def test_duplicated_data_in_fit_transform(self):
X = np.random.randn(100, 2)
d = DataInMemory([X, X])
tica = api.tica(data=d, lag=1, dim=1)
out1 = tica.get_output()
out2 = tica.fit_transform([X, X])
np.testing.assert_array_almost_equal(out1, out2)
def perform(chunksize, stride):
try:
transformed_output = tica.get_output(chunk=chunksize, stride=stride)
tica.write_to_hdf5(out, group=group, chunksize=chunksize, stride=stride)
import h5py
with h5py.File(out) as f:
assert len(f[group]) == len(data)
for (itraj, actual), desired in zip(f[group].items(), transformed_output):
np.testing.assert_equal(actual, desired, err_msg='failed for cs=%s, stride=%s'
%(chunksize, stride))
finally:
os.remove(out)
