Closed idontgetoutmuch closed 9 years ago
Sorry for the missing documentation, I will update it shortly.
The matrix norms follow the standard definitions found in other numeric software: norm_2 is the maximum singular value, norm_1 is the largest column sum of absolute values, etc.
Thanks for your comment!
Ah that makes sense thanks - so norm_2 should be the usual L2 norm on vectors?
Yes, on vectors norm_1, norm_2, and norm_Inf are the usual L norms, and norm_0 is the number of nonzero elements. On matrices we have the same definitions as in GNU-Octave: norm_1, the largest column sum of the absolute values. norm_2: Largest singular value. norm_Inf: the largest row sum of the absolute values. norm_Frob = norm_2 . flatten (Frobenius norm) and also norm_nuclear = sumElements . singularValues (norm_0 also works on matrices.)
Perhaps this is just a lack of documentation.
as expected but
If this is correct, perhaps the definition of or reference to the norm could be given with the function?