wip

CI/send_results.py

@@ -24,8 +24,8 @@ def get_result():
     result_nb = nbformat.read(result_path, as_version=4)
     nb = outputs.NotebookOutput(result_nb)
     try:
-        full_result = nb.get_cells_by_tag('result')[1].get_cell_output(outputs.CellOutputType.STDOUT)[0]
         result_flag = nb.get_cells_by_tag('result')[0].get_cell_output(outputs.CellOutputType.STDOUT)[0]
+        full_result = nb.get_cells_by_tag('result')[1].get_cell_output(outputs.CellOutputType.STDOUT)[0]
     except IndexError:
         return 'FAILED', ''
     return result_flag, json.load(full_result)

qh/HWC_IPQ_QHDA.ipynb

@@ -226,6 +226,19 @@
     "    print('Reference timestamp table saved to (Windows): ' + '\\\\\\\\cernbox-smb' + csv_full_path.replace('/', '\\\\'))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": [
+     "result"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "ipq_analysis.get_result()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
 %% Cell type:markdown id: tags:
 
 <h1><center>Analysis of a QH discharge in an IPQ Circuit</center></h1>
 
 %% Cell type:markdown id: tags:
 
 # 0. Initialise Working Environment
 
 %% Cell type:code id: tags:
 
 ``` python
 # External libraries
 print('Loading (1/16)'); import sys; import pandas as pd
 print('Loading (2/16)'); from multiprocessing import Pool
 print('Loading (3/16)'); from IPython.display import display, HTML, Javascript, clear_output
 
 # Internal libraries
 print('Loading (4/16)'); import lhcsmapi
 print('Loading (5/16)'); from lhcsmapi.Time import Time
 print('Loading (6/16)'); from lhcsmapi.Timer import Timer
 print('Loading (7/16)'); from lhcsmapi.analysis.IpqCircuitQuery import IpqCircuitQuery
 print('Loading (8/16)'); from lhcsmapi.analysis.IpqCircuitAnalysis import IpqCircuitAnalysis
 print('Loading (9/16)'); from lhcsmapi.analysis.expert_input import check_show_next, get_expert_decision
 print('Loading (10/16)'); from lhcsmapi.analysis.qh.QuenchHeaterQuery import QuenchHeaterQuery
 print('Loading (11/16)'); from lhcsmapi.analysis.report_template import apply_report_template
 print('Loading (12/16)'); from lhcsmapi.gui.DateTimeBaseModule import DateTimeBaseModule
 print('Loading (13/16)'); from lhcsmapi.gui.hwc.HwcSearchModuleMediator import HwcSearchModuleMediator
 print('Loading (14/16)'); from lhcsmapi.gui.qh.QhPmSearchModuleMediator import QhPmSearchModuleMediator
 print('Loading (15/16)'); from lhcsmapi.metadata.SignalMetadata import SignalMetadata
 print('Loading (16/16)'); from lhcsmnb.parameters import are_all_parameters_injected, get_source_timestamp_df, NbType
 
 
 clear_output()
 lhcsmapi.get_lhcsmapi_version()
 lhcsmapi.get_lhcsmhwc_version('../__init__.py')
 print('Analysis performed by %s' % HwcSearchModuleMediator.get_user())
 ```
 
 %% Cell type:markdown id: tags:
 
 # 1. Find QH Post Mortem Entries
 
 %% Cell type:code id: tags:parameters
 
 ``` python
 circuit_type = 'IPQ'
 ```
 
 %% Cell type:code id: tags:
 
 ``` python
 with Timer():
     if not are_all_parameters_injected(NbType.QH, locals()):
         qh_pm_search = QhPmSearchModuleMediator(DateTimeBaseModule(start_date_time='2021-01-12 00:00:00+01:00', end_date_time=Time.to_string(Time.now())), circuit_type=circuit_type)
     else:
         circuit_sub_type = SignalMetadata.get_circuit_type_for_circuit_name(circuit_name)
         source_timestamp_df = QuenchHeaterQuery(circuit_sub_type, circuit_name).find_source_timestamp_qh_with_pattern('*', start_time, end_time)
         display(HTML(source_timestamp_df.to_html()))
 ```
 
 %% Cell type:markdown id: tags:
 
 # 2. Query All Signals Prior to Analysis
 
 %% Cell type:code id: tags:
 
 ``` python
 with Timer():
     if not are_all_parameters_injected(NbType.QH, locals()):
         circuit_name = qh_pm_search.get_circuit_name()
         discharge_level = qh_pm_search.get_discharge_level()
         source_timestamp_df = qh_pm_search.source_timestamp_df
         is_automatic = qh_pm_search.is_automatic_mode()
 
     ipq_query = IpqCircuitQuery(circuit_type, circuit_name)
     ipq_analysis = IpqCircuitAnalysis(circuit_type, None, circuit_name=circuit_name)
 
     u_hds_dfss = ipq_query.query_qh_pm(source_timestamp_df, signal_names=['U_HDS'])
     u_hds_ref_dfss = ipq_query.query_qh_pm(source_timestamp_df, signal_names=['U_HDS'], is_ref=True)
 ```
 
