def test_skip(self):
for skip in [0, 3, 13]:
r1 = NumPyFileReader(self.npy_files[0])
out_with_skip = r1.get_output(skip=skip)[0]
r2 = NumPyFileReader(self.npy_files[0])
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 = NumPyFileReader(self.npy_files)
out_with_skip = r1.get_output(skip=skip)
r2 = NumPyFileReader(self.npy_files)
out = r2.get_output()
for i in range(0, len(self.npy_files)):
np.testing.assert_almost_equal(
out_with_skip[i],
out[i][skip::],
err_msg=
"The first %s rows of the %s'th file were skipped, but that did not "
"match the rows with skip=0 and sliced by [%s::]" %
(skip, i, skip))
def test_stridden_access(self):
reader = NumPyFileReader(self.f1)
reader.chunksize = 10
wanted = np.load(self.f1)
for stride in [2, 3, 5, 7, 15]:
first_traj = reader.get_output(stride=stride)[0]
np.testing.assert_equal(first_traj, wanted[::stride],
"did not match for stride %i" % stride)
def test_stridden_access(self):
reader = NumPyFileReader(self.f1)
reader.chunksize = 10
wanted = np.load(self.f1)
for stride in [2, 3, 5, 7, 15]:
first_traj = reader.get_output(stride=stride)[0]
np.testing.assert_equal(first_traj, wanted[::stride],
"did not match for stride %i" % stride)
def test_only_npy(self):
reader = NumPyFileReader(self.npy_files)
from_files = [np.load(f) for f in self.npy_files]
concatenated = np.vstack(from_files)
output = reader.get_output()
self.assertEqual(reader.number_of_trajectories(), len(self.npy_files))
self.assertEqual(reader.n_frames_total(), concatenated.shape[0])
for x, y in zip(output, from_files):
np.testing.assert_array_almost_equal(x, y)
def test_npz(self):
reader = NumPyFileReader(self.npz)
all_data = reader.get_output()
fh = np.load(self.npz)
data = [x[1] for x in list(fh.items())]
fh.close()
self.assertEqual(reader.number_of_trajectories(), len(data))
for outp, inp in zip(all_data, data):
np.testing.assert_equal(outp, inp)
def test_npz(self):
reader = NumPyFileReader(self.npz)
all_data = reader.get_output()
fh = np.load(self.npz)
data = [x[1] for x in fh.items()]
fh.close()
self.assertEqual(reader.number_of_trajectories(), len(data))
for outp, inp in zip(all_data, data):
np.testing.assert_equal(outp, inp)
def test_only_npy(self):
reader = NumPyFileReader(self.npy_files)
from_files = [np.load(f) for f in self.npy_files]
concatenated = np.vstack(from_files)
output = reader.get_output()
self.assertEqual(reader.number_of_trajectories(), len(self.npy_files))
self.assertEqual(reader.n_frames_total(), concatenated.shape[0])
for x, y in zip(output, from_files):
np.testing.assert_array_almost_equal(x, y)
def load_from_files(cls, files):
""" construct this by loading all files into memory
Parameters
----------
files: str or list of str
filenames to read from
"""
# import here to avoid cyclic import
from pyemma.coordinates.data.numpy_filereader import NumPyFileReader
reader = NumPyFileReader(files)
data = reader.get_output()
return cls(data)
def load_from_files(cls, files):
""" construct this by loading all files into memory
Parameters
----------
files: str or list of str
filenames to read from
"""
# import here to avoid cyclic import
from pyemma.coordinates.data.numpy_filereader import NumPyFileReader
reader = NumPyFileReader(files)
data = reader.get_output()
return cls(data)
