Flatten numpy array but also keep index of value positions?

Question

I have several 2D numpy arrays (matrix) and for each one I would like to convert it to vector containing the values of the array and a vector containing each row/column index.

Answer 1

Like @miguel-capllonch I would suggest using np.ndindex which allows you to create the desired output like this:

np.array([(v, *i) for (i, v) in zip(np.ndindex(x.shape), x.ravel())])

which results in an array that looks like this:

array([[ 3.  0.  0.]
       [ 1.  0.  1.]
       [ 4.  0.  2.]
       [ 1.  1.  0.]
       [ 5.  1.  1.]
       [ 9.  1.  2.]
       [ 2.  2.  0.]
       [ 6.  2.  1.]
       [ 5.  2.  2.]])

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Alternatively, using only numpy commands

np.hstack((list(np.ndindex(x.shape)), x.reshape((-1, 1))))