def test_featureselector():
trajectories = AlanineDipeptide().get_cached().trajectories
fs = FeatureSelector(FEATS, which_feat='phi')
assert fs.which_feat == ['phi']
y1 = fs.partial_transform(trajectories[0])
y_ref1 = FEATS[0][1].partial_transform(trajectories[0])
np.testing.assert_array_almost_equal(y_ref1, y1)
def test_featureselector():
trajectories = AlanineDipeptide().get_cached().trajectories
fs = FeatureSelector(FEATS, which_feat="phi")
assert fs.which_feat == ["phi"]
y1 = fs.partial_transform(trajectories[0])
y_ref1 = FEATS[0][1].partial_transform(trajectories[0])
np.testing.assert_array_almost_equal(y_ref1, y1)
def test_variancethreshold_vs_sklearn():
trajectories = AlanineDipeptide().get_cached().trajectories
fs = FeatureSelector(FEATS)
vt = VarianceThreshold(0.1)
vtr = VarianceThresholdR(0.1)
y = fs.partial_transform(trajectories[0])
z1 = vt.fit_transform([y])[0]
z_ref1 = vtr.fit_transform(y)
np.testing.assert_array_almost_equal(z_ref1, z1)
def test_variancethreshold_vs_sklearn():
trajectories = AlanineDipeptide().get_cached().trajectories
fs = FeatureSelector(FEATS)
vt = VarianceThreshold(0.1)
vtr = VarianceThresholdR(0.1)
y = fs.partial_transform(trajectories[0])
z1 = vt.fit_transform([y])[0]
z_ref1 = vtr.fit_transform(y)
np.testing.assert_array_almost_equal(z_ref1, z1)
