Suppose I have a numpy array A with shape (j,d,d) and I want to obtain an array with shape j, in which each entry corresponds to the determinant of each (d,d) array.

I tried using np.apply_along_axis(np.linalg.det(A), axis=0), but np.apply_along_axis only seems to work for 1D slices.

Is there an efficient way of doing that using only numpy?

CodePudding user response：

np.linalg.det can already do this for an array of arbitrary shape as long as the last two dimensions are square. You can see the documentation here.