Element-wise minimum of multiple vectors in numpy

Question

I know that in numpy I can compute the element-wise minimum of two vectors with

numpy.minimum(v1, v2)

What if I have a list of vectors of e

Answer 1

*V works if V has only 2 arrays. np.minimum is a ufunc and takes 2 arguments.

As a ufunc it has a .reduce method, so it can apply repeated to a list inputs.

In [321]: np.minimum.reduce([np.arange(3), np.arange(2,-1,-1), np.ones((3,))])
Out[321]: array([ 0.,  1.,  0.])

I suspect the np.min approach is faster, but that could depend on the array and list size.

In [323]: np.array([np.arange(3), np.arange(2,-1,-1), np.ones((3,))]).min(axis=0)
Out[323]: array([ 0.,  1.,  0.])

The ufunc also has an accumulate which can show us the results of each stage of the reduction. Here's it's not to interesting, but I could tweak the inputs to change that.

In [325]: np.minimum.accumulate([np.arange(3), np.arange(2,-1,-1), np.ones((3,))])
     ...: 
Out[325]: 
array([[ 0.,  1.,  2.],
       [ 0.,  1.,  0.],
       [ 0.,  1.,  0.]])