Element-wise array maximum function in NumPy (more than two arrays)

Question

I'm trying to return maximum values of multiple array in an element-wise comparison. For example:

A = array([0, 1, 2])
B = array([1, 0, 3])
C = array([3, 0, 4])

I want the resulting array to be array([3,1,4]).

I wanted to use numpy.maximum, but it is only good for two arrays. Is there a simple function for more than two arrays?

Solution 1

With this setup:

>>> A = np.array([0,1,2])
>>> B = np.array([1,0,3])
>>> C = np.array([3,0,4])

You can either do:

>>> np.maximum.reduce([A,B,C])
array([3, 1, 4])

Or:

>>> np.vstack([A,B,C]).max(axis=0)
array([3, 1, 4])

I would go with the first option.

Solution 2

You can use reduce. It repeatedly applies a binary function to a list of values...

For A, B and C given in question...

np.maximum.reduce([A,B,C])

 array([3,1,4])

It first computes the np.maximum of A and B and then computes the np.maximum of (np.maximum of A and B) and C.

Comments

[Sven Marnach]

I would try to hold the data in a two-dimensional array right from the start, and then use the second option.

[Daniel]

@SvenMarnach The axis argument calls reduce in the end, I don't understand why it matters.