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44 lines
1.2 KiB
44 lines
1.2 KiB
import pandas as pd |
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import numpy as np |
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import pickle as pkl |
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data_folder = "../data/" |
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stim_file = "Stiminfo_PVCre_2021_0012_s06_e14.csv" |
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stim = pd.read_csv(data_folder+stim_file) |
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spike_times_file = "Spiketimes_PVCre_2021_0012_s06_e14.npy" |
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spike_times = np.load(data_folder+spike_times_file, allow_pickle=True) |
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active = [len(spike_times[i]) > 0 for i in range(len(spike_times))] |
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spike_times = spike_times[np.where(active)] |
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num_unit = len(spike_times) |
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num_trial = len(stim) |
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# sort by firing rate |
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num_spike = list(map(len, spike_times)) |
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# num_spike = np.array([len(spike_times[i]) for i in range(len(spike_times))]) |
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spike_times = spike_times[np.argsort(num_spike)[::-1]] |
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files = ['stim_data.pkl', 'spike_data.pkl', 'corr_data.pkl'] |
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for file_name in files: |
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print(file_name) |
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file = open(file_name, 'rb') |
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data = pkl.load(file) |
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print(data.keys()) |
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for key, value in data.items(): |
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globals()[key] = value |
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file.close() |
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def pkl_save(filename:str, object:object): |
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file = open(filename+'.pkl', 'wb') |
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pkl.dump(object, file, pkl.HIGHEST_PROTOCOL) |
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file.close() |
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def pkl_load(filename:str): |
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file = open(filename+'.pkl', 'rb') |
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a = pkl.load(file) |
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file.close() |
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return a |