Hi, The relax_disp.r2eff_read* user functions should have enough information. Well, the user will have to use the relax_disp.cpmg_setup, relax_disp.spin_lock_field, relax_disp.spin_lock_offset, relax_disp.exp_type, etc. user functions to set up the metadata if relax_disp.r2eff_read was used (but not relax_disp.r2eff_read_spin). But the value.copy user function is probably insufficient as the metadata is not copied. This works if the base pipe has the metadata already though, which should be the case. Am I missing something?
Regards, Edward On 20 August 2014 18:19, Troels Emtekær Linnet <[email protected]> wrote: > Hi Edward. > > I partly implemented this. > > But I think some of the functionality still missing in the run(self) > part of the analysis. > > I think this part will give problems. > > -------- > # Select the model. > self.interpreter.relax_disp.select_model(model) > > # Copy the R2eff values from the R2eff model data pipe. > if model != MODEL_R2EFF and MODEL_R2EFF in self.models: > > self.interpreter.value.copy(pipe_from=self.name_pipe(MODEL_R2EFF), > pipe_to=model_pipe, param='r2eff') > > # Calculate the R2eff values for the fixed relaxation time > period data types. > if model == MODEL_R2EFF and not has_exponential_exp_type(): > self.interpreter.minimise.calculate() > --------- > > Just reading in R2eff values by relax_disp.r2eff_read, will not give > enough information? > > best > Troels > > 2014-08-18 18:46 GMT+02:00 Edward d'Auvergne <[email protected]>: >> I would suggest a slightly different solution. If the data pipe sent >> into the auto-analysis already contains R2eff values and errors, then >> skip that model optimisation. The flag can be used anyway to force >> the R2eff parameter optimisation. >> >> On another note, this flag is not necessarily related to the pre_run >> and can be used without a pre-run. For example, a user like Nikolai >> could have files of R2eff values that are read in via the >> relax_disp.r2eff_read. So the flag would be better called >> optimise_r2eff. You currently use the flag when no pre-run data is >> used, so that part needs no changing. >> >> Cheers, >> >> Edward >> >> >> >> On 12 August 2014 15:23, <[email protected]> wrote: >>> Author: tlinnet >>> Date: Tue Aug 12 15:23:57 2014 >>> New Revision: 25000 >>> >>> URL: http://svn.gna.org/viewcvs/relax?rev=25000&view=rev >>> Log: >>> Added keyword to relax_disp auto analysis, if R2eff values should be >>> optimised. >>> >>> Here optimisation means minimisation and Monte Carlo simulations of the >>> error. >>> >>> sr #3135(https://gna.org/support/?3135): Optimisation of the R1 relaxation >>> rate for the off-resonance R1rho relaxation dispersion models. >>> >>> Modified: >>> branches/R1_fitting/auto_analyses/relax_disp.py >>> >>> Modified: branches/R1_fitting/auto_analyses/relax_disp.py >>> URL: >>> http://svn.gna.org/viewcvs/relax/branches/R1_fitting/auto_analyses/relax_disp.py?rev=25000&r1=24999&r2=25000&view=diff >>> ============================================================================== >>> --- branches/R1_fitting/auto_analyses/relax_disp.py (original) >>> +++ branches/R1_fitting/auto_analyses/relax_disp.py Tue Aug 12 15:23:57 >>> 2014 >>> @@ -51,38 +51,39 @@ >>> opt_func_tol = 1e-25 >>> opt_max_iterations = int(1e7) >>> >>> - def __init__(self, pipe_name=None, pipe_bundle=None, results_dir=None, >>> models=[MODEL_R2EFF], grid_inc=11, mc_sim_num=500, exp_mc_sim_num=None, >>> modsel='AIC', pre_run_dir=None, insignificance=0.0, numeric_only=False, >>> mc_sim_all_models=False, eliminate=True, set_grid_r20=False): >>> + def __init__(self, pipe_name=None, pipe_bundle=None, results_dir=None, >>> models=[MODEL_R2EFF], grid_inc=11, mc_sim_num=500, exp_mc_sim_num=None, >>> modsel='AIC', pre_run_dir=None, optimise_pre_run_r2eff=True, >>> insignificance=0.0, numeric_only=False, mc_sim_all_models=False, >>> eliminate=True, set_grid_r20=False): >>> """Perform a full relaxation dispersion analysis for the given >>> list of models. >>> >>> - @keyword pipe_name: The name of the data pipe containing >>> all of the data for the analysis. >>> - @type pipe_name: str >>> - @keyword pipe_bundle: The data pipe bundle to associate all >>> spawned data pipes with. >>> - @type pipe_bundle: str >>> - @keyword results_dir: The directory where results files are >>> saved. >>> - @type results_dir: str >>> - @keyword models: The list of relaxation dispersion >>> models to optimise. >>> - @type models: list of str >>> - @keyword grid_inc: Number of grid search increments. If >>> set to None, then the grid search will be turned off and the default >>> parameter values will be used instead. >>> - @type grid_inc: int or None >>> - @keyword mc_sim_num: The number of Monte Carlo simulations >>> to