Hi Troels, For your analysis, are you using the dispersion auto-analysis? You should avoid this and write a custom script for speed. As for the optimisation accuracy, for your problem it could be dangerous to decrease this. The reason is because you are starting at the correct values and looking if this changes. But if you change the optimisation settings, you may not be able to optimise away from the correct values to the incorrect values you are most interested in. You should also really think if you should be using spin clustering, as that will be a major reason for the long computation times. And for your problem, it might hide interesting results.
I would also consider removing the Monte Carlo simulations, unless you wish to study the variation in the errors as well. But 50 simulations is no where near enough for that anyway, so you should either increase this to 500-2000 or decrease it to 0. 50 MC simulations gives very noisy errors - the error in the error is huge. Regards, Edward On 27 March 2014 17:42, Troels Emtekær Linnet <tlin...@nmr-relax.com> wrote: > Dear Edward. > > I am working on a systematic investigations of dynamic parameters for hundreds > of datasets. > > For one example, a CPMG analysis is setup for: > 17 variations of tau_cpmg > The number of MC simulations is 50. > 82 spins which are all clustered. > > There is no grid search, and only TSMFK01 is used. > I do one grid search in the start, minimise this, copy over the > parameters and take median, make a clustering analysis, and then > repeat the last step 60 times. > This would again would be needed to repeat 5-8 times for other > datasets with variations. > And then for other proteins. (Sigh..) > > I have setup relax to use 20 processors on our server, and a > dispersion analysis takes > between 2-6 Hours. > > That is a reasonable timeframe for an normal analysis of this type. > > But I have to squeeze hundreds of these analysis through relax, to get > variation of the dynamic parameters. > > Our old Igor Pro scripts, could do a global fitting in 10 minutes. > That does not include MC simulations. > > But I wonder if I could speed up relax by changing function tolerance > and maximum number of iterations: > minimise(min_algor='simplex', line_search=None, hessian_mod=None, > hessian_type=None, func_tol=OPT_FUNC_TOL, grad_tol=None, > max_iter=OPT_MAX_ITERATIONS, constraints=True, scaling=True, > verbosity=1) > > where standard values of: > OPT_FUNC_TOL = 1e-25 > OPT_MAX_ITERATIONS = 10000000 > > Could you advise if this strategy is possible? > > What I hope for, is that an analysis come down to 10-20 minutes? > Maybe I could cut away the MC simulations, since I am mostly > interested in the fitted dynamic parameters, and not so much about > their error? > > Thank you in advance! > > Best > Troels > > _______________________________________________ > relax (http://www.nmr-relax.com) > > This is the relax-users mailing list > relax-users@gna.org > > 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-users _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-users mailing list relax-users@gna.org 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-users