project reorganization: 1. executable files in bin directory now. 2. add recursive_unpack_targz.py for recursive unpacking specified in this script archives tar.gz with MVN data. 3. add asotr_unzip_plot.sh bash file for unpacking MVN data, collect asotr data into csv files and plot asotr MVN data. 4. add brd_wheel_1Hz_parser.py for demonstrate how to work with brd telemetry data

bin/impulse_response.py

@@ -0,0 +1,41 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import sys
+from importlib import reload
+sys.path.append('./')
+import asotr
+reload(asotr)
+import matplotlib.pyplot as plt
+from matplotlib import dates
+import pandas as pd
+from datetime import datetime
+
+asotr_kit = 1
+fname = f'../../python_cyclo/data/asotr0{asotr_kit}_data_T.csv' 
+
+dateparse = lambda x: datetime.strptime(x, "%d.%m.%Y %H:%M:%S.%f")
+data = pd.read_csv(fname, sep=';', parse_dates=['timestamp'], date_parser=dateparse)
+
+interp = {'method': 'polynomial', 'order': 2}
+thermocycle_info = {'date': '14.03.2025', 'type': 'impuse'}
+cut_step_resp = {'orig_time_step_begin': '14.03.2025 13:49:32', 'orig_step_duration': 20*60}
+data_info = {'data': data, 'channel': 'ch1', 'period': '1 сек', 'find_accuracy': 'seconds'}
+
+name = f'{thermocycle_info["type"]}_response_{thermocycle_info["date"].replace(".","")}'
+
+plot_info = {'title': 'Реакция на импульсное воздействие', 
+        'ox_dtime_format': "%H:%M:%S", 'legend_pos': ['upper right', 'lower left'],
+        'name_fig': f'../plots/response/{name}.png', 
+        'font': 10}
+
+tstamp_orig_begin = cut_step_resp['orig_time_step_begin']
+
+_, interp_imp_resp = asotr.cut_norm_data(data_info['data'], tstamp_orig_begin, 
+        cut_step_resp['orig_step_duration'], channel='ch1', interp=interp, 
+        accuracy=data_info['find_accuracy'])
+
+
+interp_imp_resp.to_csv(f'../data/asotr/response/asotr0{asotr_kit}_{name}.csv', index=False, sep=';', 
+        encoding='utf-8-sig', decimal='.')
+
+asotr.plot_imp_response(interp_imp_resp, data_info, plot_info, thermocycle_info)