max of Corresponding Elements in a numpy.ndarray

Question

This seems like it would be a really simple problem, but i haven't been able to find a solution so far.

I have two numpy.ndarrays (say A, B) and would like to create a third one (say C) of the same shape and dimensionality, such that each element in C is the maximum value of the corresponding elements in A and B.

What I've tried so far doesn't work, though to be honest, I haven't tried much (but I'm out of ideas)

In [173]: A Out[173]: array([[ 2.12752806e-314, 2.12752806e-314], [ 2.16171674e-314, 6.32300944e+233]]) In [174]: B Out[174]: array([[ 2.13899304e-314, 2.13899304e-314], [ 2.16168421e-314, 2.78136354e-309]]) In [175]: max(A, B) --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-175-c06ce068ec08> in <module>() ----> 1 max(A, B) ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

gg349 · Accepted Answer · 2013-10-24 05:00:05Z

1

you're looking for np.maximum(A,B)

answered Oct 24, 2013 at 5:00

gg349

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CT Zhu · Accepted Answer · 2013-10-24 04:57:36Z

How about np.where:

In [29]: where(A>B, A, B) Out[29]: array([[ 2.13899304e-314, 2.13899304e-314], [ 2.16171674e-314, 6.32300944e+233]])

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