from fury import layout
from fury.actors.odf_slicer import OdfSlicerActor
from fury.actors.peak import PeakActor
-from fury.actors.tensor import tensor_ellipsoid
+from fury.actors.tensor import double_cone, main_dir_uncertainty, \
+ tensor_ellipsoid
from fury.colormap import colormap_lookup_table
from fury.deprecator import deprecate_with_version, deprecated_params
from fury.io import load_image
@@ -4362,6 +4363,65 @@ Source code for fury.actor
return tensor_ellipsoid(centers, axes, lengths, colors, scales, opacity)
+
[docs]
+
def uncertainty_cone(
+
evals,
+
evecs,
+
signal,
+
sigma,
+
b_matrix,
+
scales=.6,
+
opacity=1.0
+
):
+
"""
+
VTK actor for visualizing the cone of uncertainty representing the
+
variance of the main direction of diffusion.
+
+
Parameters
+
----------
+
evals : ndarray (3, ) or (N, 3)
+
Eigenvalues.
+
evecs : ndarray (3, 3) or (N, 3, 3)
+
Eigenvectors.
+
signal : 3D or 4D ndarray
+
Predicted signal.
+
sigma : ndarray
+
Standard deviation of the noise.
+
b_matrix : array (N, 7)
+
Design matrix for DTI.
+
scales : float or ndarray (N, ), optional
+
Cones of uncertainty size.
+
opacity : float, optional
+
Takes values from 0 (fully transparent) to 1 (opaque), default(1.0).
+
+
Returns
+
-------
+
double_cone: Actor
+
+
"""
+
+
valid_mask = np.abs(evecs).max(axis=(-2, -1)) > 0
+
indices = np.nonzero(valid_mask)
+
+
evecs = evecs[indices]
+
evals = evals[indices]
+
signal = signal[indices]
+
+
centers = np.asarray(indices).T
+
colors = np.array([107, 107, 107])
+
+
x, y, z = evecs.shape
+
if not isinstance(scales, np.ndarray):
+
scales = np.array(scales)
+
if scales.size == 1:
+
scales = np.repeat(scales, x)
+
+
angles = main_dir_uncertainty(evals, evecs, signal, sigma, b_matrix)
+
+
return double_cone(centers, evecs, angles, colors, scales, opacity)
Source code for fury.actors.tensor