def test_nonan_nomask(self):
dmd = HODMD(d=3)
dmd.fit(X=sample_data)
for timeindex in range(sample_data.shape[1]):
ds = dmd.reconstructions_of_timeindex(timeindex)
for mx in ds:
assert not np.ma.is_masked(mx)
assert np.nan not in mx
def test_rec_method_weighted(self):
dmd = HODMD(d=2, reconstruction_method=[10, 20])
dmd.fit(X=sample_data)
assert (dmd.reconstructed_data.T[4] == np.average(
dmd.reconstructions_of_timeindex(4), axis=0,
weights=[10, 20]).T).all()
def test_rec_method_mean(self):
dmd = HODMD(d=3, reconstruction_method='mean')
dmd.fit(X=sample_data)
assert (dmd.reconstructed_data.T[2] == np.mean(
dmd.reconstructions_of_timeindex(2), axis=0).T).all()
def test_rec_method_first(self):
dmd = HODMD(d=3, reconstruction_method='first')
dmd.fit(X=sample_data)
assert (dmd.reconstructed_data == dmd.reconstructions_of_timeindex()
[:, 0].T).all()
def test_extract_versions_nonan(self):
dmd = HODMD(d=3)
dmd.fit(X=sample_data)
for timeindex in range(sample_data.shape[1]):
assert not np.nan in dmd.reconstructions_of_timeindex(timeindex)