direction
Module: direction.peaks
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class dipy.direction.peaks.PeaksAndMetrics
Bases: EuDXDirectionGetter
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__init__()
peak_directions_nl
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dipy.direction.peaks.peak_directions_nl(sphere_eval, relative_peak_threshold=0.25, min_separation_angle=25, sphere=<dipy.core.sphere.HemiSphere object>, xtol=1e-07)
Non Linear Direction Finder.
Parameters
- sphere_evalcallable
A function which can be evaluated on a sphere.
- relative_peak_thresholdfloat
Only return peaks greater than relative_peak_threshold * m where m
is the largest peak.
- min_separation_anglefloat in [0, 90]
The minimum distance between directions. If two peaks are too close
only the larger of the two is returned.
- sphereSphere
A discrete Sphere. The points on the sphere will be used for initial
estimate of maximums.
- xtolfloat
Relative tolerance for optimization.
Returns
- directionsarray (N, 3)
Points on the sphere corresponding to N local maxima on the sphere.
- valuesarray (N,)
Value of sphere_eval at each point on directions.
peak_directions
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dipy.direction.peaks.peak_directions(odf, sphere, relative_peak_threshold=0.5, min_separation_angle=25, is_symmetric=True)
Get the directions of odf peaks.
Peaks are defined as points on the odf that are greater than at least one
neighbor and greater than or equal to all neighbors. Peaks are sorted in
descending order by their values then filtered based on their relative size
and spacing on the sphere. An odf may have 0 peaks, for example if the odf
is perfectly isotropic.
Parameters
- odf1d ndarray
The odf function evaluated on the vertices of sphere
- sphereSphere
The Sphere providing discrete directions for evaluation.
- relative_peak_thresholdfloat in [0., 1.]
Only peaks greater than min + relative_peak_threshold * scale are
kept, where min = max(0, odf.min()) and
scale = odf.max() - min.
- min_separation_anglefloat in [0, 90]
The minimum distance between directions. If two peaks are too close
only the larger of the two is returned.
- is_symmetricbool, optional
If True, v is considered equal to -v.
Returns
- directions(N, 3) ndarray
N vertices for sphere, one for each peak
- values(N,) ndarray
peak values
- indices(N,) ndarray
peak indices of the directions on the sphere
Notes
If the odf has any negative values, they will be clipped to zeros.
peaks_from_model
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dipy.direction.peaks.peaks_from_model(model, data, sphere, relative_peak_threshold, min_separation_angle, mask=None, return_odf=False, return_sh=True, gfa_thr=0, normalize_peaks=False, sh_order=8, sh_basis_type=None, npeaks=5, B=None, invB=None, parallel=False, num_processes=None)
Fit the model to data and computes peaks and metrics
Parameters
- modela model instance
model will be used to fit the data.
- datandarray
Diffusion data.
- sphereSphere
The Sphere providing discrete directions for evaluation.
- relative_peak_thresholdfloat
Only return peaks greater than relative_peak_threshold * m where m
is the largest peak.
- min_separation_anglefloat in [0, 90] The minimum distance between
directions. If two peaks are too close only the larger of the two is
returned.
- maskarray, optional
If mask is provided, voxels that are False in mask are skipped and
no peaks are returned.
- return_odfbool
If True, the odfs are returned.
- return_shbool
If True, the odf as spherical harmonics coefficients is returned
- gfa_thrfloat
Voxels with gfa less than gfa_thr are skipped, no peaks are returned.
- normalize_peaksbool
If true, all peak values are calculated relative to max(odf).
- sh_orderint, optional
Maximum SH order in the SH fit. For sh_order, there will be
(sh_order + 1) * (sh_order + 2) / 2 SH coefficients (default 8).
- sh_basis_type{None, ‘tournier07’, ‘descoteaux07’}
None for the default DIPY basis,
tournier07 for the Tournier 2007 basis, and
descoteaux07 for the Descoteaux 2007 basis
(None defaults to descoteaux07).
- npeaksint
Maximum number of peaks found (default 5 peaks).
- Bndarray, optional
Matrix that transforms spherical harmonics to spherical function
sf = np.dot(sh, B).
- invBndarray, optional
Inverse of B.
- parallel: bool
If True, use multiprocessing to compute peaks and metric
(default False). Temporary files are saved in the default temporary
directory of the system. It can be changed using import tempfile
and tempfile.tempdir = '/path/to/tempdir'.
- num_processes: int, optional
If parallel is True, the number of subprocesses to use
(default multiprocessing.cpu_count()). If < 0 the maximal number of
cores minus num_processes + 1 is used (enter -1 to use as many
cores as possible). 0 raises an error.
Returns
- pamPeaksAndMetrics
An object with gfa, peak_directions, peak_values,
peak_indices, odf, shm_coeffs as attributes
reshape_peaks_for_visualization
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dipy.direction.peaks.reshape_peaks_for_visualization(peaks)
Reshape peaks for visualization.
Reshape and convert to float32 a set of peaks for visualisation with mrtrix
or the fibernavigator.
Parameters
- peaks: nd array (…, N, 3) or PeaksAndMetrics object
The peaks to be reshaped and converted to float32.
Returns
peaks : nd array (…, 3*N)