I have a 1-d numpy array which I would like to down sample with a exponential distribution. Currently, I am using signal.resample(y,downsize) for a uniform re-sample. Not sure if there is a quick way to do this but exponentially
from scipy import signal
# uniform resample example
x = np.arange(100)
y = np.sin(x)
linear_resample = signal.resample(y,15)
import numpy as np
np.random.seed(73)
# a random array of integers of length 100
arr_test = np.random.randint(300, size=100)
print(arr_test)
# lets divide 0 to 100 in exponential fashion
ls = np.logspace(0.00001, 2, num=100, endpoint=False, base=10.0).astype(np.int32)
print(ls)
# sample the array
arr_samp = arr_test[ls]
print(arr_samp)
I have use log base 10. You can change to natural if you want.
