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scikit-learn 1.3.2
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# `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'>)

  Graph of the pixel-to-pixel connections.

  Edges exist if 2 voxels are connected.

  Parameters:
    n_x int

      Dimension in x axis.

    n_y int

      Dimension in y axis.

    n_z int, default=1

      Dimension in z axis.

    mask ndarray 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_as np.ndarray or a sparse matrix class, default=sparse.coo_matrix

      The class to use to build the returned adjacency matrix.

    dtype dtype, default=int

      The data of the returned sparse matrix. By default it is int.

  Returns:
    graph np.ndarray or a sparse matrix class

      The computed adjacency matrix.

  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.asarray` to avoid type issues.