Finding min max in 3d numpy array

Question

I have the following numpy ndarray, the shape is (4,1,2):

    myarray = np.array([[[0.,4.]],
                   [[1.,5.]],
                   [[2.,6.]],
                   [[3.,7.]]])

How do I find the max, min of each column? In this case min, max for 1st column is 0, 3; and min, max for 2nd column is 4, 7.

I can't quite figure out the correct syntax for np.amin and np.amax in this these cases.

Thanks.

Try using axis param with those. Read the docs again.

Divakar
– Divakar

2016-10-23 07:53:30 +00:00
Commented Oct 23, 2016 at 7:53 — Divakar
– Divakar, Commented Oct 23, 2016 at 7:53

Kennet Celeste · Accepted Answer · 2016-10-23 08:02:40Z

5

import numpy as np

myarray = np.array([[[0., 4.]],
                    [[1., 5.]],
                    [[2., 6.]],
                    [[3., 7.]]])
maxes = np.max(myarray,axis=0)
mins = np.min(myarray,axis=0)
print 'maxes are :' ,maxes ,'\nmins are : ', mins

which gives:

maxes are : [[ 3.  7.]] 
mins are :  [[ 0.  4.]]

answered Oct 23, 2016 at 8:02

Kennet Celeste

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