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phasenn
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Code Issues Releases Wiki Activity

restored to original NN model

master
David 2019-12-21 14:04:28 +10:30
parent d2039fd4b7
commit 628dca7638
1 changed files with 16 additions and 12 deletions
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28
rateK_train.py
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@ -84,20 +84,19 @@ for i in range(0,nb_samples-dec,dec):
nv += 1
print(inputs.shape, outputs.shape)
nn = 0
nn = 1
if nn:
# our model
model = models.Sequential()
model.add(layers.Dense(3*newamp1_K, input_dim=2*newamp1_K))
#model.add(layers.Dense(3*newamp1_K, activation='relu', input_dim=2*newamp1_K))
#model.add(layers.Dense(3*newamp1_K, activation='relu'))
#model.add(layers.Dense(3*newamp1_K))
model.add(layers.Dense(3*newamp1_K, activation='tanh', input_dim=2*newamp1_K))
model.add(layers.Dense(3*newamp1_K, activation='tanh'))
model.add(layers.Dense(3*newamp1_K))
model.summary()
# fit the model
from keras import optimizers
sgd = optimizers.SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='mse', optimizer=sgd)
#sgd = optimizers.SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='mse', optimizer="adam")
history = model.fit(inputs, outputs, batch_size=nb_batch, epochs=args.epochs, validation_split=0.1)
# test the model on the training data
@ -114,7 +113,8 @@ if nn:
# plot results over all frames
var_lin = np.var(20*outputs-20*outputs_lin)
var_linpf = np.var(20*outputs-20*outputs_linpf)
print("var_lin: %3.2f var_linpf: %3.2f" % (var_lin, var_linpf))
var_nnest = np.var(20*outputs-20*outputs_nnest)
print("var_lin: %3.2f var_linpf: %3.2f var_nnest: %3.2f" % (var_lin, var_linpf, var_nnest))
# plot results for a few frames
@ -137,16 +137,20 @@ while loop:
st = (d-1)*newamp1_K
plt.plot(outputs[frame,st:st+newamp1_K],'g')
plt.plot(outputs_lin[frame,st:st+newamp1_K],'b')
plt.plot(outputs_linpf[frame,st:st+newamp1_K],'r')
if nn:
plt.plot(outputs_nnest[frame,st:st+newamp1_K],'r')
else:
plt.plot(outputs_linpf[frame,st:st+newamp1_K],'r')
plt.ylim((-1,4))
var_lin = np.var(20*outputs[frame,:]-20*outputs_lin[frame,:])
var_linpf = np.var(20*outputs[frame,:]-20*outputs_linpf[frame,:])
print("frame: %d var_lin: %3.2f var_linpf: %3.2f" % (frame,var_lin, var_linpf), end='')
print("frame: %d var_lin: %3.2f " % (frame,var_lin), end='')
if nn:
var_nnest = np.var(20*outputs[frame,:]-20*outputs_est[frame,:])
print("var_nn-est: %3.2f" % (var_nnest))
var_nnest = np.var(20*outputs[frame,:]-20*outputs_nnest[frame,:])
print("var_nnest: %3.2f" % (var_nnest), end='')
else:
print("var_linpf: %3.2f" % (var_linpf), end='')
print(flush=True)
plt.show(block=False)