:35:07.866426Z"
     },
     "papermill": {
-     "duration": 0.133362,
-     "end_time": "2022-01-11T13:27:51.765693",
+     "duration": 0.139884,
+     "end_time": "2022-02-21T14:35:07.869445",
      "exception": false,
-     "start_time": "2022-01-11T13:27:51.632331",
+     "start_time": "2022-02-21T14:35:07.729561",
      "status": "completed"
     },
     "tags": []
@@ -2417,10 +2409,10 @@
    "id": "208d3f86",
    "metadata": {
     "papermill": {
-     "duration": 0.117572,
-     "end_time": "2022-01-11T13:27:52.002363",
+     "duration": 0.120837,
+     "end_time": "2022-02-21T14:35:08.112085",
      "exception": false,
-     "start_time": "2022-01-11T13:27:51.884791",
+     "start_time": "2022-02-21T14:35:07.991248",
      "status": "completed"
     },
     "tags": []
@@ -2435,16 +2427,16 @@
    "id": "d126d150",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:52.252029Z",
-     "iopub.status.busy": "2022-01-11T13:27:52.250524Z",
-     "iopub.status.idle": "2022-01-11T13:27:52.266663Z",
-     "shell.execute_reply": "2022-01-11T13:27:52.265995Z"
+     "iopub.execute_input": "2022-02-21T14:35:08.358863Z",
+     "iopub.status.busy": "2022-02-21T14:35:08.358537Z",
+     "iopub.status.idle": "2022-02-21T14:35:08.384521Z",
+     "shell.execute_reply": "2022-02-21T14:35:08.383606Z"
     },
     "papermill": {
-     "duration": 0.1467,
-     "end_time": "2022-01-11T13:27:52.266813",
+     "duration": 0.152953,
+     "end_time": "2022-02-21T14:35:08.386674",
      "exception": false,
-     "start_time": "2022-01-11T13:27:52.120113",
+     "start_time": "2022-02-21T14:35:08.233721",
      "status": "completed"
     },
     "tags": []
@@ -2639,10 +2631,10 @@
    "id": "e4872456",
    "metadata": {
     "papermill": {
-     "duration": 0.119762,
-     "end_time": "2022-01-11T13:27:52.540790",
+     "duration": 0.122785,
+     "end_time": "2022-02-21T14:35:08.631922",
      "exception": false,
-     "start_time": "2022-01-11T13:27:52.421028",
+     "start_time": "2022-02-21T14:35:08.509137",
      "status": "completed"
     },
     "tags": []
@@ -2657,16 +2649,16 @@
    "id": "c55a1178",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:52.803893Z",
-     "iopub.status.busy": "2022-01-11T13:27:52.803174Z",
-     "iopub.status.idle": "2022-01-11T13:27:54.024339Z",
-     "shell.execute_reply": "2022-01-11T13:27:54.024873Z"
+     "iopub.execute_input": "2022-02-21T14:35:08.887019Z",
+     "iopub.status.busy": "2022-02-21T14:35:08.886690Z",
+     "iopub.status.idle": "2022-02-21T14:35:10.174733Z",
+     "shell.execute_reply": "2022-02-21T14:35:10.171739Z"
     },
     "papermill": {
-     "duration": 1.364788,
-     "end_time": "2022-01-11T13:27:54.025071",
+     "duration": 1.424603,
+     "end_time": "2022-02-21T14:35:10.178849",
      "exception": false,
-     "start_time": "2022-01-11T13:27:52.660283",
+     "start_time": "2022-02-21T14:35:08.754246",
      "status": "completed"
     },
     "scrolled": false,
@@ -2710,10 +2702,10 @@
    "id": "10fa175f",
    "metadata": {
     "papermill": {
-     "duration": 0.120956,
-     "end_time": "2022-01-11T13:27:54.268627",
+     "duration": 0.131938,
+     "end_time": "2022-02-21T14:35:10.442824",
      "exception": false,
-     "start_time": "2022-01-11T13:27:54.147671",
+     "start_time": "2022-02-21T14:35:10.310886",
      "status": "completed"
     },
     "tags": []
@@ -2728,16 +2720,16 @@
    "id": "74e72981",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:54.531496Z",
-     "iopub.status.busy": "2022-01-11T13:27:54.530772Z",
-     "iopub.status.idle": "2022-01-11T13:27:54.626554Z",
-     "shell.execute_reply": "2022-01-11T13:27:54.627050Z"
+     "iopub.execute_input": "2022-02-21T14:35:10.704180Z",
+     "iopub.status.busy": "2022-02-21T14:35:10.703718Z",
+     "iopub.status.idle": "2022-02-21T14:35:10.821414Z",
+     "shell.execute_reply": "2022-02-21T14:35:10.820655Z"
     },
     "papermill": {
-     "duration": 0.237402,
-     "end_time": "2022-01-11T13:27:54.627244",
+     "duration": 0.25318,
+     "end_time": "2022-02-21T14:35:10.823364",
      "exception": false,
-     "start_time": "2022-01-11T13:27:54.389842",
+     "start_time": "2022-02-21T14:35:10.570184",
      "status": "completed"
     },
     "tags": []
@@ -3186,10 +3178,10 @@
    "id": "56dca478",
    "metadata": {
     "papermill": {
-     "duration": 0.124204,
-     "end_time": "2022-01-11T13:27:54.876578",
+     "duration": 0.125588,
+     "end_time": "2022-02-21T14:35:11.076070",
      "exception": false,
-     "start_time": "2022-01-11T13:27:54.752374",
+     "start_time": "2022-02-21T14:35:10.950482",
      "status": "completed"
     },
     "tags": []
@@ -3204,16 +3196,16 @@
    "id": "f23b38d1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:55.139890Z",
-     "iopub.status.busy": "2022-01-11T13:27:55.138926Z",
-     "iopub.status.idle": "2022-01-11T13:27:55.164743Z",
-     "shell.execute_reply": "2022-01-11T13:27:55.165249Z"
+     "iopub.execute_input": "2022-02-21T14:35:11.334647Z",
+     "iopub.status.busy": "2022-02-21T14:35:11.334316Z",
+     "iopub.status.idle": "2022-02-21T14:35:11.370575Z",
+     "shell.execute_reply": "2022-02-21T14:35:11.369631Z"
     },
     "papermill": {
-     "duration": 0.165259,
-     "end_time": "2022-01-11T13:27:55.165459",
+     "duration": 0.169014,
+     "end_time": "2022-02-21T14:35:11.373230",
      "exception": false,
-     "start_time": "2022-01-11T13:27:55.000200",
+     "start_time": "2022-02-21T14:35:11.204216",
      "status": "completed"
     },
     "tags": []
@@ -3633,16 +3625,16 @@
    "id": "b10e17b0",
    "metadata": {
     "papermill": {
-     "duration": 0.124333,
-     "end_time": "2022-01-11T13:27:55.415359",
+     "duration": 0.130111,
+     "end_time": "2022-02-21T14:35:11.640453",
      "exception": false,
-     "start_time": "2022-01-11T13:27:55.291026",
+     "start_time": "2022-02-21T14:35:11.510342",
      "status": "completed"
     },
     "tags": []
    },
    "source": [
-    "## 8. 60A-80A-120A circuits (metadata to be updated)"
+    "## 8. 60A-80A-120A circuits"
    ]
   },
   {
@@ -3651,16 +3643,16 @@
    "id": "4eb12093",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:55.693979Z",
-     "iopub.status.busy": "2022-01-11T13:27:55.693234Z",
-     "iopub.status.idle": "2022-01-11T13:27:58.347346Z",
-     "shell.execute_reply": "2022-01-11T13:27:58.346776Z"
+     "iopub.execute_input": "2022-02-21T14:35:11.899736Z",
+     "iopub.status.busy": "2022-02-21T14:35:11.899409Z",
+     "iopub.status.idle": "2022-02-21T14:35:14.593740Z",
+     "shell.execute_reply": "2022-02-21T14:35:14.592820Z"
     },
     "papermill": {
-     "duration": 2.80669,
-     "end_time": "2022-01-11T13:27:58.347531",
+     "duration": 2.82608,
+     "end_time": "2022-02-21T14:35:14.596263",
      "exception": false,
-     "start_time": "2022-01-11T13:27:55.540841",
+     "start_time": "2022-02-21T14:35:11.770183",
      "status": "completed"
     },
     "scrolled": false,
@@ -3669,7 +3661,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 1008x504 with 1 Axes>"
       ]
@@ -3704,10 +3696,10 @@
    "id": "7d22f5e9",
    "metadata": {
     "papermill": {
-     "duration": 0.126689,
-     "end_time": "2022-01-11T13:27:58.603855",
+     "duration": 0.131252,
+     "end_time": "2022-02-21T14:35:14.857508",
      "exception": false,
-     "start_time": "2022-01-11T13:27:58.477166",
+     "start_time": "2022-02-21T14:35:14.726256",
      "status": "completed"
     },
     "tags": []
@@ -3722,16 +3714,16 @@
    "id": "e85a9e0d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:58.886494Z",
-     "iopub.status.busy": "2022-01-11T13:27:58.882230Z",
-     "iopub.status.idle": "2022-01-11T13:27:58.923755Z",
-     "shell.execute_reply": "2022-01-11T13:27:58.923209Z"
+     "iopub.execute_input": "2022-02-21T14:35:15.120579Z",
+     "iopub.status.busy": "2022-02-21T14:35:15.120232Z",
+     "iopub.status.idle": "2022-02-21T14:35:15.180086Z",
+     "shell.execute_reply": "2022-02-21T14:35:15.179287Z"
     },
     "papermill": {
-     "duration": 0.191466,
-     "end_time": "2022-01-11T13:27:58.923911",
+     "duration": 0.193958,
+     "end_time": "2022-02-21T14:35:15.182900",
      "exception": false,
-     "start_time": "2022-01-11T13:27:58.732445",
+     "start_time": "2022-02-21T14:35:14.988942",
      "status": "completed"
     },
     "scrolled": false,
@@ -4711,10 +4703,10 @@
    "id": "ccfde4ac",
    "metadata": {
     "papermill": {
-     "duration": 0.12937,
-     "end_time": "2022-01-11T13:27:59.185241",
+     "duration": 0.136145,
+     "end_time": "2022-02-21T14:35:15.452942",
      "exception": false,
-     "start_time": "2022-01-11T13:27:59.055871",
+     "start_time": "2022-02-21T14:35:15.316797",
      "status": "completed"
     },
     "tags": []
@@ -4729,16 +4721,16 @@
    "id": "147cfe26",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:59.449745Z",
-     "iopub.status.busy": "2022-01-11T13:27:59.449070Z",
-     "iopub.status.idle": "2022-01-11T13:27:59.450864Z",
-     "shell.execute_reply": "2022-01-11T13:27:59.451499Z"
+     "iopub.execute_input": "2022-02-21T14:35:15.720257Z",
+     "iopub.status.busy": "2022-02-21T14:35:15.719925Z",
+     "iopub.status.idle": "2022-02-21T14:35:15.724696Z",
+     "shell.execute_reply": "2022-02-21T14:35:15.723576Z"
     },
     "papermill": {
-     "duration": 0.136511,
-     "end_time": "2022-01-11T13:27:59.451682",
+     "duration": 0.142239,
+     "end_time": "2022-02-21T14:35:15.727477",
      "exception": false,
-     "start_time": "2022-01-11T13:27:59.315171",
+     "start_time": "2022-02-21T14:35:15.585238",
      "status": "completed"
     },
     "tags": []
@@ -4755,16 +4747,16 @@
    "id": "09010ca7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2022-01-11T13:27:59.730700Z",
-     "iopub.status.busy": "2022-01-11T13:27:59.729958Z",
-     "iopub.status.idle": "2022-01-11T13:28:09.154313Z",
-     "shell.execute_reply": "2022-01-11T13:28:09.153092Z"
+     "iopub.execute_input": "2022-02-21T14:35:15.998407Z",
+     "iopub.status.busy": "2022-02-21T14:35:15.998057Z",
+     "iopub.status.idle": "2022-02-21T14:35:25.716756Z",
+     "shell.execute_reply": "2022-02-21T14:35:25.715269Z"
     },
     "papermill": {
-     "duration": 9.572844,
-     "end_time": "2022-01-11T13:28:09.154496",
+     "duration": 9.856675,
+     "end_time": "2022-02-21T14:35:25.720533",
      "exception": false,
-     "start_time": "2022-01-11T13:27:59.581652",
+     "start_time": "2022-02-21T14:35:15.863858",
      "status": "completed"
     },
     "scrolled": false,
@@ -4825,7 +4817,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[NbConvertApp] Writing 541629 bytes to ./results/reports/AN_PGC2.html\r\n"
+      "[NbConvertApp] Writing 541754 bytes to ./results/reports/AN_PGC2.html\r\n"
      ]
     }
    ],
@@ -4844,6 +4836,23 @@
     "Time.sleep(5)\n",
     "!{sys.executable} -m jupyter nbconvert --to html $path_to_notebook --output-dir $report_destination_path --output $html_filename --TemplateExporter.exclude_input=True --TagRemovePreprocessor.remove_all_outputs_tags skip_output --TagRemovePreprocessor.remove_cell_tags skip_cell"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9bd181ca",
+   "metadata": {
+    "papermill": {
+     "duration": 0.137063,
+     "end_time": "2022-02-21T14:35:25.996327",
+     "exception": false,
+     "start_time": "2022-02-21T14:35:25.859264",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -4866,8 +4875,8 @@
   },
   "papermill": {
    "default_parameters": {},
-   "duration": 430.68139,
-   "end_time": "2022-01-11T13:28:09.910574",
+   "duration": 420.204405,
+   "end_time": "2022-02-21T14:35:26.980333",
    "environment_variables": {},
    "exception": null,
    "input_path": "/builds/LHCData/lhc-sm-hwc/test/../pgc/AN_PGC2.ipynb",
@@ -4884,8 +4893,8 @@
     "t_end": "2021-07-22 07:24:58.244000000",
     "t_start": "2021-07-22 07:24:58.230000000"
    },
-   "start_time": "2022-01-11T13:20:59.229184",
-   "version": "2.3.3"
+   "start_time": "2022-02-21T14:28:26.775928",
+   "version": "2.3.4"
   },
   "sparkconnect": {
    "bundled_options": [
diff --git a/test/resources/reports/AN_PGC2.html b/test/resources/reports/AN_PGC2.html
index 008b82fd..6c503790 100644
--- a/test/resources/reports/AN_PGC2.html
+++ b/test/resources/reports/AN_PGC2.html
@@ -13178,8 +13178,8 @@ Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdo
 
 
 <div class="output_subarea output_stream output_stdout output_text">
-<pre>Analysis executed with lhc-sm-api version: 1.5.18
-Analysis executed with lhc-sm-hwc notebooks version: 1.5.66
+<pre>Analysis executed with lhc-sm-api version: 1.5.19
+Analysis executed with lhc-sm-hwc notebooks version: 1.5.67
 user = root
 </pre>
 </div>
@@ -13643,7 +13643,7 @@ Individualy powered circuits (IPQ, IPD)
 105 type = 80-120A , name = RCBCV8.R5B1 , Imax = 100 , Imin = 0
 106 type = 80-120A , name = RCBCV9.L6B2 , Imax = 100 , Imin = 0
 107 type = 80-120A , name = RCBCV9.R5B2 , Imax = 100 , Imin = 0
-Elapsed: 366.528 s.
+Elapsed: 314.832 s.
 </pre>
 </div>
 </div>
@@ -14683,7 +14683,7 @@ Elapsed: 366.528 s.
 <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
 </div><div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
-<h2 id="8.-60A-80A-120A-circuits-(metadata-to-be-updated)">8. 60A-80A-120A circuits (metadata to be updated)<a class="anchor-link" href="#8.-60A-80A-120A-circuits-(metadata-to-be-updated)">&#182;</a></h2>
+<h2 id="8.-60A-80A-120A-circuits">8. 60A-80A-120A circuits<a class="anchor-link" href="#8.-60A-80A-120A-circuits">&#182;</a></h2>
 </div>
 </div>
 </div>
@@ -14701,7 +14701,7 @@ Elapsed: 366.528 s.
 
 
 <div class="output_png output_subarea ">
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
 "
 >
 </div>
@@ -15498,6 +15498,9 @@ Elapsed: 366.528 s.
 </div>
 <div class="cell border-box-sizing code_cell rendered">
 
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
 </div>
     </div>
   </div>
-- 
GitLab


From 058d20bfb85d618ab7cf8d447d48789016c3f2aa Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Mon, 21 Feb 2022 16:20:39 +0100
Subject: [PATCH 39/44] [SIGMON-315] \n added

---
 rq/AN_RQ_PNO.b3.ipynb | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/rq/AN_RQ_PNO.b3.ipynb b/rq/AN_RQ_PNO.b3.ipynb
index 47fb6cfb..ab8a70f4 100644
--- a/rq/AN_RQ_PNO.b3.ipynb
+++ b/rq/AN_RQ_PNO.b3.ipynb
@@ -1041,22 +1041,22 @@
     "\n",
     "!mkdir -p $report_destination_path\n",
     "\n",
-    "if not res_busbar_rqd_df.empty:",
+    "if not res_busbar_rqd_df.empty:\n",
     "    csv_path = f'{report_destination_path}/{report_filename}_RQD_BUSBAR_RESISTANCE.csv'\n",
     "    res_busbar_rqd_df.to_csv(csv_path)\n",
     "    print('RQD busbar resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
     "\n",
-    "if not res_busbar_rqf_df.empty:",
+    "if not res_busbar_rqf_df.empty:\n",
     "    csv_path = f'{report_destination_path}/{report_filename}_RQF_BUSBAR_RESISTANCE.csv'\n",
     "    res_busbar_rqf_df.to_csv(csv_path)\n",
     "    print('RQF busbar resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
     "\n",
-    "if not res_magnet_rqd_df.empty:",
+    "if not res_magnet_rqd_df.empty:\n",
     "    csv_path = f'{report_destination_path}/{report_filename}_RQD_MAGNET_RESISTANCE.csv'\n",
     "    res_magnet_rqd_df.to_csv(csv_path)\n",
     "    print('RQD magnet resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
     "\n",
-    "if not res_magnet_rqf_df.empty:",
+    "if not res_magnet_rqf_df.empty:\n",
     "    csv_path = f'{report_destination_path}/{report_filename}_RQF_MAGNET_RESISTANCE.csv'\n",
     "    res_magnet_rqf_df.to_csv(csv_path)\n",
     "    print('RQF magnet resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
-- 
GitLab


From 781974cf8b04917e86329bb51e8cbfdea05a30a8 Mon Sep 17 00:00:00 2001
From: Aleksandra Mnich <olamnich@gmail.com>
Date: Mon, 21 Feb 2022 17:05:13 +0100
Subject: [PATCH 40/44] [SIGMON-315] new references + tests uncommented

---
 .../notebooks/result_AN_RQ_PNO.b3.ipynb       | 3130 +++++++++++++----
 test/resources/reports/AN_RQ_PNO.b3.html      | 2166 +++++++++++-
 .../AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv    |   49 +
 .../AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv    |   49 +
 .../AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv    |   49 +
 .../AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv    |   49 +
 test/test_notebooks.py                        |  114 +-
 7 files changed, 4856 insertions(+), 750 deletions(-)
 create mode 100644 test/resources/reports/AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv
 create mode 100644 test/resources/reports/AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv
 create mode 100644 test/resources/reports/AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv
 create mode 100644 test/resources/reports/AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv

