def setUpClass(cls):
path = pkg_resources.resource_filename(__name__, 'data') + os.path.sep
cls.pdb_file = os.path.join(path, 'bpti_ca.pdb')
cls.feat = MDFeaturizer(cls.pdb_file)
cls.feat.add_all()
cls.traj_files = [
os.path.join(path, 'bpti_001-033.xtc'),
os.path.join(path, 'bpti_067-100.xtc')
]
# generate HMM with two gaussians
p = np.array([[0.99, 0.01], [0.01, 0.99]])
t = 10000
means = [np.array([-1, 1]), np.array([1, -1])]
widths = [np.array([0.3, 2]), np.array([0.3, 2])]
# continuous trajectory
x = np.zeros((t, 2))
# hidden trajectory
dtraj = MarkovStateModel(p).simulate(t)
for t in range(t):
s = dtraj[t]
x[t, 0] = widths[s][0] * np.random.randn() + means[s][0]
x[t, 1] = widths[s][1] * np.random.randn() + means[s][1]
cls.generated_data = x
cls.generated_lag = 10
def setUpClass(cls):
path = os.path.join(os.path.split(__file__)[0], 'data')
cls.pdb_file = os.path.join(path, 'bpti_ca.pdb')
cls.feat = MDFeaturizer(cls.pdb_file)
cls.feat.add_all()
cls.traj_files = [
os.path.join(path, 'bpti_001-033.xtc'),
os.path.join(path, 'bpti_067-100.xtc')
]
# generate HMM with two gaussians
p = np.array([[0.99, 0.01], [0.01, 0.99]])
t = 10000
means = [np.array([-1, 1]), np.array([1, -1])]
widths = [np.array([0.3, 2]), np.array([0.3, 2])]
# continuous trajectory
x = np.zeros((t, 2))
# hidden trajectory
dtraj = msmgen.generate_traj(p, t)
for t in range(t):
s = dtraj[t]
x[t, 0] = widths[s][0] * np.random.randn() + means[s][0]
x[t, 1] = widths[s][1] * np.random.randn() + means[s][1]
cls.generated_data = x
cls.generated_lag = 10
def test_read_single_file_featurizer(self):
featurizer = MDFeaturizer(self.pdb_file)
reader = api.source(self.traj_files[0], features=featurizer)
self.assertIsNotNone(reader, "The reader should not be none.")
self.assertEqual(reader.topfile, self.pdb_file, "Reader topology file and input topology file should coincide.")
self.assertListEqual(reader.trajfiles, [self.traj_files[0]], "Reader trajectories and input"
" trajectories should coincide.")
self.assertEqual(reader.featurizer.topologyfile, self.pdb_file, "Featurizers topology file and input "
"topology file should coincide.")
def test_invalid_input(self):
# neither featurizer nor topology file given
self.assertRaises(ValueError, api.source, self.traj_files, None, None)
# no input files but a topology file
self.assertRaises(ValueError, api.source, None, None, self.pdb_file)
featurizer = MDFeaturizer(self.pdb_file)
# no input files but a featurizer
self.assertRaises(ValueError, api.source, None, featurizer, None)
# empty list of input files
self.assertRaises(ValueError, api.source, [], None, self.pdb_file)
# empty tuple of input files
self.assertRaises(ValueError, api.source, (), None, self.pdb_file)