10
92 lines
3.6 KiB
Python
92 lines
3.6 KiB
Python
import psycopg2
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import matplotlib.pyplot as plt
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from scipy import signal
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import numpy as np
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# data_spin_histogram
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def histogram_slope(x_data, y_data, slope =0, bins =0, plot =True):
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if len(x_data)!=len(y_data):
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print('Scale of x_data and y_data are different.')
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return False
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elif bins == 0:
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bins = round(len(x_data)/2)
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arr_list = [y_data[i] - slope*x_data[i] for i in range(len(x_data))]
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cons_max = max(arr_list)
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cons_min = min(arr_list)
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hist_range = np.linspace(cons_min, cons_max, bins+1)
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hist_range_mid = [(hist_range[i]+hist_range[i+1])/2 for i in range(len(hist_range)-1)]
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hist_range[-1] = hist_range[-1]+1
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hist_list = [len([j for j in arr_list if j>=hist_range[i] and j<hist_range[i+1]]) for i in range(len(hist_range)-1)]
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peek_temp_list,_ = signal.find_peaks(hist_list)
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peek_temp_list = list(peek_temp_list)
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print(peek_temp_list)
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# peek_temp_list[0] = list(peek_temp_list[0])
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if np.sign(np.diff(hist_list))[0] < 0:
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# print( np.sign(np.diff(hist_list))[0])
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peek_temp_list = [0] + peek_temp_list
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if np.sign(np.diff(hist_list))[-1] > 0:
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# print(np.sign(np.diff(hist_list))[-1])
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peek_temp_list = peek_temp_list+[len(hist_list)-1]
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print(peek_temp_list)
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peek_list = [i for i in peek_temp_list if hist_list[i] >= len(x_data)/bins*3]
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print(peek_list)
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results_half = signal.peak_widths(hist_list,peek_list, rel_height=0.8)
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peak_min,peak_max = [cons_min + (cons_max-cons_min)/bins*j for j in results_half[2]],[cons_min + (cons_max-cons_min)/bins*j for j in results_half[3]]
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print(peak_min,peak_max)
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peak_80=[]
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for i in range(len(peak_min)):
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peak_filt_list = [j for j in arr_list if j>=peak_min[i] and j<=peak_max[i]]
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print(np.mean(peak_filt_list))
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print(len(peak_filt_list))
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peak_80.append(np.mean(peak_filt_list))
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print(results_half[2])
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print(results_half)
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plt.plot(peak_80, [hist_list[j] for j in peek_list], "y")
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if plot:
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plt.hist(arr_list, bins)
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plt.plot([hist_range_mid[i] for i in peek_list], [hist_list[j] for j in peek_list], "xb")
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plt.plot(peak_80, [hist_list[j] for j in peek_list], "xr")
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# plt.hlines(results_half[1],[ hist_list[int(j)] for j in results_half[2]],[ hist_list[int(j)] for j in results_half[2]], color="g")
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plt.savefig("histogrim.png")
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return hist_list, hist_range_mid, peek_list
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def run():
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conn = psycopg2.connect(database="postgres", user="biopro", password="BioProControlBox", host="127.0.0.1", port="5432")
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cur = conn.cursor()
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id = 166
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sql_str = f'select "raw_data" from "recording_data_metas" WHERE id = {id}'
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cur.execute(sql_str)
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data = cur.fetchall()[0][0]
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channel_data = []
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for i in ['1','2']:
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channel_data_temp = []
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for j in data[i]:
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# print(j)
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sql_str = f'select "data" from "{i}_recording_data_raws" WHERE id = {j}'
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cur.execute(sql_str)
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raw_data = cur.fetchall()[0][0]
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raw_data = raw_data.replace('"***"',' ').split(" ")
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channel_data_temp =channel_data_temp + [int(raw_data[k]) for k in range(len(raw_data)) if k%2]
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# print(len(channel_data_temp))
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channel_data.append(channel_data_temp)
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# print(channel_data[1][-1])
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# print(channel_data[0][:500])
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plt.plot(channel_data[0],channel_data[1],'o',markersize=2)
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plt.hlines(1e6,2.4e6,2.6e6,color='g')
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plt.savefig('test.png')
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plt.close()
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x_data, y_data ,peek_list = histogram_slope(channel_data[0],channel_data[1],bins = 200)
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print([y_data[i] for i in peek_list])
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print(peek_list, channel_data)
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channel_data.append(1.5e6)
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channel_data.append(4.5e6)
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return channel_data, peek_list
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# print([y_data])
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