def test_dimensionality_reduction_specified_dimension(self, ens1, ens2):
dimension = 3
coordinates, details = encore.reduce_dimensionality(
[ens1, ens2],
method=encore.StochasticProximityEmbeddingNative(dimension=dimension))
assert_equal(coordinates.shape[0], dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".format(coordinates))
def test_dimensionality_reduction_two_methods(self, ens1, ens2):
dims = [2, 3]
coordinates, details = \
encore.reduce_dimensionality(
[ens1, ens2],
method=[encore.StochasticProximityEmbeddingNative(dims[0]),
encore.StochasticProximityEmbeddingNative(dims[1])])
assert_equal(coordinates[1].shape[0], dims[1])
def test_dimensionality_reduction_one_ensemble(self, ens1):
dimension = 2
coordinates, details = encore.reduce_dimensionality(ens1)
assert_equal(
coordinates.shape[0],
dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".
format(coordinates))
def test_dimensionality_reduction_two_different_methods(self):
dims = [2, 3]
coordinates, details = \
encore.reduce_dimensionality(
[self.ens1, self.ens2],
method=[encore.StochasticProximityEmbeddingNative(dims[0]),
encore.PrincipalComponentAnalysis(dims[1])])
assert_equal(coordinates[1].shape[0], dims[1])
def test_dimensionality_reduction_two_methods(self, ens1, ens2):
dims = [2,3]
coordinates, details = \
encore.reduce_dimensionality(
[ens1, ens2],
method=[encore.StochasticProximityEmbeddingNative(dims[0]),
encore.StochasticProximityEmbeddingNative(dims[1])])
assert_equal(coordinates[1].shape[0], dims[1])
def test_dimensionality_reduction_three_ensembles_two_identical(self,
ens1, ens2):
coordinates, details = \
encore.reduce_dimensionality([ens1, ens2, ens1])
coordinates_ens1 = coordinates[:,np.where(details["ensemble_membership"]==1)]
coordinates_ens3 = coordinates[:,np.where(details["ensemble_membership"]==3)]
assert_almost_equal(coordinates_ens1, coordinates_ens3, decimal=0,
err_msg="Unexpected result in dimensionality reduction: {0}".format(coordinates))
def test_dimensionality_reduction_two_ensembles(self):
dimension = 2
coordinates, details = \
encore.reduce_dimensionality([self.ens1, self.ens2])
assert_equal(
coordinates.shape[0],
dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".
format(coordinates))
def test_dimensionality_reduction_two_different_methods(self, ens1, ens2):
pytest.importorskip('sklearn')
dims = [2,3]
coordinates, details = \
encore.reduce_dimensionality(
[ens1, ens2],
method=[encore.StochasticProximityEmbeddingNative(dims[0]),
encore.PrincipalComponentAnalysis(dims[1])])
assert_equal(coordinates[1].shape[0], dims[1])
def test_dimensionality_reduction_different_method(self, ens1, ens2):
pytest.importorskip('sklearn')
dimension = 3
coordinates, details = \
encore.reduce_dimensionality(
[ens1, ens2],
method=encore.PrincipalComponentAnalysis(dimension=dimension))
assert_equal(coordinates.shape[0], dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".format(coordinates))
def test_dimensionality_reduction_specified_dimension(self, ens1, ens2):
dimension = 3
coordinates, details = encore.reduce_dimensionality(
[ens1, ens2],
method=encore.StochasticProximityEmbeddingNative(
dimension=dimension))
assert_equal(
coordinates.shape[0],
dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".
format(coordinates))
def test_dimensionality_reduction_different_method(self):
dimension = 3
coordinates, details = \
encore.reduce_dimensionality(
[self.ens1, self.ens2],
method=encore.PrincipalComponentAnalysis(dimension=dimension))
assert_equal(
coordinates.shape[0],
dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".
format(coordinates))
def test_dimensionality_reduction_three_ensembles_two_identical(self):
coordinates, details = \
encore.reduce_dimensionality([self.ens1, self.ens2, self.ens1])
coordinates_ens1 = coordinates[:,
np.where(
details["ensemble_membership"] ==
1)]
coordinates_ens3 = coordinates[:,
np.where(
details["ensemble_membership"] ==
3)]
assert_almost_equal(
coordinates_ens1,
coordinates_ens3,
decimal=0,
err_msg="Unexpected result in dimensionality reduction: {0}".
format(coordinates))
import MDAnalysis
import MDAnalysis.analysis.encore as encore
reference_pdb = "structure.pdb"
xtc1 = "AC_NCS_0.xtc"
xtc2 = "AC_NCS_1.xtc"
ens1 = MDAnalysis.Universe(reference_pdb)
ens2 = MDAnalysis.Universe(reference_pdb)
ens1.load_new(xtc1)
ens2.load_new(xtc2)
# loop_ca = u.select_atoms('resid 34-50 and name CA')
coordinates, details = encore.reduce_dimensionality(
[ens1, ens2], selection='resid 34-50 and name CA', ncores=48)
plt.scatter(coordinates[0],
coordinates[1],
color=[["red", "blue"][m - 1]
for m in details["ensemble_membership"]])
plt.savefig("dim_red.png")
def test_dimensionality_reduction_two_ensembles(self, ens1, ens2):
dimension = 2
coordinates, details = \
encore.reduce_dimensionality([ens1, ens2])
assert_equal(coordinates.shape[0], dimension,
err_msg="Unexpected result in dimensionality reduction: {0}".format(coordinates))
