Commit 3bf89f45 authored by Agata Malgorzata Chadaj's avatar Agata Malgorzata Chadaj
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parent bbc4e686
Pipeline #3167783 passed with stage
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......@@ -236,7 +236,7 @@
},
"outputs": [],
"source": [
"ipq_analysis.get_notebook_result()"
"ipq_analysis.get_analysis_result()"
]
}
],
......
%% 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_notebook_result()
ipq_analysis.get_analysis_result()
```
......
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