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Description
When using numpy.linalg.norm with ord different from 2, for example 3, then I expected the norm to be computed according to the documentation, i.e. as sum(abs(x)**ord)**(1./ord)
But instead I got:
ValueError Traceback (most recent call last)
<ipython-input-784-3344f4d8d663> in <module>()
----> 1 nnorm((distpdfs_diverg['BC']/n_samples) - np.eye(n_bundles), 3)
/usr/lib/python3.5/site-packages/numpy/linalg/linalg.py in norm(x, ord, axis, keepdims)
2247 ret = _multi_svd_norm(x, row_axis, col_axis, sum)
2248 else:
-> 2249 raise ValueError("Invalid norm order for matrices.")
2250 if keepdims:
2251 ret_shape = list(x.shape)
ValueError: Invalid norm order for matrices.
Looking at the source code (numpy 1.13, numpy 1.14, and current) it seems it is simply the norm is simply not implemented for ord greater than 2 contrarily to what the doc says. Would that be something difficult to do?