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 1.10.0 changes#
General
PEP 3102 (Keyword-only arguments) has been implemented in the codebase. This means that all the functions/classes that have keyword-only arguments will raise a warning if the user tries to call them with positional arguments.
Standardized the symbols for the spherical harmonic concepts of order and phase factor with
l_value
andm_value
, respectively. In case these are arrays, we usel_values
andm_values
to be more informative of the type of the variable. For a spherical harmonic 𝑌ℓ𝑚, ℓ is referred to as the order and 𝑚 as phase factor. The parametersh_order
in the codebase becamesh_order_max
.
Align
The alpha parameter in the BundleWarp method has been updated to provide better result for the bundle warping. The default value of alpha has been changed from 0.3 to 0.5.
IO
The
dipy.io.peaks.save_peaks
anddipy.io.peaks.load_peaks
functions have been deprecated. Please Use thedipy.io.peaks.save_pam
anddipy.io.peaks.load_pam
functions instead.
Reconstruction
Applied the change of the default cvxpy solver from ECOS to CLARABEL. Starting in CXVPY 1.6.0, ECOS will no longer be installed by default with CVXPY. Since we do not want to add an explicit dependency on ECOS, we switched to the new default solver, Clarabel.
Workflows
The vol_idx parameter datatype from
dipy_median_otsu
has been changed from variable int to str. this change allows user to provide a range of values for the vol_idx parameter. e.g: –vol_idx 0,1,2 or –vol_idx 4,5,12-20,22.The odf_to_sh_order parameter has been removed from multiple workflows. The parameter was not being used and was causing confusion with the sh_order_order parameter.
NN
A new backend has been added: PyTorch. This backend is becoming the default backend for the NN module. Tensorflow backend is still available but deprecated.
DIPY 1.9.0 changes#
General
The module
dipy.boots.resampling
has moved todipy.stats.resampling
.The package
dipy.boots
has been removed.FURY minimum version is 0.10.0.
Multiple deprecated parameters have been removed from the codebase.
IO
dipy.io.bvectxt
module is removed
DIPY 1.8.0 changes#
Gradients
Change in
dipy.core.gradients
, functionreorient_bvecs
now requires the affine to have a shape of (4, 4, n) or (3, 3, n)
Direction
- Change in
dipy.direction.bootstrap_direction_getter
. The parent class was changes from
PmfGenDirectionGetter
toDirectionGetter
. TheBootPmfGen
functions were merged inBootDirectionGetter
.The class constructor parameter pmfgen was removed. Parameters data, model and sh_order=0 were added.
The class method BootDirectionGetter.from_data() was not changed.
- Change in
Change in
dipy.direction.pmf
. The classBootPmfGen
was removed; its functions were merged inBootDirectionGetter
.
DIPY 1.7.0 changes#
Denoising
Change in
dipy.denoise.localpca
, functiongenpca
can use fewer images than patch voxels.Change in
dipy.denoise.pca_noise_estimate
, functionpca_noise_estimate
has new argumentimages_as_samples
DIPY 1.6.0 changes#
DIPY 1.5.0 changes#
General
FURY minimum version is 0.8.0
Distutils has been dropped
dipy.io.bvectxt
module is deprecated and will be removed
Denoising
The default option in the command line for Patch2Self ‘ridge’ -> ‘ols’
Tracking
- Change in
dipy.tracking.pmf
The parent class
PmfGen
has new mandatory parametersphere
. The sphere vertices correspond to the spherical distribution of the pmf values.The parent class
PmfGen
has new functionget_pmf_value(point, xyz)
which return the pmf value at locationpoint
and orientationxyz
.
- Change in
Segment
The deprecated
from dipy.segment.metric import ResampleFeature
was removed and replaced byfrom dipy.segment.featurespeed import ResampleFeature
.
DIPY 1.4.1 changes#
General
- The name of the argument for the number of cores/threads has been standardized to:
num_threads
for OpenMP parallelization.num_processes
for parallelization using multiprocessing package.
- Change in the parallelization logic when using OpenMP:
If
num_threads = None
the value ofOMP_NUM_THREADS
environment variable is used. If it is not set then all available threads are used.If
num_threads > 0
that number is used as the number of threads.If
num_threads < 0
the maximum between1
andnum_cpu_cores - |num_threads + 1|
is selected. If-1
then all available threads are used.If
num_threads = 0
an error is raised.
- Change in the parallelization logic when using multiprocessing package:
The same as with OpenMP with the difference that
num_processes = None
uses all cores directly.
Tracking
- Change in DirectionGetters:
The deprecated
dipy.direction.closest_peak_direction_getter.BaseDirectionGetter
was removed and replaced bydipy.direction.closest_peak_direction_getter.BasePmfDirectionGetter
.The deprecated
dipy.reconst.EuDXDirectionGetter
was removed and replaced bydipy.reconst.eudx_direction_getter.EuDXDirectionGetter
.
