True true. Best Troels
2014-09-02 10:49 GMT+02:00 Edward d'Auvergne <[email protected]>: > Hi Troels, > > This is not the correct approach. These higher dimensions must be > missing from the gradient, Hessian, Jacobian, and covariance matrix. > If N is the number of parameters and M is the number of input data > sets (R2eff/R1rho/R1), then these structures must absolutely have the > following dimensions: > > - function = 1, > - gradient = N, > - Hessian = NxN, > - Jacobian = NxM, > - covariance matrix = NxN. > > If they don't have these exact dimensions, then they cannot be called > by those names. You have no choice. Their dimensionality matches > that of the input parameter vector! You have to loose all of the NE, > NS, NM, NO, and ND dimensions in all of these structures. > > Regards, > > Edward > > On 2 September 2014 10:29, <[email protected]> wrote: >> Author: tlinnet >> Date: Tue Sep 2 10:29:48 2014 >> New Revision: 25530 >> >> URL: http://svn.gna.org/viewcvs/relax?rev=25530&view=rev >> Log: >> Added comments to co-variance module, for explanation of data dimensionality. >> >> task #7824(https://gna.org/task/index.php?7824): Model parameter ERROR >> estimation from Jacobian and Co-variance matrix of dispersion models. >> >> Modified: >> branches/est_par_error/lib/statistics.py >> >> Modified: branches/est_par_error/lib/statistics.py >> URL: >> http://svn.gna.org/viewcvs/relax/branches/est_par_error/lib/statistics.py?rev=25530&r1=25529&r2=25530&view=diff >> ============================================================================== >> --- branches/est_par_error/lib/statistics.py (original) >> +++ branches/est_par_error/lib/statistics.py Tue Sep 2 10:29:48 2014 >> @@ -229,6 +229,11 @@ >> # Get the expected shape of the higher dimensional column numpy array. >> if len(weights.shape) == 2: >> # Extract shapes from data. >> + # NE: Number of experiments. >> + # NS: Number of spins. >> + # NM: Number of spectrometer frequencies. >> + # NO: Maximum number of offsets. >> + # ND: Number of dispersion(data) points. >> NE, NS, NM, NO, ND = 1, 1, 1, 1, weights.shape[-1] >> >> # Make a eye matrix, with Shape [ND][ND] >> >> >> _______________________________________________ >> relax (http://www.nmr-relax.com) >> >> This is the relax-commits mailing list >> [email protected] >> >> To unsubscribe from this list, get a password >> reminder, or change your subscription options, >> visit the list information page at >> https://mail.gna.org/listinfo/relax-commits > > _______________________________________________ > relax (http://www.nmr-relax.com) > > This is the relax-devel mailing list > [email protected] > > To unsubscribe from this list, get a password > reminder, or change your subscription options, > visit the list information page at > https://mail.gna.org/listinfo/relax-devel _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-devel mailing list [email protected] To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-devel