 %% Cell type:markdown id: tags:
 
 # 3. Quench Heaters
 
 *CRITERIA*:
 - all characteristic times of an exponential decay calculated with the 'charge' approach for voltage is +/- 5 ms from the reference ones
 - the initial voltage should be between 810 V and 1000 V
 - the final voltage should be between 0 V and 10 V
 
 *GRAPHS*:
 - t = 0 s corresponds to the start of the pseudo-exponential decay
 
 Voltage view (linear and log)
 - the queried and filtered quench heater voltage on the left axis (actual signal continuous, reference dashed), U_HDS
 
 %% Cell type:code id: tags:
 
 ``` python
 index = 0
 for u_hds_dfs, u_hds_ref_dfs in zip(u_hds_dfss, u_hds_ref_dfss):
     print(index, source_timestamp_df.loc[index, 'timestamp'])
     if u_hds_dfs:
         ipq_analysis.analyze_single_qh_voltage_with_ref(circuit_name, source_timestamp_df.loc[index, 'timestamp'], u_hds_dfs, u_hds_ref_dfs, nominal_voltage=discharge_level)
     else:
         print(f"No Quench Heater Discharges!")
     index += 1
 ```
 
 %% Cell type:markdown id: tags:ignore
 
 # 4. Signature Decision
 
 %% Cell type:markdown id: tags:ignore
 
 # 5. Final Report
 
 %% Cell type:code id: tags:ignore
 
 ``` python
 if not source_timestamp_df.empty:
     analysis_start_time = Time.get_analysis_start_time()
     prefix_circuit_name = circuit_name.split('.')[0]
     date_time_qh = Time.to_datetime(source_timestamp_df.loc[0, 'timestamp']).strftime("%Y-%m-%d-%Hh%M")
 
     apply_report_template()
     !mkdir -p /eos/project/m/mp3/IPQ/$prefix_circuit_name/$circuit_name/QHDA
     file_name_html = "{}_QHDA-{}-{}_{}.html".format(circuit_name, date_time_qh, analysis_start_time, signature)
     full_path = '/eos/project/m/mp3/IPQ/{}/{}/QHDA/{}'.format(prefix_circuit_name, circuit_name, file_name_html)
     print('Compact notebook report saved to (Windows): ' + '\\\\cernbox-smb' + full_path.replace('/', '\\'))
     display(Javascript('IPython.notebook.save_notebook();'))
     Time.sleep(5)
     !{sys.executable} -m jupyter nbconvert --to html $'HWC_IPQ_QHDA.ipynb' --output /eos/project/m/mp3/IPQ/$prefix_circuit_name/$circuit_name/QHDA/$file_name_html --TemplateExporter.exclude_input=True --TagRemovePreprocessor.remove_all_outputs_tags='["skip_output"]' --TagRemovePreprocessor.remove_cell_tags='["skip_cell"]'
 ```
 
 %% Cell type:markdown id: tags:ignore
 
 # 6. Save Timestamps in Reference Format (if update needed)
 
 %% Cell type:code id: tags:ignore
 
 ``` python
 if not source_timestamp_df.empty:
     analysis_start_time = Time.get_analysis_start_time()
     prefix_circuit_name = circuit_name.split('.')[0]
     !mkdir -p /eos/project/m/mp3/IPQ/$prefix_circuit_name/$circuit_name/QHDA
     file_name = "{}_QHDA-{}-{}_Reference".format(circuit_name, date_time_qh, analysis_start_time)
     csv_full_path = '/eos/project/m/mp3/IPQ/{}/{}/QHDA/{}.csv'.format(prefix_circuit_name, circuit_name, file_name)
     cell_datetime_timestamp = pd.DataFrame(source_timestamp_df.rename(columns={'source': 'Cell'})['Cell'])
     cell_datetime_timestamp['Timestamp String'] = source_timestamp_df['timestamp'].apply(lambda col: Time.to_string_short(col, n_dec_digits=9))
     cell_datetime_timestamp['Timestamp'] = source_timestamp_df['timestamp']
     cell_datetime_timestamp.to_csv(csv_full_path, index=False)
     print('Reference timestamp table saved to (Windows): ' + '\\\\cernbox-smb' + csv_full_path.replace('/', '\\'))
 ```
 
 %% Cell type:code id: tags:result
 
 ``` python
+ipq_analysis.get_result()
+```
+
+%% Cell type:code id: tags:result
+
+``` python
 ipq_analysis.get_analysis_result()
 ```