Hi Edward. In the latest step, I convert all np.X to it correct version. Keeping np. is just for speed coding, while i progress.
I think we can use chi2 function. But I need to remove the axis=1 keyword. It will not influence other results. But I wanted to mess as little as possible with other functions. 2014-06-10 14:23 GMT+02:00 Edward d'Auvergne <[email protected]>: > For a proper solution which is portable to all analysis types, the > chi-squared value should be calculated using the target_functions.chi2 > module. All other analyses use this module, and the relaxation > dispersion analysis should too. Maybe a new function is required in > this module which implements this in the numpy way (i.e. numpy.sum()). > > You should also import the functions directly from numpy rather than > importing numpy as np. I make sure that the math module and numpy > module function name clashes do not occur in relax, so 'import numpy > as np' is not used in relax. > > Regards, > > Edward > > > > On 8 June 2014 23:56, <[email protected]> wrote: >> Author: tlinnet >> Date: Sun Jun 8 23:56:36 2014 >> New Revision: 23748 >> >> URL: http://svn.gna.org/viewcvs/relax?rev=23748&view=rev >> Log: >> Just a tiny little more speed, by removing temporary storage of chi2 >> calculation. >> >> Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion >> models for Clustered analysis. >> >> Modified: >> branches/disp_spin_speed/target_functions/relax_disp.py >> >> Modified: branches/disp_spin_speed/target_functions/relax_disp.py >> URL: >> http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/target_functions/relax_disp.py?rev=23748&r1=23747&r2=23748&view=diff >> ============================================================================== >> --- branches/disp_spin_speed/target_functions/relax_disp.py (original) >> +++ branches/disp_spin_speed/target_functions/relax_disp.py Sun Jun 8 >> 23:56:36 2014 >> @@ -553,7 +553,6 @@ >> ## Back calculate the R2eff values. >> r2eff_CR72(r20a=self.R20A_a, r20b=self.R20B_a, pA=self.pA_a, >> dw=self.dw_frq_a, kex=self.kex_a, cpmg_frqs=self.cpmg_frqs_a, >> back_calc=self.back_calc_a, num_points=self.num_disp_points_a) >> >> - >> ## 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: >> # Loop over the spins. >> @@ -566,14 +565,8 @@ >> #self.back_calc[0][si][mi][0][di] = >> self.values[0][si][mi][0][di] >> self.back_calc_a[0][si][mi][0][di] = >> self.values[0][si][mi][0][di] >> >> - ## Calculate and return the chi-squared value. >> - #chi2_sum += chi2(self.values[0][si][mi][0], >> self.back_calc[0][si][mi][0], self.errors[0][si][mi][0]) >> - >> ## Calculate the chi-squared statistic. >> - chi2_sum = np.sum((1.0 / self.errors_a * (self.values_a - >> self.back_calc_a))**2) >> - >> - # Return the total chi-squared value. >> - return chi2_sum >> + return chi2_sum = np.sum((1.0 / self.errors_a * (self.values_a - >> self.back_calc_a))**2) >> >> >> def calc_ns_cpmg_2site_3D_chi2(self, R20A=None, R20B=None, dw=None, >> pA=None, kex=None): >> >> >> _______________________________________________ >> 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
