On Sun, Mar 29, 2015 at 7:39 PM, Blake Griffith <blake.a.griff...@gmail.com> wrote: > I have an open PR which lets users control the checks on the input > covariance matrix. The matrix is required to be symmetric and positve > semi-definite (PSD). The current behavior is that NumPy raises a warning if > the matrix is not PSD, and does not even check for symmetry. > > I added a symmetry check, which raises a warning when the input is not > symmetric. And added two keyword args which users can use to turn off the > checks/warnings when the matrix is ill formed. So this would only cause > another new warning to be raised in existing code. > > This is needed because sometimes the covariance matrix is only *almost* > symmetric or PSD due to roundoff error. > > Thoughts?
My only question is why is **exact** symmetry relevant? AFAIU A empirical covariance matrix might not be exactly symmetric unless we specifically force it to be. But I don't see why some roundoff errors that violate symmetry should be relevant. use allclose with floating point rtol or equivalent? Some user code might suddenly get irrelevant warnings. BTW: neg = (np.sum(u.T * v, axis=1) < 0) & (s > 0) doesn't need to be calculated if cov_psd is false. ----- some more: svd can hang if the values are not finite, i.e. nan or infs counter proposal would be to add a `check_valid` keyword with option ignore. warn, raise, and "fix" and raise an error if there are nans and check_valid is not ignore. --------- aside: np.random.multivariate_normal is only relevant if you have a new cov each call (or don't mind repeated possibly expensive calculations), so, I guess, adding checks by default won't upset many users. Josef > > > PR: https://github.com/numpy/numpy/pull/5726 > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
