convolution - w3toppers.com

Convolve2d just by using Numpy

You could generate the subarrays using as_strided: import numpy as np a = np.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]]) sub_shape = (3,3) view_shape = tuple(np.subtract(a.shape, sub_shape) + 1) + sub_shape strides = a.strides + … Read more

Using numpy `as_strided` function to create patches, tiles, rolling or sliding windows of arbitrary dimension

EDIT JAN 2020: Changed the iterable return from a list to a generator to save memory. EDIT OCT 2020: Put the generator in a separate function, since mixing generators and return statements doesn’t work intiutively. Here’s the recipe I have so far: def window_nd(a, window, steps = None, axis = None, gen_data = False): “”” … Read more