def f2(x, y=None):
if y is None:
return np.cos(5 * x) * np.exp(-x**2)
else:
return np.cos(5 * x) * np.exp(-x**2) * np.exp(-y**2)
N = 30 # number of hidden nodes
tal = 100
#In 1D
x1 = np.linspace(-2, 2, tal)
labels1 = f2(x1)
res = ANN.ANN1D(N, f1)
res.ANN_train(x1, labels1)
y = res.ANN_f_forward(x1)
#In 2D
y2 = np.linspace(-2.5, 2.5, tal)
labels2 = f2(x1, y2)
res2 = ANN.ANN2D(N, f2)
res2.ANN_train([x1, y2], labels2)
z = res2.ANN_f_forward([x1, y2])
for i in range(tal):
print('%g %g %g %g %g %g' %
(x1[i], y2[i], y[i], z[i], f2(x1[i]), f2(x1[i], y2[i])))
def f2(x, y=None):
if y is None:
return (np.cos(5 * x) * np.exp(-x**2))
else:
return (np.cos(5 * x) * np.exp(-x**2) * np.exp(-y**2))
# MAIN
nodes = 30
# 1D
x1 = np.linspace(-2.0, 2.0, 100)
labels1 = f2(x1)
AN1 = ann.ANN1D(nodes, f1)
AN1.ann_train(x1, labels1)
y = AN1.ann_feed_forward(x1)
# 2D
#x2 = linspace(-1.5, 1.5, 100);
y2 = np.linspace(-2.5, 2.5, 100)
labels2 = f2(x1, y2)
AN2 = ann.ANN2D(nodes, f1)
AN2.ann_train([x1, y2], labels2)
z = AN2.ann_feed_forward([x1, y2])
for i in range(100):
print('%g %g %g %g %g %g' %
(x1[i], y2[i], y[i], z[i], f2(x1[i]), f2(x1[i], y2[i])))
