actors#
Module: actors.odf#
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Visualize one or many ODFs with different features. |
Module: actors.odf_slicer#
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VTK actor for visualizing slices of ODF field. |
Module: actors.peak#
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FURY actor for visualizing DWI peaks. |
Module: actors.tensor#
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Visualize one or many Tensor Ellipsoids with different features. |
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Visualize one or many Double Cones with different features. |
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Calculate the angle of the cone of uncertainty that represents the perturbation of the main eigenvector of the diffusion tensor matrix. |
sh_odf#
- fury.actors.odf.sh_odf(centers, coeffs, degree, sh_basis, scales, opacity)[source]#
Visualize one or many ODFs with different features.
- Parameters:
- centersndarray(N, 3)
ODFs positions.
- coeffsndarray
2D ODFs array in SH coefficients.
- sh_basis: str, optional
Type of basis (descoteaux, tournier) ‘descoteaux’ for the default
descoteaux07DIPY basis. ‘tournier’ for the defaulttournier07DIPY basis.- degree: int, optional
Index of the highest used band of the spherical harmonics basis. Must be even, at least 2 and at most 12.
- scalesfloat or ndarray (N, )
ODFs size.
- opacityfloat
Takes values from 0 (fully transparent) to 1 (opaque).
- Returns:
- box_actor: Actor
OdfSlicerActor#
- class fury.actors.odf_slicer.OdfSlicerActor(odfs, vertices, faces, indices, scale, norm, radial_scale, shape, global_cm, colormap, opacity, *, affine=None, B=None)[source]#
Bases:
vtkActorVTK actor for visualizing slices of ODF field.
- Parameters:
- odfsndarray
SF or SH coefficients 2-dimensional array.
- vertices: ndarray
The sphere vertices used for SH to SF projection.
- faces: ndarray
Indices of sphere vertices forming triangles. Should be ordered clockwise (see fury.utils.fix_winding_order).
- indices: tuple
Indices given in tuple(x_indices, y_indices, z_indices) format for mapping 2D ODF array to 3D voxel grid.
- scalefloat
Multiplicative factor to apply to ODF amplitudes.
- normbool
Normalize SF amplitudes so that the maximum ODF amplitude per voxel along a direction is 1.
- radial_scalebool
Scale sphere points by ODF values.
- global_cmbool
If True the colormap will be applied in all ODFs. If False it will be applied individually at each voxel.
- colormapNone or str
The name of the colormap to use. Matplotlib colormaps are supported (e.g., ‘inferno’). If None then a RGB colormap is used.
- opacityfloat
Takes values from 0 (fully transparent) to 1 (opaque).
- affinearray
optional 4x4 transformation array from native coordinates to world coordinates.
- Bndarray (n_coeffs, n_vertices)
Optional SH to SF matrix for projecting odfs given in SH coefficients on the sphere. If None, then the input is assumed to be expressed in SF coefficients.
- display_extent(x1, x2, y1, y2, z1, z2)[source]#
Set visible volume from x1 (inclusive) to x2 (inclusive), y1 (inclusive) to y2 (inclusive), z1 (inclusive) to z2 (inclusive).
PeakActor#
- class fury.actors.peak.PeakActor(directions, indices, *, values=None, affine=None, colors=None, lookup_colormap=None, linewidth=1, symmetric=True)[source]#
Bases:
vtkActorFURY actor for visualizing DWI peaks.
- Parameters:
- directionsndarray
Peak directions. The shape of the array should be (X, Y, Z, D, 3).
- indicestuple
Indices given in tuple(x_indices, y_indices, z_indices) format for mapping 2D ODF array to 3D voxel grid.
- valuesndarray, optional
Peak values. The shape of the array should be (X, Y, Z, D).
- affinearray, optional
4x4 transformation array from native coordinates to world coordinates.
