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scipy.ndimage.

# generate_binary_structure

scipy.ndimage.generate_binary_structure(rank, connectivity)

  Generate a binary structure for binary morphological operations.

  Parameters:
    rankint

      Number of dimensions of the array to which the structuring element will be applied, as returned by np.ndim.

    connectivityint

      connectivity determines which elements of the output array belong to the structure, i.e., are considered as neighbors of the central element. Elements up to a squared distance of connectivity from the center are considered neighbors. connectivity may range from 1 (no diagonal elements are neighbors) to rank (all elements are neighbors).

  Returns:
    outputndarray of bools

      Structuring element which may be used for binary morphological operations, with rank dimensions and all dimensions equal to 3.

  See also

  `iterate_structure`, `binary_dilation`, `binary_erosion`

  Notes

  `generate_binary_structure` can only create structuring elements with dimensions equal to 3, i.e., minimal dimensions. For larger structuring elements, that are useful e.g., for eroding large objects, one may either use `iterate_structure`, or create directly custom arrays with numpy functions such as `numpy.ones`.

  Examples

      >>> from scipy import ndimage
      >>> import numpy as np
      >>> struct = ndimage.generate_binary_structure(2, 1)
      >>> struct
      array([[False,  True, False],
             [ True,  True,  True],
             [False,  True, False]], dtype=bool)
      >>> a = np.zeros((5,5))
      >>> a[2, 2] = 1
      >>> a
      array([[ 0.,  0.,  0.,  0.,  0.],
             [ 0.,  0.,  0.,  0.,  0.],
             [ 0.,  0.,  1.,  0.,  0.],
             [ 0.,  0.,  0.,  0.,  0.],
             [ 0.,  0.,  0.,  0.,  0.]])
      >>> b = ndimage.binary_dilation(a, structure=struct).astype(a.dtype)
      >>> b
      array([[ 0.,  0.,  0.,  0.,  0.],
             [ 0.,  0.,  1.,  0.,  0.],
             [ 0.,  1.,  1.,  1.,  0.],
             [ 0.,  0.,  1.,  0.,  0.],
             [ 0.,  0.,  0.,  0.,  0.]])
      >>> ndimage.binary_dilation(b, structure=struct).astype(a.dtype)
      array([[ 0.,  0.,  1.,  0.,  0.],
             [ 0.,  1.,  1.,  1.,  0.],
             [ 1.,  1.,  1.,  1.,  1.],
             [ 0.,  1.,  1.,  1.,  0.],
             [ 0.,  0.,  1.,  0.,  0.]])
      >>> struct = ndimage.generate_binary_structure(2, 2)
      >>> struct
      array([[ True,  True,  True],
             [ True,  True,  True],
             [ True,  True,  True]], dtype=bool)
      >>> struct = ndimage.generate_binary_structure(3, 1)
      >>> struct # no diagonal elements
      array([[[False, False, False],
              [False,  True, False],
              [False, False, False]],
             [[False,  True, False],
              [ True,  True,  True],
              [False,  True, False]],
             [[False, False, False],
              [False,  True, False],
              [False, False, False]]], dtype=bool)