stimuli figures
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contrast_sweep.dat.pdf
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contrast_sweep.dat.pdf
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@ -2,6 +2,8 @@ import os
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import numpy as np
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import matplotlib.pyplot as plt
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import nixio as nix
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import glob
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import os
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from IPython import embed
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def analyze_sams(filename):
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@ -13,37 +15,39 @@ def analyze_sams(filename):
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for g in b.groups:
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if 'sam' in g.name.lower(): # go through loop, until 'sam' is found
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break
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rtag_data = g.tags[0]
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rtag_data.metadata.pprint(max_depth=-1)
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# print(40*'*')
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stim_tag = g.multi_tags[0]
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stim_pos = stim_tag.positions[:] # beginnings of stimulations
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stim_extent = stim_tag.extents[:] # duration of stimulations
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for r in rtag_data.references:
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print(r.name, r.type)
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# embed()
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# exit()
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voltage_trace = rtag_data.references['V-1']
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rtag_data = g.tags[0]
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rtag_data.metadata.pprint(max_depth=-1)
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# print(40*'*')
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stim_tag = g.multi_tags[0]
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stim_pos = stim_tag.positions[:] # beginnings of stimulations
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stim_extent = stim_tag.extents[:] # duration of stimulations
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# embed()
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# exit()
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for r in rtag_data.references:
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print(r.name, r.type)
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# embed()
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# exit()
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voltage_trace = rtag_data.references['V-1']
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spike_data = []
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spike_data = []
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for idx in range(len(stim_pos)):
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spike_data.append(stim_tag.retrieve_data(idx, 'Spikes-1')[:])
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for idx in range(len(stim_pos)):
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spike_data.append(stim_tag.retrieve_data(idx, 'Spikes-1')[:])
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# embed()
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# exit()
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dims = voltage_trace.dimensions[0].axis(len(voltage_trace))
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# embed()
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# exit()
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dims = voltage_trace.dimensions[0].axis(len(voltage_trace))
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# # f.close()
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# embed()
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# # f.close()
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# embed()
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# exit()
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return stim_pos, stim_extent, spike_data, voltage_trace, dims
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if __name__ == '__main__':
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data_dir = '/home/lisa/data'
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data_set = '2019-06-24-aa-invivo-1'
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os.chdir(data_dir)
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data_set = glob.glob('2019-*')
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stim_pos, stim_extent, spike_data, voltage_trace, dims = analyze_sams(os.path.join(data_dir, data_set,
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data_set + '.nix'))
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print(len(spike_data))
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@ -59,5 +63,5 @@ if __name__ == '__main__':
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for k in range(len(spike_data[j])):
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print('current spike time is: ', spike_data[j][k])
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plt.plot(spike_data[j][k], -40, 'o', color='k')
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plt.ylim([-100, -30])
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# plt.ylim([-45, 0])
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plt.show()
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phase_sweep.dat.pdf
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phase_sweep.dat.pdf
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33
stimuli_figures.py
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stimuli_figures.py
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@ -0,0 +1,33 @@
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import glob
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import matplotlib.pyplot as plt
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filenames = glob.glob('*.dat')
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for i in range(len(filenames)):
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with open(filenames[i], 'r') as f:
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lines = f.readlines()
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time = []
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amplitude = []
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for l in lines:
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if len(l.strip()) > 0 and '#' not in l:
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l = l.strip().split()
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time.append(float(l[0]))
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amplitude.append(float(l[1]))
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plt.figure(figsize=(20/2.54, 12/2.54), facecolor='white', edgecolor='white')
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ax = plt.subplot(111)
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ax.spines["top"].set_visible(False)
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# ax.spines["bottom"].set_visible(False)
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ax.spines["right"].set_visible(False)
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# ax.spines["left"].set_visible(False)
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ax.get_xaxis().tick_bottom()
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ax.get_yaxis().tick_left()
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if filenames[i] == 'zap.dat':
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ax.set_xlim([0, 1])
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else:
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ax.set_xlim([0, .2])
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ax.set_title(filenames[i])
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ax.set_xlabel('time')
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ax.set_ylabel('amplitude')
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ax.plot(time, amplitude)
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plt.savefig(filenames[i]+'.pdf')
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plt.show()
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zap.dat.pdf
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zap.dat.pdf
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