I have a 1D numpy array that I want to divide to several arrays, based on the number of cells (x) in each array.
For example, if this is the array:
[0, 2, 7, 9, 13]
and x=2
I want to get the following arrays as a result:
[0,2]
[7,9]
[13]
I feel that there is a simple way to do it without using loops, but I couldn't find it.
Thank you!
import numpy as np
A = np.asarray([0, 2, 7, 9, 13])
x = 2
np.split(A, range(x, len(A), x))
# [array([0, 2]), array([7, 9]), array([13])]
Note that as @Divakar mentioned in his comment, you are better off performance wise using loops (or in this case a list comprehension).
def f(seq, n):
return [seq[i:min(i + n, len(seq))] for i in range(0, len(seq), n)]
def g(seq, n):
return np.split(seq, range(n, len(A), n))
%timeit f(range(12345), 109)
65.2µs ± 468ns (mean +- std. dev. of 7 runs, 10000 loops each)
%timeit g(range(12345), 109)
1.32ms ± 5.21 µs (mean +- std. dev. of 7 runs, 10000 loops each)
Since slicing past the last index will naturally slice till the last element, we can do away with the check
def f(seq, n):
return [seq[i : i + n] for i in range(0, len(seq), n)]
