Python. Nwise Numpy Array Iteration

Is there a numpy function that efficiently allows nwise iteration? # http://seriously.dontusethiscode.com/2013/04/28/nwise.html from itertools import tee, islice nwise = lambda xs,

Solution 1:

General purpose:

import numpy as np
from numpy.lib.stride_tricks import as_strided

def moving_slice(a, k):
    a = a.ravel()
    return as_strided(a, (a.size - k + 1, k), 2 * a.strides)

Moving avg better:

def moving_avg(a, k):
    ps = np.cumsum(a)
    return (ps[k-1:] - np.r_[0, ps[:-k]]) / k

Example:

a = np.arange(10)

moving_avg(a, 4)
# array([ 1.5,  2.5,  3.5,  4.5,  5.5,  6.5,  7.5])

ms = moving_slice(a, 4)
ms
# array([[0, 1, 2, 3],
#        [1, 2, 3, 4],
#        [2, 3, 4, 5],
#        [3, 4, 5, 6],
#        [4, 5, 6, 7],
#        [5, 6, 7, 8],
#        [6, 7, 8, 9]])

# no data are copied:
a[4] = 0
ms
# array([[0, 1, 2, 3],
#        [1, 2, 3, 0],
#        [2, 3, 0, 5],
#        [3, 0, 5, 6],
#        [0, 5, 6, 7],
#        [5, 6, 7, 8],
#        [6, 7, 8, 9]])