[Python] Find index of min value in a matrix

I've a 2-Dim array containing the residual sum of squares of a given fit (unimportant here).

RSS[i,j] = np.sum((spectrum_theo - sp_exp_int) ** 2)


I would like to find the matrix element with the minimum value AND its position (i,j) in the matrix. Find the minimum element is OK:

RSS_min = RSS[RSS != 0].min()


but for the index, I've tried:

ij_min = np.where(RSS == RSS_min)


which gives me:

ij_min = (array([3]), array([20]))


I would like to obtain instead:

ij_min = (3,20)

If I try :

ij_min = RSS.argmin()


I obtain:

ij_min = 0,


which is a wrong result.

Does it exist a function, in Scipy or elsewhere, that can do it? I've searched on the web, but I've found answers leading only with 1-Dim arrays, not 2- or N-Dim.

Thanks!

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