DIPY 1.4.0 changes#
Migration from Tavis to Azure
DIPY 1.3.0 changes#
new dependency added: tqdm
Registration
The argument interp of the method dipy.align.imaffine.AffineMap.transform has been renamed interpolation.
The argument interp of the method dipy.align.imaffine.AffineMap.transform_inverse has been renamed interpolation.
Segmentation
The tissue segmentation method
dipy.segment.TissueClassifierHMRF
now checks the tolerance-based stopping criterion at every iteration (previously it was only checked every 10th iteration). This may result in earlier termination of iterations than with previous releases.
DIPY 1.2.0 changes#
Reconstruction
The dipy.reconst.csdeconv.auto_response
has been renamed
dipy.reconst.csdeconv.auto_response_ssst
.
The dipy.reconst.csdeconv.response_from_mask
has been renamed
dipy.reconst.csdeconv.response_from_mask_ssst
.
The dipy.sims.voxel.multi_shell_fiber_response
has been moved to
dipy.reconst.mcsd.multi_shell_fiber_response
.
Segmentation
In prior releases, for users with SciPy < 1.5, a memory overlap bug occurs in
multi_median
, causing an overly smooth output. This has now been fixed,
regardless of the user’s installed SciPy version. Users of this function via
median_otsu
thresholding should check the output of their image processing
pipelines after the 1.2.0 release to make sure thresholding is still operating
as expected (if not, try readjusting the median_radius
parameter).
Tracking
The dipy.reconst.peak_direction_getter.EuDXDirectionGetter
has
been renamed dipy.reconst.eudx_direction_getter.EuDXDirectionGetter
.
The command line dipy_track_local
has been renamed dipy_track
.
Others
The dipy.core.gradients.unique_bvals
has been renamed
dipy.core.gradients.unique_bvals_magnitude
.
Visualization
Use
window.Scene()
instead ofwindow.Renderer()
.Use
scene.clear()
instead ofwindow.rm_all(scene)
.Use
scene.clear()
instead ofwindow.clear(scene)
.
DIPY 1.1.1 changes#
IO
img.get_data()
is deprecated since Nibabel 3.0.0. Using np.asanyarray(img.dataobj)
instead of img.get_data()
.
Tractogram
dipy.io.streamlines.StatefulTractogram
can be created by another one.
Workflows
dipy_nlmeans
command lines have been renamed dipy_denoise_nlmeans
.
Others
get_data
has been deprecated by Nibabel and replaced by get_fdata
. This modification has been
applied to all the codebase. The default datatype is now float64.
DIPY 1.0.0 changes#
Some of the changes introduced in the 1.0 release will break backward compatibility with previous versions. This release is compatible with Python 3.5+
Reconstruction
The spherical harmonics bases mrtrix
and fibernav
have been renamed to
tournier07
and descoteaux07
after the deprecation cycle started in the
0.15 release.
We changed dipy.data.default_sphere
from symmetric724 to repulsion724 which is
more evenly distributed.
Segmentation
The API of dipy.segment.mask.median_otsu
has changed in the following ways:
if you are providing a 4D volume, vol_idx is now a required argument.
The order of parameters has also changed.
Tractogram loading and saving
The API of dipy.io.streamlines.load_tractogram
and
dipy.io.streamlines.save_tractogram
has changed in the following ways:
When loading trk, tck, vtk, fib, or dpy) a reference nifti file is needed to
guarantee proper spatial transformation handling.
Spatial transformation handling
Functions from dipy.tracking.streamlines
were modified to enforce the
affine parameter and uniform docstrings. deform_streamlines
select_by_rois
, orient_by_rois
, _extract_vals
and values_from_volume
.
Functions from dipy.tracking.utils
were modified to enforce the
affine parameter and uniform docstring. density_map
connectivity_matrix
, seeds_from_mask
, random_seeds_from_mask
,
target
, target_line_based
, near_roi
, length
and
path_length
were all modified.
The function affine_for_trackvis
, move_streamlines
,
flexi_tvis_affine
and get_flexi_tvis_affine
were deleted.
Functions from dipy.tracking.life
were modified to enforce the
affine parameter and uniform docstring. voxel2streamline
,
setup
and fit
from class FiberModel
were all modified.
afq_profile
from dipy.stats.analysis
was modified similarly.
Simulations
dipy.sims.voxel.SingleTensor
has been replaced bydipy.sims.voxel.single_tensor
dipy.sims.voxel.MultiTensor
has been replaced bydipy.sims.voxel.multi_tensor
dipy.sims.voxel.SticksAndBall
has been replaced bydipy.sims.voxel.sticks_and_ball
Interpolation
All interpolation functions have been moved to a new module name dipy.core.interpolation
Tracking
The voxel_size parameter has been removed from the following function:
dipy.tracking.utils.connectivity_matrix
dipy.tracking.utils.density_map
dipy.tracking.utils.stremline_mapping
dipy.tracking._util._mapping_to_voxel
The dipy.reconst.peak_direction_getter.PeaksAndMetricsDirectionGetter
has
been renamed dipy.reconst.peak_direction_getter.EuDXDirectionGetter
.