- colorsNone or string (‘rgb_standard’) or tuple (3D or 4D) or array/ndarray (N, 3 or 4) or array/ndarray (K, 3 or 4) or array/ndarray(N, ) or array/ndarray (K, )
If None a standard orientation colormap is used for every line. If one tuple of color is used. Then all streamlines will have the same color. If an array (N, 3 or 4) is given, where N is equal to the number of points. Then every point is colored with a different RGB(A) color. If an array (K, 3 or 4) is given, where K is equal to the number of lines. Then every line is colored with a different RGB(A) color. If an array (N, ) is given, where N is the number of points then these are considered as the values to be used by the colormap. If an array (K,) is given, where K is the number of lines then these are considered as the values to be used by the colormap.
- lookup_colormapvtkLookupTable, optional
Add a default lookup table to the colormap. Default is None which calls
fury.actor.colormap_lookup_table().- linewidthfloat, optional
Line thickness. Default is 1.
- symmetric: bool, optional
If True, peaks are drawn for both peaks_dirs and -peaks_dirs. Else, peaks are only drawn for directions given by peaks_dirs. Default is True.
- property cross_section#
- property global_opacity#
- property high_ranges#
- property is_range#
- property linewidth#
- property low_ranges#
- property max_centers#
- property min_centers#
tensor_ellipsoid#
- fury.actors.tensor.tensor_ellipsoid(centers, axes, lengths, colors, scales, opacity)[source]#
Visualize one or many Tensor Ellipsoids with different features.
- Parameters:
- centersndarray(N, 3)
Tensor ellipsoid positions.
- axesndarray (3, 3) or (N, 3, 3)
Axes of the tensor ellipsoid.
- lengthsndarray (3, ) or (N, 3)
Axes lengths.
- colorsndarray (N,3) or tuple (3,)
R, G and B should be in the range [0, 1].
- scalesfloat or ndarray (N, )
Tensor ellipsoid size.
- opacityfloat
Takes values from 0 (fully transparent) to 1 (opaque).
- Returns:
- box_actor: Actor
double_cone#
- fury.actors.tensor.double_cone(centers, axes, angles, colors, scales, opacity)[source]#
Visualize one or many Double Cones with different features.
- Parameters:
- centersndarray(N, 3)
Cone positions.
- axesndarray (3, 3) or (N, 3, 3)
Axes of the cone.
- anglesfloat or ndarray (N, )
Angles of the cone.
- colorsndarray (N, 3) or tuple (3,)
R, G and B should be in the range [0, 1].
- scalesfloat or ndarray (N, )
Cone size.
- opacityfloat
Takes values from 0 (fully transparent) to 1 (opaque).
- Returns:
- box_actor: Actor
main_dir_uncertainty#
- fury.actors.tensor.main_dir_uncertainty(evals, evecs, signal, sigma, b_matrix)[source]#
Calculate the angle of the cone of uncertainty that represents the perturbation of the main eigenvector of the diffusion tensor matrix.
- Parameters:
- evalsndarray (3, ) or (N, 3)
Eigenvalues.
- evecsndarray (3, 3) or (N, 3, 3)
Eigenvectors.
- signal3D or 4D ndarray
Predicted signal.
- sigmandarray
Standard deviation of the noise.
- b_matrixarray (N, 7)
Design matrix for DTI.
- Returns:
- anglesarray
Notes
The uncertainty calculation is based on first-order matrix perturbation analysis described in [1]. The idea is to estimate the variance of the main eigenvector which corresponds to the main direction of diffusion, directly from estimated D and its estimated covariance matrix \(\Delta D\) (see [2], equation 4). The angle \(\Theta\) between the perturbed principal eigenvector of D, \(\epsilon_1 + \Delta\epsilon_1\), and the estimated eigenvector \(\epsilon_1\), measures the angular deviation of the main fiber direction and can be approximated by:
\[\Theta = tan^{-1}(\|\Delta \ epsilon_1\|)\]Giving way to a graphical construct for displaying both the main eigenvector of D and its associated uncertainty, with the so-called “uncertainty cone”.
References
[1]Basser, P. J. (1997). Quantifying errors in fiber direction and diffusion tensor field maps resulting from MR noise. In 5th Scientific Meeting of the ISMRM (Vol. 1740).
[2]Chang, L. C., Koay, C. G., Pierpaoli, C., & Basser, P. J. (2007). Variance of estimated DTI-derived parameters via first-order perturbation methods. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 57(1), 141-149.