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Numpy, apply function list by array size

I have a list of functions like:

func_list = [lambda x: function1(input),
             lambda x: function2(input),
             lambda x: function3(input),
             lambda x: x]

and an array of the form [4, 200, 200, 1] (batch of images).

I want to apply a list of functions in order along the 0th axis.

EDIT: Rephrase the problem. This is equivalent to the above. Let's say, instead of an array, I have a tuple of 4 identical arrays, of the form (200, 200, 1) and I want to apply function 1 to the first element, function2 on the second element, etc. Can this be done without a for loop?

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2 answers


You can iterate over the list of functions with np.apply_along_axis

:

import numpy as np
x = np.ranom.randn(100, 100)
for f in fun_list:
    x = np.apply_along_axis(f, 0, x)

Based on OP update



Assuming your functions and batches are the same size:

batch = ... # tuple of 4 images  
batch_out = tuple([np.apply_along_axis(f, 0, x) for f, x in zip(fun_list, batch)])
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I tried @ Coldspeed's answer and it works (which is why I accept it), but here is the alternative I found, without using for loops:

result = tuple(map(lambda x,y:x(y), functions, image_tuple))


Edit: Forgot to add tuple (), thanks @Coldspeed

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