def plot_animation_each_neuron(name_s, save_name, print_loss=False):
"""Plot the movie for all the networks in the information plane"""
# If we want to print the loss function also
#The bins that we extened the x axis of the accuracy each time
epochs_bins = [0, 500, 1500, 3000, 6000, 10000, 20000]
data_array = utils.get_data(name_s[0][0])
data = np.squeeze(data_array['information'])
f, (axes) = plt.subplots(1, 1)
axes = [axes]
f.subplots_adjust(left=0.14, bottom=0.1, right=.928, top=0.94, wspace=0.13, hspace=0.55)
colors = LAYERS_COLORS
#new/old version
Ix = np.squeeze(data[0,:, :, :])
Iy = np.squeeze(data[1,:, :, :])
#Interploation of the samplings (because we don't cauclaute the infomration in each epoch)
#interp_data_x = interp1d(epochsInds, Ix, axis=1)
#interp_data_y = interp1d(epochsInds, Iy, axis=1)
#new_x = np.arange(0,epochsInds[-1])
#new_data = np.array([interp_data_x(new_x), interp_data_y(new_x)])
""""
train_data = interp1d(epochsInds, np.squeeze(train_data), axis=1)(new_x)
test_data = interp1d(epochsInds, np.squeeze(test_data), axis=1)(new_x)
if print_loss:
loss_train_data = interp1d(epochsInds, np.squeeze(loss_train_data), axis=1)(new_x)
loss_test_data=interp1d(epochsInds, np.squeeze(loss_test_data), axis=1)(new_x)
"""
line_ani = animation.FuncAnimation(f, update_line_each_neuron, Ix.shape[1], repeat=False,
interval=1, blit=False, fargs=(print_loss, Ix, axes,Iy,train_data,test_data,epochs_bins, loss_train_data,loss_test_data, colors,epochsInds))
Writer = animation.writers['ffmpeg']
writer = Writer(fps=100)
#Save the movie
line_ani.save(save_name+'_movie.mp4',writer=writer,dpi=250)
plt.show()
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