import numpy as np

import autocorrelation

import matplotlib.pyplot as plt

import input_neuron

SUB_DIR = './results/9M'

FILE = 'weights.npz'

f = np.load(SUB_DIR + '/' + FILE)

network_size = (100, 400)

arr = f['arr_0']

(no_rows, no_cols) = np.shape(arr)

last_weights = np.reshape(arr[no_rows-1,:], (network_size[0], 400), order='F')

for i in range(network_size[0]):

weights = input_neuron.reshape_vec_to_grid(last_weights[i,:])

plt.matshow(weights)

plt.colorbar()

plt.title('Weights of neuron ' + str(i))

plt.savefig(SUB_DIR + '/neuron_w_' + str(i) +'.png', format="png")

plt.close()

plt.matshow(autocorrelation.autocorrelation_normalized(weights))

plt.colorbar()

plt.title('Autocorr. of neuron ' + str(i))

plt.savefig(SUB_DIR + '/neuron_a_' + str(i) +'.png', format="png")

plt.close()