diff --git a/test/resources/notebooks/result_AN_RQ_PNO.b3.ipynb b/test/resources/notebooks/result_AN_RQ_PNO.b3.ipynb
index 7d503597..d38d7cc6 100644
--- a/test/resources/notebooks/result_AN_RQ_PNO.b3.ipynb
+++ b/test/resources/notebooks/result_AN_RQ_PNO.b3.ipynb
@@ -3,19 +3,19 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "24df37d3",
+   "id": "2166722e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:39:53.030796Z",
-     "iopub.status.busy": "2021-11-09T08:39:53.029970Z",
-     "iopub.status.idle": "2021-11-09T08:40:32.450407Z",
-     "shell.execute_reply": "2021-11-09T08:40:32.448991Z"
+     "iopub.execute_input": "2022-02-21T15:26:06.600717Z",
+     "iopub.status.busy": "2022-02-21T15:26:06.600319Z",
+     "iopub.status.idle": "2022-02-21T15:26:42.641320Z",
+     "shell.execute_reply": "2022-02-21T15:26:42.639933Z"
     },
     "papermill": {
-     "duration": 39.626619,
-     "end_time": "2021-11-09T08:40:32.451034",
+     "duration": 36.10509,
+     "end_time": "2022-02-21T15:26:42.644782",
      "exception": false,
-     "start_time": "2021-11-09T08:39:52.824415",
+     "start_time": "2022-02-21T15:26:06.539692",
      "status": "completed"
     }
    },
@@ -27,13 +27,13 @@
     "\"\"\"\n",
     "if 'spark' not in locals() and 'spark' not in globals():\n",
     "    import os\n",
-    "    import socket\n",
-    "\n",
     "    from pyspark import SparkContext, SparkConf\n",
     "    from pyspark.sql import SparkSession\n",
+    "    import socket\n",
     "\n",
     "    nxcals_jars = os.getenv('NXCALS_JARS')\n",
-    "    host_name = 'spark-runner.cern.ch' if os.environ.get('CI', 'false') == 'true' else socket.gethostname()\n",
+    "    host_name = socket.gethostname()\n",
+    "\n",
     "    conf = SparkConf()\n",
     "\n",
     "    conf.set('spark.master', 'yarn')\n",
@@ -65,20 +65,19 @@
     "             \"https://cs-ccr-nxcals8.cern.ch:19093,https://cs-ccr-nxcals8.cern.ch:19094\")\n",
     "\n",
     "    sc = SparkContext(conf=conf)\n",
-    "    spark = SparkSession(sc)\n",
-    "\n"
+    "    spark = SparkSession(sc)\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "70a49297",
+   "id": "f1614b92",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.216301,
-     "end_time": "2021-11-09T08:40:32.887913",
+     "duration": 0.056318,
+     "end_time": "2022-02-21T15:26:42.759083",
      "exception": false,
-     "start_time": "2021-11-09T08:40:32.671612",
+     "start_time": "2022-02-21T15:26:42.702765",
      "status": "completed"
     },
     "tags": []
@@ -115,14 +114,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d9232869",
+   "id": "354edcb0",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.2106,
-     "end_time": "2021-11-09T08:40:33.310565",
+     "duration": 0.057241,
+     "end_time": "2022-02-21T15:26:42.877598",
      "exception": false,
-     "start_time": "2021-11-09T08:40:33.099965",
+     "start_time": "2022-02-21T15:26:42.820357",
      "status": "completed"
     },
     "tags": []
@@ -145,14 +144,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f9924408",
+   "id": "c0343794",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.220109,
-     "end_time": "2021-11-09T08:40:33.741506",
+     "duration": 0.056525,
+     "end_time": "2022-02-21T15:26:42.991175",
      "exception": false,
-     "start_time": "2021-11-09T08:40:33.521397",
+     "start_time": "2022-02-21T15:26:42.934650",
      "status": "completed"
     },
     "tags": []
@@ -164,20 +163,20 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "4d075913",
+   "id": "77cac80d",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:40:34.189558Z",
-     "iopub.status.busy": "2021-11-09T08:40:34.188752Z",
-     "iopub.status.idle": "2021-11-09T08:40:38.936558Z",
-     "shell.execute_reply": "2021-11-09T08:40:38.935813Z"
+     "iopub.execute_input": "2022-02-21T15:26:43.107459Z",
+     "iopub.status.busy": "2022-02-21T15:26:43.107051Z",
+     "iopub.status.idle": "2022-02-21T15:26:46.482468Z",
+     "shell.execute_reply": "2022-02-21T15:26:46.481475Z"
     },
     "papermill": {
-     "duration": 4.972187,
-     "end_time": "2021-11-09T08:40:38.936821",
+     "duration": 3.43648,
+     "end_time": "2022-02-21T15:26:46.484646",
      "exception": false,
-     "start_time": "2021-11-09T08:40:33.964634",
+     "start_time": "2022-02-21T15:26:43.048166",
      "status": "completed"
     },
     "scrolled": true,
@@ -188,8 +187,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Analysis executed with lhc-sm-api version: 1.5.18\n",
-      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.66\n",
+      "Analysis executed with lhc-sm-api version: 1.5.19\n",
+      "Analysis executed with lhc-sm-hwc notebooks version: 1.5.67\n",
       "Analysis performed by root\n"
      ]
     }
@@ -221,19 +220,19 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "d8cee63c",
+   "id": "1d7d38b0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:40:39.393786Z",
-     "iopub.status.busy": "2021-11-09T08:40:39.392878Z",
-     "iopub.status.idle": "2021-11-09T08:40:39.398161Z",
-     "shell.execute_reply": "2021-11-09T08:40:39.397420Z"
+     "iopub.execute_input": "2022-02-21T15:26:46.603939Z",
+     "iopub.status.busy": "2022-02-21T15:26:46.603595Z",
+     "iopub.status.idle": "2022-02-21T15:26:46.607772Z",
+     "shell.execute_reply": "2022-02-21T15:26:46.606974Z"
     },
     "papermill": {
-     "duration": 0.229469,
-     "end_time": "2021-11-09T08:40:39.398385",
+     "duration": 0.066397,
+     "end_time": "2022-02-21T15:26:46.609924",
      "exception": false,
-     "start_time": "2021-11-09T08:40:39.168916",
+     "start_time": "2022-02-21T15:26:46.543527",
      "status": "completed"
     },
     "tags": []
@@ -247,14 +246,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5865ac12",
+   "id": "c81f35b1",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.216414,
-     "end_time": "2021-11-09T08:40:39.834864",
+     "duration": 0.063045,
+     "end_time": "2022-02-21T15:26:46.734676",
      "exception": false,
-     "start_time": "2021-11-09T08:40:39.618450",
+     "start_time": "2022-02-21T15:26:46.671631",
      "status": "completed"
     },
     "tags": []
@@ -286,14 +285,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3e032650",
+   "id": "ad866e85",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.216413,
-     "end_time": "2021-11-09T08:40:40.268576",
+     "duration": 0.06444,
+     "end_time": "2022-02-21T15:26:46.859517",
      "exception": false,
-     "start_time": "2021-11-09T08:40:40.052163",
+     "start_time": "2022-02-21T15:26:46.795077",
      "status": "completed"
     },
     "tags": [
@@ -306,19 +305,19 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "f117caf1",
+   "id": "990f8294",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:40:40.717500Z",
-     "iopub.status.busy": "2021-11-09T08:40:40.716552Z",
-     "iopub.status.idle": "2021-11-09T08:40:40.721600Z",
-     "shell.execute_reply": "2021-11-09T08:40:40.720603Z"
+     "iopub.execute_input": "2022-02-21T15:26:46.986717Z",
+     "iopub.status.busy": "2022-02-21T15:26:46.986393Z",
+     "iopub.status.idle": "2022-02-21T15:26:46.991621Z",
+     "shell.execute_reply": "2022-02-21T15:26:46.990611Z"
     },
     "papermill": {
-     "duration": 0.230878,
-     "end_time": "2021-11-09T08:40:40.721807",
+     "duration": 0.07051,
+     "end_time": "2022-02-21T15:26:46.993926",
      "exception": false,
-     "start_time": "2021-11-09T08:40:40.490929",
+     "start_time": "2022-02-21T15:26:46.923416",
      "status": "completed"
     },
     "tags": [
@@ -343,19 +342,19 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "db42d75e",
+   "id": "eadde632",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:40:41.180449Z",
-     "iopub.status.busy": "2021-11-09T08:40:41.178964Z",
-     "iopub.status.idle": "2021-11-09T08:40:41.182814Z",
-     "shell.execute_reply": "2021-11-09T08:40:41.179705Z"
+     "iopub.execute_input": "2022-02-21T15:26:47.110736Z",
+     "iopub.status.busy": "2022-02-21T15:26:47.110265Z",
+     "iopub.status.idle": "2022-02-21T15:26:47.116060Z",
+     "shell.execute_reply": "2022-02-21T15:26:47.115127Z"
     },
     "papermill": {
-     "duration": 0.239605,
-     "end_time": "2021-11-09T08:40:41.183044",
+     "duration": 0.066262,
+     "end_time": "2022-02-21T15:26:47.118008",
      "exception": false,
-     "start_time": "2021-11-09T08:40:40.943439",
+     "start_time": "2022-02-21T15:26:47.051746",
      "status": "completed"
     },
     "tags": []
@@ -379,14 +378,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7ba6b51d",
+   "id": "2cf149a1",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.213224,
-     "end_time": "2021-11-09T08:40:41.618897",
+     "duration": 0.057152,
+     "end_time": "2022-02-21T15:26:47.232486",
      "exception": false,
-     "start_time": "2021-11-09T08:40:41.405673",
+     "start_time": "2022-02-21T15:26:47.175334",
      "status": "completed"
     },
     "tags": []
@@ -398,20 +397,20 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "a5cd1c7f",
+   "id": "78330cc2",
    "metadata": {
     "deleteable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:40:42.072203Z",
-     "iopub.status.busy": "2021-11-09T08:40:42.058978Z",
-     "iopub.status.idle": "2021-11-09T08:45:09.262393Z",
-     "shell.execute_reply": "2021-11-09T08:45:09.263166Z"
+     "iopub.execute_input": "2022-02-21T15:26:47.349629Z",
+     "iopub.status.busy": "2022-02-21T15:26:47.349274Z",
+     "iopub.status.idle": "2022-02-21T15:37:35.386868Z",
+     "shell.execute_reply": "2022-02-21T15:37:35.385999Z"
     },
     "papermill": {
-     "duration": 267.426565,
-     "end_time": "2021-11-09T08:45:09.263595",
+     "duration": 648.192159,
+     "end_time": "2022-02-21T15:37:35.482395",
      "exception": false,
-     "start_time": "2021-11-09T08:40:41.837030",
+     "start_time": "2022-02-21T15:26:47.290236",
      "status": "completed"
     },
     "scrolled": false,
@@ -474,7 +473,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) IEARTH.IEARTH, IAB.I_A, STATUS.I_EARTH_PCNT, STATUS.I_REF, STATUS.I_MEAS for system: RPHE.UA23.RQD.A12, className: 51_self_pmd, source: FGC at 2018-03-18 11:58:33.600\n"
+      "\tQuerying PM event signal(s) STATUS.I_EARTH_PCNT, IEARTH.IEARTH, STATUS.I_REF, STATUS.I_MEAS, IAB.I_A for system: RPHE.UA23.RQD.A12, className: 51_self_pmd, source: FGC at 2018-03-18 11:58:33.600\n"
      ]
     },
     {
@@ -493,7 +492,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) IEARTH.IEARTH, IAB.I_A, STATUS.I_EARTH_PCNT, STATUS.I_REF, STATUS.I_MEAS for system: RPHE.UA23.RQF.A12, className: 51_self_pmd, source: FGC at 2018-03-18 11:58:33.600\n"
+      "\tQuerying PM event signal(s) STATUS.I_EARTH_PCNT, IEARTH.IEARTH, STATUS.I_REF, STATUS.I_MEAS, IAB.I_A for system: RPHE.UA23.RQF.A12, className: 51_self_pmd, source: FGC at 2018-03-18 11:58:33.600\n"
      ]
     },
     {
@@ -550,7 +549,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) STATUS.I_EARTH_PCNT, STATUS.I_MEAS for system: RPHE.UA23.RQD.A12, className: 51_self_pmd, source: FGC at 2017-04-25 10:51:12.600\n"
+      "\tQuerying PM event signal(s) STATUS.I_MEAS, STATUS.I_EARTH_PCNT for system: RPHE.UA23.RQD.A12, className: 51_self_pmd, source: FGC at 2017-04-25 10:51:12.600\n"
      ]
     },
     {
@@ -569,7 +568,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\tQuerying PM event signal(s) STATUS.I_EARTH_PCNT, STATUS.I_MEAS for system: RPHE.UA23.RQF.A12, className: 51_self_pmd, source: FGC at 2017-04-25 10:51:12.600\n"
+      "\tQuerying PM event signal(s) STATUS.I_MEAS, STATUS.I_EARTH_PCNT for system: RPHE.UA23.RQF.A12, className: 51_self_pmd, source: FGC at 2017-04-25 10:51:12.600\n"
      ]
     },
     {
@@ -917,7 +916,55 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RQD.A12 query function query_signal_nxcals: 14/15.</text>"
+       "<text style=color:blue>Executing RQD.A12 query function get_busbar_resistances: 14/17.</text>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<text style=color:blue>Executing RQF.A12 query function get_busbar_resistances: 14/17.</text>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<text style=color:blue>Executing RQD.A12 query function get_busbar_resistances: 15/17.</text>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<text style=color:blue>Executing RQF.A12 query function get_busbar_resistances: 15/17.</text>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<text style=color:blue>Executing RQD.A12 query function query_signal_nxcals: 16/17.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -929,7 +976,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RQD.A12 query function query_signal_nxcals: 15/15.</text>"
+       "<text style=color:blue>Executing RQD.A12 query function query_signal_nxcals: 17/17.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -941,7 +988,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RQF.A12 query function query_signal_nxcals: 14/15.</text>"
+       "<text style=color:blue>Executing RQF.A12 query function query_signal_nxcals: 16/17.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -953,7 +1000,7 @@
     {
      "data": {
       "text/html": [
-       "<text style=color:blue>Executing RQF.A12 query function query_signal_nxcals: 15/15.</text>"
+       "<text style=color:blue>Executing RQF.A12 query function query_signal_nxcals: 17/17.</text>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -966,7 +1013,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Elapsed: 266.333 s.\n"
+      "Elapsed: 647.681 s.\n"
      ]
     }
    ],
@@ -996,7 +1043,7 @@
     "    # PC\n",
     "    i_meas_nxcals_dfs =  RqCircuitQuery(circuit_type, circuit_names).query_signal_nxcals(t_start, t_end, t0=t_start, system='PC', signal_names='I_MEAS', spark=spark)\n",
     "    i_meas_raw_nxcals_dfs =  RqCircuitQuery(circuit_type, circuit_names).query_raw_signal_nxcals(t_start, t_end, system='PC', signal_names='I_MEAS', spark=spark)\n",
-    "    plateau_start, plateau_end = RqCircuitQuery(circuit_type, circuit_names).calculate_current_plateau_start_end(t_start, t_end, i_meas_threshold=500, min_duration_in_sec=600, time_shift_in_sec=(240, 60), spark=spark)\n",
+    "    plateau_start, plateau_end = RqCircuitQuery(circuit_type, circuit_names).calculate_current_plateau_start_end(t_start, t_end, i_meas_threshold=300, min_duration_in_sec=600, time_shift_in_sec=(240, 60), spark=spark)\n",
     "\n",
     "    source_timestamp_df = rqd_query.find_source_timestamp_pc(t_start, t_end)\n",
     "    timestamp_fgc_rqd = source_timestamp_df.at[0, 'timestamp']\n",
@@ -1079,21 +1126,21 @@
     "        # # RQD\n",
     "        u_res_rqd_feature_df, i_meas_rqd_feature_df = rqd_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_RES', spark=spark)\n",
     "        res_busbar_rqd_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rq_analysis, i_meas_rqd_feature_df, u_res_rqd_feature_df, 'U_RES', Time.to_unix_timestamp(t_start), circuit_names[0])\n",
-    "        res_busbar_rqd_df = convert_to_col(res_busbar_rqd_row_df, signal_name='U_RES')\n",
+    "        res_busbar_rqd_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_busbar_rqd_row_df, signal_name='U_RES')\n",
     "        # # RQF\n",
     "        u_res_rqf_feature_df, i_meas_rqf_feature_df = rqf_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_RES', spark=spark)\n",
     "        res_busbar_rqf_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rq_analysis, i_meas_rqf_feature_df, u_res_rqf_feature_df, 'U_RES', Time.to_unix_timestamp(t_start), circuit_names[1])\n",
-    "        res_busbar_rqf_df = convert_to_col(res_busbar_rqf_row_df, signal_name='U_RES')\n",
+    "        res_busbar_rqf_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_busbar_rqf_row_df, signal_name='U_RES')\n",
     "\n",
     "        # MAGNET\n",
     "        # # RQD\n",
     "        u_mag_rqd_feature_df, i_meas_rqd_feature_df = rqd_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_MAG', spark=spark)\n",
     "        res_magnet_rqd_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rq_analysis, i_meas_rqd_feature_df, u_mag_rqd_feature_df, 'U_MAG', Time.to_unix_timestamp(t_start), circuit_names[0])\n",
-    "        res_magnet_rqd_df = convert_to_col(res_magnet_rqd_row_df, signal_name='U_MAG')\n",
+    "        res_magnet_rqd_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_magnet_rqd_row_df, signal_name='U_MAG')\n",
     "        # # RQF\n",
     "        u_mag_rqf_feature_df, i_meas_rqf_feature_df = rqf_query.get_busbar_resistances(Time.to_unix_timestamp(t_start), Time.to_unix_timestamp(t_end), plateau_start, plateau_end, signal_name='U_MAG', spark=spark)\n",
     "        res_magnet_rqf_row_df = MultipleBusbarResistanceAnalysis.calculate_resistance(rq_analysis, i_meas_rqf_feature_df, u_mag_rqf_feature_df, 'U_MAG', Time.to_unix_timestamp(t_start), circuit_names[1])\n",
-    "        res_magnet_rqf_df = convert_to_col(res_magnet_rqf_row_df, signal_name='U_MAG')\n",
+    "        res_magnet_rqf_df = MultipleBusbarResistanceAnalysis.convert_to_col(res_magnet_rqf_row_df, signal_name='U_MAG')\n",
     "    else:\n",
     "        res_busbar_rqd_df, res_busbar_rqf_df, res_magnet_rqd_df, res_magnet_rqf_df = 4*[pd.DataFrame()]\n",
     "\n",
@@ -1118,14 +1165,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d7c4a165",
+   "id": "d5c4c820",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.344927,
-     "end_time": "2021-11-09T08:45:09.953719",
+     "duration": 0.092944,
+     "end_time": "2022-02-21T15:37:35.669733",
      "exception": false,
-     "start_time": "2021-11-09T08:45:09.608792",
+     "start_time": "2022-02-21T15:37:35.576789",
      "status": "completed"
     },
     "tags": []
@@ -1137,20 +1184,20 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "34bab901",
+   "id": "bd233da8",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:10.642608Z",
-     "iopub.status.busy": "2021-11-09T08:45:10.641708Z",
-     "iopub.status.idle": "2021-11-09T08:45:10.688779Z",
-     "shell.execute_reply": "2021-11-09T08:45:10.689432Z"
+     "iopub.execute_input": "2022-02-21T15:37:35.859434Z",
+     "iopub.status.busy": "2022-02-21T15:37:35.859063Z",
+     "iopub.status.idle": "2022-02-21T15:37:35.882243Z",
+     "shell.execute_reply": "2022-02-21T15:37:35.881527Z"
     },
     "papermill": {
-     "duration": 0.39217,
-     "end_time": "2021-11-09T08:45:10.689700",
+     "duration": 0.120279,
+     "end_time": "2022-02-21T15:37:35.884485",
      "exception": false,
-     "start_time": "2021-11-09T08:45:10.297530",
+     "start_time": "2022-02-21T15:37:35.764206",
      "status": "completed"
     },
     "tags": []
@@ -1222,13 +1269,13 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1763dbd0",
+   "id": "2c6e72fc",
    "metadata": {
     "papermill": {
-     "duration": 0.342447,
-     "end_time": "2021-11-09T08:45:11.363715",
+     "duration": 0.093333,
+     "end_time": "2022-02-21T15:37:36.071364",
      "exception": false,
-     "start_time": "2021-11-09T08:45:11.021268",
+     "start_time": "2022-02-21T15:37:35.978031",
      "status": "completed"
     },
     "tags": []
@@ -1240,20 +1287,20 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "abc1bc78",
+   "id": "cb5d8141",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:12.073602Z",
-     "iopub.status.busy": "2021-11-09T08:45:12.072823Z",
-     "iopub.status.idle": "2021-11-09T08:45:12.099653Z",
-     "shell.execute_reply": "2021-11-09T08:45:12.098826Z"
+     "iopub.execute_input": "2022-02-21T15:37:36.260725Z",
+     "iopub.status.busy": "2022-02-21T15:37:36.260350Z",
+     "iopub.status.idle": "2022-02-21T15:37:36.286478Z",
+     "shell.execute_reply": "2022-02-21T15:37:36.285638Z"
     },
     "papermill": {
-     "duration": 0.389718,
-     "end_time": "2021-11-09T08:45:12.099853",
+     "duration": 0.123094,
+     "end_time": "2022-02-21T15:37:36.288533",
      "exception": false,
-     "start_time": "2021-11-09T08:45:11.710135",
+     "start_time": "2022-02-21T15:37:36.165439",
      "status": "completed"
     },
     "tags": []
@@ -1337,14 +1384,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4289673d",
+   "id": "9ba51641",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.340253,
-     "end_time": "2021-11-09T08:45:12.790464",
+     "duration": 0.094979,
+     "end_time": "2022-02-21T15:37:36.478018",
      "exception": false,
-     "start_time": "2021-11-09T08:45:12.450211",
+     "start_time": "2022-02-21T15:37:36.383039",
      "status": "completed"
     },
     "tags": []
@@ -1360,20 +1407,20 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "f08e5d43",
+   "id": "ab277985",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:13.527078Z",
-     "iopub.status.busy": "2021-11-09T08:45:13.526083Z",
-     "iopub.status.idle": "2021-11-09T08:45:14.015511Z",
-     "shell.execute_reply": "2021-11-09T08:45:14.014827Z"
+     "iopub.execute_input": "2022-02-21T15:37:36.669193Z",
+     "iopub.status.busy": "2022-02-21T15:37:36.668836Z",
+     "iopub.status.idle": "2022-02-21T15:37:37.090512Z",
+     "shell.execute_reply": "2022-02-21T15:37:37.089608Z"
     },
     "papermill": {
-     "duration": 0.876915,
-     "end_time": "2021-11-09T08:45:14.015735",
+     "duration": 0.519963,
+     "end_time": "2022-02-21T15:37:37.092919",
      "exception": false,
-     "start_time": "2021-11-09T08:45:13.138820",
+     "start_time": "2022-02-21T15:37:36.572956",
      "status": "completed"
     },
     "tags": []
@@ -1381,7 +1428,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 936x468 with 1 Axes>"
       ]
@@ -1405,14 +1452,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a13bc426",
+   "id": "98d25cde",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.335816,
-     "end_time": "2021-11-09T08:45:14.690435",
+     "duration": 0.094911,
+     "end_time": "2022-02-21T15:37:37.285057",
      "exception": false,
-     "start_time": "2021-11-09T08:45:14.354619",
+     "start_time": "2022-02-21T15:37:37.190146",
      "status": "completed"
     },
     "tags": []
@@ -1444,20 +1491,20 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "7464ded1",
+   "id": "68470fe4",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:15.388283Z",
-     "iopub.status.busy": "2021-11-09T08:45:15.387491Z",
-     "iopub.status.idle": "2021-11-09T08:45:16.361317Z",
-     "shell.execute_reply": "2021-11-09T08:45:16.361837Z"
+     "iopub.execute_input": "2022-02-21T15:37:37.479551Z",
+     "iopub.status.busy": "2022-02-21T15:37:37.479214Z",
+     "iopub.status.idle": "2022-02-21T15:37:39.095747Z",
+     "shell.execute_reply": "2022-02-21T15:37:39.094922Z"
     },
     "papermill": {
-     "duration": 1.32281,
-     "end_time": "2021-11-09T08:45:16.362089",
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+       "</style><table id=\"T_37966_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
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@@ -1530,20 +1577,20 @@
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@@ -1584,25 +1631,25 @@
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+       "</style><table id=\"T_e31f2_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
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@@ -1615,14 +1662,14 @@
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@@ -1649,20 +1696,20 @@
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@@ -1689,20 +1736,20 @@
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@@ -1728,14 +1775,14 @@
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@@ -1753,20 +1800,20 @@
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@@ -1801,20 +1848,20 @@
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@@ -1850,19 +1897,19 @@
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@@ -1896,19 +1943,19 @@
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@@ -1941,14 +1988,14 @@
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@@ -1979,20 +2026,20 @@
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@@ -2022,25 +2069,25 @@
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+       "</style><table id=\"T_de85f_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
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-       "                        <th id=\"T_107b2_level0_row1\" class=\"row_heading level0 row1\" >tau_u_dump_res</th>\n",
-       "                        <td id=\"T_107b2_row1_col0\" class=\"data row1 col0\" >25.000000</td>\n",
-       "                        <td id=\"T_107b2_row1_col1\" class=\"data row1 col1\" >35.000000</td>\n",
-       "                        <td id=\"T_107b2_row1_col2\" class=\"data row1 col2\" >33.074706</td>\n",
-       "                        <td id=\"T_107b2_row1_col3\" class=\"data row1 col3\" >True</td>\n",
+       "                        <th id=\"T_de85f_level0_row1\" class=\"row_heading level0 row1\" >tau_u_dump_res</th>\n",
+       "                        <td id=\"T_de85f_row1_col0\" class=\"data row1 col0\" >25.000000</td>\n",
+       "                        <td id=\"T_de85f_row1_col1\" class=\"data row1 col1\" >35.000000</td>\n",
+       "                        <td id=\"T_de85f_row1_col2\" class=\"data row1 col2\" >33.074706</td>\n",
+       "                        <td id=\"T_de85f_row1_col3\" class=\"data row1 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7f4517a82520>"
+       "<pandas.io.formats.style.Styler at 0x7fd3b6db2d60>"
       ]
      },
      "metadata": {},
@@ -2054,20 +2101,20 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "cd13c324",
+   "id": "81c67b86",
    "metadata": {
     "deletable": false,
     "execution": {
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-     "iopub.status.idle": "2021-11-09T08:45:32.692493Z",
-     "shell.execute_reply": "2021-11-09T08:45:32.691810Z"
+     "iopub.execute_input": "2022-02-21T15:37:47.191119Z",
+     "iopub.status.busy": "2022-02-21T15:37:47.190796Z",
+     "iopub.status.idle": "2022-02-21T15:37:47.693838Z",
+     "shell.execute_reply": "2022-02-21T15:37:47.693090Z"
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-     "start_time": "2021-11-09T08:45:31.656736",
+     "start_time": "2022-02-21T15:37:47.072814",
      "status": "completed"
     },
     "tags": []
@@ -2097,25 +2144,25 @@
      "data": {
       "text/html": [
        "<style  type=\"text/css\" >\n",
-       "</style><table id=\"T_7ffcc_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
+       "</style><table id=\"T_b1660_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
-       "                        <th id=\"T_7ffcc_level0_row0\" class=\"row_heading level0 row0\" >R</th>\n",
-       "                        <td id=\"T_7ffcc_row0_col0\" class=\"data row0 col0\" >0.005000</td>\n",
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-       "                        <td id=\"T_7ffcc_row0_col3\" class=\"data row0 col3\" >True</td>\n",
+       "                        <th id=\"T_b1660_level0_row0\" class=\"row_heading level0 row0\" >R</th>\n",
+       "                        <td id=\"T_b1660_row0_col0\" class=\"data row0 col0\" >0.005000</td>\n",
+       "                        <td id=\"T_b1660_row0_col1\" class=\"data row0 col1\" >0.010000</td>\n",
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        "            <tr>\n",
-       "                        <th id=\"T_7ffcc_level0_row1\" class=\"row_heading level0 row1\" >tau_u_dump_res</th>\n",
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-       "                        <td id=\"T_7ffcc_row1_col3\" class=\"data row1 col3\" >True</td>\n",
+       "                        <th id=\"T_b1660_level0_row1\" class=\"row_heading level0 row1\" >tau_u_dump_res</th>\n",
+       "                        <td id=\"T_b1660_row1_col0\" class=\"data row1 col0\" >25.000000</td>\n",
+       "                        <td id=\"T_b1660_row1_col1\" class=\"data row1 col1\" >35.000000</td>\n",
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+       "                        <td id=\"T_b1660_row1_col3\" class=\"data row1 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7f4517fc0dc0>"
+       "<pandas.io.formats.style.Styler at 0x7fd3bbb29970>"
       ]
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      "metadata": {},
@@ -2129,20 +2176,20 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "5a711d7c",
+   "id": "9789a2e7",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:33.599801Z",
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-     "iopub.status.idle": "2021-11-09T08:45:34.142637Z",
-     "shell.execute_reply": "2021-11-09T08:45:34.141729Z"
+     "iopub.execute_input": "2022-02-21T15:37:47.938447Z",
+     "iopub.status.busy": "2022-02-21T15:37:47.938084Z",
+     "iopub.status.idle": "2022-02-21T15:37:48.478588Z",
+     "shell.execute_reply": "2022-02-21T15:37:48.477769Z"
     },
     "papermill": {
-     "duration": 1.048311,
-     "end_time": "2021-11-09T08:45:34.142893",
+     "duration": 0.664577,
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      "exception": false,
-     "start_time": "2021-11-09T08:45:33.094582",
+     "start_time": "2022-02-21T15:37:47.815989",
      "status": "completed"
     },
     "tags": []
@@ -2172,18 +2219,18 @@
      "data": {
       "text/html": [
        "<style  type=\"text/css\" >\n",
-       "</style><table id=\"T_4f2d9_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
+       "</style><table id=\"T_15a30_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
-       "                        <th id=\"T_4f2d9_level0_row0\" class=\"row_heading level0 row0\" >t_delay_ee</th>\n",
-       "                        <td id=\"T_4f2d9_row0_col0\" class=\"data row0 col0\" >0.085000</td>\n",
-       "                        <td id=\"T_4f2d9_row0_col1\" class=\"data row0 col1\" >0.115000</td>\n",
-       "                        <td id=\"T_4f2d9_row0_col2\" class=\"data row0 col2\" >0.089000</td>\n",
-       "                        <td id=\"T_4f2d9_row0_col3\" class=\"data row0 col3\" >True</td>\n",
+       "                        <th id=\"T_15a30_level0_row0\" class=\"row_heading level0 row0\" >t_delay_ee</th>\n",
+       "                        <td id=\"T_15a30_row0_col0\" class=\"data row0 col0\" >0.085000</td>\n",
+       "                        <td id=\"T_15a30_row0_col1\" class=\"data row0 col1\" >0.115000</td>\n",
+       "                        <td id=\"T_15a30_row0_col2\" class=\"data row0 col2\" >0.089000</td>\n",
+       "                        <td id=\"T_15a30_row0_col3\" class=\"data row0 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7f4517e50400>"
+       "<pandas.io.formats.style.Styler at 0x7fd3b7185130>"
       ]
      },
      "metadata": {},
@@ -2197,20 +2244,20 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "98cf2a46",
+   "id": "7f2dab97",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:34.993618Z",
-     "iopub.status.busy": "2021-11-09T08:45:34.992903Z",
-     "iopub.status.idle": "2021-11-09T08:45:35.795400Z",
-     "shell.execute_reply": "2021-11-09T08:45:35.794611Z"
+     "iopub.execute_input": "2022-02-21T15:37:48.732051Z",
+     "iopub.status.busy": "2022-02-21T15:37:48.731723Z",
+     "iopub.status.idle": "2022-02-21T15:37:49.391257Z",
+     "shell.execute_reply": "2022-02-21T15:37:49.390463Z"
     },
     "papermill": {
-     "duration": 1.235131,
-     "end_time": "2021-11-09T08:45:35.795574",
+     "duration": 0.788768,
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      "exception": false,
-     "start_time": "2021-11-09T08:45:34.560443",
+     "start_time": "2022-02-21T15:37:48.604458",
      "status": "completed"
     },
     "scrolled": false,
@@ -2241,18 +2288,18 @@
      "data": {
       "text/html": [
        "<style  type=\"text/css\" >\n",
-       "</style><table id=\"T_77959_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
+       "</style><table id=\"T_fe7f8_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >min</th>        <th class=\"col_heading level0 col1\" >max</th>        <th class=\"col_heading level0 col2\" >act</th>        <th class=\"col_heading level0 col3\" >result</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
-       "                        <th id=\"T_77959_level0_row0\" class=\"row_heading level0 row0\" >t_delay_ee</th>\n",
-       "                        <td id=\"T_77959_row0_col0\" class=\"data row0 col0\" >0.085000</td>\n",
-       "                        <td id=\"T_77959_row0_col1\" class=\"data row0 col1\" >0.115000</td>\n",
-       "                        <td id=\"T_77959_row0_col2\" class=\"data row0 col2\" >0.090000</td>\n",
-       "                        <td id=\"T_77959_row0_col3\" class=\"data row0 col3\" >True</td>\n",
+       "                        <th id=\"T_fe7f8_level0_row0\" class=\"row_heading level0 row0\" >t_delay_ee</th>\n",
+       "                        <td id=\"T_fe7f8_row0_col0\" class=\"data row0 col0\" >0.085000</td>\n",
+       "                        <td id=\"T_fe7f8_row0_col1\" class=\"data row0 col1\" >0.115000</td>\n",
+       "                        <td id=\"T_fe7f8_row0_col2\" class=\"data row0 col2\" >0.090000</td>\n",
+       "                        <td id=\"T_fe7f8_row0_col3\" class=\"data row0 col3\" >True</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x7f451a218e20>"
+       "<pandas.io.formats.style.Styler at 0x7fd3b6db28e0>"
       ]
      },
      "metadata": {},
@@ -2266,20 +2313,20 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "3bede02a",
+   "id": "e0aae969",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:36.648055Z",
-     "iopub.status.busy": "2021-11-09T08:45:36.647289Z",
-     "iopub.status.idle": "2021-11-09T08:45:36.652489Z",
-     "shell.execute_reply": "2021-11-09T08:45:36.651941Z"
+     "iopub.execute_input": "2022-02-21T15:37:49.652057Z",
+     "iopub.status.busy": "2022-02-21T15:37:49.651738Z",
+     "iopub.status.idle": "2022-02-21T15:37:49.662269Z",
+     "shell.execute_reply": "2022-02-21T15:37:49.661473Z"
     },
     "papermill": {
-     "duration": 0.427686,
-     "end_time": "2021-11-09T08:45:36.652680",
+     "duration": 0.144196,
+     "end_time": "2022-02-21T15:37:49.664144",
      "exception": false,
-     "start_time": "2021-11-09T08:45:36.224994",
+     "start_time": "2022-02-21T15:37:49.519948",
      "status": "completed"
     },
     "tags": []
@@ -2301,14 +2348,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "19838220",
+   "id": "ad3312e2",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.422382,
-     "end_time": "2021-11-09T08:45:37.495624",
+     "duration": 0.127237,
+     "end_time": "2022-02-21T15:37:49.918516",
      "exception": false,
-     "start_time": "2021-11-09T08:45:37.073242",
+     "start_time": "2022-02-21T15:37:49.791279",
      "status": "completed"
     },
     "tags": []
@@ -2333,13 +2380,13 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fbd208bf",
+   "id": "89d3040a",
    "metadata": {
     "papermill": {
-     "duration": 0.464078,
-     "end_time": "2021-11-09T08:45:38.388689",
+     "duration": 0.127469,
+     "end_time": "2022-02-21T15:37:50.174008",
      "exception": false,
-     "start_time": "2021-11-09T08:45:37.924611",
+     "start_time": "2022-02-21T15:37:50.046539",
      "status": "completed"
     },
     "tags": []
@@ -2351,53 +2398,74 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "id": "13fcf22e",
+   "id": "59e38cb9",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:39.174994Z",
-     "iopub.status.busy": "2021-11-09T08:45:39.174219Z",
-     "iopub.status.idle": "2021-11-09T08:45:39.190774Z",
-     "shell.execute_reply": "2021-11-09T08:45:39.190088Z"
+     "iopub.execute_input": "2022-02-21T15:37:50.430635Z",
+     "iopub.status.busy": "2022-02-21T15:37:50.430292Z",
+     "iopub.status.idle": "2022-02-21T15:37:51.104572Z",
+     "shell.execute_reply": "2022-02-21T15:37:51.103808Z"
     },
     "papermill": {
-     "duration": 0.415338,
-     "end_time": "2021-11-09T08:45:39.190984",
+     "duration": 0.805341,
+     "end_time": "2022-02-21T15:37:51.106616",
      "exception": false,
-     "start_time": "2021-11-09T08:45:38.775646",
+     "start_time": "2022-02-21T15:37:50.301275",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 936x468 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_busbar_rqd_df.empty:\n",
     "    title = '%s, %s: %s-%s' % (circuit_names[0], hwc_test, Time.to_string(t_start).split('.')[0], Time.to_string(t_end).split('.')[0])\n",
-    "    res_busbar_rqd_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_busbar_rqd_df, signal_name='R_RES', max_value=10e-9, title=title)"
+    "    res_busbar_rqd_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_busbar_rqd_df, signal_name='R_RES', value_max=10e-9, title=title)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "51065e86",
+   "id": "c2249ad2",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:40.085789Z",
-     "iopub.status.busy": "2021-11-09T08:45:40.084955Z",
-     "iopub.status.idle": "2021-11-09T08:45:40.099468Z",
-     "shell.execute_reply": "2021-11-09T08:45:40.098527Z"
+     "iopub.execute_input": "2022-02-21T15:37:51.364904Z",
+     "iopub.status.busy": "2022-02-21T15:37:51.364581Z",
+     "iopub.status.idle": "2022-02-21T15:37:51.370342Z",
+     "shell.execute_reply": "2022-02-21T15:37:51.369555Z"
     },
     "papermill": {
-     "duration": 0.449059,
-     "end_time": "2021-11-09T08:45:40.099723",
+     "duration": 0.137435,
+     "end_time": "2022-02-21T15:37:51.372275",
      "exception": false,
-     "start_time": "2021-11-09T08:45:39.650664",
+     "start_time": "2022-02-21T15:37:51.234840",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All resistances within the range.\n"
+     ]
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_busbar_rqd_df.empty:\n",
     "    RqCircuitQuery.query_and_plot_outlier_voltage(res_busbar_rqd_outliers_df, t_start, t_end, i_meas_raw_nxcals_dfs[0].index[0], plateau_start, plateau_end, spark=spark)"
@@ -2406,24 +2474,471 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "e8f90383",
+   "id": "1b09ec80",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:41.005728Z",
-     "iopub.status.busy": "2021-11-09T08:45:41.004781Z",
-     "iopub.status.idle": "2021-11-09T08:45:41.009213Z",
-     "shell.execute_reply": "2021-11-09T08:45:41.007848Z"
+     "iopub.execute_input": "2022-02-21T15:37:51.640365Z",
+     "iopub.status.busy": "2022-02-21T15:37:51.639981Z",
+     "iopub.status.idle": "2022-02-21T15:37:51.695682Z",
+     "shell.execute_reply": "2022-02-21T15:37:51.694855Z"
     },
     "papermill": {
-     "duration": 0.463344,
-     "end_time": "2021-11-09T08:45:41.009433",
+     "duration": 0.195741,
+     "end_time": "2022-02-21T15:37:51.698005",
      "exception": false,
-     "start_time": "2021-11-09T08:45:40.546089",
+     "start_time": "2022-02-21T15:37:51.502264",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_cf59d_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >QPS Crate&Board</th>        <th class=\"col_heading level0 col1\" >Bus Bar Segment Name</th>        <th class=\"col_heading level0 col2\" >1st Magnet</th>        <th class=\"col_heading level0 col3\" >2nd Magnet</th>        <th class=\"col_heading level0 col4\" >Num of splices</th>        <th class=\"col_heading level0 col5\" >R_RES</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_cf59d_row0_col0\" class=\"data row0 col0\" >B10L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row0_col1\" class=\"data row0 col1\" >DCQDD.7L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row0_col2\" class=\"data row0 col2\" >MQ.11L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row0_col3\" class=\"data row0 col3\" >DFLAS.7L2.2</td>\n",
+       "                        <td id=\"T_cf59d_row0_col4\" class=\"data row0 col4\" >16</td>\n",
+       "                        <td id=\"T_cf59d_row0_col5\" class=\"data row0 col5\" >5.01E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_cf59d_row1_col0\" class=\"data row1 col0\" >B12L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row1_col1\" class=\"data row1 col1\" >DCQDB.A12L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row1_col2\" class=\"data row1 col2\" >MQ.13L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row1_col3\" class=\"data row1 col3\" >MQ.11L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row1_col4\" class=\"data row1 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row1_col5\" class=\"data row1 col5\" >2.72E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_cf59d_row2_col0\" class=\"data row2 col0\" >B14L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row2_col1\" class=\"data row2 col1\" >DCQDB.A14L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row2_col2\" class=\"data row2 col2\" >MQ.15L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row2_col3\" class=\"data row2 col3\" >MQ.13L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row2_col4\" class=\"data row2 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row2_col5\" class=\"data row2 col5\" >2.47E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "                        <td id=\"T_cf59d_row3_col0\" class=\"data row3 col0\" >B16L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row3_col1\" class=\"data row3 col1\" >DCQDB.A16L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row3_col2\" class=\"data row3 col2\" >MQ.17L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row3_col3\" class=\"data row3 col3\" >MQ.15L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row3_col4\" class=\"data row3 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row3_col5\" class=\"data row3 col5\" >2.40E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "                        <td id=\"T_cf59d_row4_col0\" class=\"data row4 col0\" >B18L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row4_col1\" class=\"data row4 col1\" >DCQDB.A18L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row4_col2\" class=\"data row4 col2\" >MQ.19L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row4_col3\" class=\"data row4 col3\" >MQ.17L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row4_col4\" class=\"data row4 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row4_col5\" class=\"data row4 col5\" >2.27E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "                        <td id=\"T_cf59d_row5_col0\" class=\"data row5 col0\" >B20L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row5_col1\" class=\"data row5 col1\" >DCQDB.A20L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row5_col2\" class=\"data row5 col2\" >MQ.21L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row5_col3\" class=\"data row5 col3\" >MQ.19L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row5_col4\" class=\"data row5 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row5_col5\" class=\"data row5 col5\" >2.46E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "                        <td id=\"T_cf59d_row6_col0\" class=\"data row6 col0\" >B22L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row6_col1\" class=\"data row6 col1\" >DCQDB.A22L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row6_col2\" class=\"data row6 col2\" >MQ.23L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row6_col3\" class=\"data row6 col3\" >MQ.21L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row6_col4\" class=\"data row6 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row6_col5\" class=\"data row6 col5\" >3.20E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "                        <td id=\"T_cf59d_row7_col0\" class=\"data row7 col0\" >B24L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row7_col1\" class=\"data row7 col1\" >DCQDB.A24L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row7_col2\" class=\"data row7 col2\" >MQ.25L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row7_col3\" class=\"data row7 col3\" >MQ.23L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row7_col4\" class=\"data row7 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row7_col5\" class=\"data row7 col5\" >2.78E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+       "                        <td id=\"T_cf59d_row8_col0\" class=\"data row8 col0\" >B26L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row8_col1\" class=\"data row8 col1\" >DCQDB.A26L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row8_col2\" class=\"data row8 col2\" >MQ.27L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row8_col3\" class=\"data row8 col3\" >MQ.25L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row8_col4\" class=\"data row8 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row8_col5\" class=\"data row8 col5\" >3.23E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+       "                        <td id=\"T_cf59d_row9_col0\" class=\"data row9 col0\" >B28L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row9_col1\" class=\"data row9 col1\" >DCQDB.A28L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row9_col2\" class=\"data row9 col2\" >MQ.29L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row9_col3\" class=\"data row9 col3\" >MQ.27L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row9_col4\" class=\"data row9 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row9_col5\" class=\"data row9 col5\" >2.61E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+       "                        <td id=\"T_cf59d_row10_col0\" class=\"data row10 col0\" >B30L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row10_col1\" class=\"data row10 col1\" >DCQDB.A30L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row10_col2\" class=\"data row10 col2\" >MQ.31L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row10_col3\" class=\"data row10 col3\" >MQ.29L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row10_col4\" class=\"data row10 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row10_col5\" class=\"data row10 col5\" >2.35E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+       "                        <td id=\"T_cf59d_row11_col0\" class=\"data row11 col0\" >B32L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row11_col1\" class=\"data row11 col1\" >DCQDB.A32L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row11_col2\" class=\"data row11 col2\" >MQ.33L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row11_col3\" class=\"data row11 col3\" >MQ.31L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row11_col4\" class=\"data row11 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row11_col5\" class=\"data row11 col5\" >2.59E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+       "                        <td id=\"T_cf59d_row12_col0\" class=\"data row12 col0\" >B33R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row12_col1\" class=\"data row12 col1\" >DCQDQ.32R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row12_col2\" class=\"data row12 col2\" >MQ.34R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row12_col3\" class=\"data row12 col3\" >MQ.32R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row12_col4\" class=\"data row12 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row12_col5\" class=\"data row12 col5\" >2.93E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
+       "                        <td id=\"T_cf59d_row13_col0\" class=\"data row13 col0\" >B31R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row13_col1\" class=\"data row13 col1\" >DCQDQ.30R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row13_col2\" class=\"data row13 col2\" >MQ.32R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row13_col3\" class=\"data row13 col3\" >MQ.30R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row13_col4\" class=\"data row13 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row13_col5\" class=\"data row13 col5\" >2.54E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
+       "                        <td id=\"T_cf59d_row14_col0\" class=\"data row14 col0\" >B29R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row14_col1\" class=\"data row14 col1\" >DCQDQ.28R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row14_col2\" class=\"data row14 col2\" >MQ.30R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row14_col3\" class=\"data row14 col3\" >MQ.28R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row14_col4\" class=\"data row14 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row14_col5\" class=\"data row14 col5\" >2.48E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
+       "                        <td id=\"T_cf59d_row15_col0\" class=\"data row15 col0\" >B27R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row15_col1\" class=\"data row15 col1\" >DCQDQ.26R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row15_col2\" class=\"data row15 col2\" >MQ.28R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row15_col3\" class=\"data row15 col3\" >MQ.26R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row15_col4\" class=\"data row15 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row15_col5\" class=\"data row15 col5\" >2.89E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
+       "                        <td id=\"T_cf59d_row16_col0\" class=\"data row16 col0\" >B25R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row16_col1\" class=\"data row16 col1\" >DCQDQ.24R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row16_col2\" class=\"data row16 col2\" >MQ.26R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row16_col3\" class=\"data row16 col3\" >MQ.24R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row16_col4\" class=\"data row16 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row16_col5\" class=\"data row16 col5\" >2.95E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
+       "                        <td id=\"T_cf59d_row17_col0\" class=\"data row17 col0\" >B23R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row17_col1\" class=\"data row17 col1\" >DCQDQ.22R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row17_col2\" class=\"data row17 col2\" >MQ.24R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row17_col3\" class=\"data row17 col3\" >MQ.22R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row17_col4\" class=\"data row17 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row17_col5\" class=\"data row17 col5\" >3.59E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
+       "                        <td id=\"T_cf59d_row18_col0\" class=\"data row18 col0\" >B21R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row18_col1\" class=\"data row18 col1\" >DCQDQ.20R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row18_col2\" class=\"data row18 col2\" >MQ.22R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row18_col3\" class=\"data row18 col3\" >MQ.20R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row18_col4\" class=\"data row18 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row18_col5\" class=\"data row18 col5\" >2.41E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
+       "                        <td id=\"T_cf59d_row19_col0\" class=\"data row19 col0\" >B19R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row19_col1\" class=\"data row19 col1\" >DCQDQ.18R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row19_col2\" class=\"data row19 col2\" >MQ.20R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row19_col3\" class=\"data row19 col3\" >MQ.18R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row19_col4\" class=\"data row19 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row19_col5\" class=\"data row19 col5\" >3.60E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
+       "                        <td id=\"T_cf59d_row20_col0\" class=\"data row20 col0\" >B17R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row20_col1\" class=\"data row20 col1\" >DCQDQ.16R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row20_col2\" class=\"data row20 col2\" >MQ.18R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row20_col3\" class=\"data row20 col3\" >MQ.16R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row20_col4\" class=\"data row20 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row20_col5\" class=\"data row20 col5\" >2.20E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
+       "                        <td id=\"T_cf59d_row21_col0\" class=\"data row21 col0\" >B15R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row21_col1\" class=\"data row21 col1\" >DCQDQ.14R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row21_col2\" class=\"data row21 col2\" >MQ.16R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row21_col3\" class=\"data row21 col3\" >MQ.14R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row21_col4\" class=\"data row21 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row21_col5\" class=\"data row21 col5\" >2.62E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
+       "                        <td id=\"T_cf59d_row22_col0\" class=\"data row22 col0\" >B13R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row22_col1\" class=\"data row22 col1\" >DCQDQ.12R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row22_col2\" class=\"data row22 col2\" >MQ.14R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row22_col3\" class=\"data row22 col3\" >MQ.12R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row22_col4\" class=\"data row22 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row22_col5\" class=\"data row22 col5\" >2.93E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
+       "                        <td id=\"T_cf59d_row23_col0\" class=\"data row23 col0\" >B11R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row23_col1\" class=\"data row23 col1\" >DCQDE.11R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row23_col2\" class=\"data row23 col2\" >MQ.12R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row23_col3\" class=\"data row23 col3\" >MQ.11R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row23_col4\" class=\"data row23 col4\" >6</td>\n",
+       "                        <td id=\"T_cf59d_row23_col5\" class=\"data row23 col5\" >1.90E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
+       "                        <td id=\"T_cf59d_row24_col0\" class=\"data row24 col0\" >B12R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row24_col1\" class=\"data row24 col1\" >DCQDB.C13R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row24_col2\" class=\"data row24 col2\" >MQ.11R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row24_col3\" class=\"data row24 col3\" >MQ.13R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row24_col4\" class=\"data row24 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row24_col5\" class=\"data row24 col5\" >2.56E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
+       "                        <td id=\"T_cf59d_row25_col0\" class=\"data row25 col0\" >B14R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row25_col1\" class=\"data row25 col1\" >DCQDB.C15R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row25_col2\" class=\"data row25 col2\" >MQ.13R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row25_col3\" class=\"data row25 col3\" >MQ.15R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row25_col4\" class=\"data row25 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row25_col5\" class=\"data row25 col5\" >2.52E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
+       "                        <td id=\"T_cf59d_row26_col0\" class=\"data row26 col0\" >B16R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row26_col1\" class=\"data row26 col1\" >DCQDB.C17R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row26_col2\" class=\"data row26 col2\" >MQ.15R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row26_col3\" class=\"data row26 col3\" >MQ.17R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row26_col4\" class=\"data row26 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row26_col5\" class=\"data row26 col5\" >2.77E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
+       "                        <td id=\"T_cf59d_row27_col0\" class=\"data row27 col0\" >B18R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row27_col1\" class=\"data row27 col1\" >DCQDB.C19R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row27_col2\" class=\"data row27 col2\" >MQ.17R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row27_col3\" class=\"data row27 col3\" >MQ.19R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row27_col4\" class=\"data row27 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row27_col5\" class=\"data row27 col5\" >3.03E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
+       "                        <td id=\"T_cf59d_row28_col0\" class=\"data row28 col0\" >B20R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row28_col1\" class=\"data row28 col1\" >DCQDB.C21R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row28_col2\" class=\"data row28 col2\" >MQ.19R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row28_col3\" class=\"data row28 col3\" >MQ.21R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row28_col4\" class=\"data row28 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row28_col5\" class=\"data row28 col5\" >3.46E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
+       "                        <td id=\"T_cf59d_row29_col0\" class=\"data row29 col0\" >B22R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row29_col1\" class=\"data row29 col1\" >DCQDB.C23R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row29_col2\" class=\"data row29 col2\" >MQ.21R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row29_col3\" class=\"data row29 col3\" >MQ.23R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row29_col4\" class=\"data row29 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row29_col5\" class=\"data row29 col5\" >2.65E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
+       "                        <td id=\"T_cf59d_row30_col0\" class=\"data row30 col0\" >B24R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row30_col1\" class=\"data row30 col1\" >DCQDB.C25R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row30_col2\" class=\"data row30 col2\" >MQ.23R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row30_col3\" class=\"data row30 col3\" >MQ.25R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row30_col4\" class=\"data row30 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row30_col5\" class=\"data row30 col5\" >3.00E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
+       "                        <td id=\"T_cf59d_row31_col0\" class=\"data row31 col0\" >B26R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row31_col1\" class=\"data row31 col1\" >DCQDB.C27R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row31_col2\" class=\"data row31 col2\" >MQ.25R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row31_col3\" class=\"data row31 col3\" >MQ.27R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row31_col4\" class=\"data row31 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row31_col5\" class=\"data row31 col5\" >2.74E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
+       "                        <td id=\"T_cf59d_row32_col0\" class=\"data row32 col0\" >B28R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row32_col1\" class=\"data row32 col1\" >DCQDB.C29R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row32_col2\" class=\"data row32 col2\" >MQ.27R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row32_col3\" class=\"data row32 col3\" >MQ.29R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row32_col4\" class=\"data row32 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row32_col5\" class=\"data row32 col5\" >2.87E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
+       "                        <td id=\"T_cf59d_row33_col0\" class=\"data row33 col0\" >B30R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row33_col1\" class=\"data row33 col1\" >DCQDB.C31R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row33_col2\" class=\"data row33 col2\" >MQ.29R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row33_col3\" class=\"data row33 col3\" >MQ.31R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row33_col4\" class=\"data row33 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row33_col5\" class=\"data row33 col5\" >2.65E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
+       "                        <td id=\"T_cf59d_row34_col0\" class=\"data row34 col0\" >B32R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row34_col1\" class=\"data row34 col1\" >DCQDB.C33R1.L</td>\n",
+       "                        <td id=\"T_cf59d_row34_col2\" class=\"data row34 col2\" >MQ.31R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row34_col3\" class=\"data row34 col3\" >MQ.33R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row34_col4\" class=\"data row34 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row34_col5\" class=\"data row34 col5\" >2.74E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
+       "                        <td id=\"T_cf59d_row35_col0\" class=\"data row35 col0\" >B34R1_3</td>\n",
+       "                        <td id=\"T_cf59d_row35_col1\" class=\"data row35 col1\" >DCQDB.A34L2.L</td>\n",
+       "                        <td id=\"T_cf59d_row35_col2\" class=\"data row35 col2\" >MQ.33R1.B2</td>\n",
+       "                        <td id=\"T_cf59d_row35_col3\" class=\"data row35 col3\" >MQ.33L2.B2</td>\n",
+       "                        <td id=\"T_cf59d_row35_col4\" class=\"data row35 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row35_col5\" class=\"data row35 col5\" >2.92E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
+       "                        <td id=\"T_cf59d_row36_col0\" class=\"data row36 col0\" >B33L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row36_col1\" class=\"data row36 col1\" >DCQDQ.34R1.R</td>\n",
+       "                        <td id=\"T_cf59d_row36_col2\" class=\"data row36 col2\" >MQ.32L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row36_col3\" class=\"data row36 col3\" >MQ.34R1.B1</td>\n",
+       "                        <td id=\"T_cf59d_row36_col4\" class=\"data row36 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row36_col5\" class=\"data row36 col5\" >2.81E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
+       "                        <td id=\"T_cf59d_row37_col0\" class=\"data row37 col0\" >B31L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row37_col1\" class=\"data row37 col1\" >DCQDQ.32L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row37_col2\" class=\"data row37 col2\" >MQ.30L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row37_col3\" class=\"data row37 col3\" >MQ.32L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row37_col4\" class=\"data row37 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row37_col5\" class=\"data row37 col5\" >2.92E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
+       "                        <td id=\"T_cf59d_row38_col0\" class=\"data row38 col0\" >B29L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row38_col1\" class=\"data row38 col1\" >DCQDQ.30L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row38_col2\" class=\"data row38 col2\" >MQ.28L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row38_col3\" class=\"data row38 col3\" >MQ.30L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row38_col4\" class=\"data row38 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row38_col5\" class=\"data row38 col5\" >2.96E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
+       "                        <td id=\"T_cf59d_row39_col0\" class=\"data row39 col0\" >B27L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row39_col1\" class=\"data row39 col1\" >DCQDQ.28L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row39_col2\" class=\"data row39 col2\" >MQ.26L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row39_col3\" class=\"data row39 col3\" >MQ.28L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row39_col4\" class=\"data row39 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row39_col5\" class=\"data row39 col5\" >2.50E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
+       "                        <td id=\"T_cf59d_row40_col0\" class=\"data row40 col0\" >B25L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row40_col1\" class=\"data row40 col1\" >DCQDQ.26L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row40_col2\" class=\"data row40 col2\" >MQ.24L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row40_col3\" class=\"data row40 col3\" >MQ.26L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row40_col4\" class=\"data row40 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row40_col5\" class=\"data row40 col5\" >2.47E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
+       "                        <td id=\"T_cf59d_row41_col0\" class=\"data row41 col0\" >B23L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row41_col1\" class=\"data row41 col1\" >DCQDQ.24L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row41_col2\" class=\"data row41 col2\" >MQ.22L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row41_col3\" class=\"data row41 col3\" >MQ.24L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row41_col4\" class=\"data row41 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row41_col5\" class=\"data row41 col5\" >3.18E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
+       "                        <td id=\"T_cf59d_row42_col0\" class=\"data row42 col0\" >B21L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row42_col1\" class=\"data row42 col1\" >DCQDQ.22L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row42_col2\" class=\"data row42 col2\" >MQ.20L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row42_col3\" class=\"data row42 col3\" >MQ.22L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row42_col4\" class=\"data row42 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row42_col5\" class=\"data row42 col5\" >2.81E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
+       "                        <td id=\"T_cf59d_row43_col0\" class=\"data row43 col0\" >B19L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row43_col1\" class=\"data row43 col1\" >DCQDQ.20L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row43_col2\" class=\"data row43 col2\" >MQ.18L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row43_col3\" class=\"data row43 col3\" >MQ.20L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row43_col4\" class=\"data row43 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row43_col5\" class=\"data row43 col5\" >2.94E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
+       "                        <td id=\"T_cf59d_row44_col0\" class=\"data row44 col0\" >B17L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row44_col1\" class=\"data row44 col1\" >DCQDQ.18L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row44_col2\" class=\"data row44 col2\" >MQ.16L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row44_col3\" class=\"data row44 col3\" >MQ.18L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row44_col4\" class=\"data row44 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row44_col5\" class=\"data row44 col5\" >2.84E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
+       "                        <td id=\"T_cf59d_row45_col0\" class=\"data row45 col0\" >B15L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row45_col1\" class=\"data row45 col1\" >DCQDQ.16L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row45_col2\" class=\"data row45 col2\" >MQ.14L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row45_col3\" class=\"data row45 col3\" >MQ.16L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row45_col4\" class=\"data row45 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row45_col5\" class=\"data row45 col5\" >2.47E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
+       "                        <td id=\"T_cf59d_row46_col0\" class=\"data row46 col0\" >B13L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row46_col1\" class=\"data row46 col1\" >DCQDQ.14L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row46_col2\" class=\"data row46 col2\" >MQ.12L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row46_col3\" class=\"data row46 col3\" >MQ.14L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row46_col4\" class=\"data row46 col4\" >8</td>\n",
+       "                        <td id=\"T_cf59d_row46_col5\" class=\"data row46 col5\" >2.56E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_cf59d_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
+       "                        <td id=\"T_cf59d_row47_col0\" class=\"data row47 col0\" >B11L2_3</td>\n",
+       "                        <td id=\"T_cf59d_row47_col1\" class=\"data row47 col1\" >DCQDQ.12L2.R</td>\n",
+       "                        <td id=\"T_cf59d_row47_col2\" class=\"data row47 col2\" >DFLAS.7L2.1</td>\n",
+       "                        <td id=\"T_cf59d_row47_col3\" class=\"data row47 col3\" >MQ.12L2.B1</td>\n",
+       "                        <td id=\"T_cf59d_row47_col4\" class=\"data row47 col4\" >20</td>\n",
+       "                        <td id=\"T_cf59d_row47_col5\" class=\"data row47 col5\" >5.95E-09</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fd3b716eb20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_busbar_rqd_df.empty:\n",
     "    rqd_busbar_metadata_resistance_df = rq_analysis.merge_busbar_metadata_with_resistance(res_busbar_rqd_df, circuit_type, circuit_names)\n",
@@ -2432,13 +2947,13 @@
   },
   {
    "cell_type": "markdown",
-   "id": "696f7d4f",
+   "id": "0ca785e9",
    "metadata": {
     "papermill": {
-     "duration": 0.48154,
-     "end_time": "2021-11-09T08:45:41.907429",
+     "duration": 0.1352,
+     "end_time": "2022-02-21T15:37:51.966696",
      "exception": false,
-     "start_time": "2021-11-09T08:45:41.425889",
+     "start_time": "2022-02-21T15:37:51.831496",
      "status": "completed"
     },
     "tags": []
@@ -2450,53 +2965,74 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "ea0ec09a",
+   "id": "dd7b5f8f",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:42.846893Z",
-     "iopub.status.busy": "2021-11-09T08:45:42.846030Z",
-     "iopub.status.idle": "2021-11-09T08:45:42.850828Z",
-     "shell.execute_reply": "2021-11-09T08:45:42.850114Z"
+     "iopub.execute_input": "2022-02-21T15:37:52.234765Z",
+     "iopub.status.busy": "2022-02-21T15:37:52.234427Z",
+     "iopub.status.idle": "2022-02-21T15:37:52.908620Z",
+     "shell.execute_reply": "2022-02-21T15:37:52.907876Z"
     },
     "papermill": {
-     "duration": 0.487154,
-     "end_time": "2021-11-09T08:45:42.851035",
+     "duration": 0.810637,
+     "end_time": "2022-02-21T15:37:52.910707",
      "exception": false,
-     "start_time": "2021-11-09T08:45:42.363881",
+     "start_time": "2022-02-21T15:37:52.100070",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 936x468 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_busbar_rqf_df.empty:\n",
     "    title = '%s, %s: %s-%s' % (circuit_names[1], hwc_test, Time.to_string(t_start).split('.')[0], Time.to_string(t_end).split('.')[0])\n",
-    "    res_busbar_rqf_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_busbar_rqf_df, signal_name='R_RES', max_value=10e-9, title=title)"
+    "    res_busbar_rqf_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_busbar_rqf_df, signal_name='R_RES', value_max=10e-9, title=title)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "5906a2a9",
+   "id": "078ce05e",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:43.731803Z",
-     "iopub.status.busy": "2021-11-09T08:45:43.731024Z",
-     "iopub.status.idle": "2021-11-09T08:45:43.737174Z",
-     "shell.execute_reply": "2021-11-09T08:45:43.736497Z"
+     "iopub.execute_input": "2022-02-21T15:37:53.180690Z",
+     "iopub.status.busy": "2022-02-21T15:37:53.180339Z",
+     "iopub.status.idle": "2022-02-21T15:37:53.186182Z",
+     "shell.execute_reply": "2022-02-21T15:37:53.185442Z"
     },
     "papermill": {
-     "duration": 0.440429,
-     "end_time": "2021-11-09T08:45:43.737367",
+     "duration": 0.145274,
+     "end_time": "2022-02-21T15:37:53.188576",
      "exception": false,
-     "start_time": "2021-11-09T08:45:43.296938",
+     "start_time": "2022-02-21T15:37:53.043302",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All resistances within the range.\n"
+     ]
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_busbar_rqf_df.empty:\n",
     "    RqCircuitQuery.query_and_plot_outlier_voltage(res_busbar_rqf_outliers_df, t_start, t_end, i_meas_raw_nxcals_dfs[0].index[0], plateau_start, plateau_end, spark=spark)"
@@ -2505,128 +3041,596 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "31828c10",
+   "id": "7e0daf41",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:44.686328Z",
-     "iopub.status.busy": "2021-11-09T08:45:44.684786Z",
-     "iopub.status.idle": "2021-11-09T08:45:44.687176Z",
-     "shell.execute_reply": "2021-11-09T08:45:44.685582Z"
-    },
-    "papermill": {
-     "duration": 0.494816,
-     "end_time": "2021-11-09T08:45:44.687384",
-     "exception": false,
-     "start_time": "2021-11-09T08:45:44.192568",
-     "status": "completed"
-    },
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "if t_pnob3 > 1800 and not res_busbar_rqf_df.empty:\n",
-    "    rqf_busbar_metadata_resistance_df = rq_analysis.merge_busbar_metadata_with_resistance(res_busbar_rqf_df, circuit_type, circuit_names)\n",
-    "    rq_analysis.display_busbar_metadata_resistance_with_threshold(rqf_busbar_metadata_resistance_df, threshold=10e-9)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ec06c2da",
-   "metadata": {
-    "deletable": false,
-    "papermill": {
-     "duration": 0.43423,
-     "end_time": "2021-11-09T08:45:45.564457",
-     "exception": false,
-     "start_time": "2021-11-09T08:45:45.130227",
-     "status": "completed"
+     "iopub.execute_input": "2022-02-21T15:37:53.459564Z",
+     "iopub.status.busy": "2022-02-21T15:37:53.459221Z",
+     "iopub.status.idle": "2022-02-21T15:37:53.512539Z",
+     "shell.execute_reply": "2022-02-21T15:37:53.511761Z"
     },
-    "tags": []
-   },
-   "source": [
-    "## 7.2. Magnet Resistance\n",
-    "\n",
-    "*ANALYSIS*:\n",
-    "\n",
-    "- Calculation of the magnet resistance as the slope of a linear fit of U,I curve obtained from the corresponding mean alues of the voltage and current\n",
-    "\n",
-    "*CRITERIA*:\n",
-    "\n",
-    "- Check if the magnet resistance is below 50 nOhm\n",
-    "\n",
-    "*GRAPHS*:\n",
-    "\n",
-    "- The magnet resistance, R\n",
-    "- The green box denotes the validity region of the magnet resostance (0, 50] nOhm"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "1f88cac4",
-   "metadata": {
     "papermill": {
-     "duration": 0.428456,
-     "end_time": "2021-11-09T08:45:46.435831",
+     "duration": 0.191677,
+     "end_time": "2022-02-21T15:37:53.514970",
      "exception": false,
-     "start_time": "2021-11-09T08:45:46.007375",
+     "start_time": "2022-02-21T15:37:53.323293",
      "status": "completed"
     },
     "tags": []
    },
-   "source": [
-    "- RQD"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "id": "146d0a00",
-   "metadata": {
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_06bb7_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >QPS Crate&Board</th>        <th class=\"col_heading level0 col1\" >Bus Bar Segment Name</th>        <th class=\"col_heading level0 col2\" >1st Magnet</th>        <th class=\"col_heading level0 col3\" >2nd Magnet</th>        <th class=\"col_heading level0 col4\" >Num of splices</th>        <th class=\"col_heading level0 col5\" >R_RES</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_06bb7_row0_col0\" class=\"data row0 col0\" >B10L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row0_col1\" class=\"data row0 col1\" >DCQFD.7L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row0_col2\" class=\"data row0 col2\" >MQ.11L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row0_col3\" class=\"data row0 col3\" >DFLAS.7L2.4</td>\n",
+       "                        <td id=\"T_06bb7_row0_col4\" class=\"data row0 col4\" >16</td>\n",
+       "                        <td id=\"T_06bb7_row0_col5\" class=\"data row0 col5\" >5.20E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_06bb7_row1_col0\" class=\"data row1 col0\" >B12L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row1_col1\" class=\"data row1 col1\" >DCQFB.A12L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row1_col2\" class=\"data row1 col2\" >MQ.13L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row1_col3\" class=\"data row1 col3\" >MQ.11L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row1_col4\" class=\"data row1 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row1_col5\" class=\"data row1 col5\" >2.15E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_06bb7_row2_col0\" class=\"data row2 col0\" >B14L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row2_col1\" class=\"data row2 col1\" >DCQFB.A14L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row2_col2\" class=\"data row2 col2\" >MQ.15L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row2_col3\" class=\"data row2 col3\" >MQ.13L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row2_col4\" class=\"data row2 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row2_col5\" class=\"data row2 col5\" >2.52E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "                        <td id=\"T_06bb7_row3_col0\" class=\"data row3 col0\" >B16L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row3_col1\" class=\"data row3 col1\" >DCQFB.A16L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row3_col2\" class=\"data row3 col2\" >MQ.17L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row3_col3\" class=\"data row3 col3\" >MQ.15L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row3_col4\" class=\"data row3 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row3_col5\" class=\"data row3 col5\" >2.11E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "                        <td id=\"T_06bb7_row4_col0\" class=\"data row4 col0\" >B18L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row4_col1\" class=\"data row4 col1\" >DCQFB.A18L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row4_col2\" class=\"data row4 col2\" >MQ.19L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row4_col3\" class=\"data row4 col3\" >MQ.17L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row4_col4\" class=\"data row4 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row4_col5\" class=\"data row4 col5\" >2.35E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "                        <td id=\"T_06bb7_row5_col0\" class=\"data row5 col0\" >B20L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row5_col1\" class=\"data row5 col1\" >DCQFB.A20L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row5_col2\" class=\"data row5 col2\" >MQ.21L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row5_col3\" class=\"data row5 col3\" >MQ.19L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row5_col4\" class=\"data row5 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row5_col5\" class=\"data row5 col5\" >2.06E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "                        <td id=\"T_06bb7_row6_col0\" class=\"data row6 col0\" >B22L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row6_col1\" class=\"data row6 col1\" >DCQFB.A22L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row6_col2\" class=\"data row6 col2\" >MQ.23L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row6_col3\" class=\"data row6 col3\" >MQ.21L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row6_col4\" class=\"data row6 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row6_col5\" class=\"data row6 col5\" >2.36E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "                        <td id=\"T_06bb7_row7_col0\" class=\"data row7 col0\" >B24L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row7_col1\" class=\"data row7 col1\" >DCQFB.A24L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row7_col2\" class=\"data row7 col2\" >MQ.25L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row7_col3\" class=\"data row7 col3\" >MQ.23L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row7_col4\" class=\"data row7 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row7_col5\" class=\"data row7 col5\" >2.42E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+       "                        <td id=\"T_06bb7_row8_col0\" class=\"data row8 col0\" >B26L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row8_col1\" class=\"data row8 col1\" >DCQFB.A26L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row8_col2\" class=\"data row8 col2\" >MQ.27L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row8_col3\" class=\"data row8 col3\" >MQ.25L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row8_col4\" class=\"data row8 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row8_col5\" class=\"data row8 col5\" >2.28E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+       "                        <td id=\"T_06bb7_row9_col0\" class=\"data row9 col0\" >B28L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row9_col1\" class=\"data row9 col1\" >DCQFB.A28L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row9_col2\" class=\"data row9 col2\" >MQ.29L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row9_col3\" class=\"data row9 col3\" >MQ.27L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row9_col4\" class=\"data row9 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row9_col5\" class=\"data row9 col5\" >2.55E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+       "                        <td id=\"T_06bb7_row10_col0\" class=\"data row10 col0\" >B30L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row10_col1\" class=\"data row10 col1\" >DCQFB.A30L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row10_col2\" class=\"data row10 col2\" >MQ.31L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row10_col3\" class=\"data row10 col3\" >MQ.29L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row10_col4\" class=\"data row10 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row10_col5\" class=\"data row10 col5\" >2.33E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+       "                        <td id=\"T_06bb7_row11_col0\" class=\"data row11 col0\" >B32L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row11_col1\" class=\"data row11 col1\" >DCQFB.C32L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row11_col2\" class=\"data row11 col2\" >MQ.33L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row11_col3\" class=\"data row11 col3\" >MQ.31L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row11_col4\" class=\"data row11 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row11_col5\" class=\"data row11 col5\" >2.51E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+       "                        <td id=\"T_06bb7_row12_col0\" class=\"data row12 col0\" >B33R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row12_col1\" class=\"data row12 col1\" >DCQFQ.32R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row12_col2\" class=\"data row12 col2\" >MQ.34R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row12_col3\" class=\"data row12 col3\" >MQ.32R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row12_col4\" class=\"data row12 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row12_col5\" class=\"data row12 col5\" >2.74E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
+       "                        <td id=\"T_06bb7_row13_col0\" class=\"data row13 col0\" >B31R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row13_col1\" class=\"data row13 col1\" >DCQFQ.30R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row13_col2\" class=\"data row13 col2\" >MQ.32R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row13_col3\" class=\"data row13 col3\" >MQ.30R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row13_col4\" class=\"data row13 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row13_col5\" class=\"data row13 col5\" >2.34E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
+       "                        <td id=\"T_06bb7_row14_col0\" class=\"data row14 col0\" >B29R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row14_col1\" class=\"data row14 col1\" >DCQFQ.28R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row14_col2\" class=\"data row14 col2\" >MQ.30R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row14_col3\" class=\"data row14 col3\" >MQ.28R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row14_col4\" class=\"data row14 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row14_col5\" class=\"data row14 col5\" >2.44E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
+       "                        <td id=\"T_06bb7_row15_col0\" class=\"data row15 col0\" >B27R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row15_col1\" class=\"data row15 col1\" >DCQFQ.26R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row15_col2\" class=\"data row15 col2\" >MQ.28R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row15_col3\" class=\"data row15 col3\" >MQ.26R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row15_col4\" class=\"data row15 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row15_col5\" class=\"data row15 col5\" >2.55E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
+       "                        <td id=\"T_06bb7_row16_col0\" class=\"data row16 col0\" >B25R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row16_col1\" class=\"data row16 col1\" >DCQFQ.24R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row16_col2\" class=\"data row16 col2\" >MQ.26R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row16_col3\" class=\"data row16 col3\" >MQ.24R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row16_col4\" class=\"data row16 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row16_col5\" class=\"data row16 col5\" >2.60E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
+       "                        <td id=\"T_06bb7_row17_col0\" class=\"data row17 col0\" >B23R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row17_col1\" class=\"data row17 col1\" >DCQFQ.22R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row17_col2\" class=\"data row17 col2\" >MQ.24R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row17_col3\" class=\"data row17 col3\" >MQ.22R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row17_col4\" class=\"data row17 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row17_col5\" class=\"data row17 col5\" >2.76E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
+       "                        <td id=\"T_06bb7_row18_col0\" class=\"data row18 col0\" >B21R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row18_col1\" class=\"data row18 col1\" >DCQFQ.20R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row18_col2\" class=\"data row18 col2\" >MQ.22R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row18_col3\" class=\"data row18 col3\" >MQ.20R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row18_col4\" class=\"data row18 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row18_col5\" class=\"data row18 col5\" >2.58E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
+       "                        <td id=\"T_06bb7_row19_col0\" class=\"data row19 col0\" >B19R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row19_col1\" class=\"data row19 col1\" >DCQFQ.18R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row19_col2\" class=\"data row19 col2\" >MQ.20R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row19_col3\" class=\"data row19 col3\" >MQ.18R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row19_col4\" class=\"data row19 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row19_col5\" class=\"data row19 col5\" >2.65E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
+       "                        <td id=\"T_06bb7_row20_col0\" class=\"data row20 col0\" >B17R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row20_col1\" class=\"data row20 col1\" >DCQFQ.16R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row20_col2\" class=\"data row20 col2\" >MQ.18R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row20_col3\" class=\"data row20 col3\" >MQ.16R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row20_col4\" class=\"data row20 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row20_col5\" class=\"data row20 col5\" >2.24E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
+       "                        <td id=\"T_06bb7_row21_col0\" class=\"data row21 col0\" >B15R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row21_col1\" class=\"data row21 col1\" >DCQFQ.14R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row21_col2\" class=\"data row21 col2\" >MQ.16R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row21_col3\" class=\"data row21 col3\" >MQ.14R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row21_col4\" class=\"data row21 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row21_col5\" class=\"data row21 col5\" >2.30E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
+       "                        <td id=\"T_06bb7_row22_col0\" class=\"data row22 col0\" >B13R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row22_col1\" class=\"data row22 col1\" >DCQFQ.12R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row22_col2\" class=\"data row22 col2\" >MQ.14R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row22_col3\" class=\"data row22 col3\" >MQ.12R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row22_col4\" class=\"data row22 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row22_col5\" class=\"data row22 col5\" >2.31E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
+       "                        <td id=\"T_06bb7_row23_col0\" class=\"data row23 col0\" >B11R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row23_col1\" class=\"data row23 col1\" >DCQFE.11R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row23_col2\" class=\"data row23 col2\" >MQ.12R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row23_col3\" class=\"data row23 col3\" >MQ.11R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row23_col4\" class=\"data row23 col4\" >6</td>\n",
+       "                        <td id=\"T_06bb7_row23_col5\" class=\"data row23 col5\" >2.14E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
+       "                        <td id=\"T_06bb7_row24_col0\" class=\"data row24 col0\" >B12R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row24_col1\" class=\"data row24 col1\" >DCQFB.C13R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row24_col2\" class=\"data row24 col2\" >MQ.11R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row24_col3\" class=\"data row24 col3\" >MQ.13R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row24_col4\" class=\"data row24 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row24_col5\" class=\"data row24 col5\" >2.87E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
+       "                        <td id=\"T_06bb7_row25_col0\" class=\"data row25 col0\" >B14R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row25_col1\" class=\"data row25 col1\" >DCQFB.A15R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row25_col2\" class=\"data row25 col2\" >MQ.13R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row25_col3\" class=\"data row25 col3\" >MQ.15R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row25_col4\" class=\"data row25 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row25_col5\" class=\"data row25 col5\" >2.30E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
+       "                        <td id=\"T_06bb7_row26_col0\" class=\"data row26 col0\" >B16R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row26_col1\" class=\"data row26 col1\" >DCQFB.C17R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row26_col2\" class=\"data row26 col2\" >MQ.15R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row26_col3\" class=\"data row26 col3\" >MQ.17R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row26_col4\" class=\"data row26 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row26_col5\" class=\"data row26 col5\" >2.51E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
+       "                        <td id=\"T_06bb7_row27_col0\" class=\"data row27 col0\" >B18R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row27_col1\" class=\"data row27 col1\" >DCQFB.C19R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row27_col2\" class=\"data row27 col2\" >MQ.17R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row27_col3\" class=\"data row27 col3\" >MQ.19R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row27_col4\" class=\"data row27 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row27_col5\" class=\"data row27 col5\" >2.87E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
+       "                        <td id=\"T_06bb7_row28_col0\" class=\"data row28 col0\" >B20R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row28_col1\" class=\"data row28 col1\" >DCQFB.C21R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row28_col2\" class=\"data row28 col2\" >MQ.19R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row28_col3\" class=\"data row28 col3\" >MQ.21R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row28_col4\" class=\"data row28 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row28_col5\" class=\"data row28 col5\" >2.67E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
+       "                        <td id=\"T_06bb7_row29_col0\" class=\"data row29 col0\" >B22R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row29_col1\" class=\"data row29 col1\" >DCQFB.C23R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row29_col2\" class=\"data row29 col2\" >MQ.21R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row29_col3\" class=\"data row29 col3\" >MQ.23R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row29_col4\" class=\"data row29 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row29_col5\" class=\"data row29 col5\" >2.41E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
+       "                        <td id=\"T_06bb7_row30_col0\" class=\"data row30 col0\" >B24R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row30_col1\" class=\"data row30 col1\" >DCQFB.C25R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row30_col2\" class=\"data row30 col2\" >MQ.23R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row30_col3\" class=\"data row30 col3\" >MQ.25R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row30_col4\" class=\"data row30 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row30_col5\" class=\"data row30 col5\" >2.78E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
+       "                        <td id=\"T_06bb7_row31_col0\" class=\"data row31 col0\" >B26R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row31_col1\" class=\"data row31 col1\" >DCQFB.C27R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row31_col2\" class=\"data row31 col2\" >MQ.25R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row31_col3\" class=\"data row31 col3\" >MQ.27R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row31_col4\" class=\"data row31 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row31_col5\" class=\"data row31 col5\" >2.61E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
+       "                        <td id=\"T_06bb7_row32_col0\" class=\"data row32 col0\" >B28R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row32_col1\" class=\"data row32 col1\" >DCQFB.C29R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row32_col2\" class=\"data row32 col2\" >MQ.27R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row32_col3\" class=\"data row32 col3\" >MQ.29R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row32_col4\" class=\"data row32 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row32_col5\" class=\"data row32 col5\" >2.71E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
