Hi, 16.02.2012 06:09, [email protected] kirjoitti: [clip] > numpy linalg.svd doesn't produce always the same results > > running this gives two different answers, > using scipy.linalg.svd I always get the same answer, which is one of > the numpy answers > (numpy random.multivariate_normal is collateral damage)
Are you using a Windows binary for Numpy compiled with the Intel compilers, or maybe linked with Intel MKL? If yes, one possibility is that the exact sequence of floating point operations in SVD or some other step in the calculation depends on the data alignment, which can affect rounding error. See http://www.nccs.nasa.gov/images/FloatingPoint_consistency.pdf That would explain why the pattern you see is quasi-deterministic. The other explanation would be using uninitialized memory at some point, but that seems quite unlikely. -- Pauli Virtanen _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
