Question

I had like to know the best fatest/optimized way of getting the maximum values element-wised of "n" matrices in Python/Numpy.

For example:

import numpy as np
matrices=[np.random.random((5,5)) for i in range(10)]
# the function np.maximum from numpy only works for two matrices.
max_matrix=np.maximum(matrices[0],matrices[1])
max_matrix=np.maximum(*matrices) # <- error

How would you overcome this problem?

Answer 1

Use reduce:

reduce(np.maximum, matrices)

From the docs:

reduce(function, iterable[, initializer])

Apply function of two arguments cumulatively to the items of iterable,
from left to right, so as to reduce the iterable to a single value.
For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates
((((1+2)+3)+4)+5). The left argument, x, is the accumulated value and
the right argument, y, is the update value from the iterable. If the
optional initializer is present, it is placed before the items of the
iterable in the calculation, and serves as a default when the iterable
is empty. If initializer is not given and iterable contains only one
item, the first item is returned.