def test_LearnBeginningMode(self):
""" testing learn_beginning mode.
"""
print("\nDyBMTestCase.testLearnFirstMode")
length = 300
period = 60
std = 0
dim = 1
data = NoisySin(length, period, std, dim).to_list()
print("\nlearn_beginning = True (Default mode)")
for d in xrange(10, 20):
model = BatchLinearDyBM(dim, delay=d, learn_beginning=True)
model.fit(data)
result = model.get_predictions(data)
rmse = RMSE(result[d:], data[d:])
print("Training RMSE", rmse)
self.assertLessEqual(rmse, 0.1)
print("\nlearn_beginning = False")
for d in xrange(10, 20):
model = BatchLinearDyBM(dim, delay=d, learn_beginning=False)
model.fit(data)
result = model.get_predictions(data)
rmse = RMSE(result[d:], data[d:])
print("Training RMSE", rmse)
self.assertLessEqual(rmse, 0.1)
def test_LearnMultiSequences(self):
""" testing learn_beginning mode.
"""
print("\nDyBMTestCase.testLearnMultiSequences")
seqs = list()
for i in xrange(10):
length = 300
period = 60
std = 0.1 * i
dim = 1
data = NoisySin(length, period, std, dim).to_list()
seqs.append(data)
for d in xrange(10, 20):
model = BatchLinearDyBM(dim, delay=d, learn_beginning=True)
model.fit_multi_seqs(seqs)
result = model.get_predictions(seqs[0])
rmse = RMSE(result[d:], seqs[0][d:])
print("Training RMSE", rmse)
self.assertLessEqual(rmse, 0.2)