mailr23748 - /branches/disp_spin_speed/target_functions/relax_disp.py


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Posted by tlinnet on June 08, 2014 - 23:56:
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):




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