def noise(): data_array = pict_data() X0 = data_array[:3] W = hopfield.weights(X0) for x in X0: error = [] for i in range(0, 101, 10): choices = np.random.choice(len(x), size=int(i*len(x)/100), replace=False) x_noise = add_noise(x, choices) error.append(calculate_error(x, hopfield.recall_until_stable(W, x_noise))) print(error) plot.plot_points(error)
def test_random(N=100, should_add_noise=False, should_remove_self_conn=False): data_array = [generate_random(100) for _ in range(300)] errors = [] for n in range(1, N): print(n) X0 = data_array[:n] if should_remove_self_conn: W = hopfield.weights(X0, True) else: W = hopfield.weights(X0) error = [] for x in X0: x_noise = x if should_add_noise: choices = np.random.choice(len(x), size=int(20*len(x)/100), replace=False) x_noise = add_noise(x, choices) error.append(1 if (x == hopfield.recall_until_stable(W, x_noise)).all() else 0) errors.append(sum(error)) print(errors) plot.plot(range(1, N), errors)
def sequential(): data_array = pict_data() X0 = data_array[:3] W = hopfield.weights(X0) X = [data_array[9], data_array[10]] # for x in X0: # plot.plot_heatmap(reformat_data(x)) # plot.plot_heatmap(reformat_data(hopfield.recall_until_stable(W, x))) for x in X: plot.plot_heatmap(reformat_data(x)) plot.plot_heatmap(reformat_data(hopfield.recall_until_stable(W, x))) res_array = hopfield.recall_sequentially(W, x) for r in res_array: plot.plot_heatmap(reformat_data(np.array(r)))
def test_capacity(start, end): data_array = pict_data() errors = [] for n in range(start, end, 1): print(n) X0 = data_array[:n] W = hopfield.weights(X0) error = [] for x in X0: choices = np.random.choice(len(x), size=int(20*len(x)/100), replace=False) x_noise = add_noise(x, choices) error.append(calculate_error(x, hopfield.recall_until_stable(W, x_noise))) errors.append(sum(error)/len(error)) print(errors) plot.plot(range(start, end), errors)
def get_weights():
x1 = [-1, -1, 1, -1, 1, -1, -1, 1]
x2 = [-1, -1, -1, -1, -1, 1, -1, -1]
x3 = [-1, 1, 1, -1, -1, 1, -1, 1]
X = [x1, x2, x3]
return hopfield.weights(X)
import hopfield
if __name__ == "__main__":
x1 = [-1, -1, 1, -1, 1, -1, -1, 1]
x2 = [-1, -1, -1, -1, -1, 1, -1, -1]
x3 = [-1, 1, 1, -1, -1, 1, -1, 1]
X = [x1, x2, x3]
W = hopfield.weights(X)
for x in X:
hopfield.test_stable(W, x)