be used for error analysis at the end of the analysis. >>> - @type mc_sim_num: int >>> - @keyword exp_mc_sim_num: The number of Monte Carlo simulations >>> for the error analysis in the 'R2eff' model when exponential curves are >>> fitted. This defaults to the value of the mc_sim_num argument when not >>> given. For the 2-point fixed-time calculation for the 'R2eff' model, this >>> argument is ignored. >>> - @type exp_mc_sim_num: int or None >>> - @type >>> - @keyword modsel: The model selection technique to use >>> in the analysis to determine which model is the best for each spin cluster. >>> This can currently be one of 'AIC', 'AICc', and 'BIC'. >>> - @type modsel: str >>> - @keyword pre_run_dir: The optional directory containing the >>> dispersion auto-analysis results from a previous run. The optimised >>> parameters from these previous results will be used as the starting point >>> for optimisation rather than performing a grid search. This is essential >>> for when large spin clusters are specified, as a grid search becomes >>> prohibitively expensive with clusters of three or more spins. At some >>> point a RelaxError will occur because the grid search is impossibly large. >>> For the cluster specific parameters, i.e. the populations of the states and >>> the exchange parameters, an average value will be used as the starting >>> point. For all other parameters, the R20 values for each spin and magnetic >>> field, as well as the parameters related to the chemical shift difference >>> dw, the optimised values of the previous run will be directly copied. >>> - @type pre_run_dir: None or str >>> - @keyword insignificance: The R2eff/R1rho value in rad/s by >>> which to judge insignificance. If the maximum difference between two >>> points on all dispersion curves for a spin is less than this value, that >>> spin will be deselected. This does not affect the 'No Rex' model. Set >>> this value to 0.0 to use all data. The value will be passed on to the >>> relax_disp.insignificance user function. >>> - @type insignificance: float >>> - @keyword numeric_only: The class of models to use in the >>> model selection. The default of False allows all dispersion models to be >>> used in the analysis (no exchange, the analytic models and the numeric >>> models). The value of True will activate a pure numeric solution - the >>> analytic models will be optimised, as they are very useful for replacing >>> the grid search for the numeric models, but the final model selection will >>> not include them. >>> - @type numeric_only: bool >>> - @keyword mc_sim_all_models: A flag which if True will cause Monte >>> Carlo simulations to be performed for each individual model. Otherwise >>> Monte Carlo simulations will be reserved for the final model. >>> - @type mc_sim_all_models: bool >>> - @keyword eliminate: A flag which if True will enable the >>> elimination of failed models and failed Monte Carlo simulations through the >>> eliminate user function. >>> - @type eliminate: bool >>> - @keyword set_grid_r20: A flag which if True will set the grid >>> R20 values from the minimum R2eff values through the r20_from_min_r2eff >>> user function. This will speed up the grid search with a factor >>> GRID_INC^(Nr_spec_freq). For a CPMG experiment with two fields and standard >>> GRID_INC=21, the speed-up is a factor 441. >>> - @type set_grid_r20: bool >>> + @keyword pipe_name: The name of the data pipe >>> containing all of the data for the analysis. >>> + @type pipe_name: str >>> + @keyword pipe_bundle: The data pipe bundle to >>> associate all spawned data pipes with. >>> + @type pipe_bundle: str >>> + @keyword results_dir: The directory where results >>> files are saved. >>> + @type results_dir: str >>> + @keyword models: The list of relaxation >>> dispersion models to optimise. >>> + @type models: list of str >>> + @keyword grid_inc: Number of grid search >>> increments. If set to None, then the grid search will be turned off and >>> the default parameter values will be used instead. >>> + @type grid_inc: int or None >>> + @keyword mc_sim_num: The number of Monte Carlo >>> simulations to be used for error analysis at the end of the analysis. >>> + @type mc_sim_num: int >>> + @keyword exp_mc_sim_num: The number of Monte Carlo >>> simulations for the error analysis in the 'R2eff' model when exponential >>> curves are fitted. This defaults to the value of the mc_sim_num argument >>> when not given. For the 2-point fixed-time calculation for the 'R2eff' >>> model, this argument is ignored. >>> + @type exp_mc_sim_num: int or None >>> + @keyword modsel: The model selection technique >>> to use in the analysis to determine which model is the best for each spin >>> cluster. This can currently be one of 'AIC', 