42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
from read_baseline_data import *
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from read_chirp_data import *
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from utility import *
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import matplotlib.pyplot as plt
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import numpy as np
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def chirp_eod_plot(df_map, eod, times):
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#die äußere Schleife geht für alle Keys durch und somit durch alle dfs
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#die innnere Schleife bildet die 16 Wiederholungen einer Frequenz ab
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for i in df_map.keys():
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freq = list(df_map[i])
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fig,axs = plt.subplots(2, 2, sharex = True, sharey = True)
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for idx, k in enumerate(freq):
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ct = times[k]
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e1 = eod[k]
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zeit = e1[0]
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eods = e1[1]
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if idx <= 3:
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axs[0, 0].plot(zeit, eods, color= 'blue', linewidth = 0.25)
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axs[0, 0].scatter(np.asarray(ct), np.ones(len(ct))*3, color = 'green', s= 22)
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elif 4<= idx <= 7:
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axs[0, 1].plot(zeit, eods, color= 'blue', linewidth = 0.25)
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axs[0, 1].scatter(np.asarray(ct), np.ones(len(ct))*3, color = 'green', s= 22)
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elif 8<= idx <= 11:
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axs[1, 0].plot(zeit, eods, color= 'blue', linewidth = 0.25)
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axs[1, 0].scatter(np.asarray(ct), np.ones(len(ct))*3, color = 'green', s= 22)
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else:
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axs[1, 1].plot(zeit, eods, color= 'blue', linewidth = 0.25)
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axs[1, 1].scatter(np.asarray(ct), np.ones(len(ct))*3, color = 'green', s= 22)
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fig.suptitle('EOD for chirps', fontsize = 16)
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axs[0,0].set_ylabel('Amplitude [mV]')
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axs[0,1].set_xlabel('Amplitude [mV]')
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axs[1,0].set_xlabel('Time [ms]')
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axs[1,1].set_xlabel('Time [ms]')
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plt.show()
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