+       "                        <td id=\"T_06bb7_row33_col0\" class=\"data row33 col0\" >B30R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row33_col1\" class=\"data row33 col1\" >DCQFB.C31R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row33_col2\" class=\"data row33 col2\" >MQ.29R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row33_col3\" class=\"data row33 col3\" >MQ.31R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row33_col4\" class=\"data row33 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row33_col5\" class=\"data row33 col5\" >2.07E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
+       "                        <td id=\"T_06bb7_row34_col0\" class=\"data row34 col0\" >B32R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row34_col1\" class=\"data row34 col1\" >DCQFB.C33R1.R</td>\n",
+       "                        <td id=\"T_06bb7_row34_col2\" class=\"data row34 col2\" >MQ.31R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row34_col3\" class=\"data row34 col3\" >MQ.33R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row34_col4\" class=\"data row34 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row34_col5\" class=\"data row34 col5\" >2.23E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
+       "                        <td id=\"T_06bb7_row35_col0\" class=\"data row35 col0\" >B34R1_4</td>\n",
+       "                        <td id=\"T_06bb7_row35_col1\" class=\"data row35 col1\" >DCQFB.A34L2.R</td>\n",
+       "                        <td id=\"T_06bb7_row35_col2\" class=\"data row35 col2\" >MQ.33R1.B1</td>\n",
+       "                        <td id=\"T_06bb7_row35_col3\" class=\"data row35 col3\" >MQ.33L2.B1</td>\n",
+       "                        <td id=\"T_06bb7_row35_col4\" class=\"data row35 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row35_col5\" class=\"data row35 col5\" >2.75E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
+       "                        <td id=\"T_06bb7_row36_col0\" class=\"data row36 col0\" >B33L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row36_col1\" class=\"data row36 col1\" >DCQFQ.34R1.L</td>\n",
+       "                        <td id=\"T_06bb7_row36_col2\" class=\"data row36 col2\" >MQ.32L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row36_col3\" class=\"data row36 col3\" >MQ.34R1.B2</td>\n",
+       "                        <td id=\"T_06bb7_row36_col4\" class=\"data row36 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row36_col5\" class=\"data row36 col5\" >2.56E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
+       "                        <td id=\"T_06bb7_row37_col0\" class=\"data row37 col0\" >B31L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row37_col1\" class=\"data row37 col1\" >DCQFQ.32L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row37_col2\" class=\"data row37 col2\" >MQ.30L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row37_col3\" class=\"data row37 col3\" >MQ.32L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row37_col4\" class=\"data row37 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row37_col5\" class=\"data row37 col5\" >2.73E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
+       "                        <td id=\"T_06bb7_row38_col0\" class=\"data row38 col0\" >B29L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row38_col1\" class=\"data row38 col1\" >DCQFQ.30L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row38_col2\" class=\"data row38 col2\" >MQ.28L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row38_col3\" class=\"data row38 col3\" >MQ.30L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row38_col4\" class=\"data row38 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row38_col5\" class=\"data row38 col5\" >2.30E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
+       "                        <td id=\"T_06bb7_row39_col0\" class=\"data row39 col0\" >B27L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row39_col1\" class=\"data row39 col1\" >DCQFQ.28L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row39_col2\" class=\"data row39 col2\" >MQ.26L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row39_col3\" class=\"data row39 col3\" >MQ.28L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row39_col4\" class=\"data row39 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row39_col5\" class=\"data row39 col5\" >2.42E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
+       "                        <td id=\"T_06bb7_row40_col0\" class=\"data row40 col0\" >B25L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row40_col1\" class=\"data row40 col1\" >DCQFQ.26L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row40_col2\" class=\"data row40 col2\" >MQ.24L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row40_col3\" class=\"data row40 col3\" >MQ.26L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row40_col4\" class=\"data row40 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row40_col5\" class=\"data row40 col5\" >2.17E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
+       "                        <td id=\"T_06bb7_row41_col0\" class=\"data row41 col0\" >B23L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row41_col1\" class=\"data row41 col1\" >DCQFQ.24L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row41_col2\" class=\"data row41 col2\" >MQ.22L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row41_col3\" class=\"data row41 col3\" >MQ.24L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row41_col4\" class=\"data row41 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row41_col5\" class=\"data row41 col5\" >2.56E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
+       "                        <td id=\"T_06bb7_row42_col0\" class=\"data row42 col0\" >B21L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row42_col1\" class=\"data row42 col1\" >DCQFQ.22L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row42_col2\" class=\"data row42 col2\" >MQ.20L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row42_col3\" class=\"data row42 col3\" >MQ.22L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row42_col4\" class=\"data row42 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row42_col5\" class=\"data row42 col5\" >2.44E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
+       "                        <td id=\"T_06bb7_row43_col0\" class=\"data row43 col0\" >B19L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row43_col1\" class=\"data row43 col1\" >DCQFQ.20L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row43_col2\" class=\"data row43 col2\" >MQ.18L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row43_col3\" class=\"data row43 col3\" >MQ.20L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row43_col4\" class=\"data row43 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row43_col5\" class=\"data row43 col5\" >2.57E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
+       "                        <td id=\"T_06bb7_row44_col0\" class=\"data row44 col0\" >B17L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row44_col1\" class=\"data row44 col1\" >DCQFQ.18L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row44_col2\" class=\"data row44 col2\" >MQ.16L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row44_col3\" class=\"data row44 col3\" >MQ.18L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row44_col4\" class=\"data row44 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row44_col5\" class=\"data row44 col5\" >2.29E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
+       "                        <td id=\"T_06bb7_row45_col0\" class=\"data row45 col0\" >B15L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row45_col1\" class=\"data row45 col1\" >DCQFQ.16L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row45_col2\" class=\"data row45 col2\" >MQ.14L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row45_col3\" class=\"data row45 col3\" >MQ.16L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row45_col4\" class=\"data row45 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row45_col5\" class=\"data row45 col5\" >2.37E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
+       "                        <td id=\"T_06bb7_row46_col0\" class=\"data row46 col0\" >B13L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row46_col1\" class=\"data row46 col1\" >DCQFQ.14L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row46_col2\" class=\"data row46 col2\" >MQ.12L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row46_col3\" class=\"data row46 col3\" >MQ.14L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row46_col4\" class=\"data row46 col4\" >8</td>\n",
+       "                        <td id=\"T_06bb7_row46_col5\" class=\"data row46 col5\" >2.28E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06bb7_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
+       "                        <td id=\"T_06bb7_row47_col0\" class=\"data row47 col0\" >B11L2_4</td>\n",
+       "                        <td id=\"T_06bb7_row47_col1\" class=\"data row47 col1\" >DCQFQ.12L2.L</td>\n",
+       "                        <td id=\"T_06bb7_row47_col2\" class=\"data row47 col2\" >DFLAS.7L2.3</td>\n",
+       "                        <td id=\"T_06bb7_row47_col3\" class=\"data row47 col3\" >MQ.12L2.B2</td>\n",
+       "                        <td id=\"T_06bb7_row47_col4\" class=\"data row47 col4\" >20</td>\n",
+       "                        <td id=\"T_06bb7_row47_col5\" class=\"data row47 col5\" >6.21E-09</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fd3bbc09ac0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if t_pnob3 > 1800 and not res_busbar_rqf_df.empty:\n",
+    "    rqf_busbar_metadata_resistance_df = rq_analysis.merge_busbar_metadata_with_resistance(res_busbar_rqf_df, circuit_type, circuit_names)\n",
+    "    rq_analysis.display_busbar_metadata_resistance_with_threshold(rqf_busbar_metadata_resistance_df, threshold=10e-9)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e117716a",
+   "metadata": {
+    "deletable": false,
+    "papermill": {
+     "duration": 0.135789,
+     "end_time": "2022-02-21T15:37:53.786462",
+     "exception": false,
+     "start_time": "2022-02-21T15:37:53.650673",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "## 7.2. Magnet Resistance\n",
+    "\n",
+    "*ANALYSIS*:\n",
+    "\n",
+    "- Calculation of the magnet resistance as the slope of a linear fit of U,I curve obtained from the corresponding mean alues of the voltage and current\n",
+    "\n",
+    "*CRITERIA*:\n",
+    "\n",
+    "- Check if the magnet resistance is below 50 nOhm\n",
+    "\n",
+    "*GRAPHS*:\n",
+    "\n",
+    "- The magnet resistance, R\n",
+    "- The green box denotes the validity region of the magnet resostance (0, 50] nOhm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8470a193",
+   "metadata": {
+    "papermill": {
+     "duration": 0.136085,
+     "end_time": "2022-02-21T15:37:54.059003",
+     "exception": false,
+     "start_time": "2022-02-21T15:37:53.922918",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "- RQD"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "184caa91",
+   "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:47.259877Z",
-     "iopub.status.busy": "2021-11-09T08:45:47.259144Z",
-     "iopub.status.idle": "2021-11-09T08:45:47.262030Z",
-     "shell.execute_reply": "2021-11-09T08:45:47.261406Z"
+     "iopub.execute_input": "2022-02-21T15:37:54.333872Z",
+     "iopub.status.busy": "2022-02-21T15:37:54.333529Z",
+     "iopub.status.idle": "2022-02-21T15:37:55.007555Z",
+     "shell.execute_reply": "2022-02-21T15:37:55.006804Z"
     },
     "papermill": {
-     "duration": 0.400605,
-     "end_time": "2021-11-09T08:45:47.262206",
+     "duration": 0.814597,
+     "end_time": "2022-02-21T15:37:55.009686",
      "exception": false,
-     "start_time": "2021-11-09T08:45:46.861601",
+     "start_time": "2022-02-21T15:37:54.195089",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 936x468 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqd_df.empty:\n",
     "    title = '%s, %s: %s-%s' % (circuit_names[0], hwc_test, Time.to_string(t_start).split('.')[0], Time.to_string(t_end).split('.')[0])\n",
-    "    res_magnet_rqd_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_magnet_rqd_df, signal_name='R_MAG', max_value=50e-9, title=title)"
+    "    res_magnet_rqd_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_magnet_rqd_df, signal_name='R_MAG', value_max=50e-9, title=title)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 30,
-   "id": "4b87e3c7",
+   "id": "c01ec26e",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:48.058529Z",
-     "iopub.status.busy": "2021-11-09T08:45:48.057730Z",
-     "iopub.status.idle": "2021-11-09T08:45:48.060862Z",
-     "shell.execute_reply": "2021-11-09T08:45:48.059806Z"
+     "iopub.execute_input": "2022-02-21T15:37:55.287672Z",
+     "iopub.status.busy": "2022-02-21T15:37:55.287315Z",
+     "iopub.status.idle": "2022-02-21T15:37:55.293047Z",
+     "shell.execute_reply": "2022-02-21T15:37:55.292284Z"
     },
     "papermill": {
-     "duration": 0.388247,
-     "end_time": "2021-11-09T08:45:48.061047",
+     "duration": 0.146712,
+     "end_time": "2022-02-21T15:37:55.295417",
      "exception": false,
-     "start_time": "2021-11-09T08:45:47.672800",
+     "start_time": "2022-02-21T15:37:55.148705",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All resistances within the range.\n"
+     ]
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqd_df.empty:\n",
     "    RqCircuitQuery.query_and_plot_outlier_voltage(res_magnet_rqd_outliers_df, t_start, t_end, i_meas_raw_nxcals_dfs[0].index[0], plateau_start, plateau_end, spark=spark)"
@@ -2635,24 +3639,471 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "id": "e3f69622",
+   "id": "4506b6ec",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:48.890222Z",
-     "iopub.status.busy": "2021-11-09T08:45:48.889484Z",
-     "iopub.status.idle": "2021-11-09T08:45:48.893763Z",
-     "shell.execute_reply": "2021-11-09T08:45:48.892649Z"
+     "iopub.execute_input": "2022-02-21T15:37:55.579293Z",
+     "iopub.status.busy": "2022-02-21T15:37:55.578914Z",
+     "iopub.status.idle": "2022-02-21T15:37:55.634585Z",
+     "shell.execute_reply": "2022-02-21T15:37:55.633626Z"
     },
     "papermill": {
-     "duration": 0.429157,
-     "end_time": "2021-11-09T08:45:48.893947",
+     "duration": 0.202789,
+     "end_time": "2022-02-21T15:37:55.637004",
      "exception": false,
-     "start_time": "2021-11-09T08:45:48.464790",
+     "start_time": "2022-02-21T15:37:55.434215",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_02997_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >QPS Crate&Board</th>        <th class=\"col_heading level0 col1\" >Bus Bar Segment Name</th>        <th class=\"col_heading level0 col2\" >1st Magnet</th>        <th class=\"col_heading level0 col3\" >2nd Magnet</th>        <th class=\"col_heading level0 col4\" >Num of splices</th>        <th class=\"col_heading level0 col5\" >R_MAG</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_02997_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_02997_row0_col0\" class=\"data row0 col0\" >B10L2_3</td>\n",
+       "                        <td id=\"T_02997_row0_col1\" class=\"data row0 col1\" >DCQDD.7L2.L</td>\n",
+       "                        <td id=\"T_02997_row0_col2\" class=\"data row0 col2\" >MQ.11L2.B2</td>\n",
+       "                        <td id=\"T_02997_row0_col3\" class=\"data row0 col3\" >DFLAS.7L2.2</td>\n",
+       "                        <td id=\"T_02997_row0_col4\" class=\"data row0 col4\" >16</td>\n",
+       "                        <td id=\"T_02997_row0_col5\" class=\"data row0 col5\" >7.52E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_02997_row1_col0\" class=\"data row1 col0\" >B12L2_3</td>\n",
+       "                        <td id=\"T_02997_row1_col1\" class=\"data row1 col1\" >DCQDB.A12L2.L</td>\n",
+       "                        <td id=\"T_02997_row1_col2\" class=\"data row1 col2\" >MQ.13L2.B2</td>\n",
+       "                        <td id=\"T_02997_row1_col3\" class=\"data row1 col3\" >MQ.11L2.B2</td>\n",
+       "                        <td id=\"T_02997_row1_col4\" class=\"data row1 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row1_col5\" class=\"data row1 col5\" >4.65E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_02997_row2_col0\" class=\"data row2 col0\" >B14L2_3</td>\n",
+       "                        <td id=\"T_02997_row2_col1\" class=\"data row2 col1\" >DCQDB.A14L2.L</td>\n",
+       "                        <td id=\"T_02997_row2_col2\" class=\"data row2 col2\" >MQ.15L2.B2</td>\n",
+       "                        <td id=\"T_02997_row2_col3\" class=\"data row2 col3\" >MQ.13L2.B2</td>\n",
+       "                        <td id=\"T_02997_row2_col4\" class=\"data row2 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row2_col5\" class=\"data row2 col5\" >3.13E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "                        <td id=\"T_02997_row3_col0\" class=\"data row3 col0\" >B16L2_3</td>\n",
+       "                        <td id=\"T_02997_row3_col1\" class=\"data row3 col1\" >DCQDB.A16L2.L</td>\n",
+       "                        <td id=\"T_02997_row3_col2\" class=\"data row3 col2\" >MQ.17L2.B2</td>\n",
+       "                        <td id=\"T_02997_row3_col3\" class=\"data row3 col3\" >MQ.15L2.B2</td>\n",
+       "                        <td id=\"T_02997_row3_col4\" class=\"data row3 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row3_col5\" class=\"data row3 col5\" >9.91E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "                        <td id=\"T_02997_row4_col0\" class=\"data row4 col0\" >B18L2_3</td>\n",
+       "                        <td id=\"T_02997_row4_col1\" class=\"data row4 col1\" >DCQDB.A18L2.L</td>\n",
+       "                        <td id=\"T_02997_row4_col2\" class=\"data row4 col2\" >MQ.19L2.B2</td>\n",
+       "                        <td id=\"T_02997_row4_col3\" class=\"data row4 col3\" >MQ.17L2.B2</td>\n",
+       "                        <td id=\"T_02997_row4_col4\" class=\"data row4 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row4_col5\" class=\"data row4 col5\" >2.36E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "                        <td id=\"T_02997_row5_col0\" class=\"data row5 col0\" >B20L2_3</td>\n",
+       "                        <td id=\"T_02997_row5_col1\" class=\"data row5 col1\" >DCQDB.A20L2.L</td>\n",
+       "                        <td id=\"T_02997_row5_col2\" class=\"data row5 col2\" >MQ.21L2.B2</td>\n",
+       "                        <td id=\"T_02997_row5_col3\" class=\"data row5 col3\" >MQ.19L2.B2</td>\n",
+       "                        <td id=\"T_02997_row5_col4\" class=\"data row5 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row5_col5\" class=\"data row5 col5\" >7.95E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "                        <td id=\"T_02997_row6_col0\" class=\"data row6 col0\" >B22L2_3</td>\n",
+       "                        <td id=\"T_02997_row6_col1\" class=\"data row6 col1\" >DCQDB.A22L2.L</td>\n",
+       "                        <td id=\"T_02997_row6_col2\" class=\"data row6 col2\" >MQ.23L2.B2</td>\n",
+       "                        <td id=\"T_02997_row6_col3\" class=\"data row6 col3\" >MQ.21L2.B2</td>\n",
+       "                        <td id=\"T_02997_row6_col4\" class=\"data row6 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row6_col5\" class=\"data row6 col5\" >8.60E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "                        <td id=\"T_02997_row7_col0\" class=\"data row7 col0\" >B24L2_3</td>\n",
+       "                        <td id=\"T_02997_row7_col1\" class=\"data row7 col1\" >DCQDB.A24L2.L</td>\n",
+       "                        <td id=\"T_02997_row7_col2\" class=\"data row7 col2\" >MQ.25L2.B2</td>\n",
+       "                        <td id=\"T_02997_row7_col3\" class=\"data row7 col3\" >MQ.23L2.B2</td>\n",
+       "                        <td id=\"T_02997_row7_col4\" class=\"data row7 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row7_col5\" class=\"data row7 col5\" >1.67E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+       "                        <td id=\"T_02997_row8_col0\" class=\"data row8 col0\" >B26L2_3</td>\n",
+       "                        <td id=\"T_02997_row8_col1\" class=\"data row8 col1\" >DCQDB.A26L2.L</td>\n",
+       "                        <td id=\"T_02997_row8_col2\" class=\"data row8 col2\" >MQ.27L2.B2</td>\n",
+       "                        <td id=\"T_02997_row8_col3\" class=\"data row8 col3\" >MQ.25L2.B2</td>\n",
+       "                        <td id=\"T_02997_row8_col4\" class=\"data row8 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row8_col5\" class=\"data row8 col5\" >7.92E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+       "                        <td id=\"T_02997_row9_col0\" class=\"data row9 col0\" >B28L2_3</td>\n",
+       "                        <td id=\"T_02997_row9_col1\" class=\"data row9 col1\" >DCQDB.A28L2.L</td>\n",
+       "                        <td id=\"T_02997_row9_col2\" class=\"data row9 col2\" >MQ.29L2.B2</td>\n",
+       "                        <td id=\"T_02997_row9_col3\" class=\"data row9 col3\" >MQ.27L2.B2</td>\n",
+       "                        <td id=\"T_02997_row9_col4\" class=\"data row9 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row9_col5\" class=\"data row9 col5\" >1.07E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+       "                        <td id=\"T_02997_row10_col0\" class=\"data row10 col0\" >B30L2_3</td>\n",
+       "                        <td id=\"T_02997_row10_col1\" class=\"data row10 col1\" >DCQDB.A30L2.L</td>\n",
+       "                        <td id=\"T_02997_row10_col2\" class=\"data row10 col2\" >MQ.31L2.B2</td>\n",
+       "                        <td id=\"T_02997_row10_col3\" class=\"data row10 col3\" >MQ.29L2.B2</td>\n",
+       "                        <td id=\"T_02997_row10_col4\" class=\"data row10 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row10_col5\" class=\"data row10 col5\" >1.58E-08</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+       "                        <td id=\"T_02997_row11_col0\" class=\"data row11 col0\" >B32L2_3</td>\n",
+       "                        <td id=\"T_02997_row11_col1\" class=\"data row11 col1\" >DCQDB.A32L2.L</td>\n",
+       "                        <td id=\"T_02997_row11_col2\" class=\"data row11 col2\" >MQ.33L2.B2</td>\n",
+       "                        <td id=\"T_02997_row11_col3\" class=\"data row11 col3\" >MQ.31L2.B2</td>\n",
+       "                        <td id=\"T_02997_row11_col4\" class=\"data row11 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row11_col5\" class=\"data row11 col5\" >9.74E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+       "                        <td id=\"T_02997_row12_col0\" class=\"data row12 col0\" >B33R1_3</td>\n",
+       "                        <td id=\"T_02997_row12_col1\" class=\"data row12 col1\" >DCQDQ.32R1.R</td>\n",
+       "                        <td id=\"T_02997_row12_col2\" class=\"data row12 col2\" >MQ.34R1.B1</td>\n",
+       "                        <td id=\"T_02997_row12_col3\" class=\"data row12 col3\" >MQ.32R1.B1</td>\n",
+       "                        <td id=\"T_02997_row12_col4\" class=\"data row12 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row12_col5\" class=\"data row12 col5\" >1.03E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
+       "                        <td id=\"T_02997_row13_col0\" class=\"data row13 col0\" >B31R1_3</td>\n",
+       "                        <td id=\"T_02997_row13_col1\" class=\"data row13 col1\" >DCQDQ.30R1.R</td>\n",
+       "                        <td id=\"T_02997_row13_col2\" class=\"data row13 col2\" >MQ.32R1.B1</td>\n",
+       "                        <td id=\"T_02997_row13_col3\" class=\"data row13 col3\" >MQ.30R1.B1</td>\n",
+       "                        <td id=\"T_02997_row13_col4\" class=\"data row13 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row13_col5\" class=\"data row13 col5\" >4.14E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
+       "                        <td id=\"T_02997_row14_col0\" class=\"data row14 col0\" >B29R1_3</td>\n",
+       "                        <td id=\"T_02997_row14_col1\" class=\"data row14 col1\" >DCQDQ.28R1.R</td>\n",
+       "                        <td id=\"T_02997_row14_col2\" class=\"data row14 col2\" >MQ.30R1.B1</td>\n",
+       "                        <td id=\"T_02997_row14_col3\" class=\"data row14 col3\" >MQ.28R1.B1</td>\n",
+       "                        <td id=\"T_02997_row14_col4\" class=\"data row14 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row14_col5\" class=\"data row14 col5\" >4.91E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
+       "                        <td id=\"T_02997_row15_col0\" class=\"data row15 col0\" >B27R1_3</td>\n",
+       "                        <td id=\"T_02997_row15_col1\" class=\"data row15 col1\" >DCQDQ.26R1.R</td>\n",
+       "                        <td id=\"T_02997_row15_col2\" class=\"data row15 col2\" >MQ.28R1.B1</td>\n",
+       "                        <td id=\"T_02997_row15_col3\" class=\"data row15 col3\" >MQ.26R1.B1</td>\n",
+       "                        <td id=\"T_02997_row15_col4\" class=\"data row15 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row15_col5\" class=\"data row15 col5\" >4.52E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
+       "                        <td id=\"T_02997_row16_col0\" class=\"data row16 col0\" >B25R1_3</td>\n",
+       "                        <td id=\"T_02997_row16_col1\" class=\"data row16 col1\" >DCQDQ.24R1.R</td>\n",
+       "                        <td id=\"T_02997_row16_col2\" class=\"data row16 col2\" >MQ.26R1.B1</td>\n",
+       "                        <td id=\"T_02997_row16_col3\" class=\"data row16 col3\" >MQ.24R1.B1</td>\n",
+       "                        <td id=\"T_02997_row16_col4\" class=\"data row16 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row16_col5\" class=\"data row16 col5\" >4.56E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
+       "                        <td id=\"T_02997_row17_col0\" class=\"data row17 col0\" >B23R1_3</td>\n",
+       "                        <td id=\"T_02997_row17_col1\" class=\"data row17 col1\" >DCQDQ.22R1.R</td>\n",
+       "                        <td id=\"T_02997_row17_col2\" class=\"data row17 col2\" >MQ.24R1.B1</td>\n",
+       "                        <td id=\"T_02997_row17_col3\" class=\"data row17 col3\" >MQ.22R1.B1</td>\n",
+       "                        <td id=\"T_02997_row17_col4\" class=\"data row17 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row17_col5\" class=\"data row17 col5\" >1.80E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
+       "                        <td id=\"T_02997_row18_col0\" class=\"data row18 col0\" >B21R1_3</td>\n",
+       "                        <td id=\"T_02997_row18_col1\" class=\"data row18 col1\" >DCQDQ.20R1.R</td>\n",
+       "                        <td id=\"T_02997_row18_col2\" class=\"data row18 col2\" >MQ.22R1.B1</td>\n",
+       "                        <td id=\"T_02997_row18_col3\" class=\"data row18 col3\" >MQ.20R1.B1</td>\n",
+       "                        <td id=\"T_02997_row18_col4\" class=\"data row18 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row18_col5\" class=\"data row18 col5\" >8.04E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
+       "                        <td id=\"T_02997_row19_col0\" class=\"data row19 col0\" >B19R1_3</td>\n",
+       "                        <td id=\"T_02997_row19_col1\" class=\"data row19 col1\" >DCQDQ.18R1.R</td>\n",
+       "                        <td id=\"T_02997_row19_col2\" class=\"data row19 col2\" >MQ.20R1.B1</td>\n",
+       "                        <td id=\"T_02997_row19_col3\" class=\"data row19 col3\" >MQ.18R1.B1</td>\n",
+       "                        <td id=\"T_02997_row19_col4\" class=\"data row19 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row19_col5\" class=\"data row19 col5\" >1.54E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
+       "                        <td id=\"T_02997_row20_col0\" class=\"data row20 col0\" >B17R1_3</td>\n",
+       "                        <td id=\"T_02997_row20_col1\" class=\"data row20 col1\" >DCQDQ.16R1.R</td>\n",
+       "                        <td id=\"T_02997_row20_col2\" class=\"data row20 col2\" >MQ.18R1.B1</td>\n",
+       "                        <td id=\"T_02997_row20_col3\" class=\"data row20 col3\" >MQ.16R1.B1</td>\n",
+       "                        <td id=\"T_02997_row20_col4\" class=\"data row20 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row20_col5\" class=\"data row20 col5\" >2.44E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
+       "                        <td id=\"T_02997_row21_col0\" class=\"data row21 col0\" >B15R1_3</td>\n",
+       "                        <td id=\"T_02997_row21_col1\" class=\"data row21 col1\" >DCQDQ.14R1.R</td>\n",
+       "                        <td id=\"T_02997_row21_col2\" class=\"data row21 col2\" >MQ.16R1.B1</td>\n",
+       "                        <td id=\"T_02997_row21_col3\" class=\"data row21 col3\" >MQ.14R1.B1</td>\n",
+       "                        <td id=\"T_02997_row21_col4\" class=\"data row21 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row21_col5\" class=\"data row21 col5\" >5.37E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
+       "                        <td id=\"T_02997_row22_col0\" class=\"data row22 col0\" >B13R1_3</td>\n",
+       "                        <td id=\"T_02997_row22_col1\" class=\"data row22 col1\" >DCQDQ.12R1.R</td>\n",
+       "                        <td id=\"T_02997_row22_col2\" class=\"data row22 col2\" >MQ.14R1.B1</td>\n",
+       "                        <td id=\"T_02997_row22_col3\" class=\"data row22 col3\" >MQ.12R1.B1</td>\n",
+       "                        <td id=\"T_02997_row22_col4\" class=\"data row22 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row22_col5\" class=\"data row22 col5\" >5.24E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
+       "                        <td id=\"T_02997_row23_col0\" class=\"data row23 col0\" >B11R1_3</td>\n",
+       "                        <td id=\"T_02997_row23_col1\" class=\"data row23 col1\" >DCQDE.11R1.R</td>\n",
+       "                        <td id=\"T_02997_row23_col2\" class=\"data row23 col2\" >MQ.12R1.B1</td>\n",
+       "                        <td id=\"T_02997_row23_col3\" class=\"data row23 col3\" >MQ.11R1.B2</td>\n",
+       "                        <td id=\"T_02997_row23_col4\" class=\"data row23 col4\" >6</td>\n",
+       "                        <td id=\"T_02997_row23_col5\" class=\"data row23 col5\" >1.12E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
+       "                        <td id=\"T_02997_row24_col0\" class=\"data row24 col0\" >B12R1_3</td>\n",
+       "                        <td id=\"T_02997_row24_col1\" class=\"data row24 col1\" >DCQDB.C13R1.L</td>\n",
+       "                        <td id=\"T_02997_row24_col2\" class=\"data row24 col2\" >MQ.11R1.B2</td>\n",
+       "                        <td id=\"T_02997_row24_col3\" class=\"data row24 col3\" >MQ.13R1.B2</td>\n",
+       "                        <td id=\"T_02997_row24_col4\" class=\"data row24 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row24_col5\" class=\"data row24 col5\" >1.30E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
+       "                        <td id=\"T_02997_row25_col0\" class=\"data row25 col0\" >B14R1_3</td>\n",
+       "                        <td id=\"T_02997_row25_col1\" class=\"data row25 col1\" >DCQDB.C15R1.L</td>\n",
+       "                        <td id=\"T_02997_row25_col2\" class=\"data row25 col2\" >MQ.13R1.B2</td>\n",
+       "                        <td id=\"T_02997_row25_col3\" class=\"data row25 col3\" >MQ.15R1.B2</td>\n",
+       "                        <td id=\"T_02997_row25_col4\" class=\"data row25 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row25_col5\" class=\"data row25 col5\" >2.23E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
+       "                        <td id=\"T_02997_row26_col0\" class=\"data row26 col0\" >B16R1_3</td>\n",
+       "                        <td id=\"T_02997_row26_col1\" class=\"data row26 col1\" >DCQDB.C17R1.L</td>\n",
+       "                        <td id=\"T_02997_row26_col2\" class=\"data row26 col2\" >MQ.15R1.B2</td>\n",
+       "                        <td id=\"T_02997_row26_col3\" class=\"data row26 col3\" >MQ.17R1.B2</td>\n",
+       "                        <td id=\"T_02997_row26_col4\" class=\"data row26 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row26_col5\" class=\"data row26 col5\" >2.44E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
+       "                        <td id=\"T_02997_row27_col0\" class=\"data row27 col0\" >B18R1_3</td>\n",
+       "                        <td id=\"T_02997_row27_col1\" class=\"data row27 col1\" >DCQDB.C19R1.L</td>\n",
+       "                        <td id=\"T_02997_row27_col2\" class=\"data row27 col2\" >MQ.17R1.B2</td>\n",
+       "                        <td id=\"T_02997_row27_col3\" class=\"data row27 col3\" >MQ.19R1.B2</td>\n",
+       "                        <td id=\"T_02997_row27_col4\" class=\"data row27 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row27_col5\" class=\"data row27 col5\" >2.88E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
+       "                        <td id=\"T_02997_row28_col0\" class=\"data row28 col0\" >B20R1_3</td>\n",
+       "                        <td id=\"T_02997_row28_col1\" class=\"data row28 col1\" >DCQDB.C21R1.L</td>\n",
+       "                        <td id=\"T_02997_row28_col2\" class=\"data row28 col2\" >MQ.19R1.B2</td>\n",
+       "                        <td id=\"T_02997_row28_col3\" class=\"data row28 col3\" >MQ.21R1.B2</td>\n",
+       "                        <td id=\"T_02997_row28_col4\" class=\"data row28 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row28_col5\" class=\"data row28 col5\" >5.83E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
+       "                        <td id=\"T_02997_row29_col0\" class=\"data row29 col0\" >B22R1_3</td>\n",
+       "                        <td id=\"T_02997_row29_col1\" class=\"data row29 col1\" >DCQDB.C23R1.L</td>\n",
+       "                        <td id=\"T_02997_row29_col2\" class=\"data row29 col2\" >MQ.21R1.B2</td>\n",
+       "                        <td id=\"T_02997_row29_col3\" class=\"data row29 col3\" >MQ.23R1.B2</td>\n",
+       "                        <td id=\"T_02997_row29_col4\" class=\"data row29 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row29_col5\" class=\"data row29 col5\" >3.97E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
+       "                        <td id=\"T_02997_row30_col0\" class=\"data row30 col0\" >B24R1_3</td>\n",
+       "                        <td id=\"T_02997_row30_col1\" class=\"data row30 col1\" >DCQDB.C25R1.L</td>\n",
+       "                        <td id=\"T_02997_row30_col2\" class=\"data row30 col2\" >MQ.23R1.B2</td>\n",
+       "                        <td id=\"T_02997_row30_col3\" class=\"data row30 col3\" >MQ.25R1.B2</td>\n",
+       "                        <td id=\"T_02997_row30_col4\" class=\"data row30 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row30_col5\" class=\"data row30 col5\" >2.80E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
+       "                        <td id=\"T_02997_row31_col0\" class=\"data row31 col0\" >B26R1_3</td>\n",
+       "                        <td id=\"T_02997_row31_col1\" class=\"data row31 col1\" >DCQDB.C27R1.L</td>\n",
+       "                        <td id=\"T_02997_row31_col2\" class=\"data row31 col2\" >MQ.25R1.B2</td>\n",
+       "                        <td id=\"T_02997_row31_col3\" class=\"data row31 col3\" >MQ.27R1.B2</td>\n",
+       "                        <td id=\"T_02997_row31_col4\" class=\"data row31 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row31_col5\" class=\"data row31 col5\" >2.94E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
+       "                        <td id=\"T_02997_row32_col0\" class=\"data row32 col0\" >B28R1_3</td>\n",
+       "                        <td id=\"T_02997_row32_col1\" class=\"data row32 col1\" >DCQDB.C29R1.L</td>\n",
+       "                        <td id=\"T_02997_row32_col2\" class=\"data row32 col2\" >MQ.27R1.B2</td>\n",
+       "                        <td id=\"T_02997_row32_col3\" class=\"data row32 col3\" >MQ.29R1.B2</td>\n",
+       "                        <td id=\"T_02997_row32_col4\" class=\"data row32 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row32_col5\" class=\"data row32 col5\" >4.14E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
+       "                        <td id=\"T_02997_row33_col0\" class=\"data row33 col0\" >B30R1_3</td>\n",
+       "                        <td id=\"T_02997_row33_col1\" class=\"data row33 col1\" >DCQDB.C31R1.L</td>\n",
+       "                        <td id=\"T_02997_row33_col2\" class=\"data row33 col2\" >MQ.29R1.B2</td>\n",
+       "                        <td id=\"T_02997_row33_col3\" class=\"data row33 col3\" >MQ.31R1.B2</td>\n",
+       "                        <td id=\"T_02997_row33_col4\" class=\"data row33 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row33_col5\" class=\"data row33 col5\" >6.63E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
+       "                        <td id=\"T_02997_row34_col0\" class=\"data row34 col0\" >B32R1_3</td>\n",
+       "                        <td id=\"T_02997_row34_col1\" class=\"data row34 col1\" >DCQDB.C33R1.L</td>\n",
+       "                        <td id=\"T_02997_row34_col2\" class=\"data row34 col2\" >MQ.31R1.B2</td>\n",
+       "                        <td id=\"T_02997_row34_col3\" class=\"data row34 col3\" >MQ.33R1.B2</td>\n",
+       "                        <td id=\"T_02997_row34_col4\" class=\"data row34 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row34_col5\" class=\"data row34 col5\" >8.69E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
+       "                        <td id=\"T_02997_row35_col0\" class=\"data row35 col0\" >B34R1_3</td>\n",
+       "                        <td id=\"T_02997_row35_col1\" class=\"data row35 col1\" >DCQDB.A34L2.L</td>\n",
+       "                        <td id=\"T_02997_row35_col2\" class=\"data row35 col2\" >MQ.33R1.B2</td>\n",
+       "                        <td id=\"T_02997_row35_col3\" class=\"data row35 col3\" >MQ.33L2.B2</td>\n",
+       "                        <td id=\"T_02997_row35_col4\" class=\"data row35 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row35_col5\" class=\"data row35 col5\" >2.72E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
+       "                        <td id=\"T_02997_row36_col0\" class=\"data row36 col0\" >B33L2_3</td>\n",
+       "                        <td id=\"T_02997_row36_col1\" class=\"data row36 col1\" >DCQDQ.34R1.R</td>\n",
+       "                        <td id=\"T_02997_row36_col2\" class=\"data row36 col2\" >MQ.32L2.B1</td>\n",
+       "                        <td id=\"T_02997_row36_col3\" class=\"data row36 col3\" >MQ.34R1.B1</td>\n",
+       "                        <td id=\"T_02997_row36_col4\" class=\"data row36 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row36_col5\" class=\"data row36 col5\" >4.59E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
+       "                        <td id=\"T_02997_row37_col0\" class=\"data row37 col0\" >B31L2_3</td>\n",
+       "                        <td id=\"T_02997_row37_col1\" class=\"data row37 col1\" >DCQDQ.32L2.R</td>\n",
+       "                        <td id=\"T_02997_row37_col2\" class=\"data row37 col2\" >MQ.30L2.B1</td>\n",
+       "                        <td id=\"T_02997_row37_col3\" class=\"data row37 col3\" >MQ.32L2.B1</td>\n",
+       "                        <td id=\"T_02997_row37_col4\" class=\"data row37 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row37_col5\" class=\"data row37 col5\" >2.53E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
+       "                        <td id=\"T_02997_row38_col0\" class=\"data row38 col0\" >B29L2_3</td>\n",
+       "                        <td id=\"T_02997_row38_col1\" class=\"data row38 col1\" >DCQDQ.30L2.R</td>\n",
+       "                        <td id=\"T_02997_row38_col2\" class=\"data row38 col2\" >MQ.28L2.B1</td>\n",
+       "                        <td id=\"T_02997_row38_col3\" class=\"data row38 col3\" >MQ.30L2.B1</td>\n",
+       "                        <td id=\"T_02997_row38_col4\" class=\"data row38 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row38_col5\" class=\"data row38 col5\" >3.14E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
+       "                        <td id=\"T_02997_row39_col0\" class=\"data row39 col0\" >B27L2_3</td>\n",
+       "                        <td id=\"T_02997_row39_col1\" class=\"data row39 col1\" >DCQDQ.28L2.R</td>\n",
+       "                        <td id=\"T_02997_row39_col2\" class=\"data row39 col2\" >MQ.26L2.B1</td>\n",
+       "                        <td id=\"T_02997_row39_col3\" class=\"data row39 col3\" >MQ.28L2.B1</td>\n",
+       "                        <td id=\"T_02997_row39_col4\" class=\"data row39 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row39_col5\" class=\"data row39 col5\" >1.78E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
+       "                        <td id=\"T_02997_row40_col0\" class=\"data row40 col0\" >B25L2_3</td>\n",
+       "                        <td id=\"T_02997_row40_col1\" class=\"data row40 col1\" >DCQDQ.26L2.R</td>\n",
+       "                        <td id=\"T_02997_row40_col2\" class=\"data row40 col2\" >MQ.24L2.B1</td>\n",
+       "                        <td id=\"T_02997_row40_col3\" class=\"data row40 col3\" >MQ.26L2.B1</td>\n",
+       "                        <td id=\"T_02997_row40_col4\" class=\"data row40 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row40_col5\" class=\"data row40 col5\" >3.78E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
+       "                        <td id=\"T_02997_row41_col0\" class=\"data row41 col0\" >B23L2_3</td>\n",
+       "                        <td id=\"T_02997_row41_col1\" class=\"data row41 col1\" >DCQDQ.24L2.R</td>\n",
+       "                        <td id=\"T_02997_row41_col2\" class=\"data row41 col2\" >MQ.22L2.B1</td>\n",
+       "                        <td id=\"T_02997_row41_col3\" class=\"data row41 col3\" >MQ.24L2.B1</td>\n",
+       "                        <td id=\"T_02997_row41_col4\" class=\"data row41 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row41_col5\" class=\"data row41 col5\" >1.94E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
+       "                        <td id=\"T_02997_row42_col0\" class=\"data row42 col0\" >B21L2_3</td>\n",
+       "                        <td id=\"T_02997_row42_col1\" class=\"data row42 col1\" >DCQDQ.22L2.R</td>\n",
+       "                        <td id=\"T_02997_row42_col2\" class=\"data row42 col2\" >MQ.20L2.B1</td>\n",
+       "                        <td id=\"T_02997_row42_col3\" class=\"data row42 col3\" >MQ.22L2.B1</td>\n",
+       "                        <td id=\"T_02997_row42_col4\" class=\"data row42 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row42_col5\" class=\"data row42 col5\" >8.79E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
+       "                        <td id=\"T_02997_row43_col0\" class=\"data row43 col0\" >B19L2_3</td>\n",
+       "                        <td id=\"T_02997_row43_col1\" class=\"data row43 col1\" >DCQDQ.20L2.R</td>\n",
+       "                        <td id=\"T_02997_row43_col2\" class=\"data row43 col2\" >MQ.18L2.B1</td>\n",
+       "                        <td id=\"T_02997_row43_col3\" class=\"data row43 col3\" >MQ.20L2.B1</td>\n",
+       "                        <td id=\"T_02997_row43_col4\" class=\"data row43 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row43_col5\" class=\"data row43 col5\" >8.95E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
+       "                        <td id=\"T_02997_row44_col0\" class=\"data row44 col0\" >B17L2_3</td>\n",
+       "                        <td id=\"T_02997_row44_col1\" class=\"data row44 col1\" >DCQDQ.18L2.R</td>\n",
+       "                        <td id=\"T_02997_row44_col2\" class=\"data row44 col2\" >MQ.16L2.B1</td>\n",
+       "                        <td id=\"T_02997_row44_col3\" class=\"data row44 col3\" >MQ.18L2.B1</td>\n",
+       "                        <td id=\"T_02997_row44_col4\" class=\"data row44 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row44_col5\" class=\"data row44 col5\" >4.10E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
+       "                        <td id=\"T_02997_row45_col0\" class=\"data row45 col0\" >B15L2_3</td>\n",
+       "                        <td id=\"T_02997_row45_col1\" class=\"data row45 col1\" >DCQDQ.16L2.R</td>\n",
+       "                        <td id=\"T_02997_row45_col2\" class=\"data row45 col2\" >MQ.14L2.B1</td>\n",
+       "                        <td id=\"T_02997_row45_col3\" class=\"data row45 col3\" >MQ.16L2.B1</td>\n",
+       "                        <td id=\"T_02997_row45_col4\" class=\"data row45 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row45_col5\" class=\"data row45 col5\" >4.09E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
+       "                        <td id=\"T_02997_row46_col0\" class=\"data row46 col0\" >B13L2_3</td>\n",
+       "                        <td id=\"T_02997_row46_col1\" class=\"data row46 col1\" >DCQDQ.14L2.R</td>\n",
+       "                        <td id=\"T_02997_row46_col2\" class=\"data row46 col2\" >MQ.12L2.B1</td>\n",
+       "                        <td id=\"T_02997_row46_col3\" class=\"data row46 col3\" >MQ.14L2.B1</td>\n",
+       "                        <td id=\"T_02997_row46_col4\" class=\"data row46 col4\" >8</td>\n",
+       "                        <td id=\"T_02997_row46_col5\" class=\"data row46 col5\" >2.06E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_02997_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
+       "                        <td id=\"T_02997_row47_col0\" class=\"data row47 col0\" >B11L2_3</td>\n",
+       "                        <td id=\"T_02997_row47_col1\" class=\"data row47 col1\" >DCQDQ.12L2.R</td>\n",
+       "                        <td id=\"T_02997_row47_col2\" class=\"data row47 col2\" >DFLAS.7L2.1</td>\n",
+       "                        <td id=\"T_02997_row47_col3\" class=\"data row47 col3\" >MQ.12L2.B1</td>\n",
+       "                        <td id=\"T_02997_row47_col4\" class=\"data row47 col4\" >20</td>\n",
+       "                        <td id=\"T_02997_row47_col5\" class=\"data row47 col5\" >6.83E-09</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fd3b6e26460>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqd_df.empty:\n",
     "    rqd_magnet_metadata_resistance_df = rq_analysis.merge_busbar_metadata_with_resistance(res_magnet_rqd_df, circuit_type, circuit_names, res_col='R_MAG')\n",
@@ -2661,13 +4112,13 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6c7d2672",
+   "id": "7ccad701",
    "metadata": {
     "papermill": {
-     "duration": 0.436205,
-     "end_time": "2021-11-09T08:45:49.769042",
+     "duration": 0.144149,
+     "end_time": "2022-02-21T15:37:55.923324",
      "exception": false,
-     "start_time": "2021-11-09T08:45:49.332837",
+     "start_time": "2022-02-21T15:37:55.779175",
      "status": "completed"
     },
     "tags": []
@@ -2679,52 +4130,73 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "id": "004789f0",
+   "id": "ffc0a5d4",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:50.635493Z",
-     "iopub.status.busy": "2021-11-09T08:45:50.634696Z",
-     "iopub.status.idle": "2021-11-09T08:45:50.639227Z",
-     "shell.execute_reply": "2021-11-09T08:45:50.639974Z"
+     "iopub.execute_input": "2022-02-21T15:37:56.208465Z",
+     "iopub.status.busy": "2022-02-21T15:37:56.208089Z",
+     "iopub.status.idle": "2022-02-21T15:37:56.866913Z",
+     "shell.execute_reply": "2022-02-21T15:37:56.866094Z"
     },
     "papermill": {
-     "duration": 0.439428,
-     "end_time": "2021-11-09T08:45:50.640185",
+     "duration": 0.804943,
+     "end_time": "2022-02-21T15:37:56.869000",
      "exception": false,
-     "start_time": "2021-11-09T08:45:50.200757",
+     "start_time": "2022-02-21T15:37:56.064057",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 936x468 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqf_df.empty:\n",
-    "    res_magnet_rqf_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_magnet_rqf_df, signal_name='R_MAG', max_value=50e-9)"
+    "    res_magnet_rqf_outliers_df = rq_analysis.analyze_busbar_magnet_resistance(res_magnet_rqf_df, signal_name='R_MAG', value_max=50e-9)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 33,
-   "id": "5ad19431",
+   "id": "e3198b1c",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:51.615689Z",
-     "iopub.status.busy": "2021-11-09T08:45:51.614837Z",
-     "iopub.status.idle": "2021-11-09T08:45:51.624633Z",
-     "shell.execute_reply": "2021-11-09T08:45:51.623884Z"
+     "iopub.execute_input": "2022-02-21T15:37:57.154691Z",
+     "iopub.status.busy": "2022-02-21T15:37:57.154315Z",
+     "iopub.status.idle": "2022-02-21T15:37:57.160799Z",
+     "shell.execute_reply": "2022-02-21T15:37:57.159837Z"
     },
     "papermill": {
-     "duration": 0.56261,
-     "end_time": "2021-11-09T08:45:51.624862",
+     "duration": 0.152059,
+     "end_time": "2022-02-21T15:37:57.162898",
      "exception": false,
-     "start_time": "2021-11-09T08:45:51.062252",
+     "start_time": "2022-02-21T15:37:57.010839",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All resistances within the range.\n"
+     ]
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqf_df.empty:\n",
     "    RqCircuitQuery.query_and_plot_outlier_voltage(res_magnet_rqf_outliers_df, t_start, t_end, i_meas_raw_nxcals_dfs[0].index[0], plateau_start, plateau_end, spark=spark)"
@@ -2733,40 +4205,487 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "id": "8ddc3cee",
+   "id": "04065a16",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:52.510771Z",
-     "iopub.status.busy": "2021-11-09T08:45:52.509914Z",
-     "iopub.status.idle": "2021-11-09T08:45:52.522593Z",
-     "shell.execute_reply": "2021-11-09T08:45:52.521863Z"
+     "iopub.execute_input": "2022-02-21T15:37:57.449981Z",
+     "iopub.status.busy": "2022-02-21T15:37:57.449636Z",
+     "iopub.status.idle": "2022-02-21T15:37:57.504491Z",
+     "shell.execute_reply": "2022-02-21T15:37:57.503704Z"
     },
     "papermill": {
-     "duration": 0.462476,
-     "end_time": "2021-11-09T08:45:52.522824",
+     "duration": 0.201121,
+     "end_time": "2022-02-21T15:37:57.506937",
      "exception": false,
-     "start_time": "2021-11-09T08:45:52.060348",
+     "start_time": "2022-02-21T15:37:57.305816",
      "status": "completed"
     },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_0bd98_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >QPS Crate&Board</th>        <th class=\"col_heading level0 col1\" >Bus Bar Segment Name</th>        <th class=\"col_heading level0 col2\" >1st Magnet</th>        <th class=\"col_heading level0 col3\" >2nd Magnet</th>        <th class=\"col_heading level0 col4\" >Num of splices</th>        <th class=\"col_heading level0 col5\" >R_MAG</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_0bd98_row0_col0\" class=\"data row0 col0\" >B10L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row0_col1\" class=\"data row0 col1\" >DCQFD.7L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row0_col2\" class=\"data row0 col2\" >MQ.11L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row0_col3\" class=\"data row0 col3\" >DFLAS.7L2.4</td>\n",
+       "                        <td id=\"T_0bd98_row0_col4\" class=\"data row0 col4\" >16</td>\n",
+       "                        <td id=\"T_0bd98_row0_col5\" class=\"data row0 col5\" >1.38E-08</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_0bd98_row1_col0\" class=\"data row1 col0\" >B12L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row1_col1\" class=\"data row1 col1\" >DCQFB.A12L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row1_col2\" class=\"data row1 col2\" >MQ.13L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row1_col3\" class=\"data row1 col3\" >MQ.11L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row1_col4\" class=\"data row1 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row1_col5\" class=\"data row1 col5\" >4.59E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_0bd98_row2_col0\" class=\"data row2 col0\" >B14L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row2_col1\" class=\"data row2 col1\" >DCQFB.A14L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row2_col2\" class=\"data row2 col2\" >MQ.15L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row2_col3\" class=\"data row2 col3\" >MQ.13L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row2_col4\" class=\"data row2 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row2_col5\" class=\"data row2 col5\" >2.33E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "                        <td id=\"T_0bd98_row3_col0\" class=\"data row3 col0\" >B16L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row3_col1\" class=\"data row3 col1\" >DCQFB.A16L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row3_col2\" class=\"data row3 col2\" >MQ.17L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row3_col3\" class=\"data row3 col3\" >MQ.15L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row3_col4\" class=\"data row3 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row3_col5\" class=\"data row3 col5\" >2.01E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "                        <td id=\"T_0bd98_row4_col0\" class=\"data row4 col0\" >B18L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row4_col1\" class=\"data row4 col1\" >DCQFB.A18L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row4_col2\" class=\"data row4 col2\" >MQ.19L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row4_col3\" class=\"data row4 col3\" >MQ.17L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row4_col4\" class=\"data row4 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row4_col5\" class=\"data row4 col5\" >3.05E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "                        <td id=\"T_0bd98_row5_col0\" class=\"data row5 col0\" >B20L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row5_col1\" class=\"data row5 col1\" >DCQFB.A20L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row5_col2\" class=\"data row5 col2\" >MQ.21L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row5_col3\" class=\"data row5 col3\" >MQ.19L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row5_col4\" class=\"data row5 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row5_col5\" class=\"data row5 col5\" >2.99E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "                        <td id=\"T_0bd98_row6_col0\" class=\"data row6 col0\" >B22L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row6_col1\" class=\"data row6 col1\" >DCQFB.A22L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row6_col2\" class=\"data row6 col2\" >MQ.23L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row6_col3\" class=\"data row6 col3\" >MQ.21L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row6_col4\" class=\"data row6 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row6_col5\" class=\"data row6 col5\" >2.32E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "                        <td id=\"T_0bd98_row7_col0\" class=\"data row7 col0\" >B24L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row7_col1\" class=\"data row7 col1\" >DCQFB.A24L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row7_col2\" class=\"data row7 col2\" >MQ.25L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row7_col3\" class=\"data row7 col3\" >MQ.23L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row7_col4\" class=\"data row7 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row7_col5\" class=\"data row7 col5\" >6.62E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+       "                        <td id=\"T_0bd98_row8_col0\" class=\"data row8 col0\" >B26L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row8_col1\" class=\"data row8 col1\" >DCQFB.A26L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row8_col2\" class=\"data row8 col2\" >MQ.27L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row8_col3\" class=\"data row8 col3\" >MQ.25L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row8_col4\" class=\"data row8 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row8_col5\" class=\"data row8 col5\" >7.79E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+       "                        <td id=\"T_0bd98_row9_col0\" class=\"data row9 col0\" >B28L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row9_col1\" class=\"data row9 col1\" >DCQFB.A28L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row9_col2\" class=\"data row9 col2\" >MQ.29L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row9_col3\" class=\"data row9 col3\" >MQ.27L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row9_col4\" class=\"data row9 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row9_col5\" class=\"data row9 col5\" >4.19E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+       "                        <td id=\"T_0bd98_row10_col0\" class=\"data row10 col0\" >B30L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row10_col1\" class=\"data row10 col1\" >DCQFB.A30L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row10_col2\" class=\"data row10 col2\" >MQ.31L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row10_col3\" class=\"data row10 col3\" >MQ.29L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row10_col4\" class=\"data row10 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row10_col5\" class=\"data row10 col5\" >3.59E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+       "                        <td id=\"T_0bd98_row11_col0\" class=\"data row11 col0\" >B32L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row11_col1\" class=\"data row11 col1\" >DCQFB.C32L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row11_col2\" class=\"data row11 col2\" >MQ.33L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row11_col3\" class=\"data row11 col3\" >MQ.31L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row11_col4\" class=\"data row11 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row11_col5\" class=\"data row11 col5\" >2.25E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+       "                        <td id=\"T_0bd98_row12_col0\" class=\"data row12 col0\" >B33R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row12_col1\" class=\"data row12 col1\" >DCQFQ.32R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row12_col2\" class=\"data row12 col2\" >MQ.34R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row12_col3\" class=\"data row12 col3\" >MQ.32R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row12_col4\" class=\"data row12 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row12_col5\" class=\"data row12 col5\" >7.04E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
+       "                        <td id=\"T_0bd98_row13_col0\" class=\"data row13 col0\" >B31R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row13_col1\" class=\"data row13 col1\" >DCQFQ.30R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row13_col2\" class=\"data row13 col2\" >MQ.32R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row13_col3\" class=\"data row13 col3\" >MQ.30R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row13_col4\" class=\"data row13 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row13_col5\" class=\"data row13 col5\" >8.23E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
+       "                        <td id=\"T_0bd98_row14_col0\" class=\"data row14 col0\" >B29R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row14_col1\" class=\"data row14 col1\" >DCQFQ.28R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row14_col2\" class=\"data row14 col2\" >MQ.30R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row14_col3\" class=\"data row14 col3\" >MQ.28R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row14_col4\" class=\"data row14 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row14_col5\" class=\"data row14 col5\" >1.17E-08</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
+       "                        <td id=\"T_0bd98_row15_col0\" class=\"data row15 col0\" >B27R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row15_col1\" class=\"data row15 col1\" >DCQFQ.26R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row15_col2\" class=\"data row15 col2\" >MQ.28R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row15_col3\" class=\"data row15 col3\" >MQ.26R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row15_col4\" class=\"data row15 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row15_col5\" class=\"data row15 col5\" >4.74E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
+       "                        <td id=\"T_0bd98_row16_col0\" class=\"data row16 col0\" >B25R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row16_col1\" class=\"data row16 col1\" >DCQFQ.24R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row16_col2\" class=\"data row16 col2\" >MQ.26R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row16_col3\" class=\"data row16 col3\" >MQ.24R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row16_col4\" class=\"data row16 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row16_col5\" class=\"data row16 col5\" >1.88E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
+       "                        <td id=\"T_0bd98_row17_col0\" class=\"data row17 col0\" >B23R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row17_col1\" class=\"data row17 col1\" >DCQFQ.22R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row17_col2\" class=\"data row17 col2\" >MQ.24R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row17_col3\" class=\"data row17 col3\" >MQ.22R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row17_col4\" class=\"data row17 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row17_col5\" class=\"data row17 col5\" >9.18E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
+       "                        <td id=\"T_0bd98_row18_col0\" class=\"data row18 col0\" >B21R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row18_col1\" class=\"data row18 col1\" >DCQFQ.20R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row18_col2\" class=\"data row18 col2\" >MQ.22R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row18_col3\" class=\"data row18 col3\" >MQ.20R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row18_col4\" class=\"data row18 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row18_col5\" class=\"data row18 col5\" >2.32E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
+       "                        <td id=\"T_0bd98_row19_col0\" class=\"data row19 col0\" >B19R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row19_col1\" class=\"data row19 col1\" >DCQFQ.18R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row19_col2\" class=\"data row19 col2\" >MQ.20R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row19_col3\" class=\"data row19 col3\" >MQ.18R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row19_col4\" class=\"data row19 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row19_col5\" class=\"data row19 col5\" >2.06E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
+       "                        <td id=\"T_0bd98_row20_col0\" class=\"data row20 col0\" >B17R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row20_col1\" class=\"data row20 col1\" >DCQFQ.16R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row20_col2\" class=\"data row20 col2\" >MQ.18R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row20_col3\" class=\"data row20 col3\" >MQ.16R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row20_col4\" class=\"data row20 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row20_col5\" class=\"data row20 col5\" >1.98E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
+       "                        <td id=\"T_0bd98_row21_col0\" class=\"data row21 col0\" >B15R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row21_col1\" class=\"data row21 col1\" >DCQFQ.14R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row21_col2\" class=\"data row21 col2\" >MQ.16R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row21_col3\" class=\"data row21 col3\" >MQ.14R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row21_col4\" class=\"data row21 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row21_col5\" class=\"data row21 col5\" >4.52E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
+       "                        <td id=\"T_0bd98_row22_col0\" class=\"data row22 col0\" >B13R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row22_col1\" class=\"data row22 col1\" >DCQFQ.12R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row22_col2\" class=\"data row22 col2\" >MQ.14R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row22_col3\" class=\"data row22 col3\" >MQ.12R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row22_col4\" class=\"data row22 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row22_col5\" class=\"data row22 col5\" >5.78E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
+       "                        <td id=\"T_0bd98_row23_col0\" class=\"data row23 col0\" >B11R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row23_col1\" class=\"data row23 col1\" >DCQFE.11R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row23_col2\" class=\"data row23 col2\" >MQ.12R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row23_col3\" class=\"data row23 col3\" >MQ.11R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row23_col4\" class=\"data row23 col4\" >6</td>\n",
+       "                        <td id=\"T_0bd98_row23_col5\" class=\"data row23 col5\" >3.43E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
+       "                        <td id=\"T_0bd98_row24_col0\" class=\"data row24 col0\" >B12R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row24_col1\" class=\"data row24 col1\" >DCQFB.C13R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row24_col2\" class=\"data row24 col2\" >MQ.11R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row24_col3\" class=\"data row24 col3\" >MQ.13R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row24_col4\" class=\"data row24 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row24_col5\" class=\"data row24 col5\" >3.38E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
+       "                        <td id=\"T_0bd98_row25_col0\" class=\"data row25 col0\" >B14R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row25_col1\" class=\"data row25 col1\" >DCQFB.A15R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row25_col2\" class=\"data row25 col2\" >MQ.13R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row25_col3\" class=\"data row25 col3\" >MQ.15R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row25_col4\" class=\"data row25 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row25_col5\" class=\"data row25 col5\" >1.55E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
+       "                        <td id=\"T_0bd98_row26_col0\" class=\"data row26 col0\" >B16R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row26_col1\" class=\"data row26 col1\" >DCQFB.C17R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row26_col2\" class=\"data row26 col2\" >MQ.15R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row26_col3\" class=\"data row26 col3\" >MQ.17R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row26_col4\" class=\"data row26 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row26_col5\" class=\"data row26 col5\" >6.20E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
+       "                        <td id=\"T_0bd98_row27_col0\" class=\"data row27 col0\" >B18R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row27_col1\" class=\"data row27 col1\" >DCQFB.C19R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row27_col2\" class=\"data row27 col2\" >MQ.17R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row27_col3\" class=\"data row27 col3\" >MQ.19R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row27_col4\" class=\"data row27 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row27_col5\" class=\"data row27 col5\" >1.28E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
+       "                        <td id=\"T_0bd98_row28_col0\" class=\"data row28 col0\" >B20R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row28_col1\" class=\"data row28 col1\" >DCQFB.C21R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row28_col2\" class=\"data row28 col2\" >MQ.19R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row28_col3\" class=\"data row28 col3\" >MQ.21R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row28_col4\" class=\"data row28 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row28_col5\" class=\"data row28 col5\" >5.69E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
+       "                        <td id=\"T_0bd98_row29_col0\" class=\"data row29 col0\" >B22R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row29_col1\" class=\"data row29 col1\" >DCQFB.C23R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row29_col2\" class=\"data row29 col2\" >MQ.21R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row29_col3\" class=\"data row29 col3\" >MQ.23R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row29_col4\" class=\"data row29 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row29_col5\" class=\"data row29 col5\" >4.83E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
+       "                        <td id=\"T_0bd98_row30_col0\" class=\"data row30 col0\" >B24R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row30_col1\" class=\"data row30 col1\" >DCQFB.C25R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row30_col2\" class=\"data row30 col2\" >MQ.23R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row30_col3\" class=\"data row30 col3\" >MQ.25R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row30_col4\" class=\"data row30 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row30_col5\" class=\"data row30 col5\" >1.65E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
+       "                        <td id=\"T_0bd98_row31_col0\" class=\"data row31 col0\" >B26R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row31_col1\" class=\"data row31 col1\" >DCQFB.C27R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row31_col2\" class=\"data row31 col2\" >MQ.25R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row31_col3\" class=\"data row31 col3\" >MQ.27R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row31_col4\" class=\"data row31 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row31_col5\" class=\"data row31 col5\" >5.02E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
+       "                        <td id=\"T_0bd98_row32_col0\" class=\"data row32 col0\" >B28R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row32_col1\" class=\"data row32 col1\" >DCQFB.C29R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row32_col2\" class=\"data row32 col2\" >MQ.27R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row32_col3\" class=\"data row32 col3\" >MQ.29R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row32_col4\" class=\"data row32 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row32_col5\" class=\"data row32 col5\" >4.72E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
+       "                        <td id=\"T_0bd98_row33_col0\" class=\"data row33 col0\" >B30R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row33_col1\" class=\"data row33 col1\" >DCQFB.C31R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row33_col2\" class=\"data row33 col2\" >MQ.29R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row33_col3\" class=\"data row33 col3\" >MQ.31R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row33_col4\" class=\"data row33 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row33_col5\" class=\"data row33 col5\" >3.49E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
+       "                        <td id=\"T_0bd98_row34_col0\" class=\"data row34 col0\" >B32R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row34_col1\" class=\"data row34 col1\" >DCQFB.C33R1.R</td>\n",
+       "                        <td id=\"T_0bd98_row34_col2\" class=\"data row34 col2\" >MQ.31R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row34_col3\" class=\"data row34 col3\" >MQ.33R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row34_col4\" class=\"data row34 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row34_col5\" class=\"data row34 col5\" >5.88E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
+       "                        <td id=\"T_0bd98_row35_col0\" class=\"data row35 col0\" >B34R1_4</td>\n",
+       "                        <td id=\"T_0bd98_row35_col1\" class=\"data row35 col1\" >DCQFB.A34L2.R</td>\n",
+       "                        <td id=\"T_0bd98_row35_col2\" class=\"data row35 col2\" >MQ.33R1.B1</td>\n",
+       "                        <td id=\"T_0bd98_row35_col3\" class=\"data row35 col3\" >MQ.33L2.B1</td>\n",
+       "                        <td id=\"T_0bd98_row35_col4\" class=\"data row35 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row35_col5\" class=\"data row35 col5\" >2.44E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
+       "                        <td id=\"T_0bd98_row36_col0\" class=\"data row36 col0\" >B33L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row36_col1\" class=\"data row36 col1\" >DCQFQ.34R1.L</td>\n",
+       "                        <td id=\"T_0bd98_row36_col2\" class=\"data row36 col2\" >MQ.32L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row36_col3\" class=\"data row36 col3\" >MQ.34R1.B2</td>\n",
+       "                        <td id=\"T_0bd98_row36_col4\" class=\"data row36 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row36_col5\" class=\"data row36 col5\" >3.77E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
+       "                        <td id=\"T_0bd98_row37_col0\" class=\"data row37 col0\" >B31L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row37_col1\" class=\"data row37 col1\" >DCQFQ.32L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row37_col2\" class=\"data row37 col2\" >MQ.30L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row37_col3\" class=\"data row37 col3\" >MQ.32L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row37_col4\" class=\"data row37 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row37_col5\" class=\"data row37 col5\" >1.31E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
+       "                        <td id=\"T_0bd98_row38_col0\" class=\"data row38 col0\" >B29L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row38_col1\" class=\"data row38 col1\" >DCQFQ.30L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row38_col2\" class=\"data row38 col2\" >MQ.28L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row38_col3\" class=\"data row38 col3\" >MQ.30L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row38_col4\" class=\"data row38 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row38_col5\" class=\"data row38 col5\" >2.13E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
+       "                        <td id=\"T_0bd98_row39_col0\" class=\"data row39 col0\" >B27L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row39_col1\" class=\"data row39 col1\" >DCQFQ.28L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row39_col2\" class=\"data row39 col2\" >MQ.26L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row39_col3\" class=\"data row39 col3\" >MQ.28L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row39_col4\" class=\"data row39 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row39_col5\" class=\"data row39 col5\" >1.97E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
+       "                        <td id=\"T_0bd98_row40_col0\" class=\"data row40 col0\" >B25L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row40_col1\" class=\"data row40 col1\" >DCQFQ.26L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row40_col2\" class=\"data row40 col2\" >MQ.24L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row40_col3\" class=\"data row40 col3\" >MQ.26L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row40_col4\" class=\"data row40 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row40_col5\" class=\"data row40 col5\" >4.47E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
+       "                        <td id=\"T_0bd98_row41_col0\" class=\"data row41 col0\" >B23L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row41_col1\" class=\"data row41 col1\" >DCQFQ.24L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row41_col2\" class=\"data row41 col2\" >MQ.22L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row41_col3\" class=\"data row41 col3\" >MQ.24L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row41_col4\" class=\"data row41 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row41_col5\" class=\"data row41 col5\" >4.78E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
+       "                        <td id=\"T_0bd98_row42_col0\" class=\"data row42 col0\" >B21L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row42_col1\" class=\"data row42 col1\" >DCQFQ.22L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row42_col2\" class=\"data row42 col2\" >MQ.20L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row42_col3\" class=\"data row42 col3\" >MQ.22L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row42_col4\" class=\"data row42 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row42_col5\" class=\"data row42 col5\" >1.06E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
+       "                        <td id=\"T_0bd98_row43_col0\" class=\"data row43 col0\" >B19L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row43_col1\" class=\"data row43 col1\" >DCQFQ.20L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row43_col2\" class=\"data row43 col2\" >MQ.18L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row43_col3\" class=\"data row43 col3\" >MQ.20L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row43_col4\" class=\"data row43 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row43_col5\" class=\"data row43 col5\" >2.66E-10</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
+       "                        <td id=\"T_0bd98_row44_col0\" class=\"data row44 col0\" >B17L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row44_col1\" class=\"data row44 col1\" >DCQFQ.18L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row44_col2\" class=\"data row44 col2\" >MQ.16L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row44_col3\" class=\"data row44 col3\" >MQ.18L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row44_col4\" class=\"data row44 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row44_col5\" class=\"data row44 col5\" >2.13E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
+       "                        <td id=\"T_0bd98_row45_col0\" class=\"data row45 col0\" >B15L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row45_col1\" class=\"data row45 col1\" >DCQFQ.16L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row45_col2\" class=\"data row45 col2\" >MQ.14L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row45_col3\" class=\"data row45 col3\" >MQ.16L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row45_col4\" class=\"data row45 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row45_col5\" class=\"data row45 col5\" >2.88E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
+       "                        <td id=\"T_0bd98_row46_col0\" class=\"data row46 col0\" >B13L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row46_col1\" class=\"data row46 col1\" >DCQFQ.14L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row46_col2\" class=\"data row46 col2\" >MQ.12L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row46_col3\" class=\"data row46 col3\" >MQ.14L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row46_col4\" class=\"data row46 col4\" >8</td>\n",
+       "                        <td id=\"T_0bd98_row46_col5\" class=\"data row46 col5\" >2.86E-09</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_0bd98_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
+       "                        <td id=\"T_0bd98_row47_col0\" class=\"data row47 col0\" >B11L2_4</td>\n",
+       "                        <td id=\"T_0bd98_row47_col1\" class=\"data row47 col1\" >DCQFQ.12L2.L</td>\n",
+       "                        <td id=\"T_0bd98_row47_col2\" class=\"data row47 col2\" >DFLAS.7L2.3</td>\n",
+       "                        <td id=\"T_0bd98_row47_col3\" class=\"data row47 col3\" >MQ.12L2.B2</td>\n",
+       "                        <td id=\"T_0bd98_row47_col4\" class=\"data row47 col4\" >20</td>\n",
+       "                        <td id=\"T_0bd98_row47_col5\" class=\"data row47 col5\" >2.36E-09</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fd3bbb59190>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "if t_pnob3 > 1800 and not res_magnet_rqf_df.empty:\n",
     "    rqf_magnet_metadata_resistance_df = rq_analysis.merge_busbar_metadata_with_resistance(res_magnet_rqf_df, circuit_type, circuit_names, res_col='R_MAG')\n",
-    "    rq_analysis.display_busbar_metadata_resistance_with_threshold(rqd_magnet_metadata_resistance_df, threshold=50e-9, res_col='R_MAG')"
+    "    rq_analysis.display_busbar_metadata_resistance_with_threshold(rqf_magnet_metadata_resistance_df, threshold=50e-9, res_col='R_MAG')"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "3d84c33a",
+   "id": "dceb4ad7",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.516281,
-     "end_time": "2021-11-09T08:45:53.472819",
+     "duration": 0.14379,
+     "end_time": "2022-02-21T15:37:57.795263",
      "exception": false,
-     "start_time": "2021-11-09T08:45:52.956538",
+     "start_time": "2022-02-21T15:37:57.651473",
      "status": "completed"
     },
     "tags": []
@@ -2787,20 +4706,20 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "id": "a666180a",
+   "id": "39411d91",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:54.408263Z",
-     "iopub.status.busy": "2021-11-09T08:45:54.407490Z",
-     "iopub.status.idle": "2021-11-09T08:45:55.052021Z",
-     "shell.execute_reply": "2021-11-09T08:45:55.051087Z"
+     "iopub.execute_input": "2022-02-21T15:37:58.085803Z",
+     "iopub.status.busy": "2022-02-21T15:37:58.085480Z",
+     "iopub.status.idle": "2022-02-21T15:37:58.624129Z",
+     "shell.execute_reply": "2022-02-21T15:37:58.623301Z"
     },
     "papermill": {
-     "duration": 1.156975,
-     "end_time": "2021-11-09T08:45:55.052199",
+     "duration": 0.686301,
+     "end_time": "2022-02-21T15:37:58.626178",
      "exception": false,
-     "start_time": "2021-11-09T08:45:53.895224",
+     "start_time": "2022-02-21T15:37:57.939877",
      "status": "completed"
     },
     "scrolled": false,
@@ -2809,7 +4728,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 936x468 with 1 Axes>"
       ]
@@ -2828,20 +4747,20 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "id": "60f20784",
+   "id": "c1829955",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:55.909737Z",
-     "iopub.status.busy": "2021-11-09T08:45:55.908891Z",
-     "iopub.status.idle": "2021-11-09T08:45:56.468653Z",
-     "shell.execute_reply": "2021-11-09T08:45:56.466225Z"
+     "iopub.execute_input": "2022-02-21T15:37:58.920372Z",
+     "iopub.status.busy": "2022-02-21T15:37:58.920040Z",
+     "iopub.status.idle": "2022-02-21T15:37:59.427015Z",
+     "shell.execute_reply": "2022-02-21T15:37:59.426261Z"
     },
     "papermill": {
-     "duration": 0.988331,
-     "end_time": "2021-11-09T08:45:56.468886",
+     "duration": 0.65718,
+     "end_time": "2022-02-21T15:37:59.429461",
      "exception": false,
-     "start_time": "2021-11-09T08:45:55.480555",
+     "start_time": "2022-02-21T15:37:58.772281",
      "status": "completed"
     },
     "tags": []
@@ -2877,14 +4796,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5adeb019",
+   "id": "cf33abfa",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.497554,
-     "end_time": "2021-11-09T08:45:57.444167",
+     "duration": 0.150842,
+     "end_time": "2022-02-21T15:37:59.731366",
      "exception": false,
-     "start_time": "2021-11-09T08:45:56.946613",
+     "start_time": "2022-02-21T15:37:59.580524",
      "status": "completed"
     },
     "tags": []
@@ -2903,20 +4822,20 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "id": "b5a23697",
+   "id": "56b93f67",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:45:58.397078Z",
-     "iopub.status.busy": "2021-11-09T08:45:58.396089Z",
-     "iopub.status.idle": "2021-11-09T08:45:59.039430Z",
-     "shell.execute_reply": "2021-11-09T08:45:59.038215Z"
+     "iopub.execute_input": "2022-02-21T15:38:00.031509Z",
+     "iopub.status.busy": "2022-02-21T15:38:00.031151Z",
+     "iopub.status.idle": "2022-02-21T15:38:00.685621Z",
+     "shell.execute_reply": "2022-02-21T15:38:00.684822Z"
     },
     "papermill": {
-     "duration": 1.092026,
-     "end_time": "2021-11-09T08:45:59.039697",
+     "duration": 0.808271,
+     "end_time": "2022-02-21T15:38:00.688094",
      "exception": false,
-     "start_time": "2021-11-09T08:45:57.947671",
+     "start_time": "2022-02-21T15:37:59.879823",
      "status": "completed"
     },
     "tags": []
@@ -2952,13 +4871,13 @@
   },
   {
    "cell_type": "markdown",
-   "id": "41ced057",
+   "id": "e9b2312f",
    "metadata": {
     "papermill": {
-     "duration": 0.431888,
-     "end_time": "2021-11-09T08:45:59.947966",
+     "duration": 0.155253,
+     "end_time": "2022-02-21T15:38:00.998695",
      "exception": false,
-     "start_time": "2021-11-09T08:45:59.516078",
+     "start_time": "2022-02-21T15:38:00.843442",
      "status": "completed"
     },
     "tags": []
@@ -2980,19 +4899,19 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "id": "b33eef17",
+   "id": "ffe54cc6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:46:00.844190Z",
-     "iopub.status.busy": "2021-11-09T08:46:00.833612Z",
-     "iopub.status.idle": "2021-11-09T08:46:01.381102Z",
-     "shell.execute_reply": "2021-11-09T08:46:01.380376Z"
+     "iopub.execute_input": "2022-02-21T15:38:01.305767Z",
+     "iopub.status.busy": "2022-02-21T15:38:01.305441Z",
+     "iopub.status.idle": "2022-02-21T15:38:01.813465Z",
+     "shell.execute_reply": "2022-02-21T15:38:01.812553Z"
     },
     "papermill": {
-     "duration": 1.015487,
-     "end_time": "2021-11-09T08:46:01.381291",
+     "duration": 0.665021,
+     "end_time": "2022-02-21T15:38:01.815782",
      "exception": false,
-     "start_time": "2021-11-09T08:46:00.365804",
+     "start_time": "2022-02-21T15:38:01.150761",
      "status": "completed"
     },
     "tags": []
@@ -3018,14 +4937,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cf247674",
+   "id": "2f907892",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.424319,
-     "end_time": "2021-11-09T08:46:02.249905",
+     "duration": 0.152451,
+     "end_time": "2022-02-21T15:38:02.122712",
      "exception": false,
-     "start_time": "2021-11-09T08:46:01.825586",
+     "start_time": "2022-02-21T15:38:01.970261",
      "status": "completed"
     },
     "tags": []
@@ -3047,20 +4966,20 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "id": "0c2459e2",
+   "id": "36455661",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:46:03.178945Z",
-     "iopub.status.busy": "2021-11-09T08:46:03.178039Z",
-     "iopub.status.idle": "2021-11-09T08:46:03.813616Z",
-     "shell.execute_reply": "2021-11-09T08:46:03.809921Z"
+     "iopub.execute_input": "2022-02-21T15:38:02.431821Z",
+     "iopub.status.busy": "2022-02-21T15:38:02.431500Z",
+     "iopub.status.idle": "2022-02-21T15:38:02.947347Z",
+     "shell.execute_reply": "2022-02-21T15:38:02.946401Z"
     },
     "papermill": {
-     "duration": 1.10922,
-     "end_time": "2021-11-09T08:46:03.813808",
+     "duration": 0.672821,
+     "end_time": "2022-02-21T15:38:02.949466",
      "exception": false,
-     "start_time": "2021-11-09T08:46:02.704588",
+     "start_time": "2022-02-21T15:38:02.276645",
      "status": "completed"
     },
     "tags": []
@@ -3086,14 +5005,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8b5d01b6",
+   "id": "b8e9f935",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.437179,
-     "end_time": "2021-11-09T08:46:04.700219",
+     "duration": 0.154372,
+     "end_time": "2022-02-21T15:38:03.258061",
      "exception": false,
-     "start_time": "2021-11-09T08:46:04.263040",
+     "start_time": "2022-02-21T15:38:03.103689",
      "status": "completed"
     },
     "tags": []
@@ -3105,19 +5024,19 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "id": "8a051cac",
+   "id": "7dd71401",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:46:05.685745Z",
-     "iopub.status.busy": "2021-11-09T08:46:05.684979Z",
-     "iopub.status.idle": "2021-11-09T08:46:05.689030Z",
-     "shell.execute_reply": "2021-11-09T08:46:05.688402Z"
+     "iopub.execute_input": "2022-02-21T15:38:03.566861Z",
+     "iopub.status.busy": "2022-02-21T15:38:03.566507Z",
+     "iopub.status.idle": "2022-02-21T15:38:03.570472Z",
+     "shell.execute_reply": "2022-02-21T15:38:03.569743Z"
     },
     "papermill": {
-     "duration": 0.532158,
-     "end_time": "2021-11-09T08:46:05.689212",
+     "duration": 0.160935,
+     "end_time": "2022-02-21T15:38:03.572331",
      "exception": false,
-     "start_time": "2021-11-09T08:46:05.157054",
+     "start_time": "2022-02-21T15:38:03.411396",
      "status": "completed"
     },
     "tags": []
@@ -3129,14 +5048,14 @@
   },
   {
    "cell_type": "raw",
-   "id": "94ef3381",
+   "id": "9d1cce08",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.452642,
-     "end_time": "2021-11-09T08:46:06.583009",
+     "duration": 0.15326,
+     "end_time": "2022-02-21T15:38:03.878750",
      "exception": false,
-     "start_time": "2021-11-09T08:46:06.130367",
+     "start_time": "2022-02-21T15:38:03.725490",
      "status": "completed"
     },
     "tags": [
@@ -3149,14 +5068,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b991adb4",
+   "id": "77deb00d",
    "metadata": {
     "deletable": false,
     "papermill": {
-     "duration": 0.464716,
-     "end_time": "2021-11-09T08:46:07.509523",
+     "duration": 0.154316,
+     "end_time": "2022-02-21T15:38:04.187914",
      "exception": false,
-     "start_time": "2021-11-09T08:46:07.044807",
+     "start_time": "2022-02-21T15:38:04.033598",
      "status": "completed"
     },
     "tags": []
@@ -3168,20 +5087,20 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "id": "b8813f8b",
+   "id": "a5101434",
    "metadata": {
     "deletable": false,
     "execution": {
-     "iopub.execute_input": "2021-11-09T08:46:08.447498Z",
-     "iopub.status.busy": "2021-11-09T08:46:08.442171Z",
-     "iopub.status.idle": "2021-11-09T08:46:22.308326Z",
-     "shell.execute_reply": "2021-11-09T08:46:22.307139Z"
+     "iopub.execute_input": "2022-02-21T15:38:04.499191Z",
+     "iopub.status.busy": "2022-02-21T15:38:04.498847Z",
+     "iopub.status.idle": "2022-02-21T15:38:14.133345Z",
+     "shell.execute_reply": "2022-02-21T15:38:14.132332Z"
     },
     "papermill": {
-     "duration": 14.315626,
-     "end_time": "2021-11-09T08:46:22.308593",
+     "duration": 9.792922,
+     "end_time": "2022-02-21T15:38:14.136098",
      "exception": false,
-     "start_time": "2021-11-09T08:46:07.992967",
+     "start_time": "2022-02-21T15:38:04.343176",
      "status": "completed"
     },
     "tags": []
@@ -3191,6 +5110,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "RQD busbar resistance table saved to (Windows): \\\\cernbox-smb.\\results\\reports\\AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv\n",
+      "RQF busbar resistance table saved to (Windows): \\\\cernbox-smb.\\results\\reports\\AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv\n",
+      "RQD magnet resistance table saved to (Windows): \\\\cernbox-smb.\\results\\reports\\AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv\n",
+      "RQF magnet resistance table saved to (Windows): \\\\cernbox-smb.\\results\\reports\\AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv\n",
       "Compact notebook report saved to (Windows): \\\\cernbox-smb.\\results\\reports\\AN_RQ_PNO.b3.html\n"
      ]
     },
@@ -3241,7 +5164,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[NbConvertApp] Writing 1269279 bytes to ./results/reports/AN_RQ_PNO.b3.html\r\n"
+      "[NbConvertApp] Writing 1514183 bytes to ./results/reports/AN_RQ_PNO.b3.html\r\n"
      ]
     }
    ],
@@ -3253,6 +5176,27 @@
     "report_filename = report_filename_template.format(circuit_name, hwc_test, Time.to_datetime(t_start).strftime(\"%Y-%m-%d-%Hh%M\"), analysis_start_time, signature)\n",
     "\n",
     "!mkdir -p $report_destination_path\n",
+    "\n",
+    "if not res_busbar_rqd_df.empty:\n",
+    "    csv_path = f'{report_destination_path}/{report_filename}_RQD_BUSBAR_RESISTANCE.csv'\n",
+    "    res_busbar_rqd_df.to_csv(csv_path)\n",
+    "    print('RQD busbar resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
+    "if not res_busbar_rqf_df.empty:\n",
+    "    csv_path = f'{report_destination_path}/{report_filename}_RQF_BUSBAR_RESISTANCE.csv'\n",
+    "    res_busbar_rqf_df.to_csv(csv_path)\n",
+    "    print('RQF busbar resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
+    "if not res_magnet_rqd_df.empty:\n",
+    "    csv_path = f'{report_destination_path}/{report_filename}_RQD_MAGNET_RESISTANCE.csv'\n",
+    "    res_magnet_rqd_df.to_csv(csv_path)\n",
+    "    print('RQD magnet resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
+    "if not res_magnet_rqf_df.empty:\n",
+    "    csv_path = f'{report_destination_path}/{report_filename}_RQF_MAGNET_RESISTANCE.csv'\n",
+    "    res_magnet_rqf_df.to_csv(csv_path)\n",
+    "    print('RQF magnet resistance table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_path.replace('/', '\\\\'))\n",
+    "\n",
     "html_filename = f'{report_filename}.html'\n",
     "html_path = f'{report_destination_path}/{report_filename}.html'\n",
     "print('Compact notebook report saved to (Windows): ' + '\\\\\\\\cernbox-smb' + html_path.replace('/', '\\\\'))\n",
@@ -3265,13 +5209,13 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2355bc8d",
+   "id": "2baadcd2",
    "metadata": {
     "papermill": {
-     "duration": 0.439233,
-     "end_time": "2021-11-09T08:46:23.236611",
+     "duration": 0.156464,
+     "end_time": "2022-02-21T15:38:14.450658",
      "exception": false,
-     "start_time": "2021-11-09T08:46:22.797378",
+     "start_time": "2022-02-21T15:38:14.294194",
      "status": "completed"
     },
     "tags": []
@@ -3300,8 +5244,8 @@
   },
   "papermill": {
    "default_parameters": {},
-   "duration": 394.538533,
-   "end_time": "2021-11-09T08:46:24.373425",
+   "duration": 732.681666,
+   "end_time": "2022-02-21T15:38:15.336025",
    "environment_variables": {},
    "exception": null,
    "input_path": "/builds/LHCData/lhc-sm-hwc/test/../rq/AN_RQ_PNO.b3.ipynb",
@@ -3318,8 +5262,8 @@
     "t_end": "2018-03-18 12:13:29.766",
     "t_start": "2018-03-18 07:17:37.130"
    },
-   "start_time": "2021-11-09T08:39:49.834892",
-   "version": "2.3.3"
+   "start_time": "2022-02-21T15:26:02.654359",
+   "version": "2.3.4"
   },
   "sparkconnect": {
    "bundled_options": [
diff --git a/test/resources/reports/AN_RQ_PNO.b3.html b/test/resources/reports/AN_RQ_PNO.b3.html
index 29dcfb3a..3500ca14 100644
--- a/test/resources/reports/AN_RQ_PNO.b3.html
+++ b/test/resources/reports/AN_RQ_PNO.b3.html
@@ -13183,8 +13183,8 @@ div#notebook {
 
