112 lines
4.6 KiB
Python
112 lines
4.6 KiB
Python
import pandas as pd
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import matplotlib.pyplot as plt
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import sys
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from importlib import reload
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sys.path.append('/home/danila/Danila/work/MVN/Soft/PID/python/')
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import asotr
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reload(asotr)
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import matplotlib.pyplot as plt
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from matplotlib import dates
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import pandas as pd
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from datetime import datetime
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asotr_kit = 1
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fname = f'../python_cyclo/data/asotr0{asotr_kit}_data_T.csv'
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dateparse = lambda x: datetime.strptime(x, "%d.%m.%Y %H:%M:%S.%f")
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data = pd.read_csv(fname, sep=';', parse_dates=['timestamp'], date_parser=dateparse)
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# date = '20.03.2025'
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# period = '1 мин'
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# time_begin_orig = date + ' 17:10:11'
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# time_begin1 = date + ' 18:10:17'
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# time_begin2 = date + ' 19:10:23'
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# step_begin = time_begin2
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# duration = 3600
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# accuracy = 'seconds'
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# name_fig = 'step_response_KDI_20242003.png'
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# date = '21.03.2025'
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# period = '1 мин'
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# time_begin_orig = date + ' 14:00:11'
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# time_begin1 = date + ' 15:00:16'
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# time_begin2 = date + ' 16:00:16'
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# step_begin = time_begin2
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# duration = 3600
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# accuracy = 'seconds'
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# name_fig = 'step_response_KDI_20242103.png'
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# date = '24.03.2025'
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# period = '1 сек'
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# time_begin_orig = date + ' 19:45:11'
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# time_begin1 = date + ' 20:45:13'
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# time_begin2 = date + ' 21:45:17'
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# step_begin = time_begin2
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# duration = 3600
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# accuracy = 'seconds'
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# name_fig = 'step_response_KDI_20242403.png'
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# interp = {'method': 'polynomial', 'order': 2}
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# thermocycle_info = {'date': '24.03.2025', 'time_begin': ['20:45:00', '21:45:11'],
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# 'duration_sec': 60*60, 'type': 'step'}
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# cut_step_resp = {'time_step_begin': '21:45:11', 'step_duration': 60*60,
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# 'orig_time_step_begin': '19:45:11', 'orig_step_duration': 25*60}
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# data_info = {'data': data, 'device': 'KDI', 'channel': 'ch1', 'period': '1 мин',
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# 'find_accuracy': 'seconds'}
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# name = f'{thermocycle_info["type"]}_response_diff_{data_info["device"]}_{thermocycle_info["date"].replace(".","")}'
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# plot_info = {'title': 'Реакция на ступенчатое воздействие',
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# 'ox_dtime_format': "%H:%M:%S", 'legend_pos': ['upper left', 'lower left'],
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# 'name_fig': f'{name}.png', 'font': 10}
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interp = {'method': 'polynomial', 'order': 2}
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thermocycle_info = {'date': '01.04.2025',
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'time_begin': ['01.04.2025 16:27:00', '01.04.2025 18:00:00'],
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'duration_sec': 92*60, 'type': 'step'}
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cut_step_resp = {'time_step_begin': '01.04.2025 18:53:21', 'step_duration': 24*60,
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'orig_time_step_begin': '01.04.2025 15:22:10', 'orig_step_duration': 24*60}
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data_info = {'data': data, 'channel': 'ch1', 'period': '1 мин',
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'find_accuracy': 'seconds'}
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plot_info = {'title': 'Реакция на ступенч. воздейств.',
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'ox_dtime_format': "%H:%M:%S", 'legend_pos': ['lower right', 'lower left'],
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'name_fig': 'step_response_diff_KDI_20240401.png', 'font': 10}
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step_resp_cut, _, _ = asotr.get_step_response_diff(data_info['data'], thermocycle_info,
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channel=data_info['channel'], interp=interp, accuracy=data_info['find_accuracy'],
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cut_step_resp=cut_step_resp)
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tstamp_orig_begin = cut_step_resp['orig_time_step_begin']
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_, interp_step_resp = asotr.cut_norm_data(data_info['data'], tstamp_orig_begin,
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cut_step_resp['orig_step_duration'], channel='ch1', interp=interp,
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accuracy=data_info['find_accuracy'])
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max_ = min(len(interp_step_resp), len(step_resp_cut))
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interp_step_resp.to_csv(f'./data/asotr0{asotr_kit}_{thermocycle_info["type"]}_{thermocycle_info["date"].replace(".","")}.csv', index=False, sep=';', encoding='utf-8-sig', decimal='.')
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title = f'{plot_info["title"]}, канал {data_info["channel"][2]} АСОТР КДИ СПИН-X1-МВН, период опроса {data_info["period"]} ({thermocycle_info["date"]})'
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fig = plt.figure(figsize=(6, 6), dpi=200)
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fig.suptitle(title, fontsize=plot_info['font'])
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ax1 = fig.add_subplot(1,1,1)
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ax1.plot(step_resp_cut['timestamp'].iloc[0:max_], step_resp_cut['temp'].iloc[0:max_], '--',
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label='реакция на ступенчатое воздействие с термоциклом')
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ax1.plot(step_resp_cut['timestamp'].iloc[0:max_], interp_step_resp['temp'].iloc[0:max_],
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label='реакция на ступенчатое воздействие')
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date_formatter = dates.DateFormatter(plot_info['ox_dtime_format'])
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ax1.xaxis.set_major_formatter(date_formatter)
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ax1.legend(loc=plot_info["legend_pos"][0], fontsize=plot_info['font'])
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ax1.grid(True)
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ax1.tick_params(axis='both', width=1, labelsize=plot_info['font'])
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ax1.set_ylabel(r'$T_{norm}$, $^\circ$C', fontsize=plot_info['font'])
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ax1.set_xlabel('Время', fontsize=plot_info['font'])
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plt.tight_layout()
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fig.savefig(plot_info["name_fig"])
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plt.show()
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