r24019 - /branches/disp_spin_speed/target_functions/relax_disp.py -- June 17, 2014 - 11:56

Author: tlinnet
Date: Tue Jun 17 11:56:45 2014
New Revision: 24019

URL: http://svn.gna.org/viewcvs/relax?rev=24019&view=rev
Log:
Moved the cleaning of data points and replacing of values of out loop for 
model ns mmq 2site.

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=24019&r1=24018&r2=24019&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py     Tue Jun 17 
11:56:45 2014
@@ -1560,20 +1560,16 @@
             # Back calculate the R2eff values for each experiment type.
             self.r2eff_ns_mmq[ei](M0=self.M0, m1=self.m1, m2=self.m2, 
R20A=r20, R20B=r20, pA=pA, pB=pB, dw=aliased_dw, dwH=aliased_dwH, k_AB=k_AB, 
k_BA=k_BA, inv_tcpmg=self.inv_relax_times[ei], tcp=self.tau_cpmg[ei], 
back_calc=self.back_calc[ei], num_points=self.num_disp_points[ei], 
power=self.power[ei])
 
-            # Clean the data for all values, which is left over at the end 
of arrays.
-            self.back_calc[ei] = self.back_calc[ei]*self.disp_struct[ei]
-
-            # 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.
-                mask_replace_blank_ei = masked_equal(self.missing, 1.0)
-                self.back_calc[mask_replace_blank_ei.mask] = 
self.values[mask_replace_blank_ei.mask]
-
-            # Calculate and return the chi-squared value.
-            chi2_sum += chi2_rankN(self.values[ei], self.back_calc[ei], 
self.errors[ei])
+        # 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_sum
+        return chi2_rankN(self.values, self.back_calc, self.errors)
 
 
     def func_ns_mmq_3site(self, params):