Hi, This should be possible. It is only a question of difficulty. The infrastructure is not in place to handle this as only the back-calculated values corresponding to the measured values are calculated. This is more scientifically valuable as the quality of fit should be judged by the residuals, specifically if there is a bias in the residuals. However having a graph with more points can be added. I am assuming that the aim is the individual graphs produced by the relax_disp.plot_disp_curves user function. This would be the easiest place to add such a feature. If you are interested in the grace.write user function, we will be in much, much more trouble as such interpolation cannot be made general, especially if the x-axis are the residue numbers. The way this could be done, assuming we are working with the relax_disp.plot_disp_curves user function, is to use the target function code already in relax. I would suggest adding this as another set to the graphs, leaving all the current sets as they are. Then it can be turned on and off, as desired. For inspiration, have a look at the _back_calc_r2eff() method in specific_analyses.relax_disp.api. The key would be to mimic this method but increase the dimensionality of the data structures for the interpolation. The values, errors and missing data structures can be created with the numpy.zeros and numpy.ones functions. You will also need to increase the dimensionality of the cpmg_frqs and spin_lock_nu1 structures sent into the Dispersion target function class for the interpolation - both will have to be handled! Hence both would need to be tested in the test suite. Have a look around the code and see what you think. Regards, Edward On 9 September 2013 21:47, Troels Emtekær Linnet <tlinnet@xxxxxxxxx> wrote:
Hi Edward. I would like to produce some graphs with more points than the standard graphs. Particularly, I am looking for something similar to make an numpy arange from min to max of cpmg frequencies, and interpolate with 50 points? Calculate the R2eff values from the fitted parameters of the model equation at populate a list of y_values. That would produce more interesting graphs to look at, than graphs with only 10-20 points. Is there a way to call the model function? Troels Emtekær Linnet _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-devel mailing list relax-devel@xxxxxxx 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