`skimage.util.shape:view_as_blocks`

source: /_skimage2/util/shape.py:8

Signature

def view_as_blocks(arr_in, block_shape)

Summary

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

Extended Summary

Blocks are non-overlapping views of the input array.

Parameters

arr_in : ndarray, shape (M[, ...]): Input array.
block_shape : tuple: The shape of the block. Each dimension must divide evenly into the corresponding dimensions of arr_in.

Returns

arr_out : ndarray: Block view of the input array.

Examples

import numpy as np
from skimage.util.shape import view_as_blocks
A = np.arange(4*4).reshape(4,4)
A
B = view_as_blocks(A, block_shape=(2, 2))
B[0, 0]
B[0, 1]

✓

array([[2, 3],
       [6, 7]])

B[1, 0, 1, 1]

✗

np.int64(13)

A = np.arange(4*4*6).reshape(4,4,6)
A  # doctest: +NORMALIZE_WHITESPACE
B = view_as_blocks(A, block_shape=(1, 2, 2))
B.shape
B[2:, 0, 2]  # doctest: +NORMALIZE_WHITESPACE

✓

array([[[[52, 53],
         [58, 59]]],


       [[[76, 77],
         [82, 83]]]])

Aliases

skimage.util.view_as_blocks