Is a Numpy way to make a sum each three elements in the interval with a step? For example:
import numpy as np
mydata = np.array([4, 2, 3, 8, -6, 10])
I would like to get this result:
np.array([9, 12])
I suppose that np.convole can do this, according to Summing elements in a sliding window – NumPy, but can I change the step from n=1 to n=3, in this case?
>Solution :
Using reshape (requires the array length to be a multiple of n):
n = 3
mydata.reshape(-1, n).sum(1)
If you don’t have a multiple, you can trim:
n = 3
mydata[:len(mydata)//n*n].reshape(-1, n).sum(1)
Using convolve, which should be much less efficient for large n as many values (n-1 out of n) are computed for nothing:
np.convolve(np.ones(n), mydata)[n-1::n]
Output: array([ 9, 12])