How can I get the amax of an array of numpy arrays?

Question

I have an array of arrays and I need to get the amax for each row.

[[-1.53286755e-02  2.93346513e-02 -7.66370669e-02 -2.19948404e-02]
 [-1.25247389e-02  1.43674174e-02 -6.83528483e-02 -1.07235834e-02]
 [-1.51151344e-02  3.38465981e-02 -7.61222318e-02 -1.83092393e-02]
 [ 4.46393713e-03  1.87037606e-02 -6.09790049e-02 -1.94273535e-02]
 [-1.64875668e-02  2.76340060e-02 -6.66617230e-02 -1.33732818e-02]
 [-3.99522949e-04  1.20752566e-02 -6.02767840e-02 -1.47377616e-02]
 [-6.86090253e-03  2.22653989e-02 -6.96686357e-02 -3.29462299e-03]
 [ 3.94986942e-03  3.54665779e-02 -7.09369779e-02 -6.11725636e-03]
 [ 3.49313393e-03  2.98086051e-02 -7.18421638e-02 -5.45137282e-03]
 [ 1.18993018e-02  2.50301771e-02 -6.93574101e-02  2.55537452e-04]
 [ 8.19707289e-04  6.50310218e-02 -1.46873474e-01  7.08404928e-03]
...

My array looks like that and I want to do np.amax on it to get the maximum value per row.

I tried best_q = np.amax(amax[0]), but this simply returns the highest value in the entire array.

I'd like to do this vectorized somehow to save processing time.

BENY · Accepted Answer · 2019-04-08 14:40:39Z

3

Check with you need to pass the correct index to aggregate, here is axis=1

np.max(a,axis = 1) # np.amax(a,axis=1)

Out[199]: 
array([0.09640129, 0.09834351, 0.09433366, 0.9100043 , 0.9104525 ,
       0.90350811])

edited Apr 8, 2019 at 14:40

answered Apr 8, 2019 at 14:32

BENY

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Pavel Kovtun · Accepted Answer · 2019-04-08 14:33:28Z

1

You need to add "axis" param to amax to get max over an axis

np.amax(a, axis=1) or np.amax(a, axis=0)

check: https://docs.scipy.org/doc/numpy/reference/generated/numpy.amax.html

answered Apr 8, 2019 at 14:33

Pavel Kovtun

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1 Comment

Pavel Kovtun Over a year ago

it's simple: all horizontal elements, or all vertical elements. like X-axis and Y-axis

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