Ok, then appropriate changes in http://www.scipy.org/NumPy_for_Matlab_Users should be made D.
Robert Kern wrote: > dmitrey wrote: > >> hi all, >> I was very surprised that norm() is present in scipy.linalg but absent >> in numpy. >> Don't you think it's better to add the one to numpy? >> > > In [237]: import numpy > > In [238]: numpy.linalg.norm? > Type: function > Base Class: <type 'function'> > Namespace: Interactive > File: > /Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/numpy-1.0.3.dev3795-py2.5-macosx-10.3-fat.egg/numpy/linalg/linalg.py > Definition: numpy.linalg.norm(x, ord=None) > Docstring: > norm(x, ord=None) -> n > > Matrix or vector norm. > > Inputs: > > x -- a rank-1 (vector) or rank-2 (matrix) array > ord -- the order of the norm. > > Comments: > For arrays of any rank, if ord is None: > calculate the square norm (Euclidean norm for vectors, > Frobenius norm for matrices) > > For vectors ord can be any real number including Inf or -Inf. > ord = Inf, computes the maximum of the magnitudes > ord = -Inf, computes minimum of the magnitudes > ord is finite, computes sum(abs(x)**ord,axis=0)**(1.0/ord) > > For matrices ord can only be one of the following values: > ord = 2 computes the largest singular value > ord = -2 computes the smallest singular value > ord = 1 computes the largest column sum of absolute values > ord = -1 computes the smallest column sum of absolute values > ord = Inf computes the largest row sum of absolute values > ord = -Inf computes the smallest row sum of absolute values > ord = 'fro' computes the frobenius norm sqrt(sum(diag(X.H * > X),axis=0)) > > For values ord < 0, the result is, strictly speaking, not a > mathematical 'norm', but it may still be useful for numerical purposes. > > _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
