def filter(input, output, **kwargs):
# Load the input streamlines using the requested parameters.
streamlines = load(input)
streamlines.filter(**kwargs)
# Save the streamlines to the output file.
save(streamlines, output)
def merge(inputs, output):
# Load all the input streamlines and merge them.
streamlines_list = [load(i) for i in inputs]
streamlines = reduce(operator.iadd, streamlines_list)
# Save the streamlines to the output file.
save(streamlines, output)
def setUpClass(cls):
"""Generates streamlines files used to test the CLI"""
cls.test_dir = tempfile.TemporaryDirectory()
# A file with all short streamlines.
streamlines = Streamlines([
np.array([[0.0, 0.0, 0.0], [1.0, 0.0, 0.0]]),
np.array([[0.0, 0.0, 0.0], [0.0, 1.0, 0.0]]),
np.array([[0.0, 0.0, 0.0], [0.0, 0.0, 1.0]]),
])
filename = os.path.join(cls.test_dir.name, 'short.trk')
save(streamlines, filename)
# A file with a single random streamline.
streamlines = Streamlines([
np.random.randn(100,3)
])
filename = os.path.join(cls.test_dir.name, 'random.trk')
save(streamlines, filename)
# A file with no streamlines.
streamlines = Streamlines()
filename = os.path.join(cls.test_dir.name, 'empty.trk')
save(streamlines, filename)
# A file with a bundle.
points = np.array([
np.linspace(0, 100, 1000),
np.zeros((1000,)),
np.zeros((1000,))]).T
points_list = [points + np.random.randn(*points.shape)
for _ in range(100)]
streamlines = Streamlines(points_list)
filename = os.path.join(cls.test_dir.name, 'bundle.trk')
save(streamlines, filename)
# Also save the bundle with flipped orientations.
flip = [np.random.rand() < 0.5 for _ in points_list]
flip[0] = False
points_list = [p[::-1] if f else p for f, p in zip(flip, points_list)]
streamlines = Streamlines(points_list)
filename = os.path.join(cls.test_dir.name, 'bundle-flipped.trk')
save(streamlines, filename)
def filter(input_filename, output_filename, **kwargs):
"""Removes streamlines from a file based on features
Removes streamlines from a file based on their features. For example,
remove all streamlines with a length below 50mm using --min-length 50.
Args:
input_filename: The file that contains the streamlines to filter.
output_filename: The file where the remaining streamlines will be
saved.
"""
# Load the input_streamlines using the requested parameters.
streamlines = load(input_filename)
streamlines.filter(**kwargs)
# Save the streamlines to the output file.
save(streamlines, output_filename)
def smooth(input_filename, output_filename, **kwargs):
"""Smooths streamlines in a file
Smooths streamlines using a least square b-spline. The distance between
knots controls the smoothness of the output streamline with larger
distances being smoother
Args:
input_filename: The file that contains the streamlines to smooth.
output_filename: The file where the smoothed streamlines will be saved.
"""
# Load the input streamlines using the requested parameters.
streamlines = load(input_filename)
streamlines.smooth(**kwargs)
# Save the streamlines to the output file.
save(streamlines, output_filename)
def transform(input, output):
"""Transforms streamlines from one fileformat to another"""
streamlines = load(input)
save(streamlines, output)