r23998 - /branches/disp_spin_speed/target_functions/relax_disp.py -- June 16, 2014 - 20:23

Author: tlinnet
Date: Mon Jun 16 20:23:34 2014
New Revision: 23998

URL: http://svn.gna.org/viewcvs/relax?rev=23998&view=rev
Log:
Removed number of points to be parsed to model MMQ CR72.

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=23998&r1=23997&r2=23998&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py     Mon Jun 16 
20:23:34 2014
@@ -1307,11 +1307,13 @@
                 aliased_dwH = dw_frq
 
             # Back calculate the R2eff values.
-            r2eff_mmq_cr72(r20=r20, pA=pA, pB=pB, dw=aliased_dw, 
dwH=aliased_dwH, kex=kex, k_AB=k_AB, k_BA=k_BA, cpmg_frqs=self.cpmg_frqs[ei], 
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])
+            r2eff_mmq_cr72(r20=r20, pA=pA, pB=pB, dw=aliased_dw, 
dwH=aliased_dwH, kex=kex, k_AB=k_AB, k_BA=k_BA, cpmg_frqs=self.cpmg_frqs[ei], 
inv_tcpmg=self.inv_relax_times[ei], tcp=self.tau_cpmg[ei], 
back_calc=self.back_calc[ei], power=self.power[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:
-                print asdf
+                # Replace with values.
+                mask_replace_blank_ei = masked_equal(self.missing[ei], 1.0)
+                self.back_calc[ei][mask_replace_blank_ei.mask] = 
self.values[ei][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])