def main3():
train_X = np.asarray([[0.2, -0.3], [0.1, -0.9]])
train_Y = np.asarray([[0.0, 1.0, 0.0], [0.0, 0.0, 1.0]])
net = ParticleNetwork(cost="mse", particle_input=ParticleInput(2))
net.append(Particle(2, 5, activation="sigmoid"))
net.append(Particle(5, 3, activation="sigmoid"))
print(net.predict(train_X))
with open("/Users/adrianlange/network.json", "w") as f:
net.write_to_json(f)
with open("/Users/adrianlange/network.json", "r") as f:
new_net = ParticleNetwork.read_from_json(f)
print(new_net.predict(train_X))
def main3():
train_X = np.asarray([[0.2, -0.3], [0.1, -0.9]])
train_Y = np.asarray([[0.0, 1.0, 0.0], [0.0, 0.0, 1.0]])
net = ParticleNetwork(cost="mse", particle_input=ParticleInput(2))
net.append(Particle(2, 5, activation="sigmoid"))
net.append(Particle(5, 3, activation="sigmoid"))
print(net.predict(train_X))
with open("/Users/alange/network.json", "w") as f:
net.write_to_json(f)
with open("/Users/alange/network.json", "r") as f:
new_net = ParticleNetwork.read_from_json(f)
print(new_net.predict(train_X))
def main():
# train_X = np.asarray([[0.2, -0.3]])
# train_Y = np.asarray([[0.0, 1.0, 0.0]])
# train_X = np.asarray([{0: 0.45, 1: 3.33}, {1: 2.22}])
train_X = np.asarray([[0.45, 3.33], [0.0, 2.22]])
train_Y = np.asarray([[0.0, 1.0, 0.0], [0.0, 0.0, 1.0]])
net = ParticleNetwork(cost="mse", particle_input=ParticleInput(2, phase_enabled=True))
net.append(Particle(2, 3, activation="sigmoid", phase_enabled=True))
# net.append(Particle(5, 3, activation="sigmoid"))
print(net.particle_input.get_rxyz())
print(net.predict(train_X))
print(net.cost(train_X, train_Y))
def main():
# train_X = np.asarray([[0.2, -0.3]])
# train_Y = np.asarray([[0.0, 1.0, 0.0]])
# train_X = np.asarray([{0: 0.45, 1: 3.33}, {1: 2.22}])
train_X = np.asarray([[0.45, 3.33], [0.0, 2.22]])
# train_Y = np.asarray([[0.0, 1.0, 0.0], [0.0, 0.0, 1.0]])
train_Y = np.asarray([[1.0], [0.0]])
net = ParticleNetwork(cost="mse", particle_input=ParticleInput(2, phase_enabled=True))
net.append(Particle(2, 3, activation="sigmoid", phase_enabled=True))
net.append(Particle(3, 1, activation="sigmoid", phase_enabled=True))
print(net.particle_input.get_rxyz())
print(net.predict(train_X))
print(net.cost(train_X, train_Y))
