Replace values of a numpy index array with values of a list
Instead of replacing the values one by one, it is possible to remap the entire array like this:
import numpy as np
a = np.array([1,2,2,1]).reshape(2,2)
# palette must be given in sorted order
palette = [1, 2]
# key gives the new values you wish palette to be mapped to.
key = np.array([0, 10])
index = np.digitize(a.ravel(), palette, right=True)
print(key[index].reshape(a.shape))
yields
[[ 0 10]
[10 0]]
Credit for the above idea goes to @JoshAdel. It is significantly faster than my original answer:
import numpy as np
import random
palette = np.arange(8)
key = palette**2
a = np.array([random.choice(palette) for i in range(514*504)]).reshape(514,504)
def using_unique():
palette, index = np.unique(a, return_inverse=True)
return key[index].reshape(a.shape)
def using_digitize():
index = np.digitize(a.ravel(), palette, right=True)
return key[index].reshape(a.shape)
if __name__ == '__main__':
assert np.allclose(using_unique(), using_digitize())
I benchmarked the two versions this way:
In [107]: %timeit using_unique()
10 loops, best of 3: 35.6 ms per loop
In [112]: %timeit using_digitize()
100 loops, best of 3: 5.14 ms per loop
Well, I suppose what you need is
a[a==2] = 10 #replace all 2's with 10's