sklearn.feature_extraction.image.grid_to_graph¶
-
sklearn.feature_extraction.image.grid_to_graph(n_x, n_y, n_z=1, *, mask=None, return_as=<class 'scipy.sparse.coo.coo_matrix'>, dtype=<class 'int'>)[source]¶ Graph of the pixel-to-pixel connections
Edges exist if 2 voxels are connected.
- Parameters
- n_xint
Dimension in x axis
- n_yint
Dimension in y axis
- n_zint, default=1
Dimension in z axis
- maskndarray of shape (n_x, n_y, n_z), dtype=bool, default=None
An optional mask of the image, to consider only part of the pixels.
- return_asnp.ndarray or a sparse matrix class, default=sparse.coo_matrix
The class to use to build the returned adjacency matrix.
- dtypedtype, default=int
The data of the returned sparse matrix. By default it is int
Notes
For scikit-learn versions 0.14.1 and prior, return_as=np.ndarray was handled by returning a dense np.matrix instance. Going forward, np.ndarray returns an np.ndarray, as expected.
For compatibility, user code relying on this method should wrap its calls in
np.asarrayto avoid type issues.