Cheers. 2014-08-29 17:15 GMT+02:00 Edward d'Auvergne <[email protected]>: > Hi, > > I've now reintroduced the old C module > target_function.relax_fit.jacobian() function. See r25429 > (http://article.gmane.org/gmane.science.nmr.relax.scm/23188). I also > renamed target_function.relax_fit.jacobian() to > target_function.relax_fit.jacobian_chi2(). > > Regards, > > Edward > > > On 29 August 2014 12:40, <[email protected]> wrote: >> Author: tlinnet >> Date: Fri Aug 29 12:40:07 2014 >> New Revision: 25429 >> >> URL: http://svn.gna.org/viewcvs/relax?rev=25429&view=rev >> Log: >> Swithced in estimate_r2eff_err() to use the chi2 Jacobian from C code, and >> Jacobian from python code. >> >> task #7822(https://gna.org/task/index.php?7822): Implement user function to >> estimate R2eff and associated errors for exponential curve fitting. >> >> Modified: >> trunk/specific_analyses/relax_disp/estimate_r2eff.py >> >> Modified: trunk/specific_analyses/relax_disp/estimate_r2eff.py >> URL: >> http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/estimate_r2eff.py?rev=25429&r1=25428&r2=25429&view=diff >> ============================================================================== >> --- trunk/specific_analyses/relax_disp/estimate_r2eff.py (original) >> +++ trunk/specific_analyses/relax_disp/estimate_r2eff.py Fri Aug 29 >> 12:40:07 2014 >> @@ -175,7 +175,7 @@ >> i0 = getattr(cur_spin, 'i0')[param_key] >> >> # Pack data >> - params = [r2eff, i0] >> + param_vector = [r2eff, i0] >> >> # The peak intensities, errors and times. >> values = [] >> @@ -193,15 +193,18 @@ >> >> # Initialise data in C code. >> scaling_list = [1.0, 1.0] >> - setup(num_params=len(params), num_times=len(times), >> values=values, sd=errors, relax_times=times, scaling_matrix=scaling_list) >> - >> + setup(num_params=len(param_vector), num_times=len(times), >> values=values, sd=errors, relax_times=times, scaling_matrix=scaling_list) >> + >> + # Determine Jacobian and weights. >> if chi2_jacobian: >> - jacobian_matrix_exp = func_exp_chi2_grad(params=params, >> times=times, values=values, errors=errors) >> + # Calculate the direct exponential Jacobian matrix from C >> code. >> + jacobian_matrix_exp = transpose(asarray( >> jacobian(param_vector) ) ) >> + >> + # The Jacobian in the C-code is from chi2 function, and is >> already weighted. >> weights = ones(errors.shape) >> else: >> - # Calculate the direct exponential Jacobian matrix from C >> code. >> - #jacobian_matrix_exp = transpose(asarray( jacobian(params) >> ) ) >> - jacobian_matrix_exp = func_exp_grad(params=params, >> times=times, values=values, errors=errors) >> + # Use the direct Jacobian from python Code >> + jacobian_matrix_exp = func_exp_grad(params=param_vector, >> times=times, values=values, errors=errors) >> weights = 1. / errors**2 >> >> # Get the co-variance >> >> >> _______________________________________________ >> 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
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