'AICc', and 'BIC'. >>> + @type modsel: str >>> + @keyword pre_run_dir: The optional directory >>> containing the dispersion auto-analysis results from a previous run. The >>> optimised parameters from these previous results will be used as the >>> starting point for optimisation rather than performing a grid search. This >>> is essential for when large spin clusters are specified, as a grid search >>> becomes prohibitively expensive with clusters of three or more spins. At >>> some point a RelaxError will occur because the grid search is impossibly >>> large. For the cluster specific parameters, i.e. the populations of the >>> states and the exchange parameters, an average value will be used as the >>> starting point. For all other parameters, the R20 values for each spin and >>> magnetic field, as well as the parameters related to the chemical shift >>> difference dw, the optimised values of the previous run will be directly >>> copied. >>> + @type pre_run_dir: None or str >>> + @keyword optimise_pre_run_r2eff: Flag to specify if the read >>> previous R2eff results should be optimised. For R1rho models where the >>> error of R2eff values are determined by Monte-Carlo simulations, it can be >>> valuable to make an initial R2eff run with a high number of Monte-Carlo >>> simulations. Any subsequent model analysis can then be based on these >>> R2eff values, without optimising the R2eff values. >>> + @type optimise_pre_run_r2eff: bool >>> + @keyword insignificance: The R2eff/R1rho value in rad/s >>> by which to judge insignificance. If the maximum difference between two >>> points on all dispersion curves for a spin is less than this value, that >>> spin will be deselected. This does not affect the 'No Rex' model. Set >>> this value to 0.0 to use all data. The value will be passed on to the >>> relax_disp.insignificance user function. >>> + @type insignificance: float >>> + @keyword numeric_only: The class of models to use in >>> the model selection. The default of False allows all dispersion models to >>> be used in the analysis (no exchange, the analytic models and the numeric >>> models). The value of True will activate a pure numeric solution - the >>> analytic models will be optimised, as they are very useful for replacing >>> the grid search for the numeric models, but the final model selection will >>> not include them. >>> + @type numeric_only: bool >>> + @keyword mc_sim_all_models: A flag which if True will >>> cause Monte Carlo simulations to be performed for each individual model. >>> Otherwise Monte Carlo simulations will be reserved for the final model. >>> + @type mc_sim_all_models: bool >>> + @keyword eliminate: A flag which if True will >>> enable the elimination of failed models and failed Monte Carlo simulations >>> through the eliminate user function. >>> + @type eliminate: bool >>> + @keyword set_grid_r20: A flag which if True will set >>> the grid R20 values from the minimum R2eff values through the >>> r20_from_min_r2eff user function. This will speed up the grid search with a >>> factor GRID_INC^(Nr_spec_freq). For a CPMG experiment with two fields and >>> standard GRID_INC=21, the speed-up is a factor 441. >>> + @type set_grid_r20: bool >>> """ >>> >>> # Printout. >>> @@ -104,6 +105,7 @@ >>> self.exp_mc_sim_num = exp_mc_sim_num >>> self.modsel = modsel >>> self.pre_run_dir = pre_run_dir >>> + self.optimise_pre_run_r2eff = optimise_pre_run_r2eff >>> self.insignificance = insignificance >>> self.set_grid_r20 = set_grid_r20 >>> self.numeric_only = numeric_only >>> @@ -481,14 +483,21 @@ >>> self.interpreter.value.set(param=param, index=None) >>> >>> # Minimise. >>> - self.interpreter.minimise.execute('simplex', >>> func_tol=self.opt_func_tol, max_iter=self.opt_max_iterations, >>> constraints=True) >>> + if model == MODEL_R2EFF: >>> + if self.optimise_pre_run_r2eff: >>> + self.interpreter.minimise.execute('simplex', >>> func_tol=self.opt_func_tol, max_iter=self.opt_max_iterations, >>> constraints=True) >>> + else: >>> + pass >>> + else: >>> + self.interpreter.minimise.execute('simplex', >>> func_tol=self.opt_func_tol, max_iter=self.opt_max_iterations, >>> constraints=True) >>> + >>> >>> # Model elimination. >>> if self.eliminate: >>> self.interpreter.eliminate() >>> >>> # Monte Carlo simulations. >>> - if self.mc_sim_all_models or len(self.models) < 2 or model == >>> MODEL_R2EFF: >>> + if self.mc_sim_all_models or len(self.models) < 2 or (model == >>> MODEL_R2EFF and self.optimise_pre_run_r2eff): >>> if model == MODEL_R2EFF and self.exp_mc_sim_num != None: >>> >>> self.interpreter.monte_carlo.setup(number=self.exp_mc_sim_num) >>> else: >>> >>> >>> _______________________________________________ >>> 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
