monkey-business/preprocessing.py at master · cli1903/monkey-business · GitHub

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-

from scipy.io import loadmat
from scipy.interpolate import interp1d
import numpy as np

"""
Created on Thu Nov 21 16:18:16 2019

@author: cindyli
"""

def get_data(file):
    monkey = loadmat(file)

    kin = monkey["KIN"]
    kin_time = monkey["kin_times"]
    spike = monkey["spikes"]

    bin_size = 0.1

    aligned = []
    spks = []


    for i in range(6):

        trial_stack = []
        trial_motion = []

        start_bins = np.arange(np.min(kin_time[:,i][0]), np.max(kin_time[:,i][0]), bin_size)

        tk = kin[:,i][0]


        spkcounts = []
        for j in range(260):
            spkcounts.append((np.histogram(spike[0][i][0][j], start_bins)[0])[1:].tolist())

        bintime = start_bins[2:]
        f = interp1d(kin_time[:,i][0][0], tk)

        kin_move = f(bintime)

        aligned.append(kin_move)
        spks.append(spkcounts)

        #print(np.array(spkcounts).shape)


        for j in range(0, len(bintime), 10):
            if j + 10 >= len(bintime):
                break
            trial_stack.append(np.array(spkcounts)[:, j:j+10])
            trial_motion.append(np.array(kin_move)[:, j + 10])


        if i == 0:
            stacked_bins = np.array(trial_stack)
            motion_labels = np.array(trial_motion)
        else:
            stacked_bins = np.vstack((stacked_bins, np.array(trial_stack)))
            motion_labels = np.vstack((motion_labels, np.array(trial_motion)))

    stacked_bins = np.transpose(stacked_bins.astype('float32'), axes = [0, 2, 1])
    motion_labels = motion_labels.astype('float32')

    #print(stacked_bins.shape)

    return stacked_bins, motion_labels

monkey1 = 'COS071212_MOCAP.mat'
#monkey2 = 'GAR080710_MOCAP.mat'

#monkey = loadmat(monkey1)


x, y = get_data(monkey1)

print(x.shape)
print(y.shape)