 
 <div class="output_subarea output_stream output_stdout output_text">
-<pre>Analysis executed with lhc-sm-api version: 1.5.18
-Analysis executed with lhc-sm-hwc notebooks version: 1.5.66
+<pre>Analysis executed with lhc-sm-api version: 1.5.19
+Analysis executed with lhc-sm-hwc notebooks version: 1.5.67
 Analysis performed by root
 </pre>
 </div>
@@ -13452,7 +13452,7 @@ t_end = &#39;2018-03-18 12:13:29.766&#39;
 
 
 <div class="output_png output_subarea ">
-<img 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
 "
 >
 </div>
@@ -13545,20 +13545,20 @@ max(I_MEAS, Reference): 10350 A
 
 <div class="output_html rendered_html output_subarea ">
 <style  type="text/css" >
-</style><table id="T_f02b1_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
+</style><table id="T_37966_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
                 <tr>
-                        <th id="T_f02b1_level0_row0" class="row_heading level0 row0" >tau_i_meas</th>
-                        <td id="T_f02b1_row0_col0" class="data row0 col0" >25</td>
-                        <td id="T_f02b1_row0_col1" class="data row0 col1" >35</td>
-                        <td id="T_f02b1_row0_col2" class="data row0 col2" >30</td>
-                        <td id="T_f02b1_row0_col3" class="data row0 col3" >True</td>
+                        <th id="T_37966_level0_row0" class="row_heading level0 row0" >tau_i_meas</th>
+                        <td id="T_37966_row0_col0" class="data row0 col0" >25</td>
+                        <td id="T_37966_row0_col1" class="data row0 col1" >35</td>
+                        <td id="T_37966_row0_col2" class="data row0 col2" >30</td>
+                        <td id="T_37966_row0_col3" class="data row0 col3" >True</td>
             </tr>
             <tr>
-                        <th id="T_f02b1_level0_row1" class="row_heading level0 row1" >tau_i_meas_ref</th>
-                        <td id="T_f02b1_row1_col0" class="data row1 col0" >25</td>
-                        <td id="T_f02b1_row1_col1" class="data row1 col1" >35</td>
-                        <td id="T_f02b1_row1_col2" class="data row1 col2" >30</td>
-                        <td id="T_f02b1_row1_col3" class="data row1 col3" >True</td>
+                        <th id="T_37966_level0_row1" class="row_heading level0 row1" >tau_i_meas_ref</th>
+                        <td id="T_37966_row1_col0" class="data row1 col0" >25</td>
+                        <td id="T_37966_row1_col1" class="data row1 col1" >35</td>
+                        <td id="T_37966_row1_col2" class="data row1 col2" >30</td>
+                        <td id="T_37966_row1_col3" class="data row1 col3" >True</td>
             </tr>
     </tbody></table>
 </div>
@@ -13621,20 +13621,20 @@ max(I_MEAS, Reference): 10580 A
 
 <div class="output_html rendered_html output_subarea ">
 <style  type="text/css" >
-</style><table id="T_c5350_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
+</style><table id="T_e31f2_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
                 <tr>
-                        <th id="T_c5350_level0_row0" class="row_heading level0 row0" >tau_i_meas</th>
-                        <td id="T_c5350_row0_col0" class="data row0 col0" >25</td>
-                        <td id="T_c5350_row0_col1" class="data row0 col1" >35</td>
-                        <td id="T_c5350_row0_col2" class="data row0 col2" >31</td>
-                        <td id="T_c5350_row0_col3" class="data row0 col3" >True</td>
+                        <th id="T_e31f2_level0_row0" class="row_heading level0 row0" >tau_i_meas</th>
+                        <td id="T_e31f2_row0_col0" class="data row0 col0" >25</td>
+                        <td id="T_e31f2_row0_col1" class="data row0 col1" >35</td>
+                        <td id="T_e31f2_row0_col2" class="data row0 col2" >31</td>
+                        <td id="T_e31f2_row0_col3" class="data row0 col3" >True</td>
             </tr>
             <tr>
-                        <th id="T_c5350_level0_row1" class="row_heading level0 row1" >tau_i_meas_ref</th>
-                        <td id="T_c5350_row1_col0" class="data row1 col0" >25</td>
-                        <td id="T_c5350_row1_col1" class="data row1 col1" >35</td>
-                        <td id="T_c5350_row1_col2" class="data row1 col2" >31</td>
-                        <td id="T_c5350_row1_col3" class="data row1 col3" >True</td>
+                        <th id="T_e31f2_level0_row1" class="row_heading level0 row1" >tau_i_meas_ref</th>
+                        <td id="T_e31f2_row1_col0" class="data row1 col0" >25</td>
+                        <td id="T_e31f2_row1_col1" class="data row1 col1" >35</td>
+                        <td id="T_e31f2_row1_col2" class="data row1 col2" >31</td>
+                        <td id="T_e31f2_row1_col3" class="data row1 col3" >True</td>
             </tr>
     </tbody></table>
 </div>
@@ -13948,20 +13948,20 @@ To obtain the second derivative of the current decay, the formula above is appli
 
 <div class="output_html rendered_html output_subarea ">
 <style  type="text/css" >
-</style><table id="T_fc0a4_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
+</style><table id="T_de85f_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
                 <tr>
-                        <th id="T_fc0a4_level0_row0" class="row_heading level0 row0" >R</th>
-                        <td id="T_fc0a4_row0_col0" class="data row0 col0" >0.005000</td>
-                        <td id="T_fc0a4_row0_col1" class="data row0 col1" >0.010000</td>
-                        <td id="T_fc0a4_row0_col2" class="data row0 col2" >0.006594</td>
-                        <td id="T_fc0a4_row0_col3" class="data row0 col3" >True</td>
+                        <th id="T_de85f_level0_row0" class="row_heading level0 row0" >R</th>
+                        <td id="T_de85f_row0_col0" class="data row0 col0" >0.005000</td>
+                        <td id="T_de85f_row0_col1" class="data row0 col1" >0.010000</td>
+                        <td id="T_de85f_row0_col2" class="data row0 col2" >0.006594</td>
+                        <td id="T_de85f_row0_col3" class="data row0 col3" >True</td>
             </tr>
             <tr>
-                        <th id="T_fc0a4_level0_row1" class="row_heading level0 row1" >tau_u_dump_res</th>
-                        <td id="T_fc0a4_row1_col0" class="data row1 col0" >25.000000</td>
-                        <td id="T_fc0a4_row1_col1" class="data row1 col1" >35.000000</td>
-                        <td id="T_fc0a4_row1_col2" class="data row1 col2" >33.074706</td>
-                        <td id="T_fc0a4_row1_col3" class="data row1 col3" >True</td>
+                        <th id="T_de85f_level0_row1" class="row_heading level0 row1" >tau_u_dump_res</th>
+                        <td id="T_de85f_row1_col0" class="data row1 col0" >25.000000</td>
+                        <td id="T_de85f_row1_col1" class="data row1 col1" >35.000000</td>
+                        <td id="T_de85f_row1_col2" class="data row1 col2" >33.074706</td>
+                        <td id="T_de85f_row1_col3" class="data row1 col3" >True</td>
             </tr>
     </tbody></table>
 </div>
@@ -14013,20 +14013,20 @@ To obtain the second derivative of the current decay, the formula above is appli
 
 <div class="output_html rendered_html output_subarea ">
 <style  type="text/css" >
-</style><table id="T_402de_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
+</style><table id="T_b1660_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
                 <tr>
-                        <th id="T_402de_level0_row0" class="row_heading level0 row0" >R</th>
-                        <td id="T_402de_row0_col0" class="data row0 col0" >0.005000</td>
-                        <td id="T_402de_row0_col1" class="data row0 col1" >0.010000</td>
-                        <td id="T_402de_row0_col2" class="data row0 col2" >0.006617</td>
-                        <td id="T_402de_row0_col3" class="data row0 col3" >True</td>
+                        <th id="T_b1660_level0_row0" class="row_heading level0 row0" >R</th>
+                        <td id="T_b1660_row0_col0" class="data row0 col0" >0.005000</td>
+                        <td id="T_b1660_row0_col1" class="data row0 col1" >0.010000</td>
+                        <td id="T_b1660_row0_col2" class="data row0 col2" >0.006617</td>
+                        <td id="T_b1660_row0_col3" class="data row0 col3" >True</td>
             </tr>
             <tr>
-                        <th id="T_402de_level0_row1" class="row_heading level0 row1" >tau_u_dump_res</th>
-                        <td id="T_402de_row1_col0" class="data row1 col0" >25.000000</td>
-                        <td id="T_402de_row1_col1" class="data row1 col1" >35.000000</td>
-                        <td id="T_402de_row1_col2" class="data row1 col2" >34.636023</td>
-                        <td id="T_402de_row1_col3" class="data row1 col3" >True</td>
+                        <th id="T_b1660_level0_row1" class="row_heading level0 row1" >tau_u_dump_res</th>
+                        <td id="T_b1660_row1_col0" class="data row1 col0" >25.000000</td>
+                        <td id="T_b1660_row1_col1" class="data row1 col1" >35.000000</td>
+                        <td id="T_b1660_row1_col2" class="data row1 col2" >34.636023</td>
+                        <td id="T_b1660_row1_col3" class="data row1 col3" >True</td>
             </tr>
     </tbody></table>
 </div>
@@ -14078,13 +14078,13 @@ To obtain the second derivative of the current decay, the formula above is appli
 
 <div class="output_html rendered_html output_subarea ">
 <style  type="text/css" >
-</style><table id="T_8e78c_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
+</style><table id="T_15a30_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
                 <tr>
-                        <th id="T_8e78c_level0_row0" class="row_heading level0 row0" >t_delay_ee</th>
-                        <td id="T_8e78c_row0_col0" class="data row0 col0" >0.085000</td>
-                        <td id="T_8e78c_row0_col1" class="data row0 col1" >0.115000</td>
-                        <td id="T_8e78c_row0_col2" class="data row0 col2" >0.089000</td>
-                        <td id="T_8e78c_row0_col3" class="data row0 col3" >True</td>
+                        <th id="T_15a30_level0_row0" class="row_heading level0 row0" >t_delay_ee</th>
+                        <td id="T_15a30_row0_col0" class="data row0 col0" >0.085000</td>
+                        <td id="T_15a30_row0_col1" class="data row0 col1" >0.115000</td>
+                        <td id="T_15a30_row0_col2" class="data row0 col2" >0.089000</td>
+                        <td id="T_15a30_row0_col3" class="data row0 col3" >True</td>
             </tr>
     </tbody></table>
 </div>
@@ -14136,13 +14136,13 @@ To obtain the second derivative of the current decay, the formula above is appli
 
 <div class="output_html rendered_html output_subarea ">
 <style  type="text/css" >
-</style><table id="T_770b3_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
+</style><table id="T_fe7f8_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >min</th>        <th class="col_heading level0 col1" >max</th>        <th class="col_heading level0 col2" >act</th>        <th class="col_heading level0 col3" >result</th>    </tr></thead><tbody>
                 <tr>
-                        <th id="T_770b3_level0_row0" class="row_heading level0 row0" >t_delay_ee</th>
-                        <td id="T_770b3_row0_col0" class="data row0 col0" >0.085000</td>
-                        <td id="T_770b3_row0_col1" class="data row0 col1" >0.115000</td>
-                        <td id="T_770b3_row0_col2" class="data row0 col2" >0.090000</td>
-                        <td id="T_770b3_row0_col3" class="data row0 col3" >True</td>
+                        <th id="T_fe7f8_level0_row0" class="row_heading level0 row0" >t_delay_ee</th>
+                        <td id="T_fe7f8_row0_col0" class="data row0 col0" >0.085000</td>
+                        <td id="T_fe7f8_row0_col1" class="data row0 col1" >0.115000</td>
+                        <td id="T_fe7f8_row0_col2" class="data row0 col2" >0.090000</td>
+                        <td id="T_fe7f8_row0_col3" class="data row0 col3" >True</td>
             </tr>
     </tbody></table>
 </div>
@@ -14207,57 +14207,511 @@ Maximum U_DUMP_RES_RQF (70.0 V) is within of the 10% reference voltage [63.5, 77
 </div>
 <div class="cell border-box-sizing code_cell rendered">
 
-</div>
-<div class="cell border-box-sizing code_cell rendered">
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
 
+<div class="output_png output_subarea ">
+<img 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
+"
+>
 </div>
-<div class="cell border-box-sizing code_cell rendered">
 
 </div>
-<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div><div class="inner_cell">
-<div class="text_cell_render border-box-sizing rendered_html">
-<ul>
-<li>RQF</li>
-</ul>
 
 </div>
 </div>
+
 </div>
 <div class="cell border-box-sizing code_cell rendered">
 
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stdout output_text">
+<pre>All resistances within the range.
+</pre>
+</div>
+</div>
+
+</div>
 </div>
-<div class="cell border-box-sizing code_cell rendered">
 
 </div>
 <div class="cell border-box-sizing code_cell rendered">
 
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+<div class="output_html rendered_html output_subarea ">
+<style  type="text/css" >
+</style><table id="T_cf59d_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >QPS Crate&Board</th>        <th class="col_heading level0 col1" >Bus Bar Segment Name</th>        <th class="col_heading level0 col2" >1st Magnet</th>        <th class="col_heading level0 col3" >2nd Magnet</th>        <th class="col_heading level0 col4" >Num of splices</th>        <th class="col_heading level0 col5" >R_RES</th>    </tr></thead><tbody>
+                <tr>
+                        <th id="T_cf59d_level0_row0" class="row_heading level0 row0" >0</th>
+                        <td id="T_cf59d_row0_col0" class="data row0 col0" >B10L2_3</td>
+                        <td id="T_cf59d_row0_col1" class="data row0 col1" >DCQDD.7L2.L</td>
+                        <td id="T_cf59d_row0_col2" class="data row0 col2" >MQ.11L2.B2</td>
+                        <td id="T_cf59d_row0_col3" class="data row0 col3" >DFLAS.7L2.2</td>
+                        <td id="T_cf59d_row0_col4" class="data row0 col4" >16</td>
+                        <td id="T_cf59d_row0_col5" class="data row0 col5" >5.01E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row1" class="row_heading level0 row1" >1</th>
+                        <td id="T_cf59d_row1_col0" class="data row1 col0" >B12L2_3</td>
+                        <td id="T_cf59d_row1_col1" class="data row1 col1" >DCQDB.A12L2.L</td>
+                        <td id="T_cf59d_row1_col2" class="data row1 col2" >MQ.13L2.B2</td>
+                        <td id="T_cf59d_row1_col3" class="data row1 col3" >MQ.11L2.B2</td>
+                        <td id="T_cf59d_row1_col4" class="data row1 col4" >8</td>
+                        <td id="T_cf59d_row1_col5" class="data row1 col5" >2.72E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row2" class="row_heading level0 row2" >2</th>
+                        <td id="T_cf59d_row2_col0" class="data row2 col0" >B14L2_3</td>
+                        <td id="T_cf59d_row2_col1" class="data row2 col1" >DCQDB.A14L2.L</td>
+                        <td id="T_cf59d_row2_col2" class="data row2 col2" >MQ.15L2.B2</td>
+                        <td id="T_cf59d_row2_col3" class="data row2 col3" >MQ.13L2.B2</td>
+                        <td id="T_cf59d_row2_col4" class="data row2 col4" >8</td>
+                        <td id="T_cf59d_row2_col5" class="data row2 col5" >2.47E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row3" class="row_heading level0 row3" >3</th>
+                        <td id="T_cf59d_row3_col0" class="data row3 col0" >B16L2_3</td>
+                        <td id="T_cf59d_row3_col1" class="data row3 col1" >DCQDB.A16L2.L</td>
+                        <td id="T_cf59d_row3_col2" class="data row3 col2" >MQ.17L2.B2</td>
+                        <td id="T_cf59d_row3_col3" class="data row3 col3" >MQ.15L2.B2</td>
+                        <td id="T_cf59d_row3_col4" class="data row3 col4" >8</td>
+                        <td id="T_cf59d_row3_col5" class="data row3 col5" >2.40E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row4" class="row_heading level0 row4" >4</th>
+                        <td id="T_cf59d_row4_col0" class="data row4 col0" >B18L2_3</td>
+                        <td id="T_cf59d_row4_col1" class="data row4 col1" >DCQDB.A18L2.L</td>
+                        <td id="T_cf59d_row4_col2" class="data row4 col2" >MQ.19L2.B2</td>
+                        <td id="T_cf59d_row4_col3" class="data row4 col3" >MQ.17L2.B2</td>
+                        <td id="T_cf59d_row4_col4" class="data row4 col4" >8</td>
+                        <td id="T_cf59d_row4_col5" class="data row4 col5" >2.27E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row5" class="row_heading level0 row5" >5</th>
+                        <td id="T_cf59d_row5_col0" class="data row5 col0" >B20L2_3</td>
+                        <td id="T_cf59d_row5_col1" class="data row5 col1" >DCQDB.A20L2.L</td>
+                        <td id="T_cf59d_row5_col2" class="data row5 col2" >MQ.21L2.B2</td>
+                        <td id="T_cf59d_row5_col3" class="data row5 col3" >MQ.19L2.B2</td>
+                        <td id="T_cf59d_row5_col4" class="data row5 col4" >8</td>
+                        <td id="T_cf59d_row5_col5" class="data row5 col5" >2.46E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row6" class="row_heading level0 row6" >6</th>
+                        <td id="T_cf59d_row6_col0" class="data row6 col0" >B22L2_3</td>
+                        <td id="T_cf59d_row6_col1" class="data row6 col1" >DCQDB.A22L2.L</td>
+                        <td id="T_cf59d_row6_col2" class="data row6 col2" >MQ.23L2.B2</td>
+                        <td id="T_cf59d_row6_col3" class="data row6 col3" >MQ.21L2.B2</td>
+                        <td id="T_cf59d_row6_col4" class="data row6 col4" >8</td>
+                        <td id="T_cf59d_row6_col5" class="data row6 col5" >3.20E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row7" class="row_heading level0 row7" >7</th>
+                        <td id="T_cf59d_row7_col0" class="data row7 col0" >B24L2_3</td>
+                        <td id="T_cf59d_row7_col1" class="data row7 col1" >DCQDB.A24L2.L</td>
+                        <td id="T_cf59d_row7_col2" class="data row7 col2" >MQ.25L2.B2</td>
+                        <td id="T_cf59d_row7_col3" class="data row7 col3" >MQ.23L2.B2</td>
+                        <td id="T_cf59d_row7_col4" class="data row7 col4" >8</td>
+                        <td id="T_cf59d_row7_col5" class="data row7 col5" >2.78E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row8" class="row_heading level0 row8" >8</th>
+                        <td id="T_cf59d_row8_col0" class="data row8 col0" >B26L2_3</td>
+                        <td id="T_cf59d_row8_col1" class="data row8 col1" >DCQDB.A26L2.L</td>
+                        <td id="T_cf59d_row8_col2" class="data row8 col2" >MQ.27L2.B2</td>
+                        <td id="T_cf59d_row8_col3" class="data row8 col3" >MQ.25L2.B2</td>
+                        <td id="T_cf59d_row8_col4" class="data row8 col4" >8</td>
+                        <td id="T_cf59d_row8_col5" class="data row8 col5" >3.23E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row9" class="row_heading level0 row9" >9</th>
+                        <td id="T_cf59d_row9_col0" class="data row9 col0" >B28L2_3</td>
+                        <td id="T_cf59d_row9_col1" class="data row9 col1" >DCQDB.A28L2.L</td>
+                        <td id="T_cf59d_row9_col2" class="data row9 col2" >MQ.29L2.B2</td>
+                        <td id="T_cf59d_row9_col3" class="data row9 col3" >MQ.27L2.B2</td>
+                        <td id="T_cf59d_row9_col4" class="data row9 col4" >8</td>
+                        <td id="T_cf59d_row9_col5" class="data row9 col5" >2.61E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row10" class="row_heading level0 row10" >10</th>
+                        <td id="T_cf59d_row10_col0" class="data row10 col0" >B30L2_3</td>
+                        <td id="T_cf59d_row10_col1" class="data row10 col1" >DCQDB.A30L2.L</td>
+                        <td id="T_cf59d_row10_col2" class="data row10 col2" >MQ.31L2.B2</td>
+                        <td id="T_cf59d_row10_col3" class="data row10 col3" >MQ.29L2.B2</td>
+                        <td id="T_cf59d_row10_col4" class="data row10 col4" >8</td>
+                        <td id="T_cf59d_row10_col5" class="data row10 col5" >2.35E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row11" class="row_heading level0 row11" >11</th>
+                        <td id="T_cf59d_row11_col0" class="data row11 col0" >B32L2_3</td>
+                        <td id="T_cf59d_row11_col1" class="data row11 col1" >DCQDB.A32L2.L</td>
+                        <td id="T_cf59d_row11_col2" class="data row11 col2" >MQ.33L2.B2</td>
+                        <td id="T_cf59d_row11_col3" class="data row11 col3" >MQ.31L2.B2</td>
+                        <td id="T_cf59d_row11_col4" class="data row11 col4" >8</td>
+                        <td id="T_cf59d_row11_col5" class="data row11 col5" >2.59E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row12" class="row_heading level0 row12" >12</th>
+                        <td id="T_cf59d_row12_col0" class="data row12 col0" >B33R1_3</td>
+                        <td id="T_cf59d_row12_col1" class="data row12 col1" >DCQDQ.32R1.R</td>
+                        <td id="T_cf59d_row12_col2" class="data row12 col2" >MQ.34R1.B1</td>
+                        <td id="T_cf59d_row12_col3" class="data row12 col3" >MQ.32R1.B1</td>
+                        <td id="T_cf59d_row12_col4" class="data row12 col4" >8</td>
+                        <td id="T_cf59d_row12_col5" class="data row12 col5" >2.93E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row13" class="row_heading level0 row13" >13</th>
+                        <td id="T_cf59d_row13_col0" class="data row13 col0" >B31R1_3</td>
+                        <td id="T_cf59d_row13_col1" class="data row13 col1" >DCQDQ.30R1.R</td>
+                        <td id="T_cf59d_row13_col2" class="data row13 col2" >MQ.32R1.B1</td>
+                        <td id="T_cf59d_row13_col3" class="data row13 col3" >MQ.30R1.B1</td>
+                        <td id="T_cf59d_row13_col4" class="data row13 col4" >8</td>
+                        <td id="T_cf59d_row13_col5" class="data row13 col5" >2.54E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row14" class="row_heading level0 row14" >14</th>
+                        <td id="T_cf59d_row14_col0" class="data row14 col0" >B29R1_3</td>
+                        <td id="T_cf59d_row14_col1" class="data row14 col1" >DCQDQ.28R1.R</td>
+                        <td id="T_cf59d_row14_col2" class="data row14 col2" >MQ.30R1.B1</td>
+                        <td id="T_cf59d_row14_col3" class="data row14 col3" >MQ.28R1.B1</td>
+                        <td id="T_cf59d_row14_col4" class="data row14 col4" >8</td>
+                        <td id="T_cf59d_row14_col5" class="data row14 col5" >2.48E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row15" class="row_heading level0 row15" >15</th>
+                        <td id="T_cf59d_row15_col0" class="data row15 col0" >B27R1_3</td>
+                        <td id="T_cf59d_row15_col1" class="data row15 col1" >DCQDQ.26R1.R</td>
+                        <td id="T_cf59d_row15_col2" class="data row15 col2" >MQ.28R1.B1</td>
+                        <td id="T_cf59d_row15_col3" class="data row15 col3" >MQ.26R1.B1</td>
+                        <td id="T_cf59d_row15_col4" class="data row15 col4" >8</td>
+                        <td id="T_cf59d_row15_col5" class="data row15 col5" >2.89E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row16" class="row_heading level0 row16" >16</th>
+                        <td id="T_cf59d_row16_col0" class="data row16 col0" >B25R1_3</td>
+                        <td id="T_cf59d_row16_col1" class="data row16 col1" >DCQDQ.24R1.R</td>
+                        <td id="T_cf59d_row16_col2" class="data row16 col2" >MQ.26R1.B1</td>
+                        <td id="T_cf59d_row16_col3" class="data row16 col3" >MQ.24R1.B1</td>
+                        <td id="T_cf59d_row16_col4" class="data row16 col4" >8</td>
+                        <td id="T_cf59d_row16_col5" class="data row16 col5" >2.95E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row17" class="row_heading level0 row17" >17</th>
+                        <td id="T_cf59d_row17_col0" class="data row17 col0" >B23R1_3</td>
+                        <td id="T_cf59d_row17_col1" class="data row17 col1" >DCQDQ.22R1.R</td>
+                        <td id="T_cf59d_row17_col2" class="data row17 col2" >MQ.24R1.B1</td>
+                        <td id="T_cf59d_row17_col3" class="data row17 col3" >MQ.22R1.B1</td>
+                        <td id="T_cf59d_row17_col4" class="data row17 col4" >8</td>
+                        <td id="T_cf59d_row17_col5" class="data row17 col5" >3.59E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row18" class="row_heading level0 row18" >18</th>
+                        <td id="T_cf59d_row18_col0" class="data row18 col0" >B21R1_3</td>
+                        <td id="T_cf59d_row18_col1" class="data row18 col1" >DCQDQ.20R1.R</td>
+                        <td id="T_cf59d_row18_col2" class="data row18 col2" >MQ.22R1.B1</td>
+                        <td id="T_cf59d_row18_col3" class="data row18 col3" >MQ.20R1.B1</td>
+                        <td id="T_cf59d_row18_col4" class="data row18 col4" >8</td>
+                        <td id="T_cf59d_row18_col5" class="data row18 col5" >2.41E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row19" class="row_heading level0 row19" >19</th>
+                        <td id="T_cf59d_row19_col0" class="data row19 col0" >B19R1_3</td>
+                        <td id="T_cf59d_row19_col1" class="data row19 col1" >DCQDQ.18R1.R</td>
+                        <td id="T_cf59d_row19_col2" class="data row19 col2" >MQ.20R1.B1</td>
+                        <td id="T_cf59d_row19_col3" class="data row19 col3" >MQ.18R1.B1</td>
+                        <td id="T_cf59d_row19_col4" class="data row19 col4" >8</td>
+                        <td id="T_cf59d_row19_col5" class="data row19 col5" >3.60E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row20" class="row_heading level0 row20" >20</th>
+                        <td id="T_cf59d_row20_col0" class="data row20 col0" >B17R1_3</td>
+                        <td id="T_cf59d_row20_col1" class="data row20 col1" >DCQDQ.16R1.R</td>
+                        <td id="T_cf59d_row20_col2" class="data row20 col2" >MQ.18R1.B1</td>
+                        <td id="T_cf59d_row20_col3" class="data row20 col3" >MQ.16R1.B1</td>
+                        <td id="T_cf59d_row20_col4" class="data row20 col4" >8</td>
+                        <td id="T_cf59d_row20_col5" class="data row20 col5" >2.20E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row21" class="row_heading level0 row21" >21</th>
+                        <td id="T_cf59d_row21_col0" class="data row21 col0" >B15R1_3</td>
+                        <td id="T_cf59d_row21_col1" class="data row21 col1" >DCQDQ.14R1.R</td>
+                        <td id="T_cf59d_row21_col2" class="data row21 col2" >MQ.16R1.B1</td>
+                        <td id="T_cf59d_row21_col3" class="data row21 col3" >MQ.14R1.B1</td>
+                        <td id="T_cf59d_row21_col4" class="data row21 col4" >8</td>
+                        <td id="T_cf59d_row21_col5" class="data row21 col5" >2.62E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row22" class="row_heading level0 row22" >22</th>
+                        <td id="T_cf59d_row22_col0" class="data row22 col0" >B13R1_3</td>
+                        <td id="T_cf59d_row22_col1" class="data row22 col1" >DCQDQ.12R1.R</td>
+                        <td id="T_cf59d_row22_col2" class="data row22 col2" >MQ.14R1.B1</td>
+                        <td id="T_cf59d_row22_col3" class="data row22 col3" >MQ.12R1.B1</td>
+                        <td id="T_cf59d_row22_col4" class="data row22 col4" >8</td>
+                        <td id="T_cf59d_row22_col5" class="data row22 col5" >2.93E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row23" class="row_heading level0 row23" >23</th>
+                        <td id="T_cf59d_row23_col0" class="data row23 col0" >B11R1_3</td>
+                        <td id="T_cf59d_row23_col1" class="data row23 col1" >DCQDE.11R1.R</td>
+                        <td id="T_cf59d_row23_col2" class="data row23 col2" >MQ.12R1.B1</td>
+                        <td id="T_cf59d_row23_col3" class="data row23 col3" >MQ.11R1.B2</td>
+                        <td id="T_cf59d_row23_col4" class="data row23 col4" >6</td>
+                        <td id="T_cf59d_row23_col5" class="data row23 col5" >1.90E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row24" class="row_heading level0 row24" >24</th>
+                        <td id="T_cf59d_row24_col0" class="data row24 col0" >B12R1_3</td>
+                        <td id="T_cf59d_row24_col1" class="data row24 col1" >DCQDB.C13R1.L</td>
+                        <td id="T_cf59d_row24_col2" class="data row24 col2" >MQ.11R1.B2</td>
+                        <td id="T_cf59d_row24_col3" class="data row24 col3" >MQ.13R1.B2</td>
+                        <td id="T_cf59d_row24_col4" class="data row24 col4" >8</td>
+                        <td id="T_cf59d_row24_col5" class="data row24 col5" >2.56E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row25" class="row_heading level0 row25" >25</th>
+                        <td id="T_cf59d_row25_col0" class="data row25 col0" >B14R1_3</td>
+                        <td id="T_cf59d_row25_col1" class="data row25 col1" >DCQDB.C15R1.L</td>
+                        <td id="T_cf59d_row25_col2" class="data row25 col2" >MQ.13R1.B2</td>
+                        <td id="T_cf59d_row25_col3" class="data row25 col3" >MQ.15R1.B2</td>
+                        <td id="T_cf59d_row25_col4" class="data row25 col4" >8</td>
+                        <td id="T_cf59d_row25_col5" class="data row25 col5" >2.52E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row26" class="row_heading level0 row26" >26</th>
+                        <td id="T_cf59d_row26_col0" class="data row26 col0" >B16R1_3</td>
+                        <td id="T_cf59d_row26_col1" class="data row26 col1" >DCQDB.C17R1.L</td>
+                        <td id="T_cf59d_row26_col2" class="data row26 col2" >MQ.15R1.B2</td>
+                        <td id="T_cf59d_row26_col3" class="data row26 col3" >MQ.17R1.B2</td>
+                        <td id="T_cf59d_row26_col4" class="data row26 col4" >8</td>
+                        <td id="T_cf59d_row26_col5" class="data row26 col5" >2.77E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row27" class="row_heading level0 row27" >27</th>
+                        <td id="T_cf59d_row27_col0" class="data row27 col0" >B18R1_3</td>
+                        <td id="T_cf59d_row27_col1" class="data row27 col1" >DCQDB.C19R1.L</td>
+                        <td id="T_cf59d_row27_col2" class="data row27 col2" >MQ.17R1.B2</td>
+                        <td id="T_cf59d_row27_col3" class="data row27 col3" >MQ.19R1.B2</td>
+                        <td id="T_cf59d_row27_col4" class="data row27 col4" >8</td>
+                        <td id="T_cf59d_row27_col5" class="data row27 col5" >3.03E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row28" class="row_heading level0 row28" >28</th>
+                        <td id="T_cf59d_row28_col0" class="data row28 col0" >B20R1_3</td>
+                        <td id="T_cf59d_row28_col1" class="data row28 col1" >DCQDB.C21R1.L</td>
+                        <td id="T_cf59d_row28_col2" class="data row28 col2" >MQ.19R1.B2</td>
+                        <td id="T_cf59d_row28_col3" class="data row28 col3" >MQ.21R1.B2</td>
+                        <td id="T_cf59d_row28_col4" class="data row28 col4" >8</td>
+                        <td id="T_cf59d_row28_col5" class="data row28 col5" >3.46E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row29" class="row_heading level0 row29" >29</th>
+                        <td id="T_cf59d_row29_col0" class="data row29 col0" >B22R1_3</td>
+                        <td id="T_cf59d_row29_col1" class="data row29 col1" >DCQDB.C23R1.L</td>
+                        <td id="T_cf59d_row29_col2" class="data row29 col2" >MQ.21R1.B2</td>
+                        <td id="T_cf59d_row29_col3" class="data row29 col3" >MQ.23R1.B2</td>
+                        <td id="T_cf59d_row29_col4" class="data row29 col4" >8</td>
+                        <td id="T_cf59d_row29_col5" class="data row29 col5" >2.65E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row30" class="row_heading level0 row30" >30</th>
+                        <td id="T_cf59d_row30_col0" class="data row30 col0" >B24R1_3</td>
+                        <td id="T_cf59d_row30_col1" class="data row30 col1" >DCQDB.C25R1.L</td>
+                        <td id="T_cf59d_row30_col2" class="data row30 col2" >MQ.23R1.B2</td>
+                        <td id="T_cf59d_row30_col3" class="data row30 col3" >MQ.25R1.B2</td>
+                        <td id="T_cf59d_row30_col4" class="data row30 col4" >8</td>
+                        <td id="T_cf59d_row30_col5" class="data row30 col5" >3.00E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row31" class="row_heading level0 row31" >31</th>
+                        <td id="T_cf59d_row31_col0" class="data row31 col0" >B26R1_3</td>
+                        <td id="T_cf59d_row31_col1" class="data row31 col1" >DCQDB.C27R1.L</td>
+                        <td id="T_cf59d_row31_col2" class="data row31 col2" >MQ.25R1.B2</td>
+                        <td id="T_cf59d_row31_col3" class="data row31 col3" >MQ.27R1.B2</td>
+                        <td id="T_cf59d_row31_col4" class="data row31 col4" >8</td>
+                        <td id="T_cf59d_row31_col5" class="data row31 col5" >2.74E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row32" class="row_heading level0 row32" >32</th>
+                        <td id="T_cf59d_row32_col0" class="data row32 col0" >B28R1_3</td>
+                        <td id="T_cf59d_row32_col1" class="data row32 col1" >DCQDB.C29R1.L</td>
+                        <td id="T_cf59d_row32_col2" class="data row32 col2" >MQ.27R1.B2</td>
+                        <td id="T_cf59d_row32_col3" class="data row32 col3" >MQ.29R1.B2</td>
+                        <td id="T_cf59d_row32_col4" class="data row32 col4" >8</td>
+                        <td id="T_cf59d_row32_col5" class="data row32 col5" >2.87E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row33" class="row_heading level0 row33" >33</th>
+                        <td id="T_cf59d_row33_col0" class="data row33 col0" >B30R1_3</td>
+                        <td id="T_cf59d_row33_col1" class="data row33 col1" >DCQDB.C31R1.L</td>
+                        <td id="T_cf59d_row33_col2" class="data row33 col2" >MQ.29R1.B2</td>
+                        <td id="T_cf59d_row33_col3" class="data row33 col3" >MQ.31R1.B2</td>
+                        <td id="T_cf59d_row33_col4" class="data row33 col4" >8</td>
+                        <td id="T_cf59d_row33_col5" class="data row33 col5" >2.65E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row34" class="row_heading level0 row34" >34</th>
+                        <td id="T_cf59d_row34_col0" class="data row34 col0" >B32R1_3</td>
+                        <td id="T_cf59d_row34_col1" class="data row34 col1" >DCQDB.C33R1.L</td>
+                        <td id="T_cf59d_row34_col2" class="data row34 col2" >MQ.31R1.B2</td>
+                        <td id="T_cf59d_row34_col3" class="data row34 col3" >MQ.33R1.B2</td>
+                        <td id="T_cf59d_row34_col4" class="data row34 col4" >8</td>
+                        <td id="T_cf59d_row34_col5" class="data row34 col5" >2.74E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row35" class="row_heading level0 row35" >35</th>
+                        <td id="T_cf59d_row35_col0" class="data row35 col0" >B34R1_3</td>
+                        <td id="T_cf59d_row35_col1" class="data row35 col1" >DCQDB.A34L2.L</td>
+                        <td id="T_cf59d_row35_col2" class="data row35 col2" >MQ.33R1.B2</td>
+                        <td id="T_cf59d_row35_col3" class="data row35 col3" >MQ.33L2.B2</td>
+                        <td id="T_cf59d_row35_col4" class="data row35 col4" >8</td>
+                        <td id="T_cf59d_row35_col5" class="data row35 col5" >2.92E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row36" class="row_heading level0 row36" >36</th>
+                        <td id="T_cf59d_row36_col0" class="data row36 col0" >B33L2_3</td>
+                        <td id="T_cf59d_row36_col1" class="data row36 col1" >DCQDQ.34R1.R</td>
+                        <td id="T_cf59d_row36_col2" class="data row36 col2" >MQ.32L2.B1</td>
+                        <td id="T_cf59d_row36_col3" class="data row36 col3" >MQ.34R1.B1</td>
+                        <td id="T_cf59d_row36_col4" class="data row36 col4" >8</td>
+                        <td id="T_cf59d_row36_col5" class="data row36 col5" >2.81E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row37" class="row_heading level0 row37" >37</th>
+                        <td id="T_cf59d_row37_col0" class="data row37 col0" >B31L2_3</td>
+                        <td id="T_cf59d_row37_col1" class="data row37 col1" >DCQDQ.32L2.R</td>
+                        <td id="T_cf59d_row37_col2" class="data row37 col2" >MQ.30L2.B1</td>
+                        <td id="T_cf59d_row37_col3" class="data row37 col3" >MQ.32L2.B1</td>
+                        <td id="T_cf59d_row37_col4" class="data row37 col4" >8</td>
+                        <td id="T_cf59d_row37_col5" class="data row37 col5" >2.92E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row38" class="row_heading level0 row38" >38</th>
+                        <td id="T_cf59d_row38_col0" class="data row38 col0" >B29L2_3</td>
+                        <td id="T_cf59d_row38_col1" class="data row38 col1" >DCQDQ.30L2.R</td>
+                        <td id="T_cf59d_row38_col2" class="data row38 col2" >MQ.28L2.B1</td>
+                        <td id="T_cf59d_row38_col3" class="data row38 col3" >MQ.30L2.B1</td>
+                        <td id="T_cf59d_row38_col4" class="data row38 col4" >8</td>
+                        <td id="T_cf59d_row38_col5" class="data row38 col5" >2.96E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row39" class="row_heading level0 row39" >39</th>
+                        <td id="T_cf59d_row39_col0" class="data row39 col0" >B27L2_3</td>
+                        <td id="T_cf59d_row39_col1" class="data row39 col1" >DCQDQ.28L2.R</td>
+                        <td id="T_cf59d_row39_col2" class="data row39 col2" >MQ.26L2.B1</td>
+                        <td id="T_cf59d_row39_col3" class="data row39 col3" >MQ.28L2.B1</td>
+                        <td id="T_cf59d_row39_col4" class="data row39 col4" >8</td>
+                        <td id="T_cf59d_row39_col5" class="data row39 col5" >2.50E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row40" class="row_heading level0 row40" >40</th>
+                        <td id="T_cf59d_row40_col0" class="data row40 col0" >B25L2_3</td>
+                        <td id="T_cf59d_row40_col1" class="data row40 col1" >DCQDQ.26L2.R</td>
+                        <td id="T_cf59d_row40_col2" class="data row40 col2" >MQ.24L2.B1</td>
+                        <td id="T_cf59d_row40_col3" class="data row40 col3" >MQ.26L2.B1</td>
+                        <td id="T_cf59d_row40_col4" class="data row40 col4" >8</td>
+                        <td id="T_cf59d_row40_col5" class="data row40 col5" >2.47E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row41" class="row_heading level0 row41" >41</th>
+                        <td id="T_cf59d_row41_col0" class="data row41 col0" >B23L2_3</td>
+                        <td id="T_cf59d_row41_col1" class="data row41 col1" >DCQDQ.24L2.R</td>
+                        <td id="T_cf59d_row41_col2" class="data row41 col2" >MQ.22L2.B1</td>
+                        <td id="T_cf59d_row41_col3" class="data row41 col3" >MQ.24L2.B1</td>
+                        <td id="T_cf59d_row41_col4" class="data row41 col4" >8</td>
+                        <td id="T_cf59d_row41_col5" class="data row41 col5" >3.18E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row42" class="row_heading level0 row42" >42</th>
+                        <td id="T_cf59d_row42_col0" class="data row42 col0" >B21L2_3</td>
+                        <td id="T_cf59d_row42_col1" class="data row42 col1" >DCQDQ.22L2.R</td>
+                        <td id="T_cf59d_row42_col2" class="data row42 col2" >MQ.20L2.B1</td>
+                        <td id="T_cf59d_row42_col3" class="data row42 col3" >MQ.22L2.B1</td>
+                        <td id="T_cf59d_row42_col4" class="data row42 col4" >8</td>
+                        <td id="T_cf59d_row42_col5" class="data row42 col5" >2.81E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row43" class="row_heading level0 row43" >43</th>
+                        <td id="T_cf59d_row43_col0" class="data row43 col0" >B19L2_3</td>
+                        <td id="T_cf59d_row43_col1" class="data row43 col1" >DCQDQ.20L2.R</td>
+                        <td id="T_cf59d_row43_col2" class="data row43 col2" >MQ.18L2.B1</td>
+                        <td id="T_cf59d_row43_col3" class="data row43 col3" >MQ.20L2.B1</td>
+                        <td id="T_cf59d_row43_col4" class="data row43 col4" >8</td>
+                        <td id="T_cf59d_row43_col5" class="data row43 col5" >2.94E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row44" class="row_heading level0 row44" >44</th>
+                        <td id="T_cf59d_row44_col0" class="data row44 col0" >B17L2_3</td>
+                        <td id="T_cf59d_row44_col1" class="data row44 col1" >DCQDQ.18L2.R</td>
+                        <td id="T_cf59d_row44_col2" class="data row44 col2" >MQ.16L2.B1</td>
+                        <td id="T_cf59d_row44_col3" class="data row44 col3" >MQ.18L2.B1</td>
+                        <td id="T_cf59d_row44_col4" class="data row44 col4" >8</td>
+                        <td id="T_cf59d_row44_col5" class="data row44 col5" >2.84E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row45" class="row_heading level0 row45" >45</th>
+                        <td id="T_cf59d_row45_col0" class="data row45 col0" >B15L2_3</td>
+                        <td id="T_cf59d_row45_col1" class="data row45 col1" >DCQDQ.16L2.R</td>
+                        <td id="T_cf59d_row45_col2" class="data row45 col2" >MQ.14L2.B1</td>
+                        <td id="T_cf59d_row45_col3" class="data row45 col3" >MQ.16L2.B1</td>
+                        <td id="T_cf59d_row45_col4" class="data row45 col4" >8</td>
+                        <td id="T_cf59d_row45_col5" class="data row45 col5" >2.47E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row46" class="row_heading level0 row46" >46</th>
+                        <td id="T_cf59d_row46_col0" class="data row46 col0" >B13L2_3</td>
+                        <td id="T_cf59d_row46_col1" class="data row46 col1" >DCQDQ.14L2.R</td>
+                        <td id="T_cf59d_row46_col2" class="data row46 col2" >MQ.12L2.B1</td>
+                        <td id="T_cf59d_row46_col3" class="data row46 col3" >MQ.14L2.B1</td>
+                        <td id="T_cf59d_row46_col4" class="data row46 col4" >8</td>
+                        <td id="T_cf59d_row46_col5" class="data row46 col5" >2.56E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_cf59d_level0_row47" class="row_heading level0 row47" >47</th>
+                        <td id="T_cf59d_row47_col0" class="data row47 col0" >B11L2_3</td>
+                        <td id="T_cf59d_row47_col1" class="data row47 col1" >DCQDQ.12L2.R</td>
+                        <td id="T_cf59d_row47_col2" class="data row47 col2" >DFLAS.7L2.1</td>
+                        <td id="T_cf59d_row47_col3" class="data row47 col3" >MQ.12L2.B1</td>
+                        <td id="T_cf59d_row47_col4" class="data row47 col4" >20</td>
+                        <td id="T_cf59d_row47_col5" class="data row47 col5" >5.95E-09</td>
+            </tr>
+    </tbody></table>
+</div>
+
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-<h2 id="7.2.-Magnet-Resistance">7.2. Magnet Resistance<a class="anchor-link" href="#7.2.-Magnet-Resistance">&#182;</a></h2><p><em>ANALYSIS</em>:</p>
-<ul>
-<li>Calculation of the magnet resistance as the slope of a linear fit of U,I curve obtained from the corresponding mean alues of the voltage and current</li>
-</ul>
-<p><em>CRITERIA</em>:</p>
-<ul>
-<li>Check if the magnet resistance is below 50 nOhm</li>
-</ul>
-<p><em>GRAPHS</em>:</p>
-<ul>
-<li>The magnet resistance, R</li>
-<li>The green box denotes the validity region of the magnet resostance (0, 50] nOhm</li>
-</ul>
 
