91 lines
4.0 KiB
Python
91 lines
4.0 KiB
Python
import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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import matplotlib.gridspec as gridspec
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from IPython import embed
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import helper_functions as hf
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from params import *
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import os
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if __name__ == '__main__':
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###################################################################################################################
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# parameter and variables
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kernel_size = 100
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kernel = np.ones(kernel_size) / kernel_size
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fig1 = plt.figure(constrained_layout=True, figsize=[15 / inch, 15 / inch])
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gs = gridspec.GridSpec(ncols=2, nrows=3, figure=fig1, hspace=0.05, wspace=0.05,
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width_ratios=[1, 1], height_ratios=[1, 1, 1], left=0.1, bottom=0.15, right=0.95, top=0.98)
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c = 0
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ax_counter = 0
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###################################################################################################################
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# load all the data of one day
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for filename_idx in [0, 1, 2, 3]:
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filename = sorted(os.listdir('../data/'))[filename_idx]
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all_max_ch_means = np.load('../data/' + filename + '/all_max_ch.npy', allow_pickle=True)
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all_xticks = np.load('../data/' + filename + '/all_xtickses.npy', allow_pickle=True)
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all_ipp = np.load('../data/' + filename + '/all_ipp.npy', allow_pickle=True)
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power_means = np.load('../data/' + filename + '/power_means.npy', allow_pickle=True)
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freq = np.load('../data/' + filename + '/fish_freq_q10.npy', allow_pickle=True)
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names = np.load('../data/' + filename + '/fish_species.npy', allow_pickle=True)
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###############################################################################################################
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# get fish
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print(filename)
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for fish_number in range(len(power_means)):
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if names[fish_number] == 'Eigenmannia' and power_means[fish_number] >= -90.0:
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ipp = all_ipp[fish_number]
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x_tickses = all_xticks[fish_number]
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max_ch_mean = all_max_ch_means[fish_number]
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# smoothing of max channel mean
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smooth_mcm = np.convolve(max_ch_mean, kernel, 'valid')
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try:
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smooth_x = x_tickses[int(np.ceil(kernel_size / 2)):-int(np.floor(kernel_size / 2))]
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except:
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embed()
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quit()
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#####################################################################################################
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# plot traces
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ax1 = fig1.add_subplot(gs[c])
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ax1.imshow(ipp[::20].T[::-1], vmin=-100, vmax=-50, aspect='auto', interpolation='gaussian',
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extent=[x_tickses[0], x_tickses[-1], -0.5, 15.5])
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ax1.plot(smooth_x[::20], smooth_mcm[::20], '.', color=color2[4])
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ax1.make_nice_ax()
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ax1.axhline(7.5, xmin=0, xmax=15, color='white', lw=4)
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ax1.set_yticks([0, 1, 2, 3, 4, 5, 6, 7, 7.5, 8, 9, 10, 11, 12, 13, 14, 15])
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ax1.set_yticklabels(['1', '', '3', '', '5', '', '7', '', 'g', '', '10', '', '12', '', '14', '', '16'],
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fontsize=9)
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print(ax_counter)
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ax1.text(-0.17, 1, chr(ord('A') + ax_counter), transform=ax1.transAxes, fontsize='large')
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ax_counter += 1
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ax1.invert_yaxis()
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ax1.xaxis_date()
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date_format = mdates.DateFormatter('%H:%M')
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ax1.xaxis.set_major_formatter(date_format)
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if c in [3, 4]:
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ax1.set_xlabel('Time', fontsize=11)
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if c in [1, 2]:
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ax1.set_xticks(ax1.get_xticks()[::2])
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if c in [0, 2, 4]:
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ax1.set_ylabel('Electrode', fontsize=11)
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c += 1
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###################################################################################################################
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# save plot
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fig1.savefig(save_path + 'eigen_trajectories.pdf')
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plt.show()
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