def test(self):
args, metric = Cluster.parser.parse_args([
'-p', get('points_on_cube/ProjectInfo.yaml', just_filename=True),
'-o', self.td,
'rmsd', '-a', get('points_on_cube/AtomIndices.dat', just_filename=True),
'hybrid', '-k', '4'], print_banner=False)
Cluster.main(args, metric)
def test(self):
args, metric = Cluster.parser.parse_args([
'-p', get('ProjectInfo.yaml', just_filename=True),
'-s', '10',
'-o', self.td,
'rmsd', '-a', get('AtomIndices.dat', just_filename=True),
'hierarchical'],
print_banner=False)
Cluster.main(args, metric)
eq(load(pjoin(self.td, 'ZMatrix.h5')), get('ZMatrix.h5'))
def test(self):
args, metric = Cluster.parser.parse_args([
'-p', get('ProjectInfo.yaml', just_filename=True),
'-o', self.td,
'rmsd', '-a', get('AtomIndices.dat', just_filename=True),
'kcenters', '-k', '100'], print_banner=False)
Cluster.main(args, metric)
eq(load(pjoin(self.td, 'Assignments.h5')),
get('Assignments.h5'))
eq(load(pjoin(self.td, 'Assignments.h5.distances')),
get('Assignments.h5.distances'))
eq(load(pjoin(self.td, 'Gens.lh5')),
get('Gens.lh5'))
def test(self):
args, metric = Cluster.parser.parse_args([
'-p', get('points_on_cube/ProjectInfo.yaml', just_filename=True),
'-o', self.td,
'rmsd', '-a', get('points_on_cube/AtomIndices.dat', just_filename=True),
'kcenters', '-k', '4'], print_banner=False)
Cluster.main(args, metric)
assignments = load(pjoin(self.td, 'Assignments.h5'))["arr_0"]
assignment_counts = np.bincount(assignments.flatten())
eq(assignment_counts, np.array([2, 2, 2, 2]))
distances = load(pjoin(self.td, 'Assignments.h5.distances'))["arr_0"]
eq(distances, np.zeros((1,8)))
def test(self):
try:
import fastcluster
except ImportError:
raise nose.SkipTest("Cannot find fastcluster, so skipping hierarchical clustering test.")
args, metric = Cluster.parser.parse_args([
'-p', get('ProjectInfo.yaml', just_filename=True),
'-s', '10',
'-o', self.td,
'rmsd', '-a', get('AtomIndices.dat', just_filename=True),
'hierarchical'],
print_banner=False)
Cluster.main(args, metric)
eq(load(pjoin(self.td, 'ZMatrix.h5')), get('ZMatrix.h5'))
def test(self):
if os.getenv('TRAVIS', None) == 'true':
raise nose.SkipTest('Skipping test_Assign on TRAVIS')
try:
import fastcluster
except ImportError:
raise nose.SkipTest("Cannot find fastcluster, so skipping hierarchical clustering test.")
args, metric = Cluster.parser.parse_args([
'-p', get('ProjectInfo.yaml', just_filename=True),
'-s', '10',
'-o', self.td,
'rmsd', '-a', get('AtomIndices.dat', just_filename=True),
'hierarchical'],
print_banner=False)
Cluster.main(args, metric)
eq(load(pjoin(self.td, 'ZMatrix.h5')), get('ZMatrix.h5'))