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+
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 <ul>
-<li>RQD</li>
+<li>RQF</li>
 </ul>
 
 </div>
@@ -14265,31 +14719,1549 @@ Maximum U_DUMP_RES_RQF (70.0 V) is within of the 10% reference voltage [63.5, 77
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-</div>
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+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
 
+    <div class="prompt"></div>
+
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+<div class="output_png output_subarea ">
+<img 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
+"
+>
 </div>
-<div class="cell border-box-sizing code_cell rendered">
 
 </div>
-<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div><div class="inner_cell">
-<div class="text_cell_render border-box-sizing rendered_html">
-<ul>
-<li>RQF</li>
-</ul>
 
 </div>
 </div>
+
 </div>
 <div class="cell border-box-sizing code_cell rendered">
 
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stdout output_text">
+<pre>All resistances within the range.
+</pre>
+</div>
+</div>
+
+</div>
 </div>
-<div class="cell border-box-sizing code_cell rendered">
 
 </div>
 <div class="cell border-box-sizing code_cell rendered">
 
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+<div class="output_html rendered_html output_subarea ">
+<style  type="text/css" >
+</style><table id="T_06bb7_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >QPS Crate&Board</th>        <th class="col_heading level0 col1" >Bus Bar Segment Name</th>        <th class="col_heading level0 col2" >1st Magnet</th>        <th class="col_heading level0 col3" >2nd Magnet</th>        <th class="col_heading level0 col4" >Num of splices</th>        <th class="col_heading level0 col5" >R_RES</th>    </tr></thead><tbody>
+                <tr>
+                        <th id="T_06bb7_level0_row0" class="row_heading level0 row0" >0</th>
+                        <td id="T_06bb7_row0_col0" class="data row0 col0" >B10L2_4</td>
+                        <td id="T_06bb7_row0_col1" class="data row0 col1" >DCQFD.7L2.R</td>
+                        <td id="T_06bb7_row0_col2" class="data row0 col2" >MQ.11L2.B1</td>
+                        <td id="T_06bb7_row0_col3" class="data row0 col3" >DFLAS.7L2.4</td>
+                        <td id="T_06bb7_row0_col4" class="data row0 col4" >16</td>
+                        <td id="T_06bb7_row0_col5" class="data row0 col5" >5.20E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row1" class="row_heading level0 row1" >1</th>
+                        <td id="T_06bb7_row1_col0" class="data row1 col0" >B12L2_4</td>
+                        <td id="T_06bb7_row1_col1" class="data row1 col1" >DCQFB.A12L2.R</td>
+                        <td id="T_06bb7_row1_col2" class="data row1 col2" >MQ.13L2.B1</td>
+                        <td id="T_06bb7_row1_col3" class="data row1 col3" >MQ.11L2.B1</td>
+                        <td id="T_06bb7_row1_col4" class="data row1 col4" >8</td>
+                        <td id="T_06bb7_row1_col5" class="data row1 col5" >2.15E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row2" class="row_heading level0 row2" >2</th>
+                        <td id="T_06bb7_row2_col0" class="data row2 col0" >B14L2_4</td>
+                        <td id="T_06bb7_row2_col1" class="data row2 col1" >DCQFB.A14L2.R</td>
+                        <td id="T_06bb7_row2_col2" class="data row2 col2" >MQ.15L2.B1</td>
+                        <td id="T_06bb7_row2_col3" class="data row2 col3" >MQ.13L2.B1</td>
+                        <td id="T_06bb7_row2_col4" class="data row2 col4" >8</td>
+                        <td id="T_06bb7_row2_col5" class="data row2 col5" >2.52E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row3" class="row_heading level0 row3" >3</th>
+                        <td id="T_06bb7_row3_col0" class="data row3 col0" >B16L2_4</td>
+                        <td id="T_06bb7_row3_col1" class="data row3 col1" >DCQFB.A16L2.R</td>
+                        <td id="T_06bb7_row3_col2" class="data row3 col2" >MQ.17L2.B1</td>
+                        <td id="T_06bb7_row3_col3" class="data row3 col3" >MQ.15L2.B1</td>
+                        <td id="T_06bb7_row3_col4" class="data row3 col4" >8</td>
+                        <td id="T_06bb7_row3_col5" class="data row3 col5" >2.11E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row4" class="row_heading level0 row4" >4</th>
+                        <td id="T_06bb7_row4_col0" class="data row4 col0" >B18L2_4</td>
+                        <td id="T_06bb7_row4_col1" class="data row4 col1" >DCQFB.A18L2.R</td>
+                        <td id="T_06bb7_row4_col2" class="data row4 col2" >MQ.19L2.B1</td>
+                        <td id="T_06bb7_row4_col3" class="data row4 col3" >MQ.17L2.B1</td>
+                        <td id="T_06bb7_row4_col4" class="data row4 col4" >8</td>
+                        <td id="T_06bb7_row4_col5" class="data row4 col5" >2.35E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row5" class="row_heading level0 row5" >5</th>
+                        <td id="T_06bb7_row5_col0" class="data row5 col0" >B20L2_4</td>
+                        <td id="T_06bb7_row5_col1" class="data row5 col1" >DCQFB.A20L2.R</td>
+                        <td id="T_06bb7_row5_col2" class="data row5 col2" >MQ.21L2.B1</td>
+                        <td id="T_06bb7_row5_col3" class="data row5 col3" >MQ.19L2.B1</td>
+                        <td id="T_06bb7_row5_col4" class="data row5 col4" >8</td>
+                        <td id="T_06bb7_row5_col5" class="data row5 col5" >2.06E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row6" class="row_heading level0 row6" >6</th>
+                        <td id="T_06bb7_row6_col0" class="data row6 col0" >B22L2_4</td>
+                        <td id="T_06bb7_row6_col1" class="data row6 col1" >DCQFB.A22L2.R</td>
+                        <td id="T_06bb7_row6_col2" class="data row6 col2" >MQ.23L2.B1</td>
+                        <td id="T_06bb7_row6_col3" class="data row6 col3" >MQ.21L2.B1</td>
+                        <td id="T_06bb7_row6_col4" class="data row6 col4" >8</td>
+                        <td id="T_06bb7_row6_col5" class="data row6 col5" >2.36E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row7" class="row_heading level0 row7" >7</th>
+                        <td id="T_06bb7_row7_col0" class="data row7 col0" >B24L2_4</td>
+                        <td id="T_06bb7_row7_col1" class="data row7 col1" >DCQFB.A24L2.R</td>
+                        <td id="T_06bb7_row7_col2" class="data row7 col2" >MQ.25L2.B1</td>
+                        <td id="T_06bb7_row7_col3" class="data row7 col3" >MQ.23L2.B1</td>
+                        <td id="T_06bb7_row7_col4" class="data row7 col4" >8</td>
+                        <td id="T_06bb7_row7_col5" class="data row7 col5" >2.42E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row8" class="row_heading level0 row8" >8</th>
+                        <td id="T_06bb7_row8_col0" class="data row8 col0" >B26L2_4</td>
+                        <td id="T_06bb7_row8_col1" class="data row8 col1" >DCQFB.A26L2.R</td>
+                        <td id="T_06bb7_row8_col2" class="data row8 col2" >MQ.27L2.B1</td>
+                        <td id="T_06bb7_row8_col3" class="data row8 col3" >MQ.25L2.B1</td>
+                        <td id="T_06bb7_row8_col4" class="data row8 col4" >8</td>
+                        <td id="T_06bb7_row8_col5" class="data row8 col5" >2.28E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row9" class="row_heading level0 row9" >9</th>
+                        <td id="T_06bb7_row9_col0" class="data row9 col0" >B28L2_4</td>
+                        <td id="T_06bb7_row9_col1" class="data row9 col1" >DCQFB.A28L2.R</td>
+                        <td id="T_06bb7_row9_col2" class="data row9 col2" >MQ.29L2.B1</td>
+                        <td id="T_06bb7_row9_col3" class="data row9 col3" >MQ.27L2.B1</td>
+                        <td id="T_06bb7_row9_col4" class="data row9 col4" >8</td>
+                        <td id="T_06bb7_row9_col5" class="data row9 col5" >2.55E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row10" class="row_heading level0 row10" >10</th>
+                        <td id="T_06bb7_row10_col0" class="data row10 col0" >B30L2_4</td>
+                        <td id="T_06bb7_row10_col1" class="data row10 col1" >DCQFB.A30L2.R</td>
+                        <td id="T_06bb7_row10_col2" class="data row10 col2" >MQ.31L2.B1</td>
+                        <td id="T_06bb7_row10_col3" class="data row10 col3" >MQ.29L2.B1</td>
+                        <td id="T_06bb7_row10_col4" class="data row10 col4" >8</td>
+                        <td id="T_06bb7_row10_col5" class="data row10 col5" >2.33E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row11" class="row_heading level0 row11" >11</th>
+                        <td id="T_06bb7_row11_col0" class="data row11 col0" >B32L2_4</td>
+                        <td id="T_06bb7_row11_col1" class="data row11 col1" >DCQFB.C32L2.R</td>
+                        <td id="T_06bb7_row11_col2" class="data row11 col2" >MQ.33L2.B1</td>
+                        <td id="T_06bb7_row11_col3" class="data row11 col3" >MQ.31L2.B1</td>
+                        <td id="T_06bb7_row11_col4" class="data row11 col4" >8</td>
+                        <td id="T_06bb7_row11_col5" class="data row11 col5" >2.51E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row12" class="row_heading level0 row12" >12</th>
+                        <td id="T_06bb7_row12_col0" class="data row12 col0" >B33R1_4</td>
+                        <td id="T_06bb7_row12_col1" class="data row12 col1" >DCQFQ.32R1.L</td>
+                        <td id="T_06bb7_row12_col2" class="data row12 col2" >MQ.34R1.B2</td>
+                        <td id="T_06bb7_row12_col3" class="data row12 col3" >MQ.32R1.B2</td>
+                        <td id="T_06bb7_row12_col4" class="data row12 col4" >8</td>
+                        <td id="T_06bb7_row12_col5" class="data row12 col5" >2.74E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row13" class="row_heading level0 row13" >13</th>
+                        <td id="T_06bb7_row13_col0" class="data row13 col0" >B31R1_4</td>
+                        <td id="T_06bb7_row13_col1" class="data row13 col1" >DCQFQ.30R1.L</td>
+                        <td id="T_06bb7_row13_col2" class="data row13 col2" >MQ.32R1.B2</td>
+                        <td id="T_06bb7_row13_col3" class="data row13 col3" >MQ.30R1.B2</td>
+                        <td id="T_06bb7_row13_col4" class="data row13 col4" >8</td>
+                        <td id="T_06bb7_row13_col5" class="data row13 col5" >2.34E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row14" class="row_heading level0 row14" >14</th>
+                        <td id="T_06bb7_row14_col0" class="data row14 col0" >B29R1_4</td>
+                        <td id="T_06bb7_row14_col1" class="data row14 col1" >DCQFQ.28R1.L</td>
+                        <td id="T_06bb7_row14_col2" class="data row14 col2" >MQ.30R1.B2</td>
+                        <td id="T_06bb7_row14_col3" class="data row14 col3" >MQ.28R1.B2</td>
+                        <td id="T_06bb7_row14_col4" class="data row14 col4" >8</td>
+                        <td id="T_06bb7_row14_col5" class="data row14 col5" >2.44E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row15" class="row_heading level0 row15" >15</th>
+                        <td id="T_06bb7_row15_col0" class="data row15 col0" >B27R1_4</td>
+                        <td id="T_06bb7_row15_col1" class="data row15 col1" >DCQFQ.26R1.L</td>
+                        <td id="T_06bb7_row15_col2" class="data row15 col2" >MQ.28R1.B2</td>
+                        <td id="T_06bb7_row15_col3" class="data row15 col3" >MQ.26R1.B2</td>
+                        <td id="T_06bb7_row15_col4" class="data row15 col4" >8</td>
+                        <td id="T_06bb7_row15_col5" class="data row15 col5" >2.55E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row16" class="row_heading level0 row16" >16</th>
+                        <td id="T_06bb7_row16_col0" class="data row16 col0" >B25R1_4</td>
+                        <td id="T_06bb7_row16_col1" class="data row16 col1" >DCQFQ.24R1.L</td>
+                        <td id="T_06bb7_row16_col2" class="data row16 col2" >MQ.26R1.B2</td>
+                        <td id="T_06bb7_row16_col3" class="data row16 col3" >MQ.24R1.B2</td>
+                        <td id="T_06bb7_row16_col4" class="data row16 col4" >8</td>
+                        <td id="T_06bb7_row16_col5" class="data row16 col5" >2.60E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row17" class="row_heading level0 row17" >17</th>
+                        <td id="T_06bb7_row17_col0" class="data row17 col0" >B23R1_4</td>
+                        <td id="T_06bb7_row17_col1" class="data row17 col1" >DCQFQ.22R1.L</td>
+                        <td id="T_06bb7_row17_col2" class="data row17 col2" >MQ.24R1.B2</td>
+                        <td id="T_06bb7_row17_col3" class="data row17 col3" >MQ.22R1.B2</td>
+                        <td id="T_06bb7_row17_col4" class="data row17 col4" >8</td>
+                        <td id="T_06bb7_row17_col5" class="data row17 col5" >2.76E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row18" class="row_heading level0 row18" >18</th>
+                        <td id="T_06bb7_row18_col0" class="data row18 col0" >B21R1_4</td>
+                        <td id="T_06bb7_row18_col1" class="data row18 col1" >DCQFQ.20R1.L</td>
+                        <td id="T_06bb7_row18_col2" class="data row18 col2" >MQ.22R1.B2</td>
+                        <td id="T_06bb7_row18_col3" class="data row18 col3" >MQ.20R1.B2</td>
+                        <td id="T_06bb7_row18_col4" class="data row18 col4" >8</td>
+                        <td id="T_06bb7_row18_col5" class="data row18 col5" >2.58E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row19" class="row_heading level0 row19" >19</th>
+                        <td id="T_06bb7_row19_col0" class="data row19 col0" >B19R1_4</td>
+                        <td id="T_06bb7_row19_col1" class="data row19 col1" >DCQFQ.18R1.L</td>
+                        <td id="T_06bb7_row19_col2" class="data row19 col2" >MQ.20R1.B2</td>
+                        <td id="T_06bb7_row19_col3" class="data row19 col3" >MQ.18R1.B2</td>
+                        <td id="T_06bb7_row19_col4" class="data row19 col4" >8</td>
+                        <td id="T_06bb7_row19_col5" class="data row19 col5" >2.65E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row20" class="row_heading level0 row20" >20</th>
+                        <td id="T_06bb7_row20_col0" class="data row20 col0" >B17R1_4</td>
+                        <td id="T_06bb7_row20_col1" class="data row20 col1" >DCQFQ.16R1.L</td>
+                        <td id="T_06bb7_row20_col2" class="data row20 col2" >MQ.18R1.B2</td>
+                        <td id="T_06bb7_row20_col3" class="data row20 col3" >MQ.16R1.B2</td>
+                        <td id="T_06bb7_row20_col4" class="data row20 col4" >8</td>
+                        <td id="T_06bb7_row20_col5" class="data row20 col5" >2.24E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row21" class="row_heading level0 row21" >21</th>
+                        <td id="T_06bb7_row21_col0" class="data row21 col0" >B15R1_4</td>
+                        <td id="T_06bb7_row21_col1" class="data row21 col1" >DCQFQ.14R1.L</td>
+                        <td id="T_06bb7_row21_col2" class="data row21 col2" >MQ.16R1.B2</td>
+                        <td id="T_06bb7_row21_col3" class="data row21 col3" >MQ.14R1.B2</td>
+                        <td id="T_06bb7_row21_col4" class="data row21 col4" >8</td>
+                        <td id="T_06bb7_row21_col5" class="data row21 col5" >2.30E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row22" class="row_heading level0 row22" >22</th>
+                        <td id="T_06bb7_row22_col0" class="data row22 col0" >B13R1_4</td>
+                        <td id="T_06bb7_row22_col1" class="data row22 col1" >DCQFQ.12R1.L</td>
+                        <td id="T_06bb7_row22_col2" class="data row22 col2" >MQ.14R1.B2</td>
+                        <td id="T_06bb7_row22_col3" class="data row22 col3" >MQ.12R1.B2</td>
+                        <td id="T_06bb7_row22_col4" class="data row22 col4" >8</td>
+                        <td id="T_06bb7_row22_col5" class="data row22 col5" >2.31E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row23" class="row_heading level0 row23" >23</th>
+                        <td id="T_06bb7_row23_col0" class="data row23 col0" >B11R1_4</td>
+                        <td id="T_06bb7_row23_col1" class="data row23 col1" >DCQFE.11R1.L</td>
+                        <td id="T_06bb7_row23_col2" class="data row23 col2" >MQ.12R1.B2</td>
+                        <td id="T_06bb7_row23_col3" class="data row23 col3" >MQ.11R1.B1</td>
+                        <td id="T_06bb7_row23_col4" class="data row23 col4" >6</td>
+                        <td id="T_06bb7_row23_col5" class="data row23 col5" >2.14E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row24" class="row_heading level0 row24" >24</th>
+                        <td id="T_06bb7_row24_col0" class="data row24 col0" >B12R1_4</td>
+                        <td id="T_06bb7_row24_col1" class="data row24 col1" >DCQFB.C13R1.R</td>
+                        <td id="T_06bb7_row24_col2" class="data row24 col2" >MQ.11R1.B1</td>
+                        <td id="T_06bb7_row24_col3" class="data row24 col3" >MQ.13R1.B1</td>
+                        <td id="T_06bb7_row24_col4" class="data row24 col4" >8</td>
+                        <td id="T_06bb7_row24_col5" class="data row24 col5" >2.87E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row25" class="row_heading level0 row25" >25</th>
+                        <td id="T_06bb7_row25_col0" class="data row25 col0" >B14R1_4</td>
+                        <td id="T_06bb7_row25_col1" class="data row25 col1" >DCQFB.A15R1.R</td>
+                        <td id="T_06bb7_row25_col2" class="data row25 col2" >MQ.13R1.B1</td>
+                        <td id="T_06bb7_row25_col3" class="data row25 col3" >MQ.15R1.B1</td>
+                        <td id="T_06bb7_row25_col4" class="data row25 col4" >8</td>
+                        <td id="T_06bb7_row25_col5" class="data row25 col5" >2.30E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row26" class="row_heading level0 row26" >26</th>
+                        <td id="T_06bb7_row26_col0" class="data row26 col0" >B16R1_4</td>
+                        <td id="T_06bb7_row26_col1" class="data row26 col1" >DCQFB.C17R1.R</td>
+                        <td id="T_06bb7_row26_col2" class="data row26 col2" >MQ.15R1.B1</td>
+                        <td id="T_06bb7_row26_col3" class="data row26 col3" >MQ.17R1.B1</td>
+                        <td id="T_06bb7_row26_col4" class="data row26 col4" >8</td>
+                        <td id="T_06bb7_row26_col5" class="data row26 col5" >2.51E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row27" class="row_heading level0 row27" >27</th>
+                        <td id="T_06bb7_row27_col0" class="data row27 col0" >B18R1_4</td>
+                        <td id="T_06bb7_row27_col1" class="data row27 col1" >DCQFB.C19R1.R</td>
+                        <td id="T_06bb7_row27_col2" class="data row27 col2" >MQ.17R1.B1</td>
+                        <td id="T_06bb7_row27_col3" class="data row27 col3" >MQ.19R1.B1</td>
+                        <td id="T_06bb7_row27_col4" class="data row27 col4" >8</td>
+                        <td id="T_06bb7_row27_col5" class="data row27 col5" >2.87E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row28" class="row_heading level0 row28" >28</th>
+                        <td id="T_06bb7_row28_col0" class="data row28 col0" >B20R1_4</td>
+                        <td id="T_06bb7_row28_col1" class="data row28 col1" >DCQFB.C21R1.R</td>
+                        <td id="T_06bb7_row28_col2" class="data row28 col2" >MQ.19R1.B1</td>
+                        <td id="T_06bb7_row28_col3" class="data row28 col3" >MQ.21R1.B1</td>
+                        <td id="T_06bb7_row28_col4" class="data row28 col4" >8</td>
+                        <td id="T_06bb7_row28_col5" class="data row28 col5" >2.67E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row29" class="row_heading level0 row29" >29</th>
+                        <td id="T_06bb7_row29_col0" class="data row29 col0" >B22R1_4</td>
+                        <td id="T_06bb7_row29_col1" class="data row29 col1" >DCQFB.C23R1.R</td>
+                        <td id="T_06bb7_row29_col2" class="data row29 col2" >MQ.21R1.B1</td>
+                        <td id="T_06bb7_row29_col3" class="data row29 col3" >MQ.23R1.B1</td>
+                        <td id="T_06bb7_row29_col4" class="data row29 col4" >8</td>
+                        <td id="T_06bb7_row29_col5" class="data row29 col5" >2.41E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row30" class="row_heading level0 row30" >30</th>
+                        <td id="T_06bb7_row30_col0" class="data row30 col0" >B24R1_4</td>
+                        <td id="T_06bb7_row30_col1" class="data row30 col1" >DCQFB.C25R1.R</td>
+                        <td id="T_06bb7_row30_col2" class="data row30 col2" >MQ.23R1.B1</td>
+                        <td id="T_06bb7_row30_col3" class="data row30 col3" >MQ.25R1.B1</td>
+                        <td id="T_06bb7_row30_col4" class="data row30 col4" >8</td>
+                        <td id="T_06bb7_row30_col5" class="data row30 col5" >2.78E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row31" class="row_heading level0 row31" >31</th>
+                        <td id="T_06bb7_row31_col0" class="data row31 col0" >B26R1_4</td>
+                        <td id="T_06bb7_row31_col1" class="data row31 col1" >DCQFB.C27R1.R</td>
+                        <td id="T_06bb7_row31_col2" class="data row31 col2" >MQ.25R1.B1</td>
+                        <td id="T_06bb7_row31_col3" class="data row31 col3" >MQ.27R1.B1</td>
+                        <td id="T_06bb7_row31_col4" class="data row31 col4" >8</td>
+                        <td id="T_06bb7_row31_col5" class="data row31 col5" >2.61E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row32" class="row_heading level0 row32" >32</th>
+                        <td id="T_06bb7_row32_col0" class="data row32 col0" >B28R1_4</td>
+                        <td id="T_06bb7_row32_col1" class="data row32 col1" >DCQFB.C29R1.R</td>
+                        <td id="T_06bb7_row32_col2" class="data row32 col2" >MQ.27R1.B1</td>
+                        <td id="T_06bb7_row32_col3" class="data row32 col3" >MQ.29R1.B1</td>
+                        <td id="T_06bb7_row32_col4" class="data row32 col4" >8</td>
+                        <td id="T_06bb7_row32_col5" class="data row32 col5" >2.71E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row33" class="row_heading level0 row33" >33</th>
+                        <td id="T_06bb7_row33_col0" class="data row33 col0" >B30R1_4</td>
+                        <td id="T_06bb7_row33_col1" class="data row33 col1" >DCQFB.C31R1.R</td>
+                        <td id="T_06bb7_row33_col2" class="data row33 col2" >MQ.29R1.B1</td>
+                        <td id="T_06bb7_row33_col3" class="data row33 col3" >MQ.31R1.B1</td>
+                        <td id="T_06bb7_row33_col4" class="data row33 col4" >8</td>
+                        <td id="T_06bb7_row33_col5" class="data row33 col5" >2.07E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row34" class="row_heading level0 row34" >34</th>
+                        <td id="T_06bb7_row34_col0" class="data row34 col0" >B32R1_4</td>
+                        <td id="T_06bb7_row34_col1" class="data row34 col1" >DCQFB.C33R1.R</td>
+                        <td id="T_06bb7_row34_col2" class="data row34 col2" >MQ.31R1.B1</td>
+                        <td id="T_06bb7_row34_col3" class="data row34 col3" >MQ.33R1.B1</td>
+                        <td id="T_06bb7_row34_col4" class="data row34 col4" >8</td>
+                        <td id="T_06bb7_row34_col5" class="data row34 col5" >2.23E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row35" class="row_heading level0 row35" >35</th>
+                        <td id="T_06bb7_row35_col0" class="data row35 col0" >B34R1_4</td>
+                        <td id="T_06bb7_row35_col1" class="data row35 col1" >DCQFB.A34L2.R</td>
+                        <td id="T_06bb7_row35_col2" class="data row35 col2" >MQ.33R1.B1</td>
+                        <td id="T_06bb7_row35_col3" class="data row35 col3" >MQ.33L2.B1</td>
+                        <td id="T_06bb7_row35_col4" class="data row35 col4" >8</td>
+                        <td id="T_06bb7_row35_col5" class="data row35 col5" >2.75E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row36" class="row_heading level0 row36" >36</th>
+                        <td id="T_06bb7_row36_col0" class="data row36 col0" >B33L2_4</td>
+                        <td id="T_06bb7_row36_col1" class="data row36 col1" >DCQFQ.34R1.L</td>
+                        <td id="T_06bb7_row36_col2" class="data row36 col2" >MQ.32L2.B2</td>
+                        <td id="T_06bb7_row36_col3" class="data row36 col3" >MQ.34R1.B2</td>
+                        <td id="T_06bb7_row36_col4" class="data row36 col4" >8</td>
+                        <td id="T_06bb7_row36_col5" class="data row36 col5" >2.56E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row37" class="row_heading level0 row37" >37</th>
+                        <td id="T_06bb7_row37_col0" class="data row37 col0" >B31L2_4</td>
+                        <td id="T_06bb7_row37_col1" class="data row37 col1" >DCQFQ.32L2.L</td>
+                        <td id="T_06bb7_row37_col2" class="data row37 col2" >MQ.30L2.B2</td>
+                        <td id="T_06bb7_row37_col3" class="data row37 col3" >MQ.32L2.B2</td>
+                        <td id="T_06bb7_row37_col4" class="data row37 col4" >8</td>
+                        <td id="T_06bb7_row37_col5" class="data row37 col5" >2.73E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row38" class="row_heading level0 row38" >38</th>
+                        <td id="T_06bb7_row38_col0" class="data row38 col0" >B29L2_4</td>
+                        <td id="T_06bb7_row38_col1" class="data row38 col1" >DCQFQ.30L2.L</td>
+                        <td id="T_06bb7_row38_col2" class="data row38 col2" >MQ.28L2.B2</td>
+                        <td id="T_06bb7_row38_col3" class="data row38 col3" >MQ.30L2.B2</td>
+                        <td id="T_06bb7_row38_col4" class="data row38 col4" >8</td>
+                        <td id="T_06bb7_row38_col5" class="data row38 col5" >2.30E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row39" class="row_heading level0 row39" >39</th>
+                        <td id="T_06bb7_row39_col0" class="data row39 col0" >B27L2_4</td>
+                        <td id="T_06bb7_row39_col1" class="data row39 col1" >DCQFQ.28L2.L</td>
+                        <td id="T_06bb7_row39_col2" class="data row39 col2" >MQ.26L2.B2</td>
+                        <td id="T_06bb7_row39_col3" class="data row39 col3" >MQ.28L2.B2</td>
+                        <td id="T_06bb7_row39_col4" class="data row39 col4" >8</td>
+                        <td id="T_06bb7_row39_col5" class="data row39 col5" >2.42E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row40" class="row_heading level0 row40" >40</th>
+                        <td id="T_06bb7_row40_col0" class="data row40 col0" >B25L2_4</td>
+                        <td id="T_06bb7_row40_col1" class="data row40 col1" >DCQFQ.26L2.L</td>
+                        <td id="T_06bb7_row40_col2" class="data row40 col2" >MQ.24L2.B2</td>
+                        <td id="T_06bb7_row40_col3" class="data row40 col3" >MQ.26L2.B2</td>
+                        <td id="T_06bb7_row40_col4" class="data row40 col4" >8</td>
+                        <td id="T_06bb7_row40_col5" class="data row40 col5" >2.17E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row41" class="row_heading level0 row41" >41</th>
+                        <td id="T_06bb7_row41_col0" class="data row41 col0" >B23L2_4</td>
+                        <td id="T_06bb7_row41_col1" class="data row41 col1" >DCQFQ.24L2.L</td>
+                        <td id="T_06bb7_row41_col2" class="data row41 col2" >MQ.22L2.B2</td>
+                        <td id="T_06bb7_row41_col3" class="data row41 col3" >MQ.24L2.B2</td>
+                        <td id="T_06bb7_row41_col4" class="data row41 col4" >8</td>
+                        <td id="T_06bb7_row41_col5" class="data row41 col5" >2.56E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row42" class="row_heading level0 row42" >42</th>
+                        <td id="T_06bb7_row42_col0" class="data row42 col0" >B21L2_4</td>
+                        <td id="T_06bb7_row42_col1" class="data row42 col1" >DCQFQ.22L2.L</td>
+                        <td id="T_06bb7_row42_col2" class="data row42 col2" >MQ.20L2.B2</td>
+                        <td id="T_06bb7_row42_col3" class="data row42 col3" >MQ.22L2.B2</td>
+                        <td id="T_06bb7_row42_col4" class="data row42 col4" >8</td>
+                        <td id="T_06bb7_row42_col5" class="data row42 col5" >2.44E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row43" class="row_heading level0 row43" >43</th>
+                        <td id="T_06bb7_row43_col0" class="data row43 col0" >B19L2_4</td>
+                        <td id="T_06bb7_row43_col1" class="data row43 col1" >DCQFQ.20L2.L</td>
+                        <td id="T_06bb7_row43_col2" class="data row43 col2" >MQ.18L2.B2</td>
+                        <td id="T_06bb7_row43_col3" class="data row43 col3" >MQ.20L2.B2</td>
+                        <td id="T_06bb7_row43_col4" class="data row43 col4" >8</td>
+                        <td id="T_06bb7_row43_col5" class="data row43 col5" >2.57E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row44" class="row_heading level0 row44" >44</th>
+                        <td id="T_06bb7_row44_col0" class="data row44 col0" >B17L2_4</td>
+                        <td id="T_06bb7_row44_col1" class="data row44 col1" >DCQFQ.18L2.L</td>
+                        <td id="T_06bb7_row44_col2" class="data row44 col2" >MQ.16L2.B2</td>
+                        <td id="T_06bb7_row44_col3" class="data row44 col3" >MQ.18L2.B2</td>
+                        <td id="T_06bb7_row44_col4" class="data row44 col4" >8</td>
+                        <td id="T_06bb7_row44_col5" class="data row44 col5" >2.29E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row45" class="row_heading level0 row45" >45</th>
+                        <td id="T_06bb7_row45_col0" class="data row45 col0" >B15L2_4</td>
+                        <td id="T_06bb7_row45_col1" class="data row45 col1" >DCQFQ.16L2.L</td>
+                        <td id="T_06bb7_row45_col2" class="data row45 col2" >MQ.14L2.B2</td>
+                        <td id="T_06bb7_row45_col3" class="data row45 col3" >MQ.16L2.B2</td>
+                        <td id="T_06bb7_row45_col4" class="data row45 col4" >8</td>
+                        <td id="T_06bb7_row45_col5" class="data row45 col5" >2.37E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row46" class="row_heading level0 row46" >46</th>
+                        <td id="T_06bb7_row46_col0" class="data row46 col0" >B13L2_4</td>
+                        <td id="T_06bb7_row46_col1" class="data row46 col1" >DCQFQ.14L2.L</td>
+                        <td id="T_06bb7_row46_col2" class="data row46 col2" >MQ.12L2.B2</td>
+                        <td id="T_06bb7_row46_col3" class="data row46 col3" >MQ.14L2.B2</td>
+                        <td id="T_06bb7_row46_col4" class="data row46 col4" >8</td>
+                        <td id="T_06bb7_row46_col5" class="data row46 col5" >2.28E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_06bb7_level0_row47" class="row_heading level0 row47" >47</th>
+                        <td id="T_06bb7_row47_col0" class="data row47 col0" >B11L2_4</td>
+                        <td id="T_06bb7_row47_col1" class="data row47 col1" >DCQFQ.12L2.L</td>
+                        <td id="T_06bb7_row47_col2" class="data row47 col2" >DFLAS.7L2.3</td>
+                        <td id="T_06bb7_row47_col3" class="data row47 col3" >MQ.12L2.B2</td>
+                        <td id="T_06bb7_row47_col4" class="data row47 col4" >20</td>
+                        <td id="T_06bb7_row47_col5" class="data row47 col5" >6.21E-09</td>
+            </tr>
+    </tbody></table>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
+</div><div class="inner_cell">
+<div class="text_cell_render border-box-sizing rendered_html">
+<h2 id="7.2.-Magnet-Resistance">7.2. Magnet Resistance<a class="anchor-link" href="#7.2.-Magnet-Resistance">&#182;</a></h2><p><em>ANALYSIS</em>:</p>
+<ul>
+<li>Calculation of the magnet resistance as the slope of a linear fit of U,I curve obtained from the corresponding mean alues of the voltage and current</li>
+</ul>
+<p><em>CRITERIA</em>:</p>
+<ul>
+<li>Check if the magnet resistance is below 50 nOhm</li>
+</ul>
+<p><em>GRAPHS</em>:</p>
+<ul>
+<li>The magnet resistance, R</li>
+<li>The green box denotes the validity region of the magnet resostance (0, 50] nOhm</li>
+</ul>
+
+</div>
+</div>
+</div>
+<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
+</div><div class="inner_cell">
+<div class="text_cell_render border-box-sizing rendered_html">
+<ul>
+<li>RQD</li>
+</ul>
+
+</div>
+</div>
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+
+<div class="output_png output_subarea ">
+<img 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Sqvrko8kdLF8Nv1mjxlmc8EXk3pMvWRrtkT+c5l5u0R8QRK3+9Xc88TUt9i8Y006qrT7tWq5W7tmjft9bO0MvP0Kgn+JmVb62zDl4A/jbsN3arB3nsAv6eMe+z2UspVpMtGWO3ulC6OLddQ9nm9rq4fDhxLubowUEQEJRndgDKG67zWvMy8LSJOqep+H/DWjrjNWZwk9bxzl0wQxq37YCyBV2Rm3bPEU1llGjGDutEsuXDJzp9POdtxQmt6Zv65upKxfUQ8LDNH2j2iOrv8XUr3j49k5nGjLJ9y9xMon8MiyhncrwKfmyLunZRE7wMR8a0+B9aTcFlmXtJj+gLKdveI7hlVW6PaqW5E2XH+N/CbiNgjMxd2Lb9U3R0iYgVKArIj5a4jte5OMw4R8WLKQejxwPspA/YfCLyH8oO0M9UP+IC7zRyamTctbVsy835VPRtQrgR+CPhdRDw9M39bzZtL6evdHXvwdOuNiFUoCfdTgNdRvl+3UtbPp4HTIuK5Q57ZnbbqTjfPo1zFOKrXMpn5L8pddsZlyrP3mdn3Ckg1/3PA56rPdx7wGuDoiNgxe9z1rMurKPvkL2ePOxf16WZxVPd3tWP5xwJfp4wjeE5XQj4x1V2+vk25Yv4CFl9J3Z2SNPw6InbLzDOr5Xvd4er3mTlsIrGEuusnyp0A53aFL8jMBdOtOyKeSDnY/Q3lwPt8Sney11NuTvC0iNh5iMR8qUS5HeihlAP051Tfr3vIzFEmBq0y/xP4z+p3fQvKSZITI+I92XX3uOqqTt0rOx+n3HzhdDoSgA5vply9ekuVqP2ccnL0OZSrZdtSuk6rl6YHQSyLL7oGKVPObOxOOSi5A3hCj5i/VnFPrFH+z6tlX9UxbV+mGKRcLfcKhrgLDvBa+t/ZojVw+fApymi1rdYg5erzWkCPu8SMYN0spM8g5SmWX7Fj2kerae+o/m61tXOQcuuOVB+oUUfrLjZHDrF9/bLPvK2q+afULOsx1fI/GPHnvALlbH1SkoMlBtJV6zmBf/YpY91q/t+GXUdd87egHIT+hiUHZt6rmp7ALtW0ua3vcNdrbjX/dQwYZEn58UvgwzU/qwdW+4U/d0zbpVcbBpTRWn7QIOWDq2Xe2GNea6D0wpptPo4eg8475rfuovOUAWW0PselGpzcUV4yxCBlyp3LknIFbySDkzvK/hw9bkbRtcyKlK5uSdfdtbreU/drlz7L7kA5k34zfQbfsnjf1fPuNZRkOYHXDmj3vkw9SPmoapkl7grF4hsjLOixfOfrqI751zLgRgKUkzwJrDrd9cPi/Xjn6+ABZbSW7zlImdKN8wbKlZwl2sXigdL7TnMbW8gQg5Qp3ZrurLa5ntvbkPW31tl0BymfSDk4f9Q04z9S1X8qsPqA5TYDvszi26wupJwkat0YZokbLfgqLwcpT0Bm3pLlPsHPoBw4fTkiVu1arHWf6L4PHQGI8iCb+dWfZ0+jOa1Bav362XdrdS96dXQ90IfSZxlgn+jxYKTpiPJwnxMpZ3Q/kplvG0W5I/YByo7/nRGxbp9laq3PrmV+PnCpe+r50DbK2Snofyn+HjLzV5SrQ7sMUfdAEbESJTl4AeVs5ouyxxmyzLyF0m1j9YjYsHs+5eoR9O8vXdeTKF1ETs0lB2bezeJxEfOraQszM3q8FlbLtQY29hsbMVS7M/NSykDFh7S2p8xc0KsNdcoboDU49JQebfgDpc/uA6PeQ9tG8Rm09i2j7Hs/jIGDk5dSa+DsLgOWeQalK+KpmdlzsGyf7XBB93JRHq7Wun3pkzKz375kpNvuAH23tY5prd8xMnPfHu9z346Yvu2u9h2rUZLD7u5F/SyxfjJzlx5tOLhmeb08ltJ95dd92rXE5zAuEfFcSlL/N8qtQsc9OLuOH1Gunu08bGBEfJJyK91TKCchuscXtGXmxZn5sszcKDNXzsy5WZ5/0dqWzppG25cLJggTlKUbzhcoYwfe0jW7dQePV0afJ/ZW9qf0574gq+4IdUV5sE7rXuhfr7H8dpSuKldRxhn0ev2R0l/1eX2KGaZ996UMMnoc5cz7O6YIaUSWbibvp/R3PajPYt+iHHhvX11m7qmatz0l4fjWEM14QJ+7quxS/fu7HvN61X8fYA1GdIeoKE/nPI6ynR1Neb7DoIOvn1X/9nqa8VO6lpmuOdW//cbdtKbfWbO8X1FuX7hjdD2ttro70JOqP3sdHPXTGn8y6gPVTn0/h2qsSOu91Pkc+q63iNiU8uN7KX3GdkR5yNrDKYOTF9Sob6Sq7iYvoXze4xhDtXH176DvVStBWeLuTcOo+vr/qKrriVXS309rm3xSdN3JqtqWd6R0OxtURh2DvnPDft9g9PuJOutnaY16vzMtEbEP5YTNVZTk4C9ThEzK0Osgis9Qug6dBDxtiKSw20uqf6c8FlpuNX0JY1l8MaA7AOVLcTvlbN1aXfO+VMWeBWzSI/Y1lC/Tv+m6tz5TPyhtZxZfkvxMj/mbUbqnrNQxrXVv4b4P0aIM4EvKLR/7LdNq26BL0mtV7zup+QAdFnerWDDEuml9BnOHXH7FrukrUx7Qc2fHMt0PSmvdn/taelzyp5xhal06X+JezNX6WOK+6K3ti9J1514d0+dREo1/AZt1TN+GHg+sqd7Dl6uyvla3/gGf1RzKnXKSMnDsXjVihn5QWt111DF/+2r+rcDDuuZtSznYvxt4yBDvdagHpVEOmO/bo5x7sbiLWd/v0BDfhUFdjD5bLXMyXQ+FY/GDus6sWd+gB6W1uh/1fVAa5aC8b1eXjuVWqrbDzWq0KanZxYhycJDUuA88PfaNre1qwPJXMKDLKKVb2V2Uvta1H9DXo5wnVdv1ddR8tg3TeFBa13L7MvX+vPVMmS9zz33UCix+OOM3h3if8xj+QWnTXj8127SAwV2MNqLsi++iXNXpnHd/yu2XE3jqNOtfyBRdjICXVfX/lepBdzXKfUC1vQ/srsUUXYwovwcP7zPvUZSucP+m6zeG0rV0K7oemki52vCFqs4f0uchbD3a0L2vC+BdVTnHTnf9Lw+vqD4wjVDV/Ybs0yUgIg6lDJL9UGa+s2P6HMoP5z6Unf6JlIE0q1G6Bj2UciDzxsz8TFeZ+1ISjD+w+A4RcyhdUR5NuWPJ3ZQBSm/PrrO6Ue4z/kDKE5oXRsTqlPsTz6E81flvfd5LUHbQmwIPzcxzqumvZPGtPjennJn6I4vPbJ+fmR/qKOcUykHOxfS/O9B3MvP3HTFPoNx95aeZWacrzxLvc4jll3icfXXZtvM2sw/KzIu6lnkrpa/kvSg/KK0nWM6nrNO7KQdJn+pRd8/tqJr+R8oVjBspV11aV3HWpKzfj3YsfyjwH5QuTJdSrmxsRDm4uB/l8v2u2XVnram24x7t/RLl4OE6Fh+MdluQXWeMI+LjlAFmV1CuoqxMGRi/DuUg5vCu5dflngOe96Z8R1oPXYPy3Tq/I+aLlM/gTkrf30spScizqvoOzczuq3qD3us6lOdQbEE5c3km5W47e1J++B+bHYNbI+LNlIPwMygPqbqe8t3cmfLduQbYLTNr3xO9Gtj5rOrP+wFPphwItO7CdV1m7t+x/MaUM8ObUA4ufkR1JYSSRN1WteGXNet/dPXeV6Kst8soJwy2o2xru2XvgbdrUM5mrkg5EdJ3QGJ1lewS4NLMnNs1byvgPzsmvYyy3+y8ocH+vcqPiNMp+6dnZub3p3ifC+mxz6jugvZ3yj7t8ur9bEY5y70iZYzKG/uU+X7KnaQ+kdPsRhkRW1LuRLMKZUBwz9tAZ1c3mYjYjLLtrk8ZqH4e5TdiV0rXosdm1zNBprE/34ayHd6Xchvh1tn93Si/RddRDujvsb+c4v2+gTKY/nrKyZE7Kd/9TSiJ+v5dy097/Qxow1Edf+5B+Q4fT7krEZRxZGd0LP9eyt3k7qaMy2kNUt6LcqvjEzJzr5p1D7Xfi/K8npMpvz1fpPcd9W7KzEO76llA2S/t2mNf/THKATyU7WEzyu9P67fjO1kNLK9u9nAjZTv5M9VYDMp+svXMigMy8+NddRxMuTJ/SOe2GxEHUcZR3UY5jul15eUeA9sj4qGU7fAkyj5vJco2uA1lX/y0zLy5RzkCryCM48XUAwo3oNxl4hZggx7zn0g58LyC8iVonTE+jz5PXWTxWZ3O1y1VGSdTdlKDnvi4kHsOxHxV9ffxNd7vgdWyn+qYdlSP9nS+FvSpf9Br366YN1XTXznEurnH+xxi+X5np3/R0b5+Z5K2ojxZ9ALKAcytlB/i/2HAGfp+21Hr86Mc5H+V8iN4O/BbejxJmfJjfiTlh/pGylmbGyg7yP3pc6Zoqu24x/ILaqzDgwdsv2dV2+w/KQPPnt5n2bk16tmlKyaqOhZ0fQY/pTxLYjrf87Upd2S5lPI9vZryQ9zr6t9DKQNAf085OPo3ZZzIWZQfvbWnUf/BU3wGC3vErEc5yDiv2mburNr/pUHb4oA2PJhyQH4dZaD1hZR9zb0HxLRufDDl4OSOdd3rvexSYztY4ntOOUBJag5Ops8+g3K16AfV53dr9f4vqz6PQU9PX4Ey9iZZisGiNd9/z+8v5Qz2l6pttrUNHErXVe2O5Y+aop4FPWLmUQYDX1x9NrdTTngdxjSfnksZt3EqZR9xS/X9eVmfZae1fqaof6jfqCpmT8rJvmsp3/ubKb8br62z/fX4LtTa79H7mKDOPmJBd1k9vgtT7t8pB+PvphycX1Gt/9soJxSPBh7d530e3F1WzW0w6epBQdnffY1y4uS26rP/FeUGCUM/gXp5e3kFYRaI8sTkMylnY6bqY7rciIjjKZcqN8vMsfbjlCRJWl44SHkWyMyrWHxXiBMjYol73C9vqq5Nj6NcWjY5kCRJGhGvIMwiEbEzpZ/otZSnBrryJEmSNFImCJIkSZLa7GIkSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLaTBAkSZIktZkgSJIkSWozQZAkSZLUZoIgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLaTBAkSZIktZkgSJIkSWozQZAkSZLUNisThIj4YkT8PSL+PKLyPhIR50TEeRHx6YiIUZQrSZIkzTazMkEAjgL2GEVBEfFYYEfgYcBDgUcBO4+ibEmSJGm2mZUJQmaeBtzQOS0iNouIH0XE2RFxekRsVbc4YBVgZWAOsBLwt5E2WJIkSZolZmWC0McRwBsycz6wP/DZOkGZ+UvgFODq6vXjzDxvbK2UJEmSZrAVm27AKETE6sBjgeM6hg/MqebtBbyvR9iVmfnkiNgc2BrYpJp+UkQ8LjNPH3OzJUmSpBlnmUgQKFdCbsrMbbtnZObxwPEDYp8N/CozFwFExInADoAJgiRJkpY7y0QXo8y8GbgkIp4LEMXDa4ZfBuwcEStGxEqUAcp2MZIkSdJyaVYmCBFxDPBLYMuIuCIiXgHsA7wiIv4AnAPsWbO4bwEXA38C/gD8ITO/P4ZmS5IkSTNeZGbTbZAkSZI0Q8zKKwiSJEmSxmPWDVJed911c+7cuX3n33LLLay22mrTKtvYZTu2ybqNnfmxTdZt7GRim6zb2Jkf22Tdxs782CbrHlfs2WeffV1mrtdzZmbOqtf8+fNzkFNOOWXgfGOX39gm6zZ25sc2Wbexk4ltsm5jZ35sk3UbO/Njm6x7XLHAb7LP8bZdjCRJkiS1mSBIkiRJajNBkCRJktRmgiBJkiSpzQRBkiRJUpsJgiRJkqQ2EwRJkiRJbSYIkiRJktpMECRJkiS1mSBIkiRJamskQYiIfSMie7xe00R7JEmSJBUrNlz/E4DbOv7+a1MNkSRJktR8gnBWZi5quA2SJEmSKo5BkCRJktTWdIJwcUT8OyIuiIhXN9wWSZIkabkXmTn5SiOeDDwKOBNYAXgB8FLgrZn5yR7L7wfsB7D+BuvMP/rYw/uWfceiOcxZ/Y5ptcvYZTu2ybqNnfmxTdZt7GRim6zb2Jkf22Tdxs782CbrHlfsHru+8OzM3K7XvEYShF4i4hvA7sB6mXl3v+W2mb9JfufXr+tbzkVnzGPznS6ZVhuMXbZjm6zb2Jkf22Tdxk4mtsm6jZ35sU3WbezMj22y7nHFbr7SgX0ThKa7GHX6FtkgHIMAACAASURBVLA2MLfhdkiSJEnLrZmUIGTXv5IkSZImbCYlCHsD1wGXNt0QSZIkaXnVyHMQIuLblAHKf6QMUn5+9XrjoPEHkiRJksarqQelXQC8HLg/EMC5wEsz8ysNtUeSJEkSDSUImXkgcGATdUuSJEnqbyaNQZAkSZLUMBMESZIkSW0mCJIkSZLaTBAkSZIktZkgSJIkSWozQZAkSZLUZoIgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLaTBAkSZIktZkgSJIkSWozQZAkSZLUZoIgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLaTBAkSZIktZkgSJIkSWozQZAkSZLUZoIgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLaTBAkSZIktZkgSJIkSWozQZAkSZLUZoIgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLaTBAkSZIktZkgSJIkSWozQZAkSZLUZoIgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLaTBAkSZIktZkgSJIkSWozQZAkSZLUZoIgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLaVuw3IyKeOs0yT8/Mf04zVpIkSVKD+iYIwA+ABGKI8hJ4FPDbpWmUJEmSpGYMShAA9gJ+P0RZf1m65kiSJElq0qAE4VJgYWZeWqegiLhXFXPHMA2IiI2BC4DVgPtk5qJh4iVJkiSNTt8EITPnDVNQZt4NDBVT+SiwiJIgSJIkSWpQo3cxiojHA3sAH2uyHZIkSZKKqcYg3ENEbAlsDKzSPS8zfzhkWSsAhwHvA24aJlaSJEnSeNRKECJiG+AYYGt639UogRWGrPs1wBzgM8A+Q8ZKkiRJGoPIzKkXijiLkkwcCFwE3Nm9TN3BzFV561DuePTizPxhROwLfIk+g5QjYj9gP4D1N1hn/tHHHt637DsWzWHO6kONkzZ2OYltsm5jZ35sk3UbO5nYJus2dubHNlm3sTM/tsm6xxW7x64vPDszt+s1r24Xo62B52Tmj6fVuiV9APhV3W5JmXkEcATANvM3yc13uqTvshedMY9B8wcxdtmObbJuY2d+bJN1GzuZ2CbrNnbmxzZZt7EzP7bJupuIrZsgnAk8YOjSe4iIhwAvBx4fEWtWk1et/r1vRNyVmbeNoi5JkiRJw6mbIOwHHBMRtwKn0GNQcWbeWrOsBwErAb/sMe8K4H+BV9YsS5IkSdII1U0QrgMWAkcPWKbuIOUzgF27pu0BvAN4KvDXmuVIkiRJGrG6CcJXgR0ozyvoOUi5rsy8DljQOS0i5lb/Pd0nKUuSJEnNqZsg7Aq8KjO/Ps7GSJIkSWpW3ScpLwTqjjEYWmYelZnh1QNJkiSpWXUThAOAd3V0BZIkSZK0DKrbxegQym1OL4yIhfS+i9H2I2yXJEmSpAbUTRD+XL0kSZIkLcNqJQiZ+R/jbogkSZKk5tUdgyBJkiRpOVC3ixERsR2wF7AJsEr3/Mx83gjbJUmSJKkBtRKEiHgtcDhwPfAXluJBaZIkSZJmrrpXEPYHvgS8JjP/Pcb2SJIkSWpQ3TEI6wPHmBxIkiRJy7a6CcKJwKPH2RBJkiRJzevbxSgiHtzx52eAIyJiJeAkej8o7dzRN0+SJEnSJA0ag/BnIDv+DuAg4L1dy0W13AqjbZokSZKkSRuUIOw6sVZIkiRJmhH6JgiZeeokGyJJkiSpeXWfg/AAYCdg42rSlcDpmXn5uBomSZIkafIGJggRcT/gs8AzWfKOR3dHxHeA12fmNWNqnyRJkqQJ6nub04hYBzgDeDzwPmBbYK3qtS1wCLAzcFpErD3+pkqSJEkat0FXEN4DrAQ8LDOv6pr3R+CPEXEk8Evg3cBbx9NESZIkSZMy6EFpewL/1SM5aMvMq4EPAs8edcMkSZIkTd6gBGFD4PwaZZxXLStJkiRplhuUIFwHzK1RxtxqWUmSJEmz3KAE4cfA2yNitX4LVPPeDpw46oZJkiRJmrxBCcLBwAbA2RGxT0Ss3poREatHxIuA3wDrU+5oJEmSJGmWG/Qk5csjYlfgq8BXgIyIm6rZawIB/B54QmZeMfaWSpIkSRq7gQ9Ky8xzgEdExM7A47jnk5RPy8zTxtw+SZIkSRM0MEFoycxTgVPH3BZJkiRJDRv0JOU1IiKGKWw6MZIkSZJmjkGDlG8EHlW3oIhYoYp5xNI2SpIkSVIzBnUxCuCxEbFuzbIGJRuSJEmSZoGpxiB8YiKtkCRJkjQjDEoQ5k2zzKumGSdJkiSpYYOeg3DpJBsiSZIkqXmOG5AkSZLUZoIgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW1LnSBExEsjYo9RNEaSJElSs0ZxBeEo4P8i4sKIeN0IypMkSZLUkKmepFzHPGBV4DHADiMoT5IkSVJDljpB6Hig2nnAl5a2PEmSJEnNcZCyJEmSpLZaVxAiYmtgd2B74H7AKsANwIXAGcBPMvO2cTVSkiRJ0mT0vYIQxUsj4izgHOBgYBPgJuBSYAXgKcC3gWsi4oiImDf+JkuSJEkal0FXEM6r/v0K8JLMPL/XQhGxKvBk4LnAnyLiNZn51dE2U5IkSdIkDEoQ3gUcn5k5qIDMvBU4ATghIjahXGWQJEmSNAv1TRAy89vDFpaZVwBXLFWLJEmSJDXGuxhJkiRJaut7BSEiLgEGdi/qlJmbjqRFkiRJkhozaAzCt7lngvACyhOTTwL+DqwPPBG4BTh2XA2UJEmSNDmDxiDs3/p/RBwIXAw8LTNv6Zi+OvAD4OZxNlKSJEnSZNQdg/A64KOdyQFAZi4CPlbNlyRJkjTL1U0Q1gA26DPvfsDqo2mOJEmSpCYNGoPQ6fvARyPiZuB7mXlnRKwM7Al8uJovSZIkaZarewXhtcBpwDeB2yLiJuA24BvA6dX82iJi74j4RURcHxG3R8QFEfHuKumQJEmS1JBaVxAy8x/AsyPiIcCjKN2NrgHOysxzp1HvOsDPgI8CNwHbAwdTuiu9fhrlSZIkSRqBul2MAMjMc4BzlrbSzPx816RTImIN4HUR8YbMrP38BUmSJEmjU/tJyhGxfkR8OCJ+WnUJekg1/U0RscMI2nI9YBcjSZIkqUG1EoSI2B74C/AcYCGwOTCnmr0h8LbpVB4RK0TEqhGxE/BG4H+8eiBJkiQ1p+4VhE8CpwBbAK8GomPemZQxBNNxS/U6HTgVOGCa5UiSJEkagahzwj4ibgP2zMyfRMQKwL+A7TLztxGxM/DjzFxl6MojHgmsSkkw3gt8PTP/X4/l9gP2A1h/g3XmH33s4X3LvGPRHOasfsewTTF2OYhtsm5jZ35sk3UbO5nYJus2dubHNlm3sTM/tsm6xxW7x64vPDszt+s1r+4g5X8A6/WZtynwt5rl3ENm/rb67xkRcR3w5Yj4eGZe3LXcEcARANvM3yQ33+mSvmVedMY8Bs0fxNhlO7bJuo2d+bFN1m3sZGKbrNvYmR/bZN3GzvzYJutuIrZuF6PvAYdExKYd0zIi1gX2B44fuuYltZKFeSMoS5IkSdI01E0Q3gHcDJxLeWAawOeACygPTHvvCNqyY/Xv9FM7SZIkSUul7oPSboyIxwAvAXajDCy+ATgSODozh+oYFRE/Ak6mPFPhLkpy8DbgG93diyRJkiRNTu0HpWXmncD/Vq+ldRawLzAX+DfwV+CdlKsSkiRJkhpSK0GIiLuAHTLzzB7z5gNnZuYKdSvNzPcA76ndSkmSJEkTUXcMQgyYtxLlKoAkSZKkWa7vFYSIeAClC1DLIyKi+1kHqwAvw4HFkiRJ0jJhUBej/wAOArJ6/U+f5W4DXjnidkmSJElqwKAE4bPAtyjdi/4I7FP92+lO4LJh72IkSZIkaWbqmyBk5rXAtQARMQ+4urqTkSRJkqRlVN3nIFwKEBErAg+gjD3oXubc0TZNkiRJ0qTVvc3pSsCnKQOS5/RZrPZtTiVJkiTNTHVvc/pe4OnAKyhjEl5PGcT8U2Ah8IxxNE6SJEnSZNVNEJ4HHAx8s/r7zMw8OjOfBJwB7DmGtkmSJEmasLoJwv2BCzPzLuB2YK2OeV8DnjPqhkmSJEmavLoJwtXAmtX/LwEe3zFvs5G2SJIkSVJjag1SBhYAjwO+D3wB+GhEbA7cATwfOGYsrZMkSZI0UXUThHcB6wJk5qEREcDewL2Bw4D3jad5kiRJkiap7nMQrgGu6fj7k8Anx9UoSZIkSc2oOwZBkiRJ0nKg7xWEiDgLyLoFZeb2I2mRJEmSpMYM6mJ0DkMkCJIkSZJmv74JQmbuO8F2SJIkSZoBHIMgSZIkqa3WXYwi4ptTLZOZz1v65kiSJElqUt3nIKzXY9pawFbA9cAFI2uRJEmSpMbUfQ7Crr2mR8T9gRPwmQiSJEnSMmGpxiBk5uXAfwMfGU1zJEmSJDVpFIOU7wI2GUE5kiRJkhpWd5Dyg3tMXhnYGng/cNYoGyVJkiSpGXUHKf+Z3g9NC+A3wCtH1iJJkiRJjambIPQapHw7cEVmXjnC9kiSJElqUN27GJ067oZIkiRJal6tQcoR8YKIOKDPvAMiwoekSZIkScuAuncxeielS1Evt1TzJUmSJM1ydROEzSkDlXs5D3jQaJojSZIkqUl1E4Rb6f+sg/sDd4ymOZIkSZKaVDdBOBl4T0Ss3zkxItYD3gX8ZNQNkyRJkjR5dW9z+g7gV8DFEfEj4GpgQ+DJwE3A28fTPEmSJEmTVOsKQmZeBjwcOJzSpegp1b+HAY/MzMvH1kJJkiRJE1P3CgKZeS3erUiSJElaptUdgyBJkiRpOdD3CkJEnAVk3YIyc/uRtEiSJElSYwZ1MTqHIRIESZIkSbNf3wQhM/edYDskSZIkzQCOQZAkSZLUVvsuRhExF3gxsAWwSvf8zHzeyFolSZIkqRG1EoSImA+cBlxGSRD+CNwXmAtcAVw0pvZJkiRJmqC6XYw+ChwHPBQI4BWZuSmwE2Ug80fG0zxJkiRJk1Q3QdgWOAa4u/p7FYDM/AVwCPCh0TdNkiRJ0qTVTRASuDMzE/g78MCOeZcDDxp1wyRJkiRNXt0E4Vxgs+r/vwTeEhEPiogHAm8HLh5H4yRJkiRNVt27GB3B4qsGBwI/Ac6v/r4F2HvE7ZIkSZLUgFoJQmZ+peP/50XE1sAOwL2BX2Xm38fUPkmSJEkTVPs5CJ0ycxFw0ojbIkmSJKlhfccgRMR2EXF9RDx1wDJPjYjrIuLh42meJEmSpEkaNEj5zcAvMvOH/Rao5p0BvG3UDZMkSZI0eYMShF2Br9Yo4xjgCaNpjiRJkqQmDUoQ1gWurFHGlcB6o2mOJEmSpCYNShBuADauUcbG1bKSJEmSZrlBCcKpwCtqlPHyatnaIuK5EfG9iLgyIhZFxNkR8cJhypAkSZI0eoMShA8BO0fEFyNi7e6ZEbFmRBwJ7Az895D1vhVYBLwFeCZwCvD1iHjDkOVIkiRJGqG+z0HIzN9XZ/WPAl4YEb8BLgMSeACwHfBv4EWZ+Ych631GZl7X8ffPImIjSuJw2JBlSZIkSRqRQVcQyMzjgS0pVwjuAB4JzAfuBD4IbFktM5Su5KDld8BGw5YlSZIkaXSmfJJyZl4NvG8CbdkBuHAC9UiSJEnqIzKz94yIyH4zBxU4jbiI2A04CXh5Zh7VY/5+wH4A62+wzvyjjz28b1l3LJrDnNXvGKrNxi4fsU3WbezMj22ybmMnE9tk3cbO/Ngm6zZ25sc2Wfe4YvfY9YVnZ+Z2veYNuoJwYUR8GDgmM2+ZqgERMR94E3AeQwxajoi5wNeB7/ZKDgAy8wjgCIBt5m+Sm+90Sd/yLjpjHoPmD2Lssh3bZN3GzvzYJus2djKxTdZt7MyPbbJuY2d+bJN1NxE7KEF4B3AI8KmI+AnwC+DPwHWU8QhrAvMoYxL2AO4PHAl8sW7l1d2RTgQuBfYZuvWSJEmSRmrQXYyOj4gTgN2BlwJvBjak3MUIICiDlc8GPg98JTP/XrfiiFgV+AGwMvD0zLx1Wu9AkiRJ0sgMHKRcjSU4qXoRERsC9wNWoTw9eWFmDt0pKiJWBI4DHgQ8dpjEQpIkSdL4THkXo07VHY2uHkG9nwWeShmzsE5ErNMx73fTSTokSZIkLb2hEoQRelL176d6zJsHLJxcUyRJkiS1NJIgZObcJuqVJEmSNNjAJylLkiRJWr6YIEiSJElqM0GQJEmS1NZ3DEJEBLALcF1m/qlj2oe7Fv1nZr5/bC2UJEmSNDGDBik/D/gqsFPHtHsB+1NudXpnNW2DiDg/M48bTxMlSZIkTcqgLkYvAb6Zmb/uMe8ZmTkvM+cBhwEvG0vrJEmSJE3UoAThUcAJNco4DdhuNM2RJEmS1KRBCcJawDWdEzLzLuC5wMUdk/9RLStJkiRplhs0BuFGYMPuiZn57a5JGwI3jbJRkiRJkpox6ArCL4Hn1yjj+dWykiRJkma5QQnCJ4FnR8R7ImKJ5aJ4N/As4BPjaqAkSZKkyenbxSgzT42ItwEfBV4dET8DLgcS2ATYDdgAeFtmnjaJxkqSJEkar0FjEMjMQyPiNOANwOOAjapZVwEnAYdl5u/G20RJkiRJkzIwQQDIzN8C/zGBtkiSJElq2KAxCFOKiM0i4t0Rcc6oGiRJkiSpOVNeQegWERtR7lz0QmA+cBelu5EkSZKkWa5WghARawN7U5KCx1GuPCRlAPPHM/PasbVQkiRJ0sT07WIUEatFxD4R8QPgauBzwLrAQcCjgAB+aHIgSZIkLTsGXUH4G3Bv4BLgY8AxmflngIi47wTaJkmSJGnCBg1SjuqVHS9JkiRJy7BBVxDWA55JGXewP/DOiDgPOAb48QTaJjXrkEPu+ffWH1w87aCDJt8eSZKkCeh7BSEzb83MYzNzT+B+wKuBa4BDgF9Trig8IyLuN5GWSpIkSRq7Ws9ByMybMvPIzNwd2AR4K3Am8Dbg8og4cYxtlCRJkjQhQz8oLTOvycxPZeYOwGaUuxptPPKWSZIkSZq4pXqScmZekpkfzMyHjapBkiRJkprTd5ByRLx0iHIyM78ygvZIkiRJatCguxgdxeJbm8YU5SRggiBJkiTNcoMShEXVv98FjgVOA+4ee4skSZIkNWbQGIT1gZdTnqZ8HHAe8D7gwZl5S/drAm2VJEmSNGaDnoNwe2Z+KzP3piQLBwJbAWdExMUR8YGI2GpSDZUkSZI0fnWfg7AoM4/OzKcBGwLHA28HPjjOxkmSJEmarEFjEO4hIjYBng+8AJhPeVDaMWNqlyRJkqQGDEwQImI94LnAC4HHAn+iDFh+bmYuHHvrJEmSJE3UoOcg/ATYBbgY+Abwysy8YELtkiRJktSAQVcQdqfc6nQR8FTgqRH9H4eQmduPtmmSJEmSJm1QgnA0ix+UJkmSJGk50DdByMx9J9gOSZIkSTNArducDiMiVoiIuyLikaMuW5IkSdJ4jTxBqPQfrCBJkiRpxhpXgiBJkiRpFjJBkCRJktRmgiBJkiSpzQRBkiRJUpsJgiRJkqS2cSQICZwK/HMMZUuSJEkao6VOECJi14g4sfV3Zt6dmbtm5l+WtmxJkiRJk9X3ScoAEbEmsAdwf+CvwPcy81/VvOcC7wAeCVw45nZKkiRJmoC+CUJEbAP8BNigY/JvI+I5wNeBxwDnAvsA3xhnIyVJkiRNxqAuRh8EbgZ2AFYFtgZuAM4CHgq8LDO3ycxjMvPusbdUkiRJ0tgN6mK0HfCmzPx19fcFEfFa4C/Afpn51bG3TpIkSdJEDbqCsAGwsGta6+8/jKMxkiRJkpo11V2Mss/0f4+6IZIkSZKaN/AuRsCPI6JXMvDT7umZuf7omiVJkiSpCYMShEMm1gpJkiRJM0LfBCEzx5YgRMTmwAGUOyQ9BDg9M3cZV32SJEmS6pmqi9G4PAR4KvArYKWG2iBJkiSpy1SDlMfl+5l5/8x8LnBOQ22QJEmS1KWRBMEHq0mSJEkzU1NXECRJkiTNQJHZ71EHE2pAxLeAdQcNUo6I/YD9ANbfYJ35Rx97eN/y7lg0hzmr3zGtthi7bMcOHX/VVfeMXWVj5tx+Zfljo43GV6+xs2P7MHbWxTZZt7EzP7bJuo2d+bFN1j2u2D12feHZmbldr3lNDVIeSmYeARwBsM38TXLznS7pu+xFZ8xj0PxBjF22Y4eOP+SeN/K6aOsPsvl5B5Y/nnfQ+Oo1dnZsH8bOutgm6zZ25sc2WbexMz+2ybqbiLWLkSRJkqQ2EwRJkiRJbSYIkiRJktoaGYMQEatSHpQGsDGwRkTsXf39w8y8tYl2SZIkScu7pgYprw8c1zWt9fc8YOFEWyNJkiQJaChByMyFQDRRtyRJkqT+HIMgSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0mCJIkSZLamrrNqSQ175BD7vn31h9cPO2ggybfHkmSZgATBM18nQdxnQdw4EGcJEnSiNnFSJIkSVKbCYIkSZKkttnfxcg+xJIkSdLIeAVBkiRJUpsJgiRJkqQ2EwRJkiRJbSYIkiRJktpm/yBlSZIkSYNv3gO1b+DjFQRJkiRJbSYIkiRJktpMECRJkiS1mSBIkiRJajNBkCRJktTmXYwkSRq1Ed1JRJKa4BUESZIkSW0mCJIkSZLa7GIkSbOJXVckSWNmgiBJywuTC0lSDXYxkiRJktRmgiBJkiSpzS5Gkgq7n0iSJJb3BGHQAZEHQ5IkSVoOLd8JgqTRWNqrD53LeuVC0mzgSUYtwxyDIEmSJKnNBEGSJElSm12MpGWJA40lNcF9j5ZFS9ONbJZ3QTNBkCRpJvFgW1LD7GIkSZIkqc0EQZIkSVKbCYIkSZKkNhMESZIkSW0OUpYkSZotHMSuCTBBmC6/oJIkSVoGmSBIkiRPfElqM0GQJGlZ4UH+cGb5w6ykcXGQsiRJkqQ2ryBI0qR5lndyPEOsmch9gGY4E4TZxp2KJEmSxsgEQZI0s3WeBPGkiCSNnQmCJEmSxsfeD8OZAZ+XCYKk2c2zy5IkjZQJgibDgzhJkpo1A85Ma3YwQZCk6fCHVpK0jPI5CJIkSZLavIIgSRo/uxlK0qxhgqBlmw9JkkbDLlWStNwwQWiCP7TLvqVZx24fkiSpQY0lCBHxYOAwYAfgJuBI4JDMvKupNi3zPGiVJC1r7L627Fuadez2MS2NJAgRsRZwMnAusCewGfBxyqDpdzfRJkmS1BAP4qQZpakrCK8B7g3slZk3AydFxBrAwRHxkWqaJEmSpAlrKkF4CvDjrkTgWODDwM7A9xtplSRJkpZkV+PlSlMJwlbAzzonZOZlEXFrNc8EQZLULO+CJmk51dSD0taiDEzudmM1T5IkSVIDIjMnX2nEv4ADMvPQrulXAEdn5oFd0/cD9qv+3BK4YEDx6wLXTbNpxi7bsU3WbezMj22ybmMnE9tk3cbO/Ngm6zZ25sc2Wfe4Yh+Ymev1nJOZE38BfwcO6jH9FkrisDRl/8ZYY2da3cbO/NjZ2m5jZ0fdxs782NnabmPdPsYR21QXo/MpYw3aIuL+wKrVPEmSJEkNaCpBOBF4ckTcp2Pa84HbgFObaZIkSZKkphKEzwF3AMdHxO7VGIODgU/k0j8D4QhjjZ2BdRs782ObrNvYycQ2WbexMz+2ybqNnfmxTdY98dhGBikDRMSDgcOBHSh3NDoSODgz72qkQZIkSZKaSxAkSZIkzTxNdTGSJEmSNAOZIEiSJElqM0GYxSJilYg4IiIe1HRbJEnSsi0iVoyIFZtuR1MiYqOIWKnpdkzCrB2DEBGrAztTnqewVjX5RspzFE7NzEVLWf4qwPqZedmQcSsBGw4TFxHzgHnAJZl5Sde8VQeErglcDjwFOAMgM28dot65JSQvrRtTxe0KPBi4G/hDZv6ixzKPBs7KzLuHKburjC0p2+j51d8B7AlsBiwEfpiZt/WJXZEyAH5rYO2qrdcAv8rMC4dsx4oAmfnv6b2T2SsiNgKuzcx/Nd2WZUlErEPHfiszr2+yPZMWEfcCHgP8KTP/OcF6VwfuHmY/OcK616m7niNiDmX7uBu4fjo373C/5X5rFCJifeD1lOOMrSjPqwK4lXK89UPg8My8dprlzwdel5kv75q+KvAcYCPgAuD73d+DiNgUeHd3bDVvLvAsYGXgmMy8PCK2Av4T2BT4K/DJzPzDEG29L3ADsEtmnv7/2zvzcKuqsoH/3hAEFHDIUjMTfESRaJAcUhNHNGcLyjDTNC0pNYdUQHN4zErIWRu+zwFNtDD7cmiwnBMnUJMUJ1TEAQVknrms74/33ffuu+465+x7zvVeDry/51nPvXvt911r7bXXfs+aV0GdHsB3gR2AAEwExsZ1VBH5ItAtX58SkQOAEeTqW+hmPhMi3b+h72F8CGFG0eepSC0nynWEAwS4CFhoGbYQrSRPj/wuxBpAVcbzdaAh8vshMBU9r+E/wNEJvZ1jPfPvDFyFFq6FwKXmfy3QYOluAG4FOuX0Giq4VfnrRLwnAh+P/E4FZub03geGJ3R/BVycu94MeNziXIpuVdsA/B3oFemusnCvAXZrZd5vBkzKpe8+oCfwgIW7yP6+BmyV0D8FPVY8y59VNM+rR4H+ZeL/hJWxp4EFuXQsML8LgU1qKFsDgRsS/t2Bo4GzUcPWKSHTp4TuVsCPgbOAT5vfdsBNwCP29/OtTGcve+6vtEKnh+X/TcCN6DezfgnZLwK7Rn4HoGehzLTyc18sY3J/A04GNq3yHRwO3AbcDgwyv8HAc/aeJwPfL6G7PnA6cD/wrn0Li9EfnHHA3iX0tgdupvm3l7mZwFhg+2rLlcWxB/BALWEkwtwJuAK4DhiYi+ch4C17X/u3ZdkCuiT8tgQus3gfBEYDWyTkBgOHRX4/AKbl8vsV4MiE7hTU7n2pyrw6z1wPdQAAFV9JREFUFbWRTwDfNr/vArMt3vnAz4F1ErqfRn8jpgIrc2ldCkwAjqsQt9utAmWrhE4hu0Wd2iyTbbXdAj5vz/UBcD1wJnC8uTPR3Sfft/ufq/K5UnWtzSxdWX1uFfptfimSK1Xf2gHdHXOp/Z2F2rGZaKNmvH1ni4B+ke6lZdyVlpbbMr9I913gC7nrLdHOzBXAf+0drQBejcsBajNG5a6Ps7juB0YB56J2byUt7VtWz1kB/Mt0N6j2W28Mt9YA2tuhRm4h8BPMoET3t7CCuwBtaVUbT7NCCxxpL+BWC/9O1AjdAXQtUGBH2cd4sX2kb6CGaA5qXPsD37d0D8/pLbRCdzpwTOSGW5p+nvkl4m0Adspdn2g6twND7DlvN7lhke70vB/wJyvsX0EbagLsiVYSrk8U2H/Q9MM4zT6oHQrk/VjLn0PQisjDaKX+BaCvyfRDP/Rxke5pwHJgDGo890R/uGZYfg0EbkCNRovKGHVoEKlDY2jyHWIQgWGmO8niWgJ8y/6OQ23LH6zcfi/S3drK5iK00vaQ5fcKKy93WzjXAx/L6e2Nfv/PA+eh394+5obYs/7Hwt2zrexWzv9TFu+v0QrZhgmZfkSNC0vfcvT7zdJ3sP39F1pJf8yef6dI949l3J/tHTyY+VWwWwNQWzkHuMfyeQ5axvtGus8Cp+euz7EydD1wFPBttCK4AjghUa6WW/yvohXukp0Jke6ppvcni2u+laXFwCXAUOCX6Hd6VqQ70J7nbSuDNwEvWhpHA1fTVPnsmojb7dYaXImjBptVo916GLgX6F4mbd1N5qHIf4+C7qeJsnGTlaNt7Ppzlq+LgSHlypX5/9WecT20njIarQPcizVgga5oI/S2xHuaY/kVu6yT4T27fj2hm7db49Fvun/O77PmF9eZ5gODc9evAVcnnu036MyNON6hVg4m0dSJexdady35/sqWu2qUOtIB7wAnFpA7EXgn4f9AQTeZ5g2EibQ0NPtYoXsc2LhCgX0J+Enuend7iT+O5C4EJuauN0cNwCy09yE/utDLwtijTD7EBfYl4MaE3C3olKC831JyvTCocRma0B2GDoO3iBcdOTnUniHr1XoZOB/YtkSa36Z5w6Rv9gFEckcB0yO/18kZ8Jz//hZ/d7sejw5ZxnJ1ZxCpQ2No9zrEIALPANfmro813V9EcpcDzyby+kl0+mHm1xVt1D5s19ugFbEzI/sxljKjmvbubiL3/efufaeguzpRPrZBRy4XoBWgpWgl7NBILlW2HkY7QT5m16fZexsbyd0F3JV4RzPQchy7R+3+s5lfhbL1d7SD4JM5v03RbyZuXCwi1xuKdnRckMjTnwGvJOIdZGXrTvT7a0AbducAvcu8vxeBC3PXB6MVxXMiuZ8CL0R+j6Dfa5fI/+fA8/b/x9EK8yWJuN1urcGVOGqwWbm8rsZuLabEiGgU/t7AosTz5kfxy7m4bLwFfCPyE7SBvRI4rVS5Mv8PyNk34JMWz0GR3JGJ8nE5MA+ti3WL7m1AmTpXomzNJd1gOwl4N/KbG5WtFdhIUSS3L7C0QrzbYHaGpsb7OLTTtXOl99kYTlHB1cWhxn+fAnL7xAXW/Fdapo2v4CbQvIGwgETPHjpEOgUdsu5TpsAuyb9soJu9uHi4cj/gw4T+HuhQ4ovYcD7VNRBWkJgOABwU55c90/dy1/NK6B4MLCgXb+6Zv4n2Hi5Bjccz5BpOubzeK3fdI/Wc9o7jeJcC+ybSmH3Y/e36CGBuQq7uDCJ1aAxz8u1uEFtZvuYndA9OpHEze/db2fUp5CqfRN9/mXK1J7CkRF5XW7buRDsxNrTrTdCpTitp3tOeKlsfAl/NXWfreQZHcl8D3or8TjX9sei6rFrK1iKiEU7zPwada573mw0ckrteXkO56oE2vP5K08jC4ySmihCN/qBTOlYBu0dyewELI7/FpG3rxy3OrAJ+AjAtIed2q/qytdpX4qjBZuX0q7FbbwEnFShXw2n5/c8Cfo/OjijnTkuUjQWpfM3FtRKdCrhLrJv7HvLfYifLrx0iuUGk7e326ChPPIuibJ0r8Y6XkZhijdr5ZZHf3eQ6XtD63hkJ3RHA1HLxRvc+j3Y0vG5ys1NyKVePuxg9AZwlIuuVErB7Z6OGPOYF4L8hhKHlHDrXNc881Fg3I4TwJrAr+jE8DuxYIlmLUMOVscxcvFiuE9Bih4AQwiPokOy1wDgRuRvYtkRcMV1FpLst+smm/MQ0oAto8twAXGCLhUErFaNEpPE5RGQjYCTag1WWEMKSEMIfQghHoD8Gx6M/EhdHoq+g8y0zDkfz6oBI7qtoj1qel9FempghqFF5267nk97FaxbF8nU7NC/zfIgOaw+o4M5IhLchOgWgkaCcjRrt0SLyK/THN2Z9e578M4D2oOV5D/1ByMdxGrqYezfgFREZlr+diKsc3dDGcswUYOOE/6PoKFDGC8CXEnI7oiOHJQkhvBpCuCiE0B+dJ3w1+uPxF7RXMs88tPxlZP9vEsltQvN8Ba0k9kwkoQf6brLdLZ5H55RnTEfzuBK7mWzMDHSaSI8K7jsJ3S+jvc5zAEIIM0MI30Erub8UkSvLpKcz+swZ8+zvrEhuNlH+hRCuRL+lFcBLIjLSFt9CsbIVy6Q2U5iGPnee+9A1BxlPodMNYwbT0n40T0AIC0IIN4cQDkRHLIajnRCX0/I9fYBO5cjI/u8dyfVGR3DyzEOnusRkftli21fQtQYxbrdytxNxlaM1dqsebRZUb7d+A4wRkVEi0tc2CgF00xAR2UZERqJTuX4dhf0EOuL2QjmHNkJipqIzEFoQQrgO7Wgcjq6LSvEeuW8x6OLmETT9/mdsjo5ExXG8GELYF228XCIiE0Qk9Z5TnCwil4rIpWijb4uEzOZoYzPPSOAIEblFRHay9J4tIj8Tkf1EZLCI/AKdfXF1wbQQQvhPCGFECKEPWle9uahuoVbE6uTQebLvoEZuHNoCP8XceegagVkms11C/7ckemAScl8HVuWu/wL8vox8N3RotEUvi91/DLioQLxnYEPKZWQ2Rj/cbJFwpRGEeFHzyITcWcCUyK8T2gOwDF1gdSVqfObb80xAW/pvAn0S8SZbtKnnia6z9R5Po634Zeg0pvlWuM+w97ySaFEW2phoQBss59pzjUd/YK+K8vmpRFpGoo25UejUJsndE7TXZyT64Y+IdO8BHitYtuIek+eIRlISOkvQEZdYdypwfOR3NrnhZPP7Fome/Nz9IfYuJ6A/ekV6S26hae7vbOCbCblhwPsJ/wH2Tm9Bfwy+ilayfoaOpA0GfoFWyOKpeIXKF/qDe3nkdyM6NeBAdKrfA1ZeJmfl2N7zC8AfIt0b0IrhnlnZQHvBHgNejfJyeu76BCuv/2PPtSX6g90T/UHeD/idldPjE8/xJxJTjwqWrbmUGHVFp/8tQr+RQQndKUQbGKA/zvGmBEcT9SBG93dCKwyvWxqLlK1/0bRmYS7pNVbHEE0ltbx9x97pNyy9c1CbcQI6/fR2ex/xuqui5Wpz4NTI7worv8PRdQ7PW75OQ3vuN7b3PB34XaR7maXxWLRC8Ql0VHcKMCn6lqYm0uN2qx3sFnVos+xeVXbL/Eag318D2tD40Nxye6a5RNPoTG848HiB5x1INO0ZnW72Crn1EAm9PbN0Je79kWhaWokwxpKYahzJdEXXImV2smSdy8rhG5G7PCE3Dvhnwv8LNG0Ek9pkZTaR3WlN2Wqta9PA2suhPfEj7AN53wrqcvv/YXSuaHLxD9qqPLRAHN2Az+Suh6IGaKMyOp3QH/k3Eve+TrG1E38jN4+1guz26Laf5dJ0TMINTsjdQW7HoujeAegCqDdp2r0om1t8BtAjofMgiQZaK97xoWiv1h3Agea3Fzp3cxE61eqUErq7oXOWZ5gBmQh8j+aLr3amxIJpyhvEBlYzg0idGkO71+4GEe0JfjoX1wTUptxN064vDaQbvr3QxffZ/OFFJjsV2DEnd26cF2hF5yVaNtqzZ32JxM46pvsNorn2JeT6AedHfk9SZsMG+15m2/PGZevXcVktEcadBdN3HPpdPlmhbD1Ey3UL5yfk7gHuSfhvgTYCsk6UeKrMZODwNi5XPSwfVlo4t6FbLF4XlemnaFkJ7oJ2XuV3L1qF9lhvnZM7mWiBc+6e2601tBJHDTbL9Ku2W+a/Lvr7exLa0Bxp/+8FrFvNMxV43oOAnhXktiPdcdCZxGL+hNyR5BasV5DtjdaDnqHAZisVwjoQGFDmfj+0s+Ac+65/gHbgJNcP2L3kboG1uLo9B8FxPkpsKsSupM/ZmBBCWNbG8W2K/gA/GkJIDRFnctsBO4cQxub8OqOL+pZWiONI4KUQwnMF0tMb7Qnri/byPVPsSZJhHYj2Sk0uI9MPbbRtivZ4zkF7TyeExF7mIjII7Vmt6rwTGyrvixrc/+b8DkGnakxDz9lIhi8iu6AVha5oz94/UuksodvH4mhWrkJ0BkpbISIXotP5ti5VbkWkP9qo3jyE0KmKOHZH33HFM1VEpCdNPd2jQggvtja+XFgD0Dm175aJayA6JaOxXJVKp4h8BngvhLA8db9gmrqh3+PCnN8A1JZMQ0eCVpXQ/RS60Hdd4LWsbLYi7nXRBl+L8oXbrVZRyW6JyPaozWpWtihvs54JVZ77UavNMvkvo3ZrXVpptxJhdUW35R0dQni1HnQ7Mu661PUGguO0nmoP0utg3W7oPuh1E28bxF1XutUctFhJ3w7q2RId2Sx5QJiIbIJu/VtxPVFCtwu6aLeavKr6mV23kE52EOfrQdfMtSa+kod4um5J3brJ50r6UsNBrR2l+xHH3Qtdx7BaPXOt+VWSth6ScOdubXCU2G/eddtWt17TndKlhoMW20K/QJo7A1u2Zbyu2266pQ7ivIamqS8NRAdxVtAte4jnaq7b0M7xdnQ+l3zeWuKOwk65ZtMlozg7RLde092R+VXKtdgtx3Ecx2lbbJrE1ei89GfR6Ws3ichh6Im7RaZZ1KL/Q/Swxc3ROeNjQgi3RGI7oHObO+X0qo7XddtH1zgLXWd1GVoJPNlGhA5H5zI/gy5uHYMeyHmd6641urXoL0EXZY+h5e5X66ENo0vRKWwxHaVbr+nuyPxKU7Ql4c7d2uCo8iA9122dbr2mu1pdaj9osWp9ajgFvsZ4XbcddM2/qoM4XXfN161FnxoOau0o3XpNd0fmVylXj+cgOM5HyR7oorPZFVxqoZnrFtet13RXq7stethWIyGE+9EtDTcAHrfFy6WoRf9MdMTgqBDCmBDC19DtGHcHHhSR1BkVbRGv67aPLsBn0N2RMibZ36ciuX+jB3q67tqjW7V+COHdEMIw9CDE44HJIrJ/IvwWdJRuvaa7I/OrXMDu3Lkzh879bbGPdEJuCC17AV23oG69prtaXXRh25ASshuiU3veB35UIq+q1qeGU+BrjNd120HXZGYBh+WuP4ZOO/hCJHcALU8Hd901WLct9HM6P0Q7QO5Gz4Eo1DPdUbr1mu6OzK+88xEEx2nOE2ivXSUCLU8Hdd3iuh0Zd0foTqL56eBNgnrC8T7oNJOrSoRXi34tp8DXEq/rto8u6AnyA3M6q0II3ULLrUH7o3vlu+7ao9sW+pnOtehWq++gZ3SElOzqoluv6e7I/IoDc+fOnTmqPEjPdVunW6/prlaX2g9arFqfGk6BrzFe120HXbtX9UGcrrtm67aFfgnZige1rm669ZrujtL1cxAcx3HWYERkKHAacHAI4cMSMp3QU5P3CyH0bs/0OY7jOKsf3kBwHMdxHMdxHKcRX4PgOI7jOI7jOE4j3kBwHMdxHMdxHKcRbyA4juPUKSJygYiEnFssIpNF5MSPKL43RWTMRxF2K9NxbO6Z451YUvIP5eR/1B5pdBzHqWfW6egEOI7jODUxD92/HGA94BDgtyKyMIQwruOS1S7sjW7TWonhQE90O1fHcRynAt5AcBzHqW9WhhCeyF3fLyK7ovvq100DQUS6hRCWtFLt6RDCwkpCIYQXLY6q0uY4jrO24VOMHMdx1jwWAJ2zi9yUnPXzQvGUIRHZXUQeFZH55p6zbVKJ9M4TkRkislBEbhWRXrl764nINSLysk15ekNErhWRnlEYQUROF5ErRGQmMLktM8BxHMepHh9BcBzHqXNEJLPl3YFDgUHAca0MoydwD3qw2kXoSdADgA0i0W8BrwEnAJsBlwL/ix72laWhEzAKmAl82v4fD+wfhfUT4BHgaLzDynEcZ7XBGwiO4zj1zcbAisjvqhDCza0Mpy/QC/hRCGGB+d2XkOsGHJRN7RGRRcAtItIvhDAlhDATOCkTtsbLG8C/RWTLEMJbubDeCyF8s5XpdBzHcT5ivMfGcRynvpkH7Ghud+BU4BgROb+V4UwFFgLjROQwEYlHDjL+Gc37/zM62rBj5iEiR4vIsyKyEG28/Ntu9Y3C+msr01gWEVkn79oybMdxnLUJbyA4juPUNytDCBPNPRZCuAqdIjRSRDYqGkgIYQ6wH7p24Y/ATBG5V0T6RKIfRHqL0YbFZgAicgRwM7pj0FBgF+AIE+8ahfV+0fQVZEXkHMdxnCrwHhbHcZw1jylAF2Br4ENgqfl3ieQ2zF/YbkgHiEg3YF/gMnQnpF1yYp/I64hId2B94D3zGgo8GUIYnpMZVCKdoeDzFGXHyiKO4zhOJbyB4DiOs+bxWfs73f6+bX/7AY8BiMjO6NkALbDtRu8Wkc8CI6Lb+4nI+rlpRkegFf2Jdt0NWBbpHFXNQ7SWEMLEylKO4zhOJbyB4DiOU9+sIyJZD38XYCBwLvCXEMIM838KeAe4SkTOAzYCzgLmZ4GIyEHozkf/B7wFfAr4PvBAFN8S4F4RGY1OKxoN/Dk7awD4J3CtiIwCngQOBPYp+jAicixwI9A7hPBmUT3HcRyn7fAGguM4Tn3Ti6YTglcA04DfABdnAiGE5bY24DrgDuBldKehW3PhvIaOBFyCTiOaiW57OjKK73b0nIXr0alFd5HbtQj4LdAHXSzdFW0wDAOeoBjdgeXA3ILyjuM4ThsjIbT1FFDHcRzHqQ4RGQusCiF8t4zMsegowwbAwhBCQ4UwO6E7La0ATg4hXNN2KXYcx1nz8F2MHMdxnNWJL6OLo4swF5hUQO5+fFcjx3GcwvgIguM4jlNXiMjGQG+7XJxb/1BKflugh11Os8PcHMdxnBJ4A8FxHMdxHMdxnEZ8ipHjOI7jOI7jOI14A8FxHMdxHMdxnEa8geA4juM4juM4TiPeQHAcx3Ecx3EcpxFvIDiO4ziO4ziO08j/A+M1qEOQuN2VAAAAAElFTkSuQmCC
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stdout output_text">
+<pre>All resistances within the range.
+</pre>
+</div>
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+<div class="output_html rendered_html output_subarea ">
+<style  type="text/css" >
+</style><table id="T_02997_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >QPS Crate&Board</th>        <th class="col_heading level0 col1" >Bus Bar Segment Name</th>        <th class="col_heading level0 col2" >1st Magnet</th>        <th class="col_heading level0 col3" >2nd Magnet</th>        <th class="col_heading level0 col4" >Num of splices</th>        <th class="col_heading level0 col5" >R_MAG</th>    </tr></thead><tbody>
+                <tr>
+                        <th id="T_02997_level0_row0" class="row_heading level0 row0" >0</th>
+                        <td id="T_02997_row0_col0" class="data row0 col0" >B10L2_3</td>
+                        <td id="T_02997_row0_col1" class="data row0 col1" >DCQDD.7L2.L</td>
+                        <td id="T_02997_row0_col2" class="data row0 col2" >MQ.11L2.B2</td>
+                        <td id="T_02997_row0_col3" class="data row0 col3" >DFLAS.7L2.2</td>
+                        <td id="T_02997_row0_col4" class="data row0 col4" >16</td>
+                        <td id="T_02997_row0_col5" class="data row0 col5" >7.52E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row1" class="row_heading level0 row1" >1</th>
+                        <td id="T_02997_row1_col0" class="data row1 col0" >B12L2_3</td>
+                        <td id="T_02997_row1_col1" class="data row1 col1" >DCQDB.A12L2.L</td>
+                        <td id="T_02997_row1_col2" class="data row1 col2" >MQ.13L2.B2</td>
+                        <td id="T_02997_row1_col3" class="data row1 col3" >MQ.11L2.B2</td>
+                        <td id="T_02997_row1_col4" class="data row1 col4" >8</td>
+                        <td id="T_02997_row1_col5" class="data row1 col5" >4.65E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row2" class="row_heading level0 row2" >2</th>
+                        <td id="T_02997_row2_col0" class="data row2 col0" >B14L2_3</td>
+                        <td id="T_02997_row2_col1" class="data row2 col1" >DCQDB.A14L2.L</td>
+                        <td id="T_02997_row2_col2" class="data row2 col2" >MQ.15L2.B2</td>
+                        <td id="T_02997_row2_col3" class="data row2 col3" >MQ.13L2.B2</td>
+                        <td id="T_02997_row2_col4" class="data row2 col4" >8</td>
+                        <td id="T_02997_row2_col5" class="data row2 col5" >3.13E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row3" class="row_heading level0 row3" >3</th>
+                        <td id="T_02997_row3_col0" class="data row3 col0" >B16L2_3</td>
+                        <td id="T_02997_row3_col1" class="data row3 col1" >DCQDB.A16L2.L</td>
