Is there a 'pythonic' way to cleanly down-sample without multiple for loops?
This example below is the type of for loop I wish to get rid of.
import numpy as np
unsampled_array = [1,3,5,7,9,11,13,15,17,19]
number_of_samples = 7
downsampled_array = []
downsampling_indices = np.linspace(0, len(unsampled_array)-1, number_of_samples).round()
for index in downsampling_indices:
downsampled_array.append(unsampled_array[int(index)])
print(downsampled_array)
>>> [ 1 5 7 9 13 17 19]
You need function np.ix_
, as follows:
import numpy as np
unsampled_array = np.array([1,3,5,7,9,11,13,15,17,19])
number_of_samples = 5
downsampling_indices = np.linspace(0, len(unsampled_array)-1, number_of_samples).round()
downsampling_indices = np.array(downsampling_indices, dtype=np.int64)
indices = np.ix_(downsampling_indices)
downsampled_array = unsampled_array[indices]
print(downsampled_array)