Status: New
Owner: ----
Labels: Type-Defect Priority-Medium
New issue 2225 by [email protected]: Enhancing Matrix Norm
http://code.google.com/p/sympy/issues/detail?id=2225
Currently the norm function on matrices only works for rows or columns (1d
matrices) and only performs the 2-norm
norm(x) = sqrt(Sum_i (x[i])**2))
I think it would be nice to have Sympy's norm function identically to
numpy's linalg.norm. This can be done without breaking backwards
compatibility.
help numpy.linalg.norm yields:
...
The following norms can be calculated:
===== ============================ ==========================
ord norm for matrices norm for vectors
===== ============================ ==========================
None Frobenius norm 2-norm
'fro' Frobenius norm --
inf max(sum(abs(x), axis=1)) max(abs(x))
-inf min(sum(abs(x), axis=1)) min(abs(x))
1 max(sum(abs(x), axis=0)) as below
-1 min(sum(abs(x), axis=0)) as below
2 2-norm (largest sing. value) as below
-2 smallest singular value as below
other -- sum(abs(x)**ord)**(1./ord)
===== ============================ ==========================
Thoughts? Concerns?
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