+                        <td id="T_02997_row3_col2" class="data row3 col2" >MQ.17L2.B2</td>
+                        <td id="T_02997_row3_col3" class="data row3 col3" >MQ.15L2.B2</td>
+                        <td id="T_02997_row3_col4" class="data row3 col4" >8</td>
+                        <td id="T_02997_row3_col5" class="data row3 col5" >9.91E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row4" class="row_heading level0 row4" >4</th>
+                        <td id="T_02997_row4_col0" class="data row4 col0" >B18L2_3</td>
+                        <td id="T_02997_row4_col1" class="data row4 col1" >DCQDB.A18L2.L</td>
+                        <td id="T_02997_row4_col2" class="data row4 col2" >MQ.19L2.B2</td>
+                        <td id="T_02997_row4_col3" class="data row4 col3" >MQ.17L2.B2</td>
+                        <td id="T_02997_row4_col4" class="data row4 col4" >8</td>
+                        <td id="T_02997_row4_col5" class="data row4 col5" >2.36E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row5" class="row_heading level0 row5" >5</th>
+                        <td id="T_02997_row5_col0" class="data row5 col0" >B20L2_3</td>
+                        <td id="T_02997_row5_col1" class="data row5 col1" >DCQDB.A20L2.L</td>
+                        <td id="T_02997_row5_col2" class="data row5 col2" >MQ.21L2.B2</td>
+                        <td id="T_02997_row5_col3" class="data row5 col3" >MQ.19L2.B2</td>
+                        <td id="T_02997_row5_col4" class="data row5 col4" >8</td>
+                        <td id="T_02997_row5_col5" class="data row5 col5" >7.95E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row6" class="row_heading level0 row6" >6</th>
+                        <td id="T_02997_row6_col0" class="data row6 col0" >B22L2_3</td>
+                        <td id="T_02997_row6_col1" class="data row6 col1" >DCQDB.A22L2.L</td>
+                        <td id="T_02997_row6_col2" class="data row6 col2" >MQ.23L2.B2</td>
+                        <td id="T_02997_row6_col3" class="data row6 col3" >MQ.21L2.B2</td>
+                        <td id="T_02997_row6_col4" class="data row6 col4" >8</td>
+                        <td id="T_02997_row6_col5" class="data row6 col5" >8.60E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row7" class="row_heading level0 row7" >7</th>
+                        <td id="T_02997_row7_col0" class="data row7 col0" >B24L2_3</td>
+                        <td id="T_02997_row7_col1" class="data row7 col1" >DCQDB.A24L2.L</td>
+                        <td id="T_02997_row7_col2" class="data row7 col2" >MQ.25L2.B2</td>
+                        <td id="T_02997_row7_col3" class="data row7 col3" >MQ.23L2.B2</td>
+                        <td id="T_02997_row7_col4" class="data row7 col4" >8</td>
+                        <td id="T_02997_row7_col5" class="data row7 col5" >1.67E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row8" class="row_heading level0 row8" >8</th>
+                        <td id="T_02997_row8_col0" class="data row8 col0" >B26L2_3</td>
+                        <td id="T_02997_row8_col1" class="data row8 col1" >DCQDB.A26L2.L</td>
+                        <td id="T_02997_row8_col2" class="data row8 col2" >MQ.27L2.B2</td>
+                        <td id="T_02997_row8_col3" class="data row8 col3" >MQ.25L2.B2</td>
+                        <td id="T_02997_row8_col4" class="data row8 col4" >8</td>
+                        <td id="T_02997_row8_col5" class="data row8 col5" >7.92E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row9" class="row_heading level0 row9" >9</th>
+                        <td id="T_02997_row9_col0" class="data row9 col0" >B28L2_3</td>
+                        <td id="T_02997_row9_col1" class="data row9 col1" >DCQDB.A28L2.L</td>
+                        <td id="T_02997_row9_col2" class="data row9 col2" >MQ.29L2.B2</td>
+                        <td id="T_02997_row9_col3" class="data row9 col3" >MQ.27L2.B2</td>
+                        <td id="T_02997_row9_col4" class="data row9 col4" >8</td>
+                        <td id="T_02997_row9_col5" class="data row9 col5" >1.07E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row10" class="row_heading level0 row10" >10</th>
+                        <td id="T_02997_row10_col0" class="data row10 col0" >B30L2_3</td>
+                        <td id="T_02997_row10_col1" class="data row10 col1" >DCQDB.A30L2.L</td>
+                        <td id="T_02997_row10_col2" class="data row10 col2" >MQ.31L2.B2</td>
+                        <td id="T_02997_row10_col3" class="data row10 col3" >MQ.29L2.B2</td>
+                        <td id="T_02997_row10_col4" class="data row10 col4" >8</td>
+                        <td id="T_02997_row10_col5" class="data row10 col5" >1.58E-08</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row11" class="row_heading level0 row11" >11</th>
+                        <td id="T_02997_row11_col0" class="data row11 col0" >B32L2_3</td>
+                        <td id="T_02997_row11_col1" class="data row11 col1" >DCQDB.A32L2.L</td>
+                        <td id="T_02997_row11_col2" class="data row11 col2" >MQ.33L2.B2</td>
+                        <td id="T_02997_row11_col3" class="data row11 col3" >MQ.31L2.B2</td>
+                        <td id="T_02997_row11_col4" class="data row11 col4" >8</td>
+                        <td id="T_02997_row11_col5" class="data row11 col5" >9.74E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row12" class="row_heading level0 row12" >12</th>
+                        <td id="T_02997_row12_col0" class="data row12 col0" >B33R1_3</td>
+                        <td id="T_02997_row12_col1" class="data row12 col1" >DCQDQ.32R1.R</td>
+                        <td id="T_02997_row12_col2" class="data row12 col2" >MQ.34R1.B1</td>
+                        <td id="T_02997_row12_col3" class="data row12 col3" >MQ.32R1.B1</td>
+                        <td id="T_02997_row12_col4" class="data row12 col4" >8</td>
+                        <td id="T_02997_row12_col5" class="data row12 col5" >1.03E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row13" class="row_heading level0 row13" >13</th>
+                        <td id="T_02997_row13_col0" class="data row13 col0" >B31R1_3</td>
+                        <td id="T_02997_row13_col1" class="data row13 col1" >DCQDQ.30R1.R</td>
+                        <td id="T_02997_row13_col2" class="data row13 col2" >MQ.32R1.B1</td>
+                        <td id="T_02997_row13_col3" class="data row13 col3" >MQ.30R1.B1</td>
+                        <td id="T_02997_row13_col4" class="data row13 col4" >8</td>
+                        <td id="T_02997_row13_col5" class="data row13 col5" >4.14E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row14" class="row_heading level0 row14" >14</th>
+                        <td id="T_02997_row14_col0" class="data row14 col0" >B29R1_3</td>
+                        <td id="T_02997_row14_col1" class="data row14 col1" >DCQDQ.28R1.R</td>
+                        <td id="T_02997_row14_col2" class="data row14 col2" >MQ.30R1.B1</td>
+                        <td id="T_02997_row14_col3" class="data row14 col3" >MQ.28R1.B1</td>
+                        <td id="T_02997_row14_col4" class="data row14 col4" >8</td>
+                        <td id="T_02997_row14_col5" class="data row14 col5" >4.91E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row15" class="row_heading level0 row15" >15</th>
+                        <td id="T_02997_row15_col0" class="data row15 col0" >B27R1_3</td>
+                        <td id="T_02997_row15_col1" class="data row15 col1" >DCQDQ.26R1.R</td>
+                        <td id="T_02997_row15_col2" class="data row15 col2" >MQ.28R1.B1</td>
+                        <td id="T_02997_row15_col3" class="data row15 col3" >MQ.26R1.B1</td>
+                        <td id="T_02997_row15_col4" class="data row15 col4" >8</td>
+                        <td id="T_02997_row15_col5" class="data row15 col5" >4.52E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row16" class="row_heading level0 row16" >16</th>
+                        <td id="T_02997_row16_col0" class="data row16 col0" >B25R1_3</td>
+                        <td id="T_02997_row16_col1" class="data row16 col1" >DCQDQ.24R1.R</td>
+                        <td id="T_02997_row16_col2" class="data row16 col2" >MQ.26R1.B1</td>
+                        <td id="T_02997_row16_col3" class="data row16 col3" >MQ.24R1.B1</td>
+                        <td id="T_02997_row16_col4" class="data row16 col4" >8</td>
+                        <td id="T_02997_row16_col5" class="data row16 col5" >4.56E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row17" class="row_heading level0 row17" >17</th>
+                        <td id="T_02997_row17_col0" class="data row17 col0" >B23R1_3</td>
+                        <td id="T_02997_row17_col1" class="data row17 col1" >DCQDQ.22R1.R</td>
+                        <td id="T_02997_row17_col2" class="data row17 col2" >MQ.24R1.B1</td>
+                        <td id="T_02997_row17_col3" class="data row17 col3" >MQ.22R1.B1</td>
+                        <td id="T_02997_row17_col4" class="data row17 col4" >8</td>
+                        <td id="T_02997_row17_col5" class="data row17 col5" >1.80E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row18" class="row_heading level0 row18" >18</th>
+                        <td id="T_02997_row18_col0" class="data row18 col0" >B21R1_3</td>
+                        <td id="T_02997_row18_col1" class="data row18 col1" >DCQDQ.20R1.R</td>
+                        <td id="T_02997_row18_col2" class="data row18 col2" >MQ.22R1.B1</td>
+                        <td id="T_02997_row18_col3" class="data row18 col3" >MQ.20R1.B1</td>
+                        <td id="T_02997_row18_col4" class="data row18 col4" >8</td>
+                        <td id="T_02997_row18_col5" class="data row18 col5" >8.04E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row19" class="row_heading level0 row19" >19</th>
+                        <td id="T_02997_row19_col0" class="data row19 col0" >B19R1_3</td>
+                        <td id="T_02997_row19_col1" class="data row19 col1" >DCQDQ.18R1.R</td>
+                        <td id="T_02997_row19_col2" class="data row19 col2" >MQ.20R1.B1</td>
+                        <td id="T_02997_row19_col3" class="data row19 col3" >MQ.18R1.B1</td>
+                        <td id="T_02997_row19_col4" class="data row19 col4" >8</td>
+                        <td id="T_02997_row19_col5" class="data row19 col5" >1.54E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row20" class="row_heading level0 row20" >20</th>
+                        <td id="T_02997_row20_col0" class="data row20 col0" >B17R1_3</td>
+                        <td id="T_02997_row20_col1" class="data row20 col1" >DCQDQ.16R1.R</td>
+                        <td id="T_02997_row20_col2" class="data row20 col2" >MQ.18R1.B1</td>
+                        <td id="T_02997_row20_col3" class="data row20 col3" >MQ.16R1.B1</td>
+                        <td id="T_02997_row20_col4" class="data row20 col4" >8</td>
+                        <td id="T_02997_row20_col5" class="data row20 col5" >2.44E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row21" class="row_heading level0 row21" >21</th>
+                        <td id="T_02997_row21_col0" class="data row21 col0" >B15R1_3</td>
+                        <td id="T_02997_row21_col1" class="data row21 col1" >DCQDQ.14R1.R</td>
+                        <td id="T_02997_row21_col2" class="data row21 col2" >MQ.16R1.B1</td>
+                        <td id="T_02997_row21_col3" class="data row21 col3" >MQ.14R1.B1</td>
+                        <td id="T_02997_row21_col4" class="data row21 col4" >8</td>
+                        <td id="T_02997_row21_col5" class="data row21 col5" >5.37E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row22" class="row_heading level0 row22" >22</th>
+                        <td id="T_02997_row22_col0" class="data row22 col0" >B13R1_3</td>
+                        <td id="T_02997_row22_col1" class="data row22 col1" >DCQDQ.12R1.R</td>
+                        <td id="T_02997_row22_col2" class="data row22 col2" >MQ.14R1.B1</td>
+                        <td id="T_02997_row22_col3" class="data row22 col3" >MQ.12R1.B1</td>
+                        <td id="T_02997_row22_col4" class="data row22 col4" >8</td>
+                        <td id="T_02997_row22_col5" class="data row22 col5" >5.24E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row23" class="row_heading level0 row23" >23</th>
+                        <td id="T_02997_row23_col0" class="data row23 col0" >B11R1_3</td>
+                        <td id="T_02997_row23_col1" class="data row23 col1" >DCQDE.11R1.R</td>
+                        <td id="T_02997_row23_col2" class="data row23 col2" >MQ.12R1.B1</td>
+                        <td id="T_02997_row23_col3" class="data row23 col3" >MQ.11R1.B2</td>
+                        <td id="T_02997_row23_col4" class="data row23 col4" >6</td>
+                        <td id="T_02997_row23_col5" class="data row23 col5" >1.12E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row24" class="row_heading level0 row24" >24</th>
+                        <td id="T_02997_row24_col0" class="data row24 col0" >B12R1_3</td>
+                        <td id="T_02997_row24_col1" class="data row24 col1" >DCQDB.C13R1.L</td>
+                        <td id="T_02997_row24_col2" class="data row24 col2" >MQ.11R1.B2</td>
+                        <td id="T_02997_row24_col3" class="data row24 col3" >MQ.13R1.B2</td>
+                        <td id="T_02997_row24_col4" class="data row24 col4" >8</td>
+                        <td id="T_02997_row24_col5" class="data row24 col5" >1.30E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row25" class="row_heading level0 row25" >25</th>
+                        <td id="T_02997_row25_col0" class="data row25 col0" >B14R1_3</td>
+                        <td id="T_02997_row25_col1" class="data row25 col1" >DCQDB.C15R1.L</td>
+                        <td id="T_02997_row25_col2" class="data row25 col2" >MQ.13R1.B2</td>
+                        <td id="T_02997_row25_col3" class="data row25 col3" >MQ.15R1.B2</td>
+                        <td id="T_02997_row25_col4" class="data row25 col4" >8</td>
+                        <td id="T_02997_row25_col5" class="data row25 col5" >2.23E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row26" class="row_heading level0 row26" >26</th>
+                        <td id="T_02997_row26_col0" class="data row26 col0" >B16R1_3</td>
+                        <td id="T_02997_row26_col1" class="data row26 col1" >DCQDB.C17R1.L</td>
+                        <td id="T_02997_row26_col2" class="data row26 col2" >MQ.15R1.B2</td>
+                        <td id="T_02997_row26_col3" class="data row26 col3" >MQ.17R1.B2</td>
+                        <td id="T_02997_row26_col4" class="data row26 col4" >8</td>
+                        <td id="T_02997_row26_col5" class="data row26 col5" >2.44E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row27" class="row_heading level0 row27" >27</th>
+                        <td id="T_02997_row27_col0" class="data row27 col0" >B18R1_3</td>
+                        <td id="T_02997_row27_col1" class="data row27 col1" >DCQDB.C19R1.L</td>
+                        <td id="T_02997_row27_col2" class="data row27 col2" >MQ.17R1.B2</td>
+                        <td id="T_02997_row27_col3" class="data row27 col3" >MQ.19R1.B2</td>
+                        <td id="T_02997_row27_col4" class="data row27 col4" >8</td>
+                        <td id="T_02997_row27_col5" class="data row27 col5" >2.88E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row28" class="row_heading level0 row28" >28</th>
+                        <td id="T_02997_row28_col0" class="data row28 col0" >B20R1_3</td>
+                        <td id="T_02997_row28_col1" class="data row28 col1" >DCQDB.C21R1.L</td>
+                        <td id="T_02997_row28_col2" class="data row28 col2" >MQ.19R1.B2</td>
+                        <td id="T_02997_row28_col3" class="data row28 col3" >MQ.21R1.B2</td>
+                        <td id="T_02997_row28_col4" class="data row28 col4" >8</td>
+                        <td id="T_02997_row28_col5" class="data row28 col5" >5.83E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row29" class="row_heading level0 row29" >29</th>
+                        <td id="T_02997_row29_col0" class="data row29 col0" >B22R1_3</td>
+                        <td id="T_02997_row29_col1" class="data row29 col1" >DCQDB.C23R1.L</td>
+                        <td id="T_02997_row29_col2" class="data row29 col2" >MQ.21R1.B2</td>
+                        <td id="T_02997_row29_col3" class="data row29 col3" >MQ.23R1.B2</td>
+                        <td id="T_02997_row29_col4" class="data row29 col4" >8</td>
+                        <td id="T_02997_row29_col5" class="data row29 col5" >3.97E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row30" class="row_heading level0 row30" >30</th>
+                        <td id="T_02997_row30_col0" class="data row30 col0" >B24R1_3</td>
+                        <td id="T_02997_row30_col1" class="data row30 col1" >DCQDB.C25R1.L</td>
+                        <td id="T_02997_row30_col2" class="data row30 col2" >MQ.23R1.B2</td>
+                        <td id="T_02997_row30_col3" class="data row30 col3" >MQ.25R1.B2</td>
+                        <td id="T_02997_row30_col4" class="data row30 col4" >8</td>
+                        <td id="T_02997_row30_col5" class="data row30 col5" >2.80E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row31" class="row_heading level0 row31" >31</th>
+                        <td id="T_02997_row31_col0" class="data row31 col0" >B26R1_3</td>
+                        <td id="T_02997_row31_col1" class="data row31 col1" >DCQDB.C27R1.L</td>
+                        <td id="T_02997_row31_col2" class="data row31 col2" >MQ.25R1.B2</td>
+                        <td id="T_02997_row31_col3" class="data row31 col3" >MQ.27R1.B2</td>
+                        <td id="T_02997_row31_col4" class="data row31 col4" >8</td>
+                        <td id="T_02997_row31_col5" class="data row31 col5" >2.94E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row32" class="row_heading level0 row32" >32</th>
+                        <td id="T_02997_row32_col0" class="data row32 col0" >B28R1_3</td>
+                        <td id="T_02997_row32_col1" class="data row32 col1" >DCQDB.C29R1.L</td>
+                        <td id="T_02997_row32_col2" class="data row32 col2" >MQ.27R1.B2</td>
+                        <td id="T_02997_row32_col3" class="data row32 col3" >MQ.29R1.B2</td>
+                        <td id="T_02997_row32_col4" class="data row32 col4" >8</td>
+                        <td id="T_02997_row32_col5" class="data row32 col5" >4.14E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row33" class="row_heading level0 row33" >33</th>
+                        <td id="T_02997_row33_col0" class="data row33 col0" >B30R1_3</td>
+                        <td id="T_02997_row33_col1" class="data row33 col1" >DCQDB.C31R1.L</td>
+                        <td id="T_02997_row33_col2" class="data row33 col2" >MQ.29R1.B2</td>
+                        <td id="T_02997_row33_col3" class="data row33 col3" >MQ.31R1.B2</td>
+                        <td id="T_02997_row33_col4" class="data row33 col4" >8</td>
+                        <td id="T_02997_row33_col5" class="data row33 col5" >6.63E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row34" class="row_heading level0 row34" >34</th>
+                        <td id="T_02997_row34_col0" class="data row34 col0" >B32R1_3</td>
+                        <td id="T_02997_row34_col1" class="data row34 col1" >DCQDB.C33R1.L</td>
+                        <td id="T_02997_row34_col2" class="data row34 col2" >MQ.31R1.B2</td>
+                        <td id="T_02997_row34_col3" class="data row34 col3" >MQ.33R1.B2</td>
+                        <td id="T_02997_row34_col4" class="data row34 col4" >8</td>
+                        <td id="T_02997_row34_col5" class="data row34 col5" >8.69E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row35" class="row_heading level0 row35" >35</th>
+                        <td id="T_02997_row35_col0" class="data row35 col0" >B34R1_3</td>
+                        <td id="T_02997_row35_col1" class="data row35 col1" >DCQDB.A34L2.L</td>
+                        <td id="T_02997_row35_col2" class="data row35 col2" >MQ.33R1.B2</td>
+                        <td id="T_02997_row35_col3" class="data row35 col3" >MQ.33L2.B2</td>
+                        <td id="T_02997_row35_col4" class="data row35 col4" >8</td>
+                        <td id="T_02997_row35_col5" class="data row35 col5" >2.72E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row36" class="row_heading level0 row36" >36</th>
+                        <td id="T_02997_row36_col0" class="data row36 col0" >B33L2_3</td>
+                        <td id="T_02997_row36_col1" class="data row36 col1" >DCQDQ.34R1.R</td>
+                        <td id="T_02997_row36_col2" class="data row36 col2" >MQ.32L2.B1</td>
+                        <td id="T_02997_row36_col3" class="data row36 col3" >MQ.34R1.B1</td>
+                        <td id="T_02997_row36_col4" class="data row36 col4" >8</td>
+                        <td id="T_02997_row36_col5" class="data row36 col5" >4.59E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row37" class="row_heading level0 row37" >37</th>
+                        <td id="T_02997_row37_col0" class="data row37 col0" >B31L2_3</td>
+                        <td id="T_02997_row37_col1" class="data row37 col1" >DCQDQ.32L2.R</td>
+                        <td id="T_02997_row37_col2" class="data row37 col2" >MQ.30L2.B1</td>
+                        <td id="T_02997_row37_col3" class="data row37 col3" >MQ.32L2.B1</td>
+                        <td id="T_02997_row37_col4" class="data row37 col4" >8</td>
+                        <td id="T_02997_row37_col5" class="data row37 col5" >2.53E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row38" class="row_heading level0 row38" >38</th>
+                        <td id="T_02997_row38_col0" class="data row38 col0" >B29L2_3</td>
+                        <td id="T_02997_row38_col1" class="data row38 col1" >DCQDQ.30L2.R</td>
+                        <td id="T_02997_row38_col2" class="data row38 col2" >MQ.28L2.B1</td>
+                        <td id="T_02997_row38_col3" class="data row38 col3" >MQ.30L2.B1</td>
+                        <td id="T_02997_row38_col4" class="data row38 col4" >8</td>
+                        <td id="T_02997_row38_col5" class="data row38 col5" >3.14E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row39" class="row_heading level0 row39" >39</th>
+                        <td id="T_02997_row39_col0" class="data row39 col0" >B27L2_3</td>
+                        <td id="T_02997_row39_col1" class="data row39 col1" >DCQDQ.28L2.R</td>
+                        <td id="T_02997_row39_col2" class="data row39 col2" >MQ.26L2.B1</td>
+                        <td id="T_02997_row39_col3" class="data row39 col3" >MQ.28L2.B1</td>
+                        <td id="T_02997_row39_col4" class="data row39 col4" >8</td>
+                        <td id="T_02997_row39_col5" class="data row39 col5" >1.78E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row40" class="row_heading level0 row40" >40</th>
+                        <td id="T_02997_row40_col0" class="data row40 col0" >B25L2_3</td>
+                        <td id="T_02997_row40_col1" class="data row40 col1" >DCQDQ.26L2.R</td>
+                        <td id="T_02997_row40_col2" class="data row40 col2" >MQ.24L2.B1</td>
+                        <td id="T_02997_row40_col3" class="data row40 col3" >MQ.26L2.B1</td>
+                        <td id="T_02997_row40_col4" class="data row40 col4" >8</td>
+                        <td id="T_02997_row40_col5" class="data row40 col5" >3.78E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row41" class="row_heading level0 row41" >41</th>
+                        <td id="T_02997_row41_col0" class="data row41 col0" >B23L2_3</td>
+                        <td id="T_02997_row41_col1" class="data row41 col1" >DCQDQ.24L2.R</td>
+                        <td id="T_02997_row41_col2" class="data row41 col2" >MQ.22L2.B1</td>
+                        <td id="T_02997_row41_col3" class="data row41 col3" >MQ.24L2.B1</td>
+                        <td id="T_02997_row41_col4" class="data row41 col4" >8</td>
+                        <td id="T_02997_row41_col5" class="data row41 col5" >1.94E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row42" class="row_heading level0 row42" >42</th>
+                        <td id="T_02997_row42_col0" class="data row42 col0" >B21L2_3</td>
+                        <td id="T_02997_row42_col1" class="data row42 col1" >DCQDQ.22L2.R</td>
+                        <td id="T_02997_row42_col2" class="data row42 col2" >MQ.20L2.B1</td>
+                        <td id="T_02997_row42_col3" class="data row42 col3" >MQ.22L2.B1</td>
+                        <td id="T_02997_row42_col4" class="data row42 col4" >8</td>
+                        <td id="T_02997_row42_col5" class="data row42 col5" >8.79E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row43" class="row_heading level0 row43" >43</th>
+                        <td id="T_02997_row43_col0" class="data row43 col0" >B19L2_3</td>
+                        <td id="T_02997_row43_col1" class="data row43 col1" >DCQDQ.20L2.R</td>
+                        <td id="T_02997_row43_col2" class="data row43 col2" >MQ.18L2.B1</td>
+                        <td id="T_02997_row43_col3" class="data row43 col3" >MQ.20L2.B1</td>
+                        <td id="T_02997_row43_col4" class="data row43 col4" >8</td>
+                        <td id="T_02997_row43_col5" class="data row43 col5" >8.95E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row44" class="row_heading level0 row44" >44</th>
+                        <td id="T_02997_row44_col0" class="data row44 col0" >B17L2_3</td>
+                        <td id="T_02997_row44_col1" class="data row44 col1" >DCQDQ.18L2.R</td>
+                        <td id="T_02997_row44_col2" class="data row44 col2" >MQ.16L2.B1</td>
+                        <td id="T_02997_row44_col3" class="data row44 col3" >MQ.18L2.B1</td>
+                        <td id="T_02997_row44_col4" class="data row44 col4" >8</td>
+                        <td id="T_02997_row44_col5" class="data row44 col5" >4.10E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row45" class="row_heading level0 row45" >45</th>
+                        <td id="T_02997_row45_col0" class="data row45 col0" >B15L2_3</td>
+                        <td id="T_02997_row45_col1" class="data row45 col1" >DCQDQ.16L2.R</td>
+                        <td id="T_02997_row45_col2" class="data row45 col2" >MQ.14L2.B1</td>
+                        <td id="T_02997_row45_col3" class="data row45 col3" >MQ.16L2.B1</td>
+                        <td id="T_02997_row45_col4" class="data row45 col4" >8</td>
+                        <td id="T_02997_row45_col5" class="data row45 col5" >4.09E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row46" class="row_heading level0 row46" >46</th>
+                        <td id="T_02997_row46_col0" class="data row46 col0" >B13L2_3</td>
+                        <td id="T_02997_row46_col1" class="data row46 col1" >DCQDQ.14L2.R</td>
+                        <td id="T_02997_row46_col2" class="data row46 col2" >MQ.12L2.B1</td>
+                        <td id="T_02997_row46_col3" class="data row46 col3" >MQ.14L2.B1</td>
+                        <td id="T_02997_row46_col4" class="data row46 col4" >8</td>
+                        <td id="T_02997_row46_col5" class="data row46 col5" >2.06E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_02997_level0_row47" class="row_heading level0 row47" >47</th>
+                        <td id="T_02997_row47_col0" class="data row47 col0" >B11L2_3</td>
+                        <td id="T_02997_row47_col1" class="data row47 col1" >DCQDQ.12L2.R</td>
+                        <td id="T_02997_row47_col2" class="data row47 col2" >DFLAS.7L2.1</td>
+                        <td id="T_02997_row47_col3" class="data row47 col3" >MQ.12L2.B1</td>
+                        <td id="T_02997_row47_col4" class="data row47 col4" >20</td>
+                        <td id="T_02997_row47_col5" class="data row47 col5" >6.83E-09</td>
+            </tr>
+    </tbody></table>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
+</div><div class="inner_cell">
+<div class="text_cell_render border-box-sizing rendered_html">
+<ul>
+<li>RQF</li>
+</ul>
+
+</div>
+</div>
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
+<div class="output_wrapper">
+<div class="output">
+
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+<div class="output_area">
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+    <div class="prompt"></div>
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+<div class="output_png output_subarea ">
+<img 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
+"
+>
+</div>
+
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+<div class="output_subarea output_stream output_stdout output_text">
+<pre>All resistances within the range.
+</pre>
+</div>
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
+
+
+<div class="output_html rendered_html output_subarea ">
+<style  type="text/css" >
+</style><table id="T_0bd98_" ><thead>    <tr>        <th class="blank level0" ></th>        <th class="col_heading level0 col0" >QPS Crate&Board</th>        <th class="col_heading level0 col1" >Bus Bar Segment Name</th>        <th class="col_heading level0 col2" >1st Magnet</th>        <th class="col_heading level0 col3" >2nd Magnet</th>        <th class="col_heading level0 col4" >Num of splices</th>        <th class="col_heading level0 col5" >R_MAG</th>    </tr></thead><tbody>
+                <tr>
+                        <th id="T_0bd98_level0_row0" class="row_heading level0 row0" >0</th>
+                        <td id="T_0bd98_row0_col0" class="data row0 col0" >B10L2_4</td>
+                        <td id="T_0bd98_row0_col1" class="data row0 col1" >DCQFD.7L2.R</td>
+                        <td id="T_0bd98_row0_col2" class="data row0 col2" >MQ.11L2.B1</td>
+                        <td id="T_0bd98_row0_col3" class="data row0 col3" >DFLAS.7L2.4</td>
+                        <td id="T_0bd98_row0_col4" class="data row0 col4" >16</td>
+                        <td id="T_0bd98_row0_col5" class="data row0 col5" >1.38E-08</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row1" class="row_heading level0 row1" >1</th>
+                        <td id="T_0bd98_row1_col0" class="data row1 col0" >B12L2_4</td>
+                        <td id="T_0bd98_row1_col1" class="data row1 col1" >DCQFB.A12L2.R</td>
+                        <td id="T_0bd98_row1_col2" class="data row1 col2" >MQ.13L2.B1</td>
+                        <td id="T_0bd98_row1_col3" class="data row1 col3" >MQ.11L2.B1</td>
+                        <td id="T_0bd98_row1_col4" class="data row1 col4" >8</td>
+                        <td id="T_0bd98_row1_col5" class="data row1 col5" >4.59E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row2" class="row_heading level0 row2" >2</th>
+                        <td id="T_0bd98_row2_col0" class="data row2 col0" >B14L2_4</td>
+                        <td id="T_0bd98_row2_col1" class="data row2 col1" >DCQFB.A14L2.R</td>
+                        <td id="T_0bd98_row2_col2" class="data row2 col2" >MQ.15L2.B1</td>
+                        <td id="T_0bd98_row2_col3" class="data row2 col3" >MQ.13L2.B1</td>
+                        <td id="T_0bd98_row2_col4" class="data row2 col4" >8</td>
+                        <td id="T_0bd98_row2_col5" class="data row2 col5" >2.33E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row3" class="row_heading level0 row3" >3</th>
+                        <td id="T_0bd98_row3_col0" class="data row3 col0" >B16L2_4</td>
+                        <td id="T_0bd98_row3_col1" class="data row3 col1" >DCQFB.A16L2.R</td>
+                        <td id="T_0bd98_row3_col2" class="data row3 col2" >MQ.17L2.B1</td>
+                        <td id="T_0bd98_row3_col3" class="data row3 col3" >MQ.15L2.B1</td>
+                        <td id="T_0bd98_row3_col4" class="data row3 col4" >8</td>
+                        <td id="T_0bd98_row3_col5" class="data row3 col5" >2.01E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row4" class="row_heading level0 row4" >4</th>
+                        <td id="T_0bd98_row4_col0" class="data row4 col0" >B18L2_4</td>
+                        <td id="T_0bd98_row4_col1" class="data row4 col1" >DCQFB.A18L2.R</td>
+                        <td id="T_0bd98_row4_col2" class="data row4 col2" >MQ.19L2.B1</td>
+                        <td id="T_0bd98_row4_col3" class="data row4 col3" >MQ.17L2.B1</td>
+                        <td id="T_0bd98_row4_col4" class="data row4 col4" >8</td>
+                        <td id="T_0bd98_row4_col5" class="data row4 col5" >3.05E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row5" class="row_heading level0 row5" >5</th>
+                        <td id="T_0bd98_row5_col0" class="data row5 col0" >B20L2_4</td>
+                        <td id="T_0bd98_row5_col1" class="data row5 col1" >DCQFB.A20L2.R</td>
+                        <td id="T_0bd98_row5_col2" class="data row5 col2" >MQ.21L2.B1</td>
+                        <td id="T_0bd98_row5_col3" class="data row5 col3" >MQ.19L2.B1</td>
+                        <td id="T_0bd98_row5_col4" class="data row5 col4" >8</td>
+                        <td id="T_0bd98_row5_col5" class="data row5 col5" >2.99E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row6" class="row_heading level0 row6" >6</th>
+                        <td id="T_0bd98_row6_col0" class="data row6 col0" >B22L2_4</td>
+                        <td id="T_0bd98_row6_col1" class="data row6 col1" >DCQFB.A22L2.R</td>
+                        <td id="T_0bd98_row6_col2" class="data row6 col2" >MQ.23L2.B1</td>
+                        <td id="T_0bd98_row6_col3" class="data row6 col3" >MQ.21L2.B1</td>
+                        <td id="T_0bd98_row6_col4" class="data row6 col4" >8</td>
+                        <td id="T_0bd98_row6_col5" class="data row6 col5" >2.32E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row7" class="row_heading level0 row7" >7</th>
+                        <td id="T_0bd98_row7_col0" class="data row7 col0" >B24L2_4</td>
+                        <td id="T_0bd98_row7_col1" class="data row7 col1" >DCQFB.A24L2.R</td>
+                        <td id="T_0bd98_row7_col2" class="data row7 col2" >MQ.25L2.B1</td>
+                        <td id="T_0bd98_row7_col3" class="data row7 col3" >MQ.23L2.B1</td>
+                        <td id="T_0bd98_row7_col4" class="data row7 col4" >8</td>
+                        <td id="T_0bd98_row7_col5" class="data row7 col5" >6.62E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row8" class="row_heading level0 row8" >8</th>
+                        <td id="T_0bd98_row8_col0" class="data row8 col0" >B26L2_4</td>
+                        <td id="T_0bd98_row8_col1" class="data row8 col1" >DCQFB.A26L2.R</td>
+                        <td id="T_0bd98_row8_col2" class="data row8 col2" >MQ.27L2.B1</td>
+                        <td id="T_0bd98_row8_col3" class="data row8 col3" >MQ.25L2.B1</td>
+                        <td id="T_0bd98_row8_col4" class="data row8 col4" >8</td>
+                        <td id="T_0bd98_row8_col5" class="data row8 col5" >7.79E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row9" class="row_heading level0 row9" >9</th>
+                        <td id="T_0bd98_row9_col0" class="data row9 col0" >B28L2_4</td>
+                        <td id="T_0bd98_row9_col1" class="data row9 col1" >DCQFB.A28L2.R</td>
+                        <td id="T_0bd98_row9_col2" class="data row9 col2" >MQ.29L2.B1</td>
+                        <td id="T_0bd98_row9_col3" class="data row9 col3" >MQ.27L2.B1</td>
+                        <td id="T_0bd98_row9_col4" class="data row9 col4" >8</td>
+                        <td id="T_0bd98_row9_col5" class="data row9 col5" >4.19E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row10" class="row_heading level0 row10" >10</th>
+                        <td id="T_0bd98_row10_col0" class="data row10 col0" >B30L2_4</td>
+                        <td id="T_0bd98_row10_col1" class="data row10 col1" >DCQFB.A30L2.R</td>
+                        <td id="T_0bd98_row10_col2" class="data row10 col2" >MQ.31L2.B1</td>
+                        <td id="T_0bd98_row10_col3" class="data row10 col3" >MQ.29L2.B1</td>
+                        <td id="T_0bd98_row10_col4" class="data row10 col4" >8</td>
+                        <td id="T_0bd98_row10_col5" class="data row10 col5" >3.59E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row11" class="row_heading level0 row11" >11</th>
+                        <td id="T_0bd98_row11_col0" class="data row11 col0" >B32L2_4</td>
+                        <td id="T_0bd98_row11_col1" class="data row11 col1" >DCQFB.C32L2.R</td>
+                        <td id="T_0bd98_row11_col2" class="data row11 col2" >MQ.33L2.B1</td>
+                        <td id="T_0bd98_row11_col3" class="data row11 col3" >MQ.31L2.B1</td>
+                        <td id="T_0bd98_row11_col4" class="data row11 col4" >8</td>
+                        <td id="T_0bd98_row11_col5" class="data row11 col5" >2.25E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row12" class="row_heading level0 row12" >12</th>
+                        <td id="T_0bd98_row12_col0" class="data row12 col0" >B33R1_4</td>
+                        <td id="T_0bd98_row12_col1" class="data row12 col1" >DCQFQ.32R1.L</td>
+                        <td id="T_0bd98_row12_col2" class="data row12 col2" >MQ.34R1.B2</td>
+                        <td id="T_0bd98_row12_col3" class="data row12 col3" >MQ.32R1.B2</td>
+                        <td id="T_0bd98_row12_col4" class="data row12 col4" >8</td>
+                        <td id="T_0bd98_row12_col5" class="data row12 col5" >7.04E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row13" class="row_heading level0 row13" >13</th>
+                        <td id="T_0bd98_row13_col0" class="data row13 col0" >B31R1_4</td>
+                        <td id="T_0bd98_row13_col1" class="data row13 col1" >DCQFQ.30R1.L</td>
+                        <td id="T_0bd98_row13_col2" class="data row13 col2" >MQ.32R1.B2</td>
+                        <td id="T_0bd98_row13_col3" class="data row13 col3" >MQ.30R1.B2</td>
+                        <td id="T_0bd98_row13_col4" class="data row13 col4" >8</td>
+                        <td id="T_0bd98_row13_col5" class="data row13 col5" >8.23E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row14" class="row_heading level0 row14" >14</th>
+                        <td id="T_0bd98_row14_col0" class="data row14 col0" >B29R1_4</td>
+                        <td id="T_0bd98_row14_col1" class="data row14 col1" >DCQFQ.28R1.L</td>
+                        <td id="T_0bd98_row14_col2" class="data row14 col2" >MQ.30R1.B2</td>
+                        <td id="T_0bd98_row14_col3" class="data row14 col3" >MQ.28R1.B2</td>
+                        <td id="T_0bd98_row14_col4" class="data row14 col4" >8</td>
+                        <td id="T_0bd98_row14_col5" class="data row14 col5" >1.17E-08</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row15" class="row_heading level0 row15" >15</th>
+                        <td id="T_0bd98_row15_col0" class="data row15 col0" >B27R1_4</td>
+                        <td id="T_0bd98_row15_col1" class="data row15 col1" >DCQFQ.26R1.L</td>
+                        <td id="T_0bd98_row15_col2" class="data row15 col2" >MQ.28R1.B2</td>
+                        <td id="T_0bd98_row15_col3" class="data row15 col3" >MQ.26R1.B2</td>
+                        <td id="T_0bd98_row15_col4" class="data row15 col4" >8</td>
+                        <td id="T_0bd98_row15_col5" class="data row15 col5" >4.74E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row16" class="row_heading level0 row16" >16</th>
+                        <td id="T_0bd98_row16_col0" class="data row16 col0" >B25R1_4</td>
+                        <td id="T_0bd98_row16_col1" class="data row16 col1" >DCQFQ.24R1.L</td>
+                        <td id="T_0bd98_row16_col2" class="data row16 col2" >MQ.26R1.B2</td>
+                        <td id="T_0bd98_row16_col3" class="data row16 col3" >MQ.24R1.B2</td>
+                        <td id="T_0bd98_row16_col4" class="data row16 col4" >8</td>
+                        <td id="T_0bd98_row16_col5" class="data row16 col5" >1.88E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row17" class="row_heading level0 row17" >17</th>
+                        <td id="T_0bd98_row17_col0" class="data row17 col0" >B23R1_4</td>
+                        <td id="T_0bd98_row17_col1" class="data row17 col1" >DCQFQ.22R1.L</td>
+                        <td id="T_0bd98_row17_col2" class="data row17 col2" >MQ.24R1.B2</td>
+                        <td id="T_0bd98_row17_col3" class="data row17 col3" >MQ.22R1.B2</td>
+                        <td id="T_0bd98_row17_col4" class="data row17 col4" >8</td>
+                        <td id="T_0bd98_row17_col5" class="data row17 col5" >9.18E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row18" class="row_heading level0 row18" >18</th>
+                        <td id="T_0bd98_row18_col0" class="data row18 col0" >B21R1_4</td>
+                        <td id="T_0bd98_row18_col1" class="data row18 col1" >DCQFQ.20R1.L</td>
+                        <td id="T_0bd98_row18_col2" class="data row18 col2" >MQ.22R1.B2</td>
+                        <td id="T_0bd98_row18_col3" class="data row18 col3" >MQ.20R1.B2</td>
+                        <td id="T_0bd98_row18_col4" class="data row18 col4" >8</td>
+                        <td id="T_0bd98_row18_col5" class="data row18 col5" >2.32E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row19" class="row_heading level0 row19" >19</th>
+                        <td id="T_0bd98_row19_col0" class="data row19 col0" >B19R1_4</td>
+                        <td id="T_0bd98_row19_col1" class="data row19 col1" >DCQFQ.18R1.L</td>
+                        <td id="T_0bd98_row19_col2" class="data row19 col2" >MQ.20R1.B2</td>
+                        <td id="T_0bd98_row19_col3" class="data row19 col3" >MQ.18R1.B2</td>
+                        <td id="T_0bd98_row19_col4" class="data row19 col4" >8</td>
+                        <td id="T_0bd98_row19_col5" class="data row19 col5" >2.06E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row20" class="row_heading level0 row20" >20</th>
+                        <td id="T_0bd98_row20_col0" class="data row20 col0" >B17R1_4</td>
+                        <td id="T_0bd98_row20_col1" class="data row20 col1" >DCQFQ.16R1.L</td>
+                        <td id="T_0bd98_row20_col2" class="data row20 col2" >MQ.18R1.B2</td>
+                        <td id="T_0bd98_row20_col3" class="data row20 col3" >MQ.16R1.B2</td>
+                        <td id="T_0bd98_row20_col4" class="data row20 col4" >8</td>
+                        <td id="T_0bd98_row20_col5" class="data row20 col5" >1.98E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row21" class="row_heading level0 row21" >21</th>
+                        <td id="T_0bd98_row21_col0" class="data row21 col0" >B15R1_4</td>
+                        <td id="T_0bd98_row21_col1" class="data row21 col1" >DCQFQ.14R1.L</td>
+                        <td id="T_0bd98_row21_col2" class="data row21 col2" >MQ.16R1.B2</td>
+                        <td id="T_0bd98_row21_col3" class="data row21 col3" >MQ.14R1.B2</td>
+                        <td id="T_0bd98_row21_col4" class="data row21 col4" >8</td>
+                        <td id="T_0bd98_row21_col5" class="data row21 col5" >4.52E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row22" class="row_heading level0 row22" >22</th>
+                        <td id="T_0bd98_row22_col0" class="data row22 col0" >B13R1_4</td>
+                        <td id="T_0bd98_row22_col1" class="data row22 col1" >DCQFQ.12R1.L</td>
+                        <td id="T_0bd98_row22_col2" class="data row22 col2" >MQ.14R1.B2</td>
+                        <td id="T_0bd98_row22_col3" class="data row22 col3" >MQ.12R1.B2</td>
+                        <td id="T_0bd98_row22_col4" class="data row22 col4" >8</td>
+                        <td id="T_0bd98_row22_col5" class="data row22 col5" >5.78E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row23" class="row_heading level0 row23" >23</th>
+                        <td id="T_0bd98_row23_col0" class="data row23 col0" >B11R1_4</td>
+                        <td id="T_0bd98_row23_col1" class="data row23 col1" >DCQFE.11R1.L</td>
+                        <td id="T_0bd98_row23_col2" class="data row23 col2" >MQ.12R1.B2</td>
+                        <td id="T_0bd98_row23_col3" class="data row23 col3" >MQ.11R1.B1</td>
+                        <td id="T_0bd98_row23_col4" class="data row23 col4" >6</td>
+                        <td id="T_0bd98_row23_col5" class="data row23 col5" >3.43E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row24" class="row_heading level0 row24" >24</th>
+                        <td id="T_0bd98_row24_col0" class="data row24 col0" >B12R1_4</td>
+                        <td id="T_0bd98_row24_col1" class="data row24 col1" >DCQFB.C13R1.R</td>
+                        <td id="T_0bd98_row24_col2" class="data row24 col2" >MQ.11R1.B1</td>
+                        <td id="T_0bd98_row24_col3" class="data row24 col3" >MQ.13R1.B1</td>
+                        <td id="T_0bd98_row24_col4" class="data row24 col4" >8</td>
+                        <td id="T_0bd98_row24_col5" class="data row24 col5" >3.38E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row25" class="row_heading level0 row25" >25</th>
+                        <td id="T_0bd98_row25_col0" class="data row25 col0" >B14R1_4</td>
+                        <td id="T_0bd98_row25_col1" class="data row25 col1" >DCQFB.A15R1.R</td>
+                        <td id="T_0bd98_row25_col2" class="data row25 col2" >MQ.13R1.B1</td>
+                        <td id="T_0bd98_row25_col3" class="data row25 col3" >MQ.15R1.B1</td>
+                        <td id="T_0bd98_row25_col4" class="data row25 col4" >8</td>
+                        <td id="T_0bd98_row25_col5" class="data row25 col5" >1.55E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row26" class="row_heading level0 row26" >26</th>
+                        <td id="T_0bd98_row26_col0" class="data row26 col0" >B16R1_4</td>
+                        <td id="T_0bd98_row26_col1" class="data row26 col1" >DCQFB.C17R1.R</td>
+                        <td id="T_0bd98_row26_col2" class="data row26 col2" >MQ.15R1.B1</td>
+                        <td id="T_0bd98_row26_col3" class="data row26 col3" >MQ.17R1.B1</td>
+                        <td id="T_0bd98_row26_col4" class="data row26 col4" >8</td>
+                        <td id="T_0bd98_row26_col5" class="data row26 col5" >6.20E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row27" class="row_heading level0 row27" >27</th>
+                        <td id="T_0bd98_row27_col0" class="data row27 col0" >B18R1_4</td>
+                        <td id="T_0bd98_row27_col1" class="data row27 col1" >DCQFB.C19R1.R</td>
+                        <td id="T_0bd98_row27_col2" class="data row27 col2" >MQ.17R1.B1</td>
+                        <td id="T_0bd98_row27_col3" class="data row27 col3" >MQ.19R1.B1</td>
+                        <td id="T_0bd98_row27_col4" class="data row27 col4" >8</td>
+                        <td id="T_0bd98_row27_col5" class="data row27 col5" >1.28E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row28" class="row_heading level0 row28" >28</th>
+                        <td id="T_0bd98_row28_col0" class="data row28 col0" >B20R1_4</td>
+                        <td id="T_0bd98_row28_col1" class="data row28 col1" >DCQFB.C21R1.R</td>
+                        <td id="T_0bd98_row28_col2" class="data row28 col2" >MQ.19R1.B1</td>
+                        <td id="T_0bd98_row28_col3" class="data row28 col3" >MQ.21R1.B1</td>
+                        <td id="T_0bd98_row28_col4" class="data row28 col4" >8</td>
+                        <td id="T_0bd98_row28_col5" class="data row28 col5" >5.69E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row29" class="row_heading level0 row29" >29</th>
+                        <td id="T_0bd98_row29_col0" class="data row29 col0" >B22R1_4</td>
+                        <td id="T_0bd98_row29_col1" class="data row29 col1" >DCQFB.C23R1.R</td>
+                        <td id="T_0bd98_row29_col2" class="data row29 col2" >MQ.21R1.B1</td>
+                        <td id="T_0bd98_row29_col3" class="data row29 col3" >MQ.23R1.B1</td>
+                        <td id="T_0bd98_row29_col4" class="data row29 col4" >8</td>
+                        <td id="T_0bd98_row29_col5" class="data row29 col5" >4.83E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row30" class="row_heading level0 row30" >30</th>
+                        <td id="T_0bd98_row30_col0" class="data row30 col0" >B24R1_4</td>
+                        <td id="T_0bd98_row30_col1" class="data row30 col1" >DCQFB.C25R1.R</td>
+                        <td id="T_0bd98_row30_col2" class="data row30 col2" >MQ.23R1.B1</td>
+                        <td id="T_0bd98_row30_col3" class="data row30 col3" >MQ.25R1.B1</td>
+                        <td id="T_0bd98_row30_col4" class="data row30 col4" >8</td>
+                        <td id="T_0bd98_row30_col5" class="data row30 col5" >1.65E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row31" class="row_heading level0 row31" >31</th>
+                        <td id="T_0bd98_row31_col0" class="data row31 col0" >B26R1_4</td>
+                        <td id="T_0bd98_row31_col1" class="data row31 col1" >DCQFB.C27R1.R</td>
+                        <td id="T_0bd98_row31_col2" class="data row31 col2" >MQ.25R1.B1</td>
+                        <td id="T_0bd98_row31_col3" class="data row31 col3" >MQ.27R1.B1</td>
+                        <td id="T_0bd98_row31_col4" class="data row31 col4" >8</td>
+                        <td id="T_0bd98_row31_col5" class="data row31 col5" >5.02E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row32" class="row_heading level0 row32" >32</th>
+                        <td id="T_0bd98_row32_col0" class="data row32 col0" >B28R1_4</td>
+                        <td id="T_0bd98_row32_col1" class="data row32 col1" >DCQFB.C29R1.R</td>
+                        <td id="T_0bd98_row32_col2" class="data row32 col2" >MQ.27R1.B1</td>
+                        <td id="T_0bd98_row32_col3" class="data row32 col3" >MQ.29R1.B1</td>
+                        <td id="T_0bd98_row32_col4" class="data row32 col4" >8</td>
+                        <td id="T_0bd98_row32_col5" class="data row32 col5" >4.72E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row33" class="row_heading level0 row33" >33</th>
+                        <td id="T_0bd98_row33_col0" class="data row33 col0" >B30R1_4</td>
+                        <td id="T_0bd98_row33_col1" class="data row33 col1" >DCQFB.C31R1.R</td>
+                        <td id="T_0bd98_row33_col2" class="data row33 col2" >MQ.29R1.B1</td>
+                        <td id="T_0bd98_row33_col3" class="data row33 col3" >MQ.31R1.B1</td>
+                        <td id="T_0bd98_row33_col4" class="data row33 col4" >8</td>
+                        <td id="T_0bd98_row33_col5" class="data row33 col5" >3.49E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row34" class="row_heading level0 row34" >34</th>
+                        <td id="T_0bd98_row34_col0" class="data row34 col0" >B32R1_4</td>
+                        <td id="T_0bd98_row34_col1" class="data row34 col1" >DCQFB.C33R1.R</td>
+                        <td id="T_0bd98_row34_col2" class="data row34 col2" >MQ.31R1.B1</td>
+                        <td id="T_0bd98_row34_col3" class="data row34 col3" >MQ.33R1.B1</td>
+                        <td id="T_0bd98_row34_col4" class="data row34 col4" >8</td>
+                        <td id="T_0bd98_row34_col5" class="data row34 col5" >5.88E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row35" class="row_heading level0 row35" >35</th>
+                        <td id="T_0bd98_row35_col0" class="data row35 col0" >B34R1_4</td>
+                        <td id="T_0bd98_row35_col1" class="data row35 col1" >DCQFB.A34L2.R</td>
+                        <td id="T_0bd98_row35_col2" class="data row35 col2" >MQ.33R1.B1</td>
+                        <td id="T_0bd98_row35_col3" class="data row35 col3" >MQ.33L2.B1</td>
+                        <td id="T_0bd98_row35_col4" class="data row35 col4" >8</td>
+                        <td id="T_0bd98_row35_col5" class="data row35 col5" >2.44E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row36" class="row_heading level0 row36" >36</th>
+                        <td id="T_0bd98_row36_col0" class="data row36 col0" >B33L2_4</td>
+                        <td id="T_0bd98_row36_col1" class="data row36 col1" >DCQFQ.34R1.L</td>
+                        <td id="T_0bd98_row36_col2" class="data row36 col2" >MQ.32L2.B2</td>
+                        <td id="T_0bd98_row36_col3" class="data row36 col3" >MQ.34R1.B2</td>
+                        <td id="T_0bd98_row36_col4" class="data row36 col4" >8</td>
+                        <td id="T_0bd98_row36_col5" class="data row36 col5" >3.77E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row37" class="row_heading level0 row37" >37</th>
+                        <td id="T_0bd98_row37_col0" class="data row37 col0" >B31L2_4</td>
+                        <td id="T_0bd98_row37_col1" class="data row37 col1" >DCQFQ.32L2.L</td>
+                        <td id="T_0bd98_row37_col2" class="data row37 col2" >MQ.30L2.B2</td>
+                        <td id="T_0bd98_row37_col3" class="data row37 col3" >MQ.32L2.B2</td>
+                        <td id="T_0bd98_row37_col4" class="data row37 col4" >8</td>
+                        <td id="T_0bd98_row37_col5" class="data row37 col5" >1.31E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row38" class="row_heading level0 row38" >38</th>
+                        <td id="T_0bd98_row38_col0" class="data row38 col0" >B29L2_4</td>
+                        <td id="T_0bd98_row38_col1" class="data row38 col1" >DCQFQ.30L2.L</td>
+                        <td id="T_0bd98_row38_col2" class="data row38 col2" >MQ.28L2.B2</td>
+                        <td id="T_0bd98_row38_col3" class="data row38 col3" >MQ.30L2.B2</td>
+                        <td id="T_0bd98_row38_col4" class="data row38 col4" >8</td>
+                        <td id="T_0bd98_row38_col5" class="data row38 col5" >2.13E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row39" class="row_heading level0 row39" >39</th>
+                        <td id="T_0bd98_row39_col0" class="data row39 col0" >B27L2_4</td>
+                        <td id="T_0bd98_row39_col1" class="data row39 col1" >DCQFQ.28L2.L</td>
+                        <td id="T_0bd98_row39_col2" class="data row39 col2" >MQ.26L2.B2</td>
+                        <td id="T_0bd98_row39_col3" class="data row39 col3" >MQ.28L2.B2</td>
+                        <td id="T_0bd98_row39_col4" class="data row39 col4" >8</td>
+                        <td id="T_0bd98_row39_col5" class="data row39 col5" >1.97E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row40" class="row_heading level0 row40" >40</th>
+                        <td id="T_0bd98_row40_col0" class="data row40 col0" >B25L2_4</td>
+                        <td id="T_0bd98_row40_col1" class="data row40 col1" >DCQFQ.26L2.L</td>
+                        <td id="T_0bd98_row40_col2" class="data row40 col2" >MQ.24L2.B2</td>
+                        <td id="T_0bd98_row40_col3" class="data row40 col3" >MQ.26L2.B2</td>
+                        <td id="T_0bd98_row40_col4" class="data row40 col4" >8</td>
+                        <td id="T_0bd98_row40_col5" class="data row40 col5" >4.47E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row41" class="row_heading level0 row41" >41</th>
+                        <td id="T_0bd98_row41_col0" class="data row41 col0" >B23L2_4</td>
+                        <td id="T_0bd98_row41_col1" class="data row41 col1" >DCQFQ.24L2.L</td>
+                        <td id="T_0bd98_row41_col2" class="data row41 col2" >MQ.22L2.B2</td>
+                        <td id="T_0bd98_row41_col3" class="data row41 col3" >MQ.24L2.B2</td>
+                        <td id="T_0bd98_row41_col4" class="data row41 col4" >8</td>
+                        <td id="T_0bd98_row41_col5" class="data row41 col5" >4.78E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row42" class="row_heading level0 row42" >42</th>
+                        <td id="T_0bd98_row42_col0" class="data row42 col0" >B21L2_4</td>
+                        <td id="T_0bd98_row42_col1" class="data row42 col1" >DCQFQ.22L2.L</td>
+                        <td id="T_0bd98_row42_col2" class="data row42 col2" >MQ.20L2.B2</td>
+                        <td id="T_0bd98_row42_col3" class="data row42 col3" >MQ.22L2.B2</td>
+                        <td id="T_0bd98_row42_col4" class="data row42 col4" >8</td>
+                        <td id="T_0bd98_row42_col5" class="data row42 col5" >1.06E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row43" class="row_heading level0 row43" >43</th>
+                        <td id="T_0bd98_row43_col0" class="data row43 col0" >B19L2_4</td>
+                        <td id="T_0bd98_row43_col1" class="data row43 col1" >DCQFQ.20L2.L</td>
+                        <td id="T_0bd98_row43_col2" class="data row43 col2" >MQ.18L2.B2</td>
+                        <td id="T_0bd98_row43_col3" class="data row43 col3" >MQ.20L2.B2</td>
+                        <td id="T_0bd98_row43_col4" class="data row43 col4" >8</td>
+                        <td id="T_0bd98_row43_col5" class="data row43 col5" >2.66E-10</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row44" class="row_heading level0 row44" >44</th>
+                        <td id="T_0bd98_row44_col0" class="data row44 col0" >B17L2_4</td>
+                        <td id="T_0bd98_row44_col1" class="data row44 col1" >DCQFQ.18L2.L</td>
+                        <td id="T_0bd98_row44_col2" class="data row44 col2" >MQ.16L2.B2</td>
+                        <td id="T_0bd98_row44_col3" class="data row44 col3" >MQ.18L2.B2</td>
+                        <td id="T_0bd98_row44_col4" class="data row44 col4" >8</td>
+                        <td id="T_0bd98_row44_col5" class="data row44 col5" >2.13E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row45" class="row_heading level0 row45" >45</th>
+                        <td id="T_0bd98_row45_col0" class="data row45 col0" >B15L2_4</td>
+                        <td id="T_0bd98_row45_col1" class="data row45 col1" >DCQFQ.16L2.L</td>
+                        <td id="T_0bd98_row45_col2" class="data row45 col2" >MQ.14L2.B2</td>
+                        <td id="T_0bd98_row45_col3" class="data row45 col3" >MQ.16L2.B2</td>
+                        <td id="T_0bd98_row45_col4" class="data row45 col4" >8</td>
+                        <td id="T_0bd98_row45_col5" class="data row45 col5" >2.88E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row46" class="row_heading level0 row46" >46</th>
+                        <td id="T_0bd98_row46_col0" class="data row46 col0" >B13L2_4</td>
+                        <td id="T_0bd98_row46_col1" class="data row46 col1" >DCQFQ.14L2.L</td>
+                        <td id="T_0bd98_row46_col2" class="data row46 col2" >MQ.12L2.B2</td>
+                        <td id="T_0bd98_row46_col3" class="data row46 col3" >MQ.14L2.B2</td>
+                        <td id="T_0bd98_row46_col4" class="data row46 col4" >8</td>
+                        <td id="T_0bd98_row46_col5" class="data row46 col5" >2.86E-09</td>
+            </tr>
+            <tr>
+                        <th id="T_0bd98_level0_row47" class="row_heading level0 row47" >47</th>
+                        <td id="T_0bd98_row47_col0" class="data row47 col0" >B11L2_4</td>
+                        <td id="T_0bd98_row47_col1" class="data row47 col1" >DCQFQ.12L2.L</td>
+                        <td id="T_0bd98_row47_col2" class="data row47 col2" >DFLAS.7L2.3</td>
+                        <td id="T_0bd98_row47_col3" class="data row47 col3" >MQ.12L2.B2</td>
+                        <td id="T_0bd98_row47_col4" class="data row47 col4" >20</td>
+                        <td id="T_0bd98_row47_col5" class="data row47 col5" >2.36E-09</td>
+            </tr>
+    </tbody></table>
+</div>
+
+</div>
+
+</div>
+</div>
+
 </div>
 <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
 </div><div class="inner_cell">
@@ -14321,7 +16293,7 @@ Maximum U_DUMP_RES_RQF (70.0 V) is within of the 10% reference voltage [63.5, 77
 
