API changes¶
Here we provide information about functions or classes that have been removed, renamed or are deprecated (not recommended) during different release circles.
Dipy 0.10 Changes¶
** New visualization module**
fvtk.slicer
input parameters have changed. Now the slicer function is
more powerfull and supports RGB images too. See tutorial viz_slice.py
for
more information.
Interpolation The default behavior of the function core.sphere.interp_rbf has changed. The default smoothing parameter is now set to 0.1 (previously 0). In addition, the default norm is now angle (was previously euclidean_norm). Note that the use of euclidean_norm is discouraged, and this norm will be deprecated in the 0.11 release cycle.
Registration
The following utilty functions from vector_fields
module were renamed:
warp_2d_affine
is now transform_2d_affine
warp_2d_affine_nn
is now transform_2d_affine_nn
warp_3d_affine
is now transform_3d_affine
warp_3d_affine_nn
is now transform_3d_affine_nn
Dipy 0.9 Changes¶
GQI integration length
Calculation of integration length in GQI2 now matches the calculation in the ‘standard’ method. Using values of 1-1.3 for either is recommended (see docs and references therein).
Dipy 0.8 Changes¶
Peaks
The module peaks
is now available from dipy.direction
and it can still
be accessed from dipy.reconst
but it will be completelly removed in version
0.10.
Resample
The function resample
from dipy.align.aniso2iso
is deprecated. Please,
use instead reslice
from dipy.align.reslice
. The module aniso2iso
will be completely removed in version 0.10.
Changes between 0.7.1 and 0.6¶
Peaks_from_model
The function peaks_from_model
is now available from dipy.reconst.peaks
. Please replace all imports like
from dipy.reconst.odf import peaks_from_model
with
from dipy.reconst.peaks import peaks_from_model
Target
The function target
from dipy.tracking.utils
now takes an affine
transform instead of a voxel sizes array. Please update all code using
target
in a way similar to this
img = nib.load(anat)
voxel_dim = img.get_header()['pixdim'][1:4]
streamlines = utils.target(streamlines, img.get_data(), voxel_dim)
to something similar to
img = nib.load(anat)
streamlines = utils.target(streamlines, img.get_data(), img.get_affine())