I have a collection of 2D narrays, depending on two integer indexes, say p1 and p2, with each matrix of the same shape.

Then I need to find, for each pair (p1,p2), the maximum value of the matrix and the indexes of these maxima. A trivial, albeit slow, way to do this would would be to do something like this

```
import numpy as np
import itertools
range1=range(1,10)
range2=range(1,20)
for p1,p2 in itertools.product(range1,range1):
mat=np.random.rand(10,10)
index=np.unravel_index(mat.argmax(), mat.shape)
m=mat[index]
print m, index
```

For my application this is unfortunately too slow, I guess due to the usage of double for loops. Therefore I tried to pack everything in a 4-dimensional array (say BigMatrix), where the first two coordinates are the indexes p1,p2, and the other 2 are the coordinates of the matrices.

The np.amax command

```
>>res=np.amax(BigMatrix,axis=(2,3))
>>res.shape
(10,20)
>>res[p1,p2]==np.amax(BigMatrix[p1,p2,:,:])
True
```

works as expected, as it loops through the 2 and 3 axis. How can I do the same for np.argmax? Please keep in mind that speed is important.

Thank you very much in advance,

Enzo