def test_splines():
# create a helix
t = np.linspace(0, 1.75 * 2 * np.pi, 100)
x = np.sin(t)
y = np.cos(t)
z = t
# add noise
x += np.random.normal(scale=0.1, size=x.shape)
y += np.random.normal(scale=0.1, size=y.shape)
z += np.random.normal(scale=0.1, size=z.shape)
xyz = np.vstack((x, y, z)).T
# get the B-splines smoothed result
tm.spline(xyz, 3, 2, -1)
def test_splines():
# create a helix
t = np.linspace(0, 1.75*2*np.pi, 100)
x = np.sin(t)
y = np.cos(t)
z = t
# add noise
x += np.random.normal(scale=0.1, size=x.shape)
y += np.random.normal(scale=0.1, size=y.shape)
z += np.random.normal(scale=0.1, size=z.shape)
xyz = np.vstack((x, y, z)).T
# get the B-splines smoothed result
tm.spline(xyz, 3, 2, -1)
def convert_tck_to_trk(filename_in,
filename_out,
reference_affine,
reference_shape,
compress_err_thr=0.1,
smooth=None,
nr_cpus=-1,
tracking_format="trk_legacy"):
streamlines = nib.streamlines.load(
filename_in).streamlines # Load Fibers (Tck)
if smooth is not None:
streamlines_smooth = []
for sl in streamlines:
streamlines_smooth.append(spline(sl, s=smooth))
streamlines = streamlines_smooth
#Compressing also good to remove checkerboard artefacts from tracking on peaks
if compress_err_thr is not None:
streamlines = compress_streamlines(streamlines,
compress_err_thr,
nr_cpus=nr_cpus)
if tracking_format == "trk_legacy":
save_streamlines_as_trk_legacy(filename_out, streamlines,
reference_affine, reference_shape)
else:
save_streamlines(filename_out, streamlines, reference_affine,
reference_shape)
def convert_tck_to_trk(filename_in, filename_out, reference_affine, compress_err_thr=0.1, smooth=None):
'''
Convert tck file to trk file and compress
:param filename_in:
:param filename_out:
:param compress_err_thr: compress fibers if setting error threshold here (default: 0.1mm)
:param smooth: smooth streamlines (default: None)
10: slight smoothing, 100: very smooth from beginning to end
:return:
'''
#Hide large number of nipype logging outputs
from nipype import config, logging
config.set('execution', 'remove_unnecessary_outputs', 'true')
config.set('logging', 'workflow_level', 'WARNING')
config.set('logging', 'interface_level', 'WARNING')
logging.update_logging(config)
from nipype.interfaces.mrtrix.convert import read_mrtrix_tracks
from dipy.tracking.metrics import spline
hdr, streamlines = read_mrtrix_tracks(filename_in, as_generator=False) # Load Fibers (Tck)
if smooth is not None:
streamlines_smooth = []
for sl in streamlines:
streamlines_smooth.append(spline(sl, s=smooth))
streamlines = streamlines_smooth
#Compressing also good to remove checkerboard artefacts from tracking on peaks
if compress_err_thr is not None:
streamlines = FiberUtils.compress_streamlines(streamlines, compress_err_thr)
FiberUtils.save_streamlines_as_trk(filename_out, streamlines, reference_affine)
def convert_tck_to_trk(filename_in, filename_out, reference_affine, reference_shape,
compress_err_thr=0.1, smooth=None, nr_cpus=-1, tracking_format="trk_legacy"):
'''
Convert tck file to trk file and compress
:param filename_in:
:param filename_out:
:param compress_err_thr: compress fibers if setting error threshold here (default: 0.1mm)
:param smooth: smooth streamlines (default: None)
10: slight smoothing, 100: very smooth from beginning to end
:param nr_cpus:
:return:
'''
from dipy.tracking.metrics import spline
streamlines = nib.streamlines.load(filename_in).streamlines # Load Fibers (Tck)
if smooth is not None:
streamlines_smooth = []
for sl in streamlines:
streamlines_smooth.append(spline(sl, s=smooth))
streamlines = streamlines_smooth
#Compressing also good to remove checkerboard artefacts from tracking on peaks
if compress_err_thr is not None:
streamlines = compress_streamlines(streamlines, compress_err_thr, nr_cpus=nr_cpus)
if tracking_format == "trk_legacy":
save_streamlines_as_trk_legacy(filename_out, streamlines, reference_affine, reference_shape)
else:
save_streamlines(filename_out, streamlines, reference_affine, reference_shape)
def smooth_streamlines(streamlines, smoothing_factor=10):
"""
Args:
streamlines:
smoothing_factor: 10: slight smoothing, 100: very smooth from beginning to end
Returns:
"""
streamlines_smooth = []
for sl in streamlines:
streamlines_smooth.append(spline(sl, s=smoothing_factor))
return streamlines_smooth
def convert_tck_to_trk(filename_in,
filename_out,
reference_affine,
compress_err_thr=0.1,
smooth=None):
'''
Convert tck file to trk file and compress
:param filename_in:
:param filename_out:
:param compress_err_thr: compress fibers if setting error threshold here (default: 0.1mm)
:param smooth: smooth streamlines (default: None)
10: slight smoothing, 100: very smooth from beginning to end
:return:
'''
#Hide large number of nipype logging outputs
from nipype import config, logging
config.set('execution', 'remove_unnecessary_outputs', 'true')
config.set('logging', 'workflow_level', 'WARNING')
config.set('logging', 'interface_level', 'WARNING')
logging.update_logging(config)
from nipype.interfaces.mrtrix.convert import read_mrtrix_tracks
from dipy.tracking.metrics import spline
hdr, streamlines = read_mrtrix_tracks(
filename_in, as_generator=False) # Load Fibers (Tck)
if smooth is not None:
streamlines_smooth = []
for sl in streamlines:
streamlines_smooth.append(spline(sl, s=smooth))
streamlines = streamlines_smooth
#Compressing also good to remove checkerboard artefacts from tracking on peaks
if compress_err_thr is not None:
streamlines = FiberUtils.compress_streamlines(
streamlines, compress_err_thr)
FiberUtils.save_streamlines_as_trk(filename_out, streamlines,
reference_affine)
