Hi Edward. I don't think such things should be modified in the back-end code, but rather it the front-end code, helping selecting the right model.
Using scripting, it should be possible to do access all parts of the code. Even if it does not give any sense. A better functionality, would be to implement a function, which go through the self.models, and suggest the correct models to use instead. Best Troels 2014-08-18 11:02 GMT+02:00 Edward d'Auvergne <[email protected]>: > Hi, > > If all the 'No Rex' models are merged into a single model, then the > methods here would remain identical. However the logic of the "if > model == MODEL_NOREX:" block would be modified to select the correct > target function based on the data that the user input. Or even > simpler, the logic could be placed higher up in a function in the > specific_analyses.relax_disp.data module, and then a new argument > added to the target function class for choosing between the target > functions. Note that a 4th target function will probably be added in > the future when off-resonance CPMG data is handled, to allow R1 to be > optimised with this data. > > Cheers, > > Edward > > > > On 4 August 2014 19:22, <[email protected]> wrote: >> Author: tlinnet >> Date: Mon Aug 4 19:22:10 2014 >> New Revision: 24945 >> >> URL: http://svn.gna.org/viewcvs/relax?rev=24945&view=rev >> Log: >> Implemented target and calculation function for MODEL_NOREX_R1RHO, >> MODEL_NOREX_R1RHO_FIT_R1. >> >> bug #22440(https://gna.org/bugs/?22440): The "NOREX" model is not covering >> R1rho models. >> 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/target_functions/relax_disp.py >> >> Modified: branches/R1_fitting/target_functions/relax_disp.py >> URL: >> http://svn.gna.org/viewcvs/relax/branches/R1_fitting/target_functions/relax_disp.py?rev=24945&r1=24944&r2=24945&view=diff >> ============================================================================== >> --- branches/R1_fitting/target_functions/relax_disp.py (original) >> +++ branches/R1_fitting/target_functions/relax_disp.py Mon Aug 4 19:22:10 >> 2014 >> @@ -55,7 +55,7 @@ >> from lib.errors import RelaxError >> from lib.float import isNaN >> from target_functions.chi2 import chi2_rankN >> -from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_DQ, >> EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, >> EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST_CPMG, EXP_TYPE_R1RHO, >> MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, >> MODEL_DPL94_FIT_R1, MODEL_IT99, MODEL_LIST_CPMG, MODEL_LIST_FULL, >> MODEL_LIST_MMQ, MODEL_LIST_MQ_CPMG, MODEL_LIST_NUMERIC, MODEL_LIST_R1RHO, >> MODEL_LIST_R1RHO_FULL, MODEL_LIST_R1RHO_FIT_R1, MODEL_LM63, >> MODEL_LM63_3SITE, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_MMQ_CR72, >> MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL, >> MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR, >> MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE, MODEL_NS_MMQ_3SITE, >> MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE, >> MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_PARAM_DW_MIX_DOUBLE, >> MODEL_PARAM_DW_MIX_QUADRUPLE, MODEL_PARAM_INV_RELAX_TIMES, MODEL_PARAM_R20B, >> MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01 >> +from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_DQ, >> EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, >> EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST_CPMG, EXP_TYPE_R1RHO, >> MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, >> MODEL_DPL94_FIT_R1, MODEL_IT99, MODEL_LIST_CPMG, MODEL_LIST_FULL, >> MODEL_LIST_MMQ, MODEL_LIST_MQ_CPMG, MODEL_LIST_NUMERIC, MODEL_LIST_R1RHO, >> MODEL_LIST_R1RHO_FULL, MODEL_LIST_R1RHO_FIT_R1, MODEL_LM63, >> MODEL_LM63_3SITE, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_MMQ_CR72, >> MODEL_NOREX, MODEL_NOREX_R1RHO, MODEL_NOREX_R1RHO_FIT_R1, >> MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL, >> MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR, >> MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE, MODEL_NS_MMQ_3SITE, >> MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE, >> MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_PARAM_DW_MIX_DOUBLE, >> MODEL_PARAM_DW_MIX_QUADRUPLE, MODEL_PARAM_INV_RELAX_TIMES, MODEL_PARAM_R20B, >> MODEL _TAP03, MODEL_TP02, MODEL_TSMFK01 >> >> >> class Dispersion: >> @@ -482,6 +482,10 @@ >> # Set up the model. >> if model == MODEL_NOREX: >> self.func = self.func_NOREX >> + if model == MODEL_NOREX_R1RHO: >> + self.func = self.func_NOREX_R1RHO >> + if model == MODEL_NOREX_R1RHO_FIT_R1: >> + self.func = self.func_NOREX_R1RHO_FIT_R1 >> if model == MODEL_LM63: >> self.func = self.func_LM63 >> if model == MODEL_LM63_3SITE: >> @@ -653,6 +657,35 @@ >> return chi2_rankN(self.values, self.back_calc, self.errors) >> >> >> + def calc_NOREX_R1RHO(self, R1=None, r1rho_prime=None): >> + """Calculation function for no exchange, for R1rho off resonance >> models. >> + >> + @keyword R1: The R1 value. >> + @type R1: list of float >> + @keyword r1rho_prime: The R1rho value for all states in the >> absence of exchange. >> + @type r1rho_prime: list of float >> + @return: The chi-squared value. >> + @rtype: float >> + """ >> + >> + # Reshape r1rho_prime to per experiment, spin and frequency. >> + self.r1rho_prime_struct[:] = multiply.outer( >> r1rho_prime.reshape(self.NE, self.NS, self.NM), self.no_nd_ones ) >> + >> + # Make back calculation. >> + self.back_calc[:] = R1 * cos(self.tilt_angles)**2 + >> self.r1rho_prime_struct * sin(self.tilt_angles)**2 >> + >> + # Clean the data for all values, which is left over at the end of >> arrays. >> + self.back_calc = self.back_calc*self.disp_struct >> + >> + # For all missing data points, set the back-calculated value to the >> measured values so that it has no effect on the chi-squared value. >> + if self.has_missing: >> + # Replace with values. >> + self.back_calc[self.mask_replace_blank.mask] = >> self.values[self.mask_replace_blank.mask] >> + >> + # Return the total chi-squared value. >> + return chi2_rankN(self.values, self.back_calc, self.errors) >> + >> + >> def calc_ns_cpmg_2site_3D_chi2(self, R20A=None, R20B=None, dw=None, >> pA=None, kex=None): >> """Calculate the chi-squared value of the 'NS CPMG 2-site' models. >> >> @@ -1395,6 +1428,50 @@ >> return chi2_rankN(self.values, self.back_calc, self.errors) >> >> >> + def func_NOREX_R1RHO(self, params): >> + """Target function for no exchange, for R1rho off resonance models. >> + >> + @param params: The vector of parameter values. >> + @type params: numpy rank-1 float array >> + @return: The chi-squared value. >> + @rtype: float >> + """ >> + >> + # Scaling. >> + if self.scaling_flag: >> + params = dot(params, self.scaling_matrix) >> + >> + # Unpack the parameter values. >> + r1rho_prime = params >> + >> + # Calculate and return the chi-squared value. >> + return self.calc_NOREX_R1RHO(R1=self.r1, r1rho_prime=r1rho_prime) >> + >> + >> + def func_NOREX_R1RHO_FIT_R1(self, params): >> + """Target function for no exchange, for R1rho off resonance models, >> where R1 is fitted. >> + >> + @param params: The vector of parameter values. >> + @type params: numpy rank-1 float array >> + @return: The chi-squared value. >> + @rtype: float >> + """ >> + >> + # Scaling. >> + if self.scaling_flag: >> + params = dot(params, self.scaling_matrix) >> + >> + # Unpack the parameter values. >> + r1 = params[:self.end_index[0]] >> + r1rho_prime = params[self.end_index[0]:self.end_index[1]] >> + >> + # Reshape R1 to per experiment, spin and frequency. >> + self.r1_struct[:] = multiply.outer( r1.reshape(self.NE, self.NS, >> self.NM), self.no_nd_ones ) >> + >> + # Calculate and return the chi-squared value. >> + return self.calc_NOREX_R1RHO(R1=self.r1_struct, >> r1rho_prime=r1rho_prime) >> + >> + >> def func_ns_cpmg_2site_3D(self, params): >> """Target function for the reduced numerical solution for the >> 2-site Bloch-McConnell equations. >> >> >> >> _______________________________________________ >> 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
