view_as_blocks(arr_in, block_shape)

Blocks are non-overlapping views of the input array.

Parameters

arr_in : ndarray

N-d input array.

block_shape : tuple

The shape of the block. Each dimension must divide evenly into the corresponding dimensions of :None:None:`arr_in`.

Returns

arr_out : ndarray

Block view of the input array.

Block view of the input n-dimensional array (using re-striding).

Examples

This example is valid syntax, but we were not able to check execution

>>> import numpy as np
... from skimage.util.shape import view_as_blocks
... A = np.arange(4*4).reshape(4,4)
... A
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15]])

This example is valid syntax, but we were not able to check execution

>>> B = view_as_blocks(A, block_shape=(2, 2))
... B[0, 0]
array([[0, 1],
       [4, 5]])

This example is valid syntax, but we were not able to check execution

>>> B[0, 1]
array([[2, 3],
       [6, 7]])

This example is valid syntax, but we were not able to check execution

>>> B[1, 0, 1, 1]
13

This example is valid syntax, but we were not able to check execution

>>> A = np.arange(4*4*6).reshape(4,4,6)
... A  # doctest: +NORMALIZE_WHITESPACE
array([[[ 0,  1,  2,  3,  4,  5],
        [ 6,  7,  8,  9, 10, 11],
        [12, 13, 14, 15, 16, 17],
        [18, 19, 20, 21, 22, 23]],
       [[24, 25, 26, 27, 28, 29],
        [30, 31, 32, 33, 34, 35],
        [36, 37, 38, 39, 40, 41],
        [42, 43, 44, 45, 46, 47]],
       [[48, 49, 50, 51, 52, 53],
        [54, 55, 56, 57, 58, 59],
        [60, 61, 62, 63, 64, 65],
        [66, 67, 68, 69, 70, 71]],
       [[72, 73, 74, 75, 76, 77],
        [78, 79, 80, 81, 82, 83],
        [84, 85, 86, 87, 88, 89],
        [90, 91, 92, 93, 94, 95]]])

This example is valid syntax, but we were not able to check execution

>>> B = view_as_blocks(A, block_shape=(1, 2, 2))
... B.shape
(4, 2, 3, 1, 2, 2)

This example is valid syntax, but we were not able to check execution

>>> B[2:, 0, 2]  # doctest: +NORMALIZE_WHITESPACE
array([[[[52, 53],
         [58, 59]]],
       [[[76, 77],
         [82, 83]]]])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

skimage.util.shape.view_as_blocks

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File: /skimage/util/shape.py#9
type: <class 'function'>
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