 
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
 "
 >
 </div>
diff --git a/test/resources/reports/AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv b/test/resources/reports/AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv
new file mode 100644
index 00000000..5aa4c5be
--- /dev/null
+++ b/test/resources/reports/AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv
@@ -0,0 +1,49 @@
+,R_RES,nxcals_variable_name
+0,5.005406409696642e-09,DCQDD.7L2.L:U_RES
+1,2.7190890040233706e-09,DCQDB.A12L2.L:U_RES
+2,2.473160729760327e-09,DCQDB.A14L2.L:U_RES
+3,2.3981555559034203e-09,DCQDB.A16L2.L:U_RES
+4,2.2697455167033935e-09,DCQDB.A18L2.L:U_RES
+5,2.460182634942789e-09,DCQDB.A20L2.L:U_RES
+6,3.196136403513823e-09,DCQDB.A22L2.L:U_RES
+7,2.7750530967214535e-09,DCQDB.A24L2.L:U_RES
+8,3.2274744941949077e-09,DCQDB.A26L2.L:U_RES
+9,2.610298869937421e-09,DCQDB.A28L2.L:U_RES
+10,2.353965816348502e-09,DCQDB.A30L2.L:U_RES
+11,2.5866915409589816e-09,DCQDB.A32L2.L:U_RES
+12,2.9298850055011185e-09,DCQDQ.32R1.R:U_RES
+13,2.5400236222810883e-09,DCQDQ.30R1.R:U_RES
+14,2.4760058972514008e-09,DCQDQ.28R1.R:U_RES
+15,2.8931415156008777e-09,DCQDQ.26R1.R:U_RES
+16,2.9513191392706223e-09,DCQDQ.24R1.R:U_RES
+17,3.585721070162732e-09,DCQDQ.22R1.R:U_RES
+18,2.4051620248057708e-09,DCQDQ.20R1.R:U_RES
+19,3.6005225050591783e-09,DCQDQ.18R1.R:U_RES
+20,2.204857555179589e-09,DCQDQ.16R1.R:U_RES
+21,2.6181424039429464e-09,DCQDQ.14R1.R:U_RES
+22,2.9336755061061773e-09,DCQDQ.12R1.R:U_RES
+23,1.9031555009254833e-09,DCQDE.11R1.R:U_RES
+24,2.558099391771824e-09,DCQDB.C13R1.L:U_RES
+25,2.516593994458455e-09,DCQDB.C15R1.L:U_RES
+26,2.7689733909149604e-09,DCQDB.C17R1.L:U_RES
+27,3.0263049477087892e-09,DCQDB.C19R1.L:U_RES
+28,3.460165683276628e-09,DCQDB.C21R1.L:U_RES
+29,2.6523330707195374e-09,DCQDB.C23R1.L:U_RES
+30,3.0017438744118006e-09,DCQDB.C25R1.L:U_RES
+31,2.7415234500227612e-09,DCQDB.C27R1.L:U_RES
+32,2.8684548784159936e-09,DCQDB.C29R1.L:U_RES
+33,2.6469465190176544e-09,DCQDB.C31R1.L:U_RES
+34,2.737704846135209e-09,DCQDB.C33R1.L:U_RES
+35,2.9183994238275554e-09,DCQDB.A34L2.L:U_RES
+36,2.8088102799422925e-09,DCQDQ.34R1.R:U_RES
+37,2.923303133284713e-09,DCQDQ.32L2.R:U_RES
+38,2.960873271201226e-09,DCQDQ.30L2.R:U_RES
+39,2.496928176087152e-09,DCQDQ.28L2.R:U_RES
+40,2.4728454221338307e-09,DCQDQ.26L2.R:U_RES
+41,3.1814144277189702e-09,DCQDQ.24L2.R:U_RES
+42,2.813820377151309e-09,DCQDQ.22L2.R:U_RES
+43,2.9403588161157018e-09,DCQDQ.20L2.R:U_RES
+44,2.839858301008204e-09,DCQDQ.18L2.R:U_RES
+45,2.469498308102411e-09,DCQDQ.16L2.R:U_RES
+46,2.5569301424443232e-09,DCQDQ.14L2.R:U_RES
+47,5.9505745233000705e-09,DCQDQ.12L2.R:U_RES
diff --git a/test/resources/reports/AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv b/test/resources/reports/AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv
new file mode 100644
index 00000000..c06df97b
--- /dev/null
+++ b/test/resources/reports/AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv
@@ -0,0 +1,49 @@
+,R_MAG,nxcals_variable_name
+0,7.517435817352054e-09,DCQDD.7L2.L:U_MAG
+1,4.648965480100468e-09,DCQDB.A12L2.L:U_MAG
+2,3.127474626550427e-09,DCQDB.A14L2.L:U_MAG
+3,9.906245097217475e-10,DCQDB.A16L2.L:U_MAG
+4,2.363560986012841e-09,DCQDB.A18L2.L:U_MAG
+5,7.953164280952839e-10,DCQDB.A20L2.L:U_MAG
+6,8.597952173850168e-10,DCQDB.A22L2.L:U_MAG
+7,1.6736161498384505e-09,DCQDB.A24L2.L:U_MAG
+8,7.91942909327516e-09,DCQDB.A26L2.L:U_MAG
+9,1.0749073322166617e-09,DCQDB.A28L2.L:U_MAG
+10,1.5774009165672596e-08,DCQDB.A30L2.L:U_MAG
+11,9.739326631146066e-10,DCQDB.A32L2.L:U_MAG
+12,1.0339541097246728e-09,DCQDQ.32R1.R:U_MAG
+13,4.1369144159171066e-09,DCQDQ.30R1.R:U_MAG
+14,4.908116253360012e-09,DCQDQ.28R1.R:U_MAG
+15,4.5174778350362375e-09,DCQDQ.26R1.R:U_MAG
+16,4.560739023230201e-09,DCQDQ.24R1.R:U_MAG
+17,1.7966294030117578e-09,DCQDQ.22R1.R:U_MAG
+18,8.040896006043584e-09,DCQDQ.20R1.R:U_MAG
+19,1.5445566628172354e-09,DCQDQ.18R1.R:U_MAG
+20,2.437684804177365e-09,DCQDQ.16R1.R:U_MAG
+21,5.373051372455636e-09,DCQDQ.14R1.R:U_MAG
+22,5.243265395447448e-09,DCQDQ.12R1.R:U_MAG
+23,1.1170640513883744e-09,DCQDE.11R1.R:U_MAG
+24,1.2956271332443753e-09,DCQDB.C13R1.L:U_MAG
+25,2.2320838940595565e-09,DCQDB.C15R1.L:U_MAG
+26,2.4359093028518804e-09,DCQDB.C17R1.L:U_MAG
+27,2.8794360925700047e-10,DCQDB.C19R1.L:U_MAG
+28,5.829174726710127e-09,DCQDB.C21R1.L:U_MAG
+29,3.9717339394211445e-09,DCQDB.C23R1.L:U_MAG
+30,2.7976866150734706e-09,DCQDB.C25R1.L:U_MAG
+31,2.9387179062067085e-09,DCQDB.C27R1.L:U_MAG
+32,4.1380647226757366e-09,DCQDB.C29R1.L:U_MAG
+33,6.631900806346967e-10,DCQDB.C31R1.L:U_MAG
+34,8.694486718481624e-10,DCQDB.C33R1.L:U_MAG
+35,2.722226173566896e-09,DCQDB.A34L2.L:U_MAG
+36,4.589217433583593e-09,DCQDQ.34R1.R:U_MAG
+37,2.531729086594775e-09,DCQDQ.32L2.R:U_MAG
+38,3.144971676180865e-09,DCQDQ.30L2.R:U_MAG
+39,1.7847301338446185e-09,DCQDQ.28L2.R:U_MAG
+40,3.7781879741755777e-10,DCQDQ.26L2.R:U_MAG
+41,1.939651118612203e-09,DCQDQ.24L2.R:U_MAG
+42,8.788429466840987e-10,DCQDQ.22L2.R:U_MAG
+43,8.946262383390424e-10,DCQDQ.20L2.R:U_MAG
+44,4.095299269317697e-09,DCQDQ.18L2.R:U_MAG
+45,4.0897933531942225e-09,DCQDQ.16L2.R:U_MAG
+46,2.064560663554185e-09,DCQDQ.14L2.R:U_MAG
+47,6.833734110006704e-09,DCQDQ.12L2.R:U_MAG
diff --git a/test/resources/reports/AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv b/test/resources/reports/AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv
new file mode 100644
index 00000000..ab862d4a
--- /dev/null
+++ b/test/resources/reports/AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv
@@ -0,0 +1,49 @@
+,R_RES,nxcals_variable_name
+0,5.204620666578405e-09,DCQFD.7L2.R:U_RES
+1,2.147683175105384e-09,DCQFB.A12L2.R:U_RES
+2,2.524414522910348e-09,DCQFB.A14L2.R:U_RES
+3,2.1063460781072236e-09,DCQFB.A16L2.R:U_RES
+4,2.3477719728538483e-09,DCQFB.A18L2.R:U_RES
+5,2.0623445878248667e-09,DCQFB.A20L2.R:U_RES
+6,2.3636970999562458e-09,DCQFB.A22L2.R:U_RES
+7,2.422666073097023e-09,DCQFB.A24L2.R:U_RES
+8,2.275738519457434e-09,DCQFB.A26L2.R:U_RES
+9,2.5510563578660895e-09,DCQFB.A28L2.R:U_RES
+10,2.331113883433012e-09,DCQFB.A30L2.R:U_RES
+11,2.509543034355956e-09,DCQFB.C32L2.R:U_RES
+12,2.7364182265766875e-09,DCQFQ.32R1.L:U_RES
+13,2.338469501310364e-09,DCQFQ.30R1.L:U_RES
+14,2.44083898329161e-09,DCQFQ.28R1.L:U_RES
+15,2.551194955750432e-09,DCQFQ.26R1.L:U_RES
+16,2.5956425201085464e-09,DCQFQ.24R1.L:U_RES
+17,2.7608920353676748e-09,DCQFQ.22R1.L:U_RES
+18,2.575096957821639e-09,DCQFQ.20R1.L:U_RES
+19,2.6450758816547975e-09,DCQFQ.18R1.L:U_RES
+20,2.237308622164336e-09,DCQFQ.16R1.L:U_RES
+21,2.298772463392404e-09,DCQFQ.14R1.L:U_RES
+22,2.31026844715585e-09,DCQFQ.12R1.L:U_RES
+23,2.1442454613693793e-09,DCQFE.11R1.L:U_RES
+24,2.866086568932842e-09,DCQFB.C13R1.R:U_RES
+25,2.297965354455296e-09,DCQFB.A15R1.R:U_RES
+26,2.5079322898422266e-09,DCQFB.C17R1.R:U_RES
+27,2.872602162439274e-09,DCQFB.C19R1.R:U_RES
+28,2.665964324621731e-09,DCQFB.C21R1.R:U_RES
+29,2.4130844928501265e-09,DCQFB.C23R1.R:U_RES
+30,2.780263544257242e-09,DCQFB.C25R1.R:U_RES
+31,2.6054932225609567e-09,DCQFB.C27R1.R:U_RES
+32,2.7083733471044e-09,DCQFB.C29R1.R:U_RES
+33,2.073712160280574e-09,DCQFB.C31R1.R:U_RES
+34,2.2262747772372376e-09,DCQFB.C33R1.R:U_RES
+35,2.75023470344456e-09,DCQFB.A34L2.R:U_RES
+36,2.5578782994040773e-09,DCQFQ.34R1.L:U_RES
+37,2.7268541571875055e-09,DCQFQ.32L2.L:U_RES
+38,2.302274676033614e-09,DCQFQ.30L2.L:U_RES
+39,2.420758734819853e-09,DCQFQ.28L2.L:U_RES
+40,2.1708469571122342e-09,DCQFQ.26L2.L:U_RES
+41,2.5595792112381566e-09,DCQFQ.24L2.L:U_RES
+42,2.444799961346575e-09,DCQFQ.22L2.L:U_RES
+43,2.5679951997191126e-09,DCQFQ.20L2.L:U_RES
+44,2.2944472835785272e-09,DCQFQ.18L2.L:U_RES
+45,2.37030313053357e-09,DCQFQ.16L2.L:U_RES
+46,2.278586343654509e-09,DCQFQ.14L2.L:U_RES
+47,6.213193551448753e-09,DCQFQ.12L2.L:U_RES
diff --git a/test/resources/reports/AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv b/test/resources/reports/AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv
new file mode 100644
index 00000000..000c2b87
--- /dev/null
+++ b/test/resources/reports/AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv
@@ -0,0 +1,49 @@
+,R_MAG,nxcals_variable_name
+0,1.3774461277528924e-08,DCQFD.7L2.R:U_MAG
+1,4.593104009740815e-09,DCQFB.A12L2.R:U_MAG
+2,2.3331224341132563e-09,DCQFB.A14L2.R:U_MAG
+3,2.012606382321664e-09,DCQFB.A16L2.R:U_MAG
+4,3.0515875055118433e-10,DCQFB.A18L2.R:U_MAG
+5,2.9902050771508936e-09,DCQFB.A20L2.R:U_MAG
+6,2.3213266979163673e-09,DCQFB.A22L2.R:U_MAG
+7,6.617717593300705e-09,DCQFB.A24L2.R:U_MAG
+8,7.787816629710635e-10,DCQFB.A26L2.R:U_MAG
+9,4.190377111803944e-10,DCQFB.A28L2.R:U_MAG
+10,3.5932499535494152e-09,DCQFB.A30L2.R:U_MAG
+11,2.2518627371636514e-09,DCQFB.C32L2.R:U_MAG
+12,7.039472482947111e-09,DCQFQ.32R1.L:U_MAG
+13,8.225374398304984e-09,DCQFQ.30R1.L:U_MAG
+14,1.173180909672193e-08,DCQFQ.28R1.L:U_MAG
+15,4.7377998306979644e-09,DCQFQ.26R1.L:U_MAG
+16,1.8757112594387887e-09,DCQFQ.24R1.L:U_MAG
+17,9.178491706608517e-10,DCQFQ.22R1.L:U_MAG
+18,2.317462973353226e-09,DCQFQ.20R1.L:U_MAG
+19,2.061391207347584e-09,DCQFQ.18R1.L:U_MAG
+20,1.9812603835001072e-10,DCQFQ.16R1.L:U_MAG
+21,4.517724985584574e-09,DCQFQ.14R1.L:U_MAG
+22,5.783785444504251e-10,DCQFQ.12R1.L:U_MAG
+23,3.429929392460477e-09,DCQFE.11R1.L:U_MAG
+24,3.3845571299138574e-09,DCQFB.C13R1.R:U_MAG
+25,1.552469702515567e-09,DCQFB.A15R1.R:U_MAG
+26,6.1967804640801885e-09,DCQFB.C17R1.R:U_MAG
+27,1.2766708184033831e-10,DCQFB.C19R1.R:U_MAG
+28,5.689985147693167e-09,DCQFB.C21R1.R:U_MAG
+29,4.8281171280252385e-09,DCQFB.C23R1.R:U_MAG
+30,1.6478595949009407e-09,DCQFB.C25R1.R:U_MAG
+31,5.019250860152577e-09,DCQFB.C27R1.R:U_MAG
+32,4.723701264825256e-09,DCQFB.C29R1.R:U_MAG
+33,3.4850161992574785e-09,DCQFB.C31R1.R:U_MAG
+34,5.883712516535988e-09,DCQFB.C33R1.R:U_MAG
+35,2.440368059031519e-09,DCQFB.A34L2.R:U_MAG
+36,3.772089150711774e-09,DCQFQ.34R1.L:U_MAG
+37,1.3139105236838541e-09,DCQFQ.32L2.L:U_MAG
+38,2.1298432088493994e-09,DCQFQ.30L2.L:U_MAG
+39,1.9689921697335223e-09,DCQFQ.28L2.L:U_MAG
+40,4.466960455215494e-09,DCQFQ.26L2.L:U_MAG
+41,4.777574090781143e-09,DCQFQ.24L2.L:U_MAG
+42,1.062783160149471e-09,DCQFQ.22L2.L:U_MAG
+43,2.6555345008515265e-10,DCQFQ.20L2.L:U_MAG
+44,2.134453434746134e-09,DCQFQ.18L2.L:U_MAG
+45,2.8762224868247758e-09,DCQFQ.16L2.L:U_MAG
+46,2.8624292810428466e-09,DCQFQ.14L2.L:U_MAG
+47,2.362827233048337e-09,DCQFQ.12L2.L:U_MAG
diff --git a/test/test_notebooks.py b/test/test_notebooks.py
index 92137171..cd9beafd 100644
--- a/test/test_notebooks.py
+++ b/test/test_notebooks.py
@@ -114,18 +114,12 @@ RQ_NOTEBOOKS = [
     ('rq', 'AN_RQ_PNO.a6', 'PNO.a6', 'RQD.A12', 'HWC_2017', '2017-04-26 21:32:51.083', '2017-04-27 01:54:29.036',
      ['AN_RQ_PNO.a6_RQD_BUSBAR_RESISTANCE.csv', 'AN_RQ_PNO.a6_RQF_BUSBAR_RESISTANCE.csv',
       'AN_RQ_PNO.a6_RQD_MAGNET_RESISTANCE.csv', 'AN_RQ_PNO.a6_RQF_MAGNET_RESISTANCE.csv']),
-    ('rq', 'AN_RQ_PNO.b3', 'PNO.b3', 'RQD.A12', 'HWC_2018_1', '2018-03-18 07:17:37.130', '2018-03-18 12:13:29.766',
-     []),
-]
-
-TO_TEST = [
     ('rq', 'AN_RQ_PNO.b3', 'PNO.b3', 'RQD.A12', 'HWC_2018_1', '2018-03-18 07:17:37.130', '2018-03-18 12:13:29.766',
      ['AN_RQ_PNO.b3_RQD_BUSBAR_RESISTANCE.csv', 'AN_RQ_PNO.b3_RQF_BUSBAR_RESISTANCE.csv',
       'AN_RQ_PNO.b3_RQD_MAGNET_RESISTANCE.csv', 'AN_RQ_PNO.b3_RQF_MAGNET_RESISTANCE.csv']),
-    ('rb', 'AN_RB_PNO.b2', 'PNO.b2', 'RB.A12', 'HWC_2018_1', '2018-03-17 11:34:53.954', '2018-03-17 16:06:41.537',
-     [])
 ]
 
