import numpy as np
from scipy.interpolate import interp1d
# generate some example data
W = 3
H = 10
M = 5
A2 = np.arange(W * M).reshape(W, M)
print(A2)
# [[ 0 1 2 3 4]
# [ 5 6 7 8 9]
# [10 11 12 13 14]]
# the initial column indices for A2
x = np.arange(M)
# we create a scipy.interpolate.interp1d instance
itp_A2 = interp1d(x, A2, kind='nearest')
# the output column coordinates for A1
xi = np.linspace(0, M - 1, H)
# we get the interpolated output by calling the interp1d instance with the
# output coordinates
A1 = itp_A2(xi)
print(A1)
# [[ 0. 0. 1. 1. 2. 2. 3. 3. 4. 4.]
# [ 5. 5. 6. 6. 7. 7. 8. 8. 9. 9.]
# [ 10. 10. 11. 11. 12. 12. 13. 13. 14. 14.]]