def test_skip(self):
for skip in [0, 3, 13]:
r1 = FeatureReader(self.trajfile, self.topfile)
out_with_skip = r1.get_output(skip=skip)[0]
r2 = FeatureReader(self.trajfile, self.topfile)
out = r2.get_output()[0]
np.testing.assert_almost_equal(out_with_skip, out[skip::],
err_msg="The first %s rows were skipped, but that did not "
"match the rows with skip=0 and sliced by [%s::]" % (skip, skip))
def test_skip_input_list(self):
for skip in [0, 3, 13]:
r1 = FeatureReader([self.trajfile, self.trajfile2], self.topfile)
out_with_skip = r1.get_output(skip=skip)
r2 = FeatureReader([self.trajfile, self.trajfile2], self.topfile)
out = r2.get_output()
np.testing.assert_almost_equal(out_with_skip[0], out[0][skip::],
err_msg="The first %s rows of the first file were skipped, but that did not "
"match the rows with skip=0 and sliced by [%s::]" % (skip, skip))
np.testing.assert_almost_equal(out_with_skip[1], out[1][skip::],
err_msg="The first %s rows of the second file were skipped, but that did not"
" match the rows with skip=0 and sliced by [%s::]" % (skip, skip))
def test_partial_fit(self):
reader = FeatureReader(self.trajnames, self.temppdb, chunksize=10000)
output = reader.get_output()
params = {'dim': self.dim, 'lag': 1001}
ref = api.tica(reader, **params)
partial = api.tica(**params)
for traj in output:
partial.partial_fit(traj)
np.testing.assert_allclose(partial.eigenvalues, ref.eigenvalues, atol=1e-3)
# only compare first two eigenvectors, because we only have two metastable processes
np.testing.assert_allclose(np.abs(partial.eigenvectors[:2]),
np.abs(ref.eigenvectors[:2]), rtol=1e-3, atol=1e-3)