+
 HWC_NOTEBOOKS = [nb for notebooks in [RQ_NOTEBOOKS, RB_NOTEBOOKS, NQPS_NOTEBOOKS, IT_NOTEBOOKS,
                                       IPQ_NOTEBOOKS, IPD_NOTEBOOKS, PGC_NOTEBOOKS] for nb in notebooks]
 
@@ -174,7 +168,7 @@ def setup():
     os.environ[lhcsmapi.nb_version_env] = version
 
 
-@pytest.mark.parametrize('directory,notebook,hwc_test,circuit_name,campaign,t_start,t_end,csv_files', TO_TEST)
+@pytest.mark.parametrize('directory,notebook,hwc_test,circuit_name,campaign,t_start,t_end,csv_files', HWC_NOTEBOOKS)
 def test_hwc_notebook(directory, notebook, hwc_test, circuit_name, campaign, t_start, t_end, csv_files):
     _test_notebook(directory,
                    notebook,
@@ -189,58 +183,58 @@ def test_hwc_notebook(directory, notebook, hwc_test, circuit_name, campaign, t_s
                    csv_files)
 
 
-# @pytest.mark.parametrize('directory,notebook,circuit_name,timestamp_fgc,csv_files', FGC_SEARCH_NOTEBOOKS)
-# def test_fgc_search_notebook(directory, notebook, circuit_name, timestamp_fgc, csv_files):
-#     _test_notebook(directory,
-#                    notebook,
-#                    {
-#                        'circuit_name': circuit_name,
-#                        'timestamp_fgc': timestamp_fgc,
-#                        'author': 'test',
-#                        'is_automatic': True
-#                    },
-#                    csv_files)
-#
-#
-# @pytest.mark.parametrize('directory,notebook,circuit_type,circuit_names,timestamps_fgc,csv_files',
-#                          FGC_2_SEARCH_NOTEBOOKS)
-# def test_fgc_2_search_notebook(directory, notebook, circuit_type, circuit_names, timestamps_fgc, csv_files):
-#     _test_notebook(directory,
-#                    notebook,
-#                    {
-#                        'circuit_type': circuit_type,
-#                        'circuit_names': circuit_names,
-#                        'timestamps_fgc': timestamps_fgc,
-#                        'author': 'test',
-#                        'is_automatic': True
-#                    },
-#                    csv_files)
-#
-#
-# @pytest.mark.parametrize('directory,notebook,circuit_name,discharge_level,start_time,end_time,csv_files', QH_NOTEBOOKS)
-# def test_qh_search_notebook(directory, notebook, circuit_name, discharge_level, start_time, end_time, csv_files):
-#     _test_notebook(directory,
-#                    notebook,
-#                    {
-#                        'circuit_name': circuit_name,
-#                        'discharge_level': discharge_level,
-#                        'start_time': start_time,
-#                        'end_time': end_time,
-#                        'is_automatic': True
-#                    },
-#                    csv_files)
-#
-#
-# @pytest.mark.parametrize('directory,notebook,start_time,stop_time,csv_files', QHD_PM_LIST)
-# def test_qh_list_notebook(directory, notebook, start_time, stop_time, csv_files):
-#     _test_notebook(directory,
-#                    notebook,
-#                    {
-#                        'start_time': start_time,
-#                        'stop_time': stop_time,
-#                        'initial_charge_check': True
-#                    },
-#                    csv_files)
+@pytest.mark.parametrize('directory,notebook,circuit_name,timestamp_fgc,csv_files', FGC_SEARCH_NOTEBOOKS)
+def test_fgc_search_notebook(directory, notebook, circuit_name, timestamp_fgc, csv_files):
+    _test_notebook(directory,
+                   notebook,
+                   {
+                       'circuit_name': circuit_name,
+                       'timestamp_fgc': timestamp_fgc,
+                       'author': 'test',
+                       'is_automatic': True
+                   },
+                   csv_files)
+
+
+@pytest.mark.parametrize('directory,notebook,circuit_type,circuit_names,timestamps_fgc,csv_files',
+                         FGC_2_SEARCH_NOTEBOOKS)
+def test_fgc_2_search_notebook(directory, notebook, circuit_type, circuit_names, timestamps_fgc, csv_files):
+    _test_notebook(directory,
+                   notebook,
+                   {
+                       'circuit_type': circuit_type,
+                       'circuit_names': circuit_names,
+                       'timestamps_fgc': timestamps_fgc,
+                       'author': 'test',
+                       'is_automatic': True
+                   },
+                   csv_files)
+
+
+@pytest.mark.parametrize('directory,notebook,circuit_name,discharge_level,start_time,end_time,csv_files', QH_NOTEBOOKS)
+def test_qh_search_notebook(directory, notebook, circuit_name, discharge_level, start_time, end_time, csv_files):
+    _test_notebook(directory,
+                   notebook,
+                   {
+                       'circuit_name': circuit_name,
+                       'discharge_level': discharge_level,
+                       'start_time': start_time,
+                       'end_time': end_time,
+                       'is_automatic': True
+                   },
+                   csv_files)
+
+
+@pytest.mark.parametrize('directory,notebook,start_time,stop_time,csv_files', QHD_PM_LIST)
+def test_qh_list_notebook(directory, notebook, start_time, stop_time, csv_files):
+    _test_notebook(directory,
+                   notebook,
+                   {
+                       'start_time': start_time,
+                       'stop_time': stop_time,
+                       'initial_charge_check': True
+                   },
+                   csv_files)
 
 
 def _test_notebook(directory, notebook_name, notebook_parameters, csv_files):
-- 
GitLab


From cb34b62e7b5cc3013f6caa0174a024634283ff33 Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Wed, 23 Feb 2022 10:03:15 +0100
Subject: [PATCH 41/44] version bump + release notes

---
 RELEASE.md  | 6 ++++++
 __init__.py | 2 +-
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/RELEASE.md b/RELEASE.md
index 3e4856a1..1deecafd 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -1,6 +1,12 @@
 RELEASE NOTES
 =============
 
+Version: 1.5.68
+- Fixes and improvements in AN_RQ_PNO.b3 and AN_RB_PNO.b2: [SIGMON-315](https://its.cern.ch/jira/browse/SIGMON-315)
+- HWC_QHD_PM_LIST_CCC supports empty buffers: [SIGMON-257](https://its.cern.ch/jira/browse/SIGMON-257)
+- Certain plots synchronized to PIC in RB_PLI3.d2: [SIGMON-308](https://its.cern.ch/jira/browse/SIGMON-308)
+- 600A_FPA uses proper metadata  (valid at the time of FGC): [SIGMON-309](https://its.cern.ch/jira/browse/SIGMON-309)
+
 Version: 1.5.67
 - new HWC_QHDA_PM_LIST_CCC notebook [SIGMON-233](https://its.cern.ch/jira/browse/SIGMON-233), [SIGMON-224](https://its.cern.ch/jira/browse/SIGMON-224), [SIGMON-272](https://its.cern.ch/jira/browse/SIGMON-272), [SIGMON-255](https://its.cern.ch/jira/browse/SIGMON-255)
 - Statistics for PM and Nxcals nQPS in AN_RB_FPA: [SIGMON-249](https://its.cern.ch/jira/browse/SIGMON-249)
diff --git a/__init__.py b/__init__.py
index df371940..8821faa7 100644
--- a/__init__.py
+++ b/__init__.py
@@ -1 +1 @@
-__version__ = "1.5.67"
+__version__ = "1.5.68"
-- 
GitLab


From c4d2651b4410a6fe793406ffd2587f00e04d7e58 Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Wed, 23 Feb 2022 11:50:59 +0100
Subject: [PATCH 42/44] version updated in reference csvs

---
 test/resources/reports/AN_600A_FPA.csv        |  2 +-
 test/resources/reports/AN_600A_RCBXHV_FPA.csv |  2 +-
 test/resources/reports/AN_600A_RCDO_FPA.csv   |  2 +-
 test/resources/reports/AN_60A_FPA.csv         |  2 +-
 test/resources/reports/AN_80-120A_FPA.csv     |  2 +-
 test/resources/reports/AN_IPD_FPA.csv         |  2 +-
 test/resources/reports/AN_IPD_PLI2.f2.csv     |  2 +-
 test/resources/reports/AN_IPQ_FPA.csv         |  2 +-
 test/resources/reports/AN_IPQ_PLI2.f3.csv     |  2 +-
 test/resources/reports/AN_IT_FPA.csv          |  2 +-
 test/resources/reports/AN_IT_PLI3.f6.csv      |  2 +-
 test/resources/reports/AN_RB_FPA.csv          | 16 ++++++++--------
 test/resources/reports/AN_RB_PLI2.f1.csv      |  2 +-
 test/resources/reports/AN_RQ_FPA.csv          |  2 +-
 test/resources/reports/AN_RQ_PLI2.f1.csv      |  2 +-
 15 files changed, 22 insertions(+), 22 deletions(-)

diff --git a/test/resources/reports/AN_600A_FPA.csv b/test/resources/reports/AN_600A_FPA.csv
index 4b8a20fd..ef1127c7 100644
--- a/test/resources/reports/AN_600A_FPA.csv
+++ b/test/resources/reports/AN_600A_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Delta_t(EE-PIC),Ramp rate,Plateau duration,I_Q_circ,MIITS_circ,I_Earth_max,EE analysis,U_EE_max,Delta_t(QPS-PIC),Type of Quench,Quench count,QDS trigger origin,dU_QPS/dt,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RQS.R8B2,RQS,HWC 2021,2021-04-28,18:50:57.780,,2021-04-28 18:50:57.764,16.0,,1.4,0,228.9,0.00304,-10.192871,No EE,,5.0,,,,-31.374847874999972,,test,1.5.19,1.5.67
+RQS.R8B2,RQS,HWC 2021,2021-04-28,18:50:57.780,,2021-04-28 18:50:57.764,16.0,,1.4,0,228.9,0.00304,-10.192871,No EE,,5.0,,,,-31.374847874999972,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_600A_RCBXHV_FPA.csv b/test/resources/reports/AN_600A_RCBXHV_FPA.csv
index 5597676c..f67114d3 100644
--- a/test/resources/reports/AN_600A_RCBXHV_FPA.csv
+++ b/test/resources/reports/AN_600A_RCBXHV_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Ramp rate H,Ramp rate V,Plateau duration H,Plateau duration V,I_Q_H,I_Q_V,I_radius,phase,MIITS_H,MIITS_V,I_Earth_max_H,I_Earth_max_V,Delta_t(QPS-PIC),Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_QPS/dt_H,dU_QPS/dt_V,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RCBX2.L5,RCBX,HWC 2021,2021-01-28,08:21:40.800,,1970-01-01 01:00:00,1611818500800.0,,0,,30.38,,-0.0,0.0,,,0.0,,-0.061035,0.0,,,,,,,,test,1.5.19,1.5.67
+RCBX2.L5,RCBX,HWC 2021,2021-01-28,08:21:40.800,,1970-01-01 01:00:00,1611818500800.0,,0,,30.38,,-0.0,0.0,,,0.0,,-0.061035,0.0,,,,,,,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_600A_RCDO_FPA.csv b/test/resources/reports/AN_600A_RCDO_FPA.csv
index 08418583..f06f55f0 100644
--- a/test/resources/reports/AN_600A_RCDO_FPA.csv
+++ b/test/resources/reports/AN_600A_RCDO_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Delta_t(EE_RCD-PIC),Ramp rate RCO,Ramp rate RCD,Plateau duration RCO,Plateau duration RCD,I_Q_RCO,I_Q_RCD,MIITS_RCO,MIITS_RCD,I_Earth_max_RCO,I_Earth_max_RCD,EE_RCD analysis,U_EE_RCD_max,Delta_t(QPS-PIC),Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_QPS/dt_RCO,dU_QPS/dt_RCD,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RCD-RCO.A45B2,RCD-RCO,HWC 2021,2021-01-28,15:55:23.720,,2021-01-28 15:55:23.710,10.0,-1611845723710.0,0,,3.1,,-58.0,,3e-05,,6.298828,,,,3.0,,,,,-62.810797924999996,,,test,1.5.19,1.5.67
+RCD-RCO.A45B2,RCD-RCO,HWC 2021,2021-01-28,15:55:23.720,,2021-01-28 15:55:23.710,10.0,-1611845723710.0,0,,3.1,,-58.0,,3e-05,,6.298828,,,,3.0,,,,,-62.810797924999996,,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_60A_FPA.csv b/test/resources/reports/AN_60A_FPA.csv
index 9dfe9766..cd15a60b 100644
--- a/test/resources/reports/AN_60A_FPA.csv
+++ b/test/resources/reports/AN_60A_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Ramp rate,Plateau duration,I_Q_circ,MIITS_circ,I_Earth_max,Type of Quench,Quench count,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RCBH11.L8B1,RCBH,HWC 2021,2021-01-27,20:30:44.600,,0,359.98,0.0,0.0,-0.762939,,,,test,1.5.19,1.5.67
+RCBH11.L8B1,RCBH,HWC 2021,2021-01-27,20:30:44.600,,0,359.98,0.0,0.0,-0.762939,,,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_80-120A_FPA.csv b/test/resources/reports/AN_80-120A_FPA.csv
index e1619002..05537e1a 100644
--- a/test/resources/reports/AN_80-120A_FPA.csv
+++ b/test/resources/reports/AN_80-120A_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Ramp rate,Plateau duration,I_Q_circ,MIITS_circ,I_Earth_max,Type of Quench,Quench count,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RCBCH5.L5B2,RCBCH,HWC 2021,2021-01-26,17:44:10.120,,0,359.98,0.0,,-0.781246,,,,test,1.5.19,1.5.67
+RCBCH5.L5B2,RCBCH,HWC 2021,2021-01-26,17:44:10.120,,0,359.98,0.0,,-0.781246,,,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_IPD_FPA.csv b/test/resources/reports/AN_IPD_FPA.csv
index 09a2cb9e..baa36eae 100644
--- a/test/resources/reports/AN_IPD_FPA.csv
+++ b/test/resources/reports/AN_IPD_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Ramp rate,Plateau duration,I_Q_circ,MIITS_circ,I_Earth_max,Delta_t(QPS-PIC),Type of Quench,Quench count,QDS trigger origin,dU_QPS/dt,QH analysis,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RD1.L2,RD1,HWC 2021,2021-02-04,14:00:50.160,,1970-01-01 01:00:00,1612443650160.0,0,7.9,3860.2,0.2202,32.104492,0.0,,,,,,,test,1.5.19,1.5.67
+RD1.L2,RD1,HWC 2021,2021-02-04,14:00:50.160,,1970-01-01 01:00:00,1612443650160.0,0,7.9,3860.2,0.2202,32.104492,0.0,,,,,,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_IPD_PLI2.f2.csv b/test/resources/reports/AN_IPD_PLI2.f2.csv
index 12137546..47983852 100644
--- a/test/resources/reports/AN_IPD_PLI2.f2.csv
+++ b/test/resources/reports/AN_IPD_PLI2.f2.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Ramp rate,Plateau duration,I_Q_circ,MIITS_circ,I_Earth_max,Delta_t(QPS-PIC),Type of Quench,Quench count,QDS trigger origin,dU_QPS/dt,QH analysis,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RD1.L2,RD1,HWC 2015,2015-02-14,08:00:22.560,,2015-02-14 08:00:22.538,22.0,0,359.98,988.1,2.054,-4.02832,2.0,,,,,Fail,,root,1.5.19,1.5.67
+RD1.L2,RD1,HWC 2015,2015-02-14,08:00:22.560,,2015-02-14 08:00:22.538,22.0,0,359.98,988.1,2.054,-4.02832,2.0,,,,,Fail,,root,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_IPQ_FPA.csv b/test/resources/reports/AN_IPQ_FPA.csv
index 89da70ee..5eedb239 100644
--- a/test/resources/reports/AN_IPQ_FPA.csv
+++ b/test/resources/reports/AN_IPQ_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC_Bn),Time (FGC_Bn),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Ramp rate B1,Ramp rate B2,Plateau duration B1,Plateau duration B2,I_Q_B1,I_Q_B2,MIITS_B1,MIITS_B2,I_Earth_max_B1,I_Earth_max_B2,Delta_t(QPS-PIC),Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_QPS_B1/dt,dU_QPS_B2/dt,QH analysis,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RQ10.L4,RQ10,HWC 2021,2021-02-26,07:05:51.500,,2021-02-26 07:05:51.483,17.0,0,0,55.68,55.68,100.0,100.0,0.02657,0.02644,2.319336,,0.0,,B1,,,,,Pass,,test,1.5.19,1.5.67
+RQ10.L4,RQ10,HWC 2021,2021-02-26,07:05:51.500,,2021-02-26 07:05:51.483,17.0,0,0,55.68,55.68,100.0,100.0,0.02657,0.02644,2.319336,,0.0,,B1,,,,,Pass,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_IPQ_PLI2.f3.csv b/test/resources/reports/AN_IPQ_PLI2.f3.csv
index a0844f55..2ef36e9d 100644
--- a/test/resources/reports/AN_IPQ_PLI2.f3.csv
+++ b/test/resources/reports/AN_IPQ_PLI2.f3.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC_Bn),Time (FGC_Bn),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Ramp rate B1,Ramp rate B2,Plateau duration B1,Plateau duration B2,I_Q_B1,I_Q_B2,MIITS_B1,MIITS_B2,I_Earth_max_B1,I_Earth_max_B2,Delta_t(QPS-PIC),Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_QPS_B1/dt,dU_QPS_B2/dt,QH analysis,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RQ10.L5,RQ10,HWC 2015,2015-03-07,03:46:55.600,,2015-03-07 03:46:55.586,14.0,0,0,359.98,349.54,1597.8,1596.8,1.128,1.057,,-2.807617,2.0,,B1,,,-3.9774576666666657,-213.13476499999982,Pass,,root,1.5.19,1.5.67
+RQ10.L5,RQ10,HWC 2015,2015-03-07,03:46:55.600,,2015-03-07 03:46:55.586,14.0,0,0,359.98,349.54,1597.8,1596.8,1.128,1.057,,-2.807617,2.0,,B1,,,-3.9774576666666657,-213.13476499999982,Pass,,root,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_IT_FPA.csv b/test/resources/reports/AN_IT_FPA.csv
index 3e6d68a5..2e839c28 100644
--- a/test/resources/reports/AN_IT_FPA.csv
+++ b/test/resources/reports/AN_IT_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC_RQX),Time (FGC_RQX),FPA Reason,Timestamp_PIC,Delta_t(FGC_RQX-PIC),Ramp rate RQX,Ramp rate RTQX1,Ramp rate RTQX2,Plateau duration RQX,Plateau duration RTQX1,Plateau duration RTQX2,I_Q_RQX,I_Q_RTQX1,I_Q_RTQX2,MIITS_RQX,MIITS_RTQX1,MIITS_RTQX2,I_Earth_max,Delta_t(QPS-PIC),I_Q_Q1,I_Q_Q2,I_Q_Q3,Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_QPS/dt,QH analysis,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RQX.L5,RQX,HWC 2021,2021-01-29,15:10:11.340,,2021-01-29 15:10:11.327,13.0,0,0,0,71.76,99.9,59.92,200.0,0.0,150.0,1.871,0.0,0.01409,-4.150391,-3.0,200.0,349.3,200.0,,Q2,,,2.0828247458333338,Pass,,test,1.5.19,1.5.67
+RQX.L5,RQX,HWC 2021,2021-01-29,15:10:11.340,,2021-01-29 15:10:11.327,13.0,0,0,0,71.76,99.9,59.92,200.0,0.0,150.0,1.871,0.0,0.01409,-4.150391,-3.0,200.0,349.3,200.0,,Q2,,,2.0828247458333338,Pass,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_IT_PLI3.f6.csv b/test/resources/reports/AN_IT_PLI3.f6.csv
index 68928c13..36c2ee99 100644
--- a/test/resources/reports/AN_IT_PLI3.f6.csv
+++ b/test/resources/reports/AN_IT_PLI3.f6.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC_RQX),Time (FGC_RQX),FPA Reason,Timestamp_PIC,Delta_t(FGC_RQX-PIC),Ramp rate RQX,Ramp rate RTQX1,Ramp rate RTQX2,Plateau duration RQX,Plateau duration RTQX1,Plateau duration RTQX2,I_Q_RQX,I_Q_RTQX1,I_Q_RTQX2,MIITS_RQX,MIITS_RTQX1,MIITS_RTQX2,I_Earth_max,Delta_t(QPS-PIC),I_Q_Q1,I_Q_Q2,I_Q_Q3,Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_QPS/dt,QH analysis,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RQX.L1,RQX,HWC 2015,2015-03-14,14:48:21.900,,2015-03-14 14:48:21.876,24.0,0,0,0,359.98,359.98,359.98,3050.0,-0.0,2000.0,5.575,0.0,0.99792,22.766114,-4.0,3042.6,5044.8,3048.5,,Q2,,,6.9851345,Pass,,root,1.5.19,1.5.67
+RQX.L1,RQX,HWC 2015,2015-03-14,14:48:21.900,,2015-03-14 14:48:21.876,24.0,0,0,0,359.98,359.98,359.98,3050.0,-0.0,2000.0,5.575,0.0,0.99792,22.766114,-4.0,3042.6,5044.8,3048.5,,Q2,,,6.9851345,Pass,,root,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_RB_FPA.csv b/test/resources/reports/AN_RB_FPA.csv
index ee744ce9..487f6bba 100644
--- a/test/resources/reports/AN_RB_FPA.csv
+++ b/test/resources/reports/AN_RB_FPA.csv
@@ -1,9 +1,9 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Delta_t(EE_even-PIC),Delta_t(EE_odd-PIC),Ramp rate,Plateau duration,I_Q_circ,MIITS_circ,I_Earth_max,EE analysis,V feeler analysis,U_EE_max_ODD,U_EE_max_EVEN,Position,I_Q_M,Nr in Q event,Delta_t(iQPS-PIC),nQPS crate name,Delta_t(nQPS-PIC),Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_iQPS/dt,V_symm_max,dV_symm/dt,R_DL_max,I at R_DL_max,QH analysis,Short magnet ID,Manufacturer,Inner cable type,Outer cable type,I_Q_SM18,dI_Q_Acc,dI_Q_LHC,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,B21R1,11949,1,-9,B20R1,-5,,EXT,,,+12.12,,,45.0,11917,Pass,,,,,,,,,test,1.5.19,1.5.67
-RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,C21R1,9202,2,26359,B21R1,2231,,INT,,,-3.29,,,53.2,3902,Pass,,,,,,,,,test,1.5.19,1.5.67
-RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,A21R1,9166,3,26743,B21R1,2231,,EXT,,,+5.13,,,46.3,6504,Pass,,,,,,,,,test,1.5.19,1.5.67
-RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,A22R1,5073,4,81374,B22R1,3542,,EXT,,,+0.68,,,40.8,4696,Pass,,,,,,,,,test,1.5.19,1.5.67
-RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,B22R1,2479,5,144405,B23R1,3313,,INT,,,-0.19,,,25.2,1223,Pass,,,,,,,,,test,1.5.19,1.5.67
-RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,B20R1,2475,6,144535,B21R1,2231,,EXT,,,+2.56,,,11.9,2262,Pass,,,,,,,,,test,1.5.19,1.5.67
-RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,C20R1,388,7,296835,B20R1,-5,,EXT,,,+0.01,,,nan,nan,Pass,,,,,,,,,test,1.5.19,1.5.67
-RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,A20R1,388,8,296835,B20R1,-5,,INT,,,+0.00,,,nan,nan,Pass,,,,,,,,,test,1.5.19,1.5.67
+RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,B21R1,11949,1,-9,B20R1,-5,,EXT,,,+12.12,,,45.0,11917,Pass,,,,,,,,,test,1.5.20,1.5.68
+RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,C21R1,9202,2,26359,B21R1,2231,,INT,,,-3.29,,,53.2,3902,Pass,,,,,,,,,test,1.5.20,1.5.68
+RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,A21R1,9166,3,26743,B21R1,2231,,EXT,,,+5.13,,,46.3,6504,Pass,,,,,,,,,test,1.5.20,1.5.68
+RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,A22R1,5073,4,81374,B22R1,3542,,EXT,,,+0.68,,,40.8,4696,Pass,,,,,,,,,test,1.5.20,1.5.68
+RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,B22R1,2479,5,144405,B23R1,3313,,INT,,,-0.19,,,25.2,1223,Pass,,,,,,,,,test,1.5.20,1.5.68
+RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,B20R1,2475,6,144535,B21R1,2231,,EXT,,,+2.56,,,11.9,2262,Pass,,,,,,,,,test,1.5.20,1.5.68
+RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,C20R1,388,7,296835,B20R1,-5,,EXT,,,+0.01,,,nan,nan,Pass,,,,,,,,,test,1.5.20,1.5.68
+RB.A12,RB,HWC 2021,2021-06-05,08:56:08.900,,2021-06-05 08:56:08.877,23,591,95,0,5765,11950.0,6809.2,56.2,,,835,840,A20R1,388,8,296835,B20R1,-5,,INT,,,+0.00,,,nan,nan,Pass,,,,,,,,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_RB_PLI2.f1.csv b/test/resources/reports/AN_RB_PLI2.f1.csv
index fce2f946..ac2a4b07 100644
--- a/test/resources/reports/AN_RB_PLI2.f1.csv
+++ b/test/resources/reports/AN_RB_PLI2.f1.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Delta_t(EE_even-PIC),Delta_t(EE_odd-PIC),Ramp rate,Plateau duration,I_Q_circ,MIITS_circ,I_Earth_max,EE analysis,V feeler analysis,U_EE_max_ODD,U_EE_max_EVEN,Position,I_Q_M,Nr in Q event,Delta_t(iQPS-PIC),nQPS crate name,Delta_t(nQPS-PIC),Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_iQPS/dt,V_symm_max,dV_symm/dt,R_DL_max,I at R_DL_max,QH analysis,Short magnet ID,Manufacturer,Inner cable type,Outer cable type,I_Q_SM18,dI_Q_Acc,dI_Q_LHC,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RB.A23,RB,HWC 2021,2021-05-04,16:28:50.820,,2021-05-04 16:28:50.795,25.0,588.0,87.0,0,91.64,2000.0,209.628,21.230468,,,142.525108,140.213490999,B17R2,1999,,-17.0,B16R2,96.0,,INT,,,0.4167755376344086,,,19.83,987.55,Pass,,,,,,,,,root,1.5.19,1.5.67
+RB.A23,RB,HWC 2021,2021-05-04,16:28:50.820,,2021-05-04 16:28:50.795,25.0,588.0,87.0,0,91.64,2000.0,209.628,21.230468,,,142.525108,140.213490999,B17R2,1999,,-17.0,B16R2,96.0,,INT,,,0.4167755376344086,,,19.83,987.55,Pass,,,,,,,,,root,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_RQ_FPA.csv b/test/resources/reports/AN_RQ_FPA.csv
index ed7b07c2..c1274342 100644
--- a/test/resources/reports/AN_RQ_FPA.csv
+++ b/test/resources/reports/AN_RQ_FPA.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Delta_t(EE_RQD-PIC),Delta_t(EE_RQF-PIC),Ramp rate RQD,Ramp rate RQF,Plateau duration RQD,Plateau duration RQF,I_Q_RQD,I_Q_RQF,MIITS_RQD,MIITS_RQF,I_Earth_max_RQD,I_Earth_max_RQF,EE analysis RQD,EE analysis RQF,V feeler analysis RQD,V feeler analysis RQF,U_EE_max_RQD,U_EE_max_RQF,Position,I_Q_MQD,I_Q_MQF,Nr in Q event,Delta_t(iQPS-PIC),nQPS RQD crate name,nQPS RQF crate name,Delta_t(nQPS_RQD-PIC),Delta_t(nQPS_RQF-PIC),Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_iQPS/dt_RQD,dU_iQPS/dt_RQF,V_symm_max_RQD,V_symm_max_RQF,dV_symm_RQD/dt,dV_symm_RQF/dt,R_DL_max_RQD,R_DL_max_RQF,I_RQD at R_DL_max_RQD,I_RQF at R_DL_max_RQF,QH analysis,SSS ID,I_Q_SM18,dI_Q_Acc,dI_Q_LHC,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RQ.A23,RQ,HWC 2021,2021-05-11,19:29:10.020,,2021-05-11 19:29:10.020,3.0,91.0,91.0,-10.0,-10.0,0,0,6305.9,6305.9,564.741,583.533,12.206054,10.336913,,,,,48.098684463,48.268335970399995,30L3,6306,6306,,-15.20704,B31L3,B31L3,76.0,76.0,,RQF/EXT,,,,13.23,,,,,,,,,Pass,,,,,,test,1.5.19,1.5.67
+RQ.A23,RQ,HWC 2021,2021-05-11,19:29:10.020,,2021-05-11 19:29:10.020,3.0,91.0,91.0,-10.0,-10.0,0,0,6305.9,6305.9,564.741,583.533,12.206054,10.336913,,,,,48.098684463,48.268335970399995,30L3,6306,6306,,-15.20704,B31L3,B31L3,76.0,76.0,,RQF/EXT,,,,13.23,,,,,,,,,Pass,,,,,,test,1.5.20,1.5.68
diff --git a/test/resources/reports/AN_RQ_PLI2.f1.csv b/test/resources/reports/AN_RQ_PLI2.f1.csv
index 2e361809..44740138 100644
--- a/test/resources/reports/AN_RQ_PLI2.f1.csv
+++ b/test/resources/reports/AN_RQ_PLI2.f1.csv
@@ -1,2 +1,2 @@
 Circuit Name,Circuit Family,Period,Date (FGC),Time (FGC),FPA Reason,Timestamp_PIC,Delta_t(FGC-PIC),Delta_t(EE_RQD-PIC),Delta_t(EE_RQF-PIC),Ramp rate RQD,Ramp rate RQF,Plateau duration RQD,Plateau duration RQF,I_Q_RQD,I_Q_RQF,MIITS_RQD,MIITS_RQF,I_Earth_max_RQD,I_Earth_max_RQF,EE analysis RQD,EE analysis RQF,V feeler analysis RQD,V feeler analysis RQF,U_EE_max_RQD,U_EE_max_RQF,Position,I_Q_MQD,I_Q_MQF,Nr in Q event,Delta_t(iQPS-PIC),nQPS RQD crate name,nQPS RQF crate name,Delta_t(nQPS_RQD-PIC),Delta_t(nQPS_RQF-PIC),Type of Quench,Quench origin,Quench count,QDS trigger origin,dU_iQPS/dt_RQD,dU_iQPS/dt_RQF,V_symm_max_RQD,V_symm_max_RQF,dV_symm_RQD/dt,dV_symm_RQF/dt,R_DL_max_RQD,R_DL_max_RQF,I_RQD at R_DL_max_RQD,I_RQF at R_DL_max_RQF,QH analysis,SSS ID,I_Q_SM18,dI_Q_Acc,dI_Q_LHC,Comment,Analysis performed by,lhcsmapi version,lhcsm notebook version
-RQ.A45,RQ,HWC 2021,2021-04-07,20:51:53.400,,2021-04-07 20:51:53.380,20.0,92.0,92.0,0,0,139.26,139.16,1999.9,1999.9,54.115,54.824,5.720703,5.46582,,,,,12.674892499999999,12.8579679734,24L5,1999,1999,,-9.577732,B25L5,B25L5,149.0,149.0,,RQD/INT,,,0.1,,,,,,4.07,16.82,1315.54,962.83,Pass,,,,,,root,1.5.19,1.5.67
+RQ.A45,RQ,HWC 2021,2021-04-07,20:51:53.400,,2021-04-07 20:51:53.380,20.0,92.0,92.0,0,0,139.26,139.16,1999.9,1999.9,54.115,54.824,5.720703,5.46582,,,,,12.674892499999999,12.8579679734,24L5,1999,1999,,-9.577732,B25L5,B25L5,149.0,149.0,,RQD/INT,,,0.1,,,,,,4.07,16.82,1315.54,962.83,Pass,,,,,,root,1.5.20,1.5.68
-- 
GitLab


From 94d74330859ce2436b0d5aac408372c15458934a Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Wed, 23 Feb 2022 12:10:16 +0100
Subject: [PATCH 43/44] release.md formatting

---
 RELEASE.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/RELEASE.md b/RELEASE.md
index 1deecafd..39ff1bb8 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -7,6 +7,7 @@ Version: 1.5.68
 - Certain plots synchronized to PIC in RB_PLI3.d2: [SIGMON-308](https://its.cern.ch/jira/browse/SIGMON-308)
 - 600A_FPA uses proper metadata  (valid at the time of FGC): [SIGMON-309](https://its.cern.ch/jira/browse/SIGMON-309)
 
+
 Version: 1.5.67
 - new HWC_QHDA_PM_LIST_CCC notebook [SIGMON-233](https://its.cern.ch/jira/browse/SIGMON-233), [SIGMON-224](https://its.cern.ch/jira/browse/SIGMON-224), [SIGMON-272](https://its.cern.ch/jira/browse/SIGMON-272), [SIGMON-255](https://its.cern.ch/jira/browse/SIGMON-255)
 - Statistics for PM and Nxcals nQPS in AN_RB_FPA: [SIGMON-249](https://its.cern.ch/jira/browse/SIGMON-249)
@@ -17,7 +18,7 @@ Version: 1.5.67
 - Logs for the environment setup improved: [SIGMON-240](https://its.cern.ch/jira/browse/SIGMON-240)
 - A dedicated 'agent_sigmon' configured on Jenkins: [SIGMON-280](https://its.cern.ch/jira/browse/SIGMON-280)
 - Fix CI caching for the reports: [SIGMON-237](https://its.cern.ch/jira/browse/SIGMON-237)
-  
+
 
 Version: 1.5.66
 - Adapt notebooks to the CI: [SIGMON-141](https://its.cern.ch/jira/browse/SIGMON-141)
-- 
GitLab


From 98bfe497cda5e5eee3863f2bca7e023038a1a23a Mon Sep 17 00:00:00 2001
From: almnich <aleksandra.mnich@cern.ch>
Date: Wed, 23 Feb 2022 12:26:55 +0100
Subject: [PATCH 44/44] release notes update

---
 RELEASE.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/RELEASE.md b/RELEASE.md
index 39ff1bb8..be83e4b6 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -5,7 +5,8 @@ Version: 1.5.68
 - Fixes and improvements in AN_RQ_PNO.b3 and AN_RB_PNO.b2: [SIGMON-315](https://its.cern.ch/jira/browse/SIGMON-315)
 - HWC_QHD_PM_LIST_CCC supports empty buffers: [SIGMON-257](https://its.cern.ch/jira/browse/SIGMON-257)
 - Certain plots synchronized to PIC in RB_PLI3.d2: [SIGMON-308](https://its.cern.ch/jira/browse/SIGMON-308)
-- 600A_FPA uses proper metadata  (valid at the time of FGC): [SIGMON-309](https://its.cern.ch/jira/browse/SIGMON-309)
+- 600A_FPA uses proper metadata  (valid at the time of the FGC): [SIGMON-309](https://its.cern.ch/jira/browse/SIGMON-309)
+- Improvements in the PGC notebooks: [SIGMON-305](https://its.cern.ch/jira/browse/SIGMON-305)
 
 
 Version: 1.5.67
-- 
GitLab