I'm curious why scipy/numpy defaults to calculating the Frobenius norm for matrices [1], when Matlab, Octave, and Mathematica all default to calculating the induced 2-norm [2]. Is it solely because the Frobenius norm is easier to calculate, or is there some other good mathematical reason for doing things differently?
Thanks, Jason [1] http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.norm.html [2] * Matlab (http://www.mathworks.com/help/matlab/ref/norm.html). * Octave (http://www.network-theory.co.uk/docs/octave3/octave_198.html). * Mathematica (http://reference.wolfram.com/mathematica/ref/Norm.html) _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
