Hi, I've been lurking for a while here but never really introduced myself. I'm a mathematician in Brazil working with optimization and numerical analysis and I'm looking into scipy/numpy basically because I want to ditch matlab.
I'm just curious as to why you say "scipy.linalg.solve(), NOT numpy.linalg.solve()". Can you explain the reason for this? I find myself looking for information such as this on the internet but I rarely find real documentation for these things, and I seem to have so many performance issues with python... I'm curious to see what I'm missing here. Thanks, and sorry if I hijacked the thread, - Melissa On Mon, Aug 30, 2010 at 3:59 PM, David Warde-Farley <d...@cs.toronto.edu> wrote: > > On 2010-08-30, at 11:28 AM, Daniel Elliott wrote: > >> Hello, >> >> I am new to Python (coming from R and Matlab/Octave). I was preparing >> to write my usual compute pdf of a really high dimensional (e.g. 10000 >> dimensions) Gaussian code in Python but I noticed that numpy had a >> function for computing the log determinant in these situations. > > Yep. Keep in mind this is a fairly recent addition, in 1.5 I think, so if you > ship code make sure to list this dependency. > >> Is there a function for performing the inverse or even the pdf of a >> multinomial normal in these situations as well? > > > There's a function for the inverse, but you almost never want to use it, > especially if your goal is the multivariate normal density. A basic > explanation of why is available here: > http://www.johndcook.com/blog/2010/01/19/dont-invert-that-matrix/ > > In the case of the multivariate normal density the covariance is assumed to > be positive definite, and thus a Cholesky decomposition is appropriate. > scipy.linalg.solve() (NOT numpy.linalg.solve()) with the sym_pos=True > argument will do this for you. > > What do you mean by a "multinomial normal"? Do you mean multivariate normal? > Offhand I can't remember if it exists in scipy.stats, but I know there's code > for it in PyMC. > > David > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > -- Melissa Weber Mendonça -- "Knowledge is knowing a tomato is a fruit; wisdom is knowing you don't put tomato in fruit salad." _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