The LocalTracking and ParticleFilteringTracking functions were moved from
dipy.tracking.local.localtracking
to dipy.tracking.local_tracking
.
They now need to be imported from dipy.tracking.local_tracking
.
functions argument tissue_classifier were renamed stopping_criterion
The TissueClassifier were renamed StoppingCriterion and moved from
dipy.tracking.local.tissue_classifier
to dipy.tracking.stopping_criterion
.
They now need to be imported from dipy.tracking.stopping_criterion
.
TissueClassifier -> StoppingCriterion
BinaryTissueClassifier -> BinaryStoppingCriterion
ThresholdTissueClassifier -> ThresholdStoppingCriterion
ConstrainedTissueClassifier -> AnatomicalStoppingCriterion
ActTissueClassifier -> ActStoppingCriterion
CmcTissueClassifier -> CmcStoppingCriterion
The dipy.tracking.local.tissue_classifier.TissueClass
was renamed
dipy.tracking.stopping_criterion.StreamlineStatus
.
The EuDX tracking function has been removed. EuDX tractography can be
performed using dipy.tracking.local_tracking
using
dipy.reconst.peak_direction_getter.EuDXDirectionGetter
.
Streamlines
dipy.io.trackvis
has been removed. Use dipy.io.streamline
instead.
Other
dipy.external
package has been removed.dipy.fixes
package has been removed.dipy.segment.quickbundes
module has been removed.dipy.reconst.peaks
module has been removed.Compatibility with Python 2.7 has been removed.
DIPY 0.16 Changes#
Stats
Welcome to the new module dipy.viz.stats
. This module will be used to integrate various analyses.
Tracking
New option to adjust the number of threads for SLR in Recobundles
The tracking algorithm excludes the stop point inside the mask during the tracking process.
Notes
Replacement of Nose by Pytest
DIPY 0.15 Changes#
IO
load_tck
and save_tck
from dipy.io.streamline
have been added. They are highly recommended for managing streamlines.
Gradient Table
The default value of b0_thresold
has been changed(from 0 to 50). This change can impact your algorithm.
If you want to assure that your code runs in exactly the same manner as before, please initialize your gradient table with the keyword argument b0_threshold
set to 0.
Visualization
dipy.viz.fvtk
module has been removed. Use dipy.viz.*
instead. This implies the following important changes:
- Use from dipy.viz import window, actor
instead of from dipy.viz import fvtk`.
- Use ``window.Renderer()
instead of fvtk.ren()
.
- All available actors are in dipy.viz.actor
instead of dipy.fvtk.actor
.
- UI elements are available in dipy.viz.ui
.
dipy.viz
depends on the FURY package. To learn more about FURY, go to https://fury.gl
DIPY 0.14 Changes#
Streamlines
dipy.io.trackvis
module is deprecated. Use dipy.io.streamline
instead. Furthermore,
load_trk
and save_trk
from dipy.io.streamline
is highly recommended for managing streamlines.
When you create streamlines, you should use from dipy.tracking.streamlines import Streamlines
. This new
object uses much less memory and it is easier to process.
Visualization
dipy.viz.fvtk
module is deprecated. Use dipy.viz.*
instead. This implies the following important changes:
- Use from dipy.viz import window, actor
instead of from dipy.viz import fvtk`.
- Use ``window.Renderer()
instead of fvtk.ren()
.
- All available actors are in dipy.viz.actor
instead of dipy.fvtk.actor
.
- UI elements are available in dipy.viz.ui
.
DIPY 0.13 Changes#
No major API changes.
Notes
dipy.io.trackvis
module will be deprecated on release 0.14. Use dipy.io.streamline
instead.
dipy.viz.fvtk
module will be deprecated on release 0.14. Use dipy.viz.ui
instead.
DIPY 0.12 Changes#
Dropped support for Python 2.6*
It has been 6 years since the release of Python 2.7, and multiple other versions have been released since. As far as we know, DIPY still works well on Python 2.6, but we no longer test on this version, and we recommend that users upgrade to Python 2.7 or newer to use DIPY.
Tracking
probabilistic_direction_getter.ProbabilisticDirectionGetter
input parameters
have changed. Now the optional parameter pmf_threshold=0.1
(previously fixed
to 0.0) removes directions with probability lower than pmf_threshold
from
the probability mass function (pmf) when selecting the tracking direction.
DKI
The default of DKI model fitting was changed from “OLS” to “WLS”.
The default max_kurtosis of the functions axial_kurtosis, mean_kurtosis, radial_kurotis was changed from 3 to 10.
Visualization
Prefer using the UI elements in dipy.viz.ui
rather than
dipy.viz.widgets
.
IO
Use the module nibabel.streamlines
for saving trk files and not
nibabel.trackvis
. Requires upgrading to nibabel 2+.
DIPY 0.10 Changes#
New visualization module
fvtk.slicer
input parameters have changed. Now the slicer function is
more powerful 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 utility 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
The 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 completely 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.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.affine)