mailr24925 - /branches/R1_fitting/target_functions/relax_disp.py


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Posted by tlinnet on August 04, 2014 - 16:27:
Author: tlinnet
Date: Mon Aug  4 16:27:36 2014
New Revision: 24925

URL: http://svn.gna.org/viewcvs/relax?rev=24925&view=rev
Log:
Added initial target function for model DPL94_fit_r1.

sr #3135(https://gna.org/support/?3135): Optimisation of the R1 relaxation 
rate for the off-resonance R1rho relaxation dispersion models.

Modified:
    branches/R1_fitting/target_functions/relax_disp.py

Modified: branches/R1_fitting/target_functions/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/R1_fitting/target_functions/relax_disp.py?rev=24925&r1=24924&r2=24925&view=diff
==============================================================================
--- branches/R1_fitting/target_functions/relax_disp.py  (original)
+++ branches/R1_fitting/target_functions/relax_disp.py  Mon Aug  4 16:27:36 
2014
@@ -1022,6 +1022,29 @@
         return self.calc_DPL94(R1=self.r1, r1rho_prime=r1rho_prime, 
phi_ex=phi_ex, kex=kex)
 
 
+    def func_DPL94_fit_r1(self, params):
+        """Target function for the Davis, Perlman and London (1994) fast 
2-site off-resonance exchange model for R1rho-type experiments, where R1 is 
fitted.
+
+        @param params:  The vector of parameter values.
+        @type params:   numpy rank-1 float array
+        @return:        The chi-squared value.
+        @rtype:         float
+        """
+
+        # Scaling.
+        if self.scaling_flag:
+            params = dot(params, self.scaling_matrix)
+
+        # Unpack the parameter values.
+        r1 = params[:self.end_index[0]]
+        r1rho_prime = params[:self.end_index[0]]
+        phi_ex = params[self.end_index[0]:self.end_index[1]]
+        kex = params[self.end_index[1]]
+
+        # Calculate and return the chi-squared value.
+        return self.calc_DPL94(R1=self.r1, r1rho_prime=r1rho_prime, 
phi_ex=phi_ex, kex=kex)
+
+
     def func_IT99(self, params):
         """Target function for the Ishima and Torchia (1999) 2-site model 
for all timescales with pA >> pB.
 




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