r21236 - /branches/relax_disp/target_functions/relax_disp.py -- October 25, 2013 - 19:09

Author: bugman
Date: Fri Oct 25 19:09:14 2013
New Revision: 21236

URL: http://svn.gna.org/viewcvs/relax?rev=21236&view=rev
Log:
The 'MMQ 2-site' model target function can now handle multiple CPMG data 
types.


Modified:
    branches/relax_disp/target_functions/relax_disp.py

Modified: branches/relax_disp/target_functions/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/relax_disp/target_functions/relax_disp.py?rev=21236&r1=21235&r2=21236&view=diff
==============================================================================
--- branches/relax_disp/target_functions/relax_disp.py (original)
+++ branches/relax_disp/target_functions/relax_disp.py Fri Oct 25 19:09:14 
2013
@@ -162,7 +162,10 @@
             self.scaling_flag = True
 
         # Create the structure for holding the back-calculated R2eff values 
(matching the dimensions of the values structure).
-        self.back_calc = zeros((num_spins, num_frq, num_disp_points), 
float64)
+        if self.model in [MODEL_MMQ_2SITE]:
+            self.back_calc = zeros((self.num_exp, num_spins, num_frq, 
num_disp_points), float64)
+        else:
+            self.back_calc = zeros((num_spins, num_frq, num_disp_points), 
float64)
 
         # Initialise the post spin parameter indices.
         self.end_index = []
@@ -442,6 +445,9 @@
         For the single experiment type models, the first dimension of the 
values, errors, and missing data structures will be removed to simplify the 
target functions.
         """
 
+        # The number of experiments.
+        self.num_exp = len(self.exp_types)
+
         # The non-combined data models.
         if not self.model in [MODEL_MMQ_2SITE]:
             # Remove the first dimension of the data structures.
@@ -834,27 +840,29 @@
         # Initialise.
         chi2_sum = 0.0
 
-        # Loop over the spins.
-        for spin_index in range(self.num_spins):
-            # Loop over the spectrometer frequencies.
-            for frq_index in range(self.num_frq):
-                # The R20 index.
-                r20_index = frq_index + spin_index*self.num_frq
-
-                # Convert dw from ppm to rad/s.
-                dw_frq = dw[spin_index] * self.frqs[spin_index, frq_index]
-                dwH_frq = dwH[spin_index] * self.frqs[spin_index, frq_index]
-
-                # Back calculate the R2eff values.
-                r2eff_mmq_2site(M0=self.M0, m1=self.m1, m2=self.m2, 
r20=R20[r20_index], pA=pA, pB=pB, dw=dw_frq, dwH=dwH_frq, k_AB=k_AB, 
k_BA=k_BA, inv_tcpmg=self.inv_relax_time, tcp=self.tau_cpmg, 
back_calc=self.back_calc[spin_index, frq_index], 
num_points=self.num_disp_points, n=self.n)
-
-                # 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.
-                for point_index in range(self.num_disp_points):
-                    if self.missing[spin_index, frq_index, point_index]:
-                        self.back_calc[spin_index, frq_index, point_index] = 
self.values[spin_index, frq_index, point_index]
-
-                # Calculate and return the chi-squared value.
-                chi2_sum += chi2(self.values[spin_index, frq_index], 
self.back_calc[spin_index, frq_index], self.errors[spin_index, frq_index])
+        # Loop over the experiment types.
+        for exp_index in range(self.num_exp):
+            # Loop over the spins.
+            for spin_index in range(self.num_spins):
+                # Loop over the spectrometer frequencies.
+                for frq_index in range(self.num_frq):
+                    # The R20 index.
+                    r20_index = frq_index + spin_index*self.num_frq
+
+                    # Convert dw from ppm to rad/s.
+                    dw_frq = dw[spin_index] * self.frqs[spin_index, 
frq_index]
+                    dwH_frq = dwH[spin_index] * self.frqs[spin_index, 
frq_index]
+
+                    # Back calculate the R2eff values.
+                    r2eff_mmq_2site(M0=self.M0, m1=self.m1, m2=self.m2, 
r20=R20[r20_index], pA=pA, pB=pB, dw=dw_frq, dwH=dwH_frq, k_AB=k_AB, 
k_BA=k_BA, inv_tcpmg=self.inv_relax_time, tcp=self.tau_cpmg, 
back_calc=self.back_calc[exp_index, spin_index, frq_index], 
num_points=self.num_disp_points, n=self.n)
+
+                    # 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.
+                    for point_index in range(self.num_disp_points):
+                        if self.missing[exp_index, spin_index, frq_index, 
point_index]:
+                            self.back_calc[exp_index, spin_index, frq_index, 
point_index] = self.values[exp_index, spin_index, frq_index, point_index]
+
+                    # Calculate and return the chi-squared value.
+                    chi2_sum += chi2(self.values[exp_index, spin_index, 
frq_index], self.back_calc[exp_index, spin_index, frq_index], 
self.errors[exp_index, spin_index, frq_index])
 
         # Return the total chi-squared value.
         return chi2_sum