r20678 - /branches/relax_disp/target_functions/relax_disp.py -- August 22, 2013 - 14:50

Author: bugman
Date: Thu Aug 22 14:50:38 2013
New Revision: 20678

URL: http://svn.gna.org/viewcvs/relax?rev=20678&view=rev
Log:
Added preliminary support for chemical shifts to the dispersion target 
functions.


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=20678&r1=20677&r2=20678&view=diff
==============================================================================
--- branches/relax_disp/target_functions/relax_disp.py (original)
+++ branches/relax_disp/target_functions/relax_disp.py Thu Aug 22 14:50:38 
2013
@@ -46,7 +46,7 @@
 
 
 class Dispersion:
-    def __init__(self, model=None, num_params=None, num_spins=None, 
num_frq=None, num_disp_points=None, values=None, errors=None, missing=None, 
frqs=None, cpmg_frqs=None, spin_lock_nu1=None, relax_time=None, 
scaling_matrix=None):
+    def __init__(self, model=None, num_params=None, num_spins=None, 
num_frq=None, num_disp_points=None, values=None, errors=None, missing=None, 
frqs=None, cpmg_frqs=None, spin_lock_nu1=None, relax_time=None, 
scaling_matrix=None, chemical_shifts=None):
         """Relaxation dispersion target functions for optimisation.
 
         Models
@@ -101,6 +101,8 @@
         @type relax_time:           float
         @keyword scaling_matrix:    The square and diagonal scaling matrix.
         @type scaling_matrix:       numpy rank-2 float array
+        @keyword chemical_shifts:   The chemical shifts for all spins in the 
cluster in rad/s.  The first dimension is that of the spin cluster (each 
element corresponds to a different spin in the block) and the second 
dimension is the spectrometer field strength.  The ppm values are not used to 
save computation time, therefore they must be converted to rad/s by the 
calling code.
+        @type chemical_shifts:      numpy rank-2 float array
         """
 
         # Check the args.
@@ -112,6 +114,8 @@
             raise RelaxError("No errors have been supplied to the target 
function.")
         if missing == None:
             raise RelaxError("No missing data information has been supplied 
to the target function.")
+        if model in [MODEL_DPL94, MODEL_TP02] and chemical_shifts == None:
+            raise RelaxError("Chemical shifts must be supplied for the 
off-resonance dispersion models.")
 
         # Store the arguments.
         self.num_params = num_params
@@ -126,6 +130,7 @@
         self.spin_lock_nu1 = spin_lock_nu1
         self.relax_time = relax_time
         self.scaling_matrix = scaling_matrix
+        self.chemical_shifts = chemical_shifts
 
         # Scaling initialisation.
         self.scaling_flag = False
@@ -464,7 +469,7 @@
                 phi_ex_scaled = phi_ex[spin_index] * self.frqs[spin_index, 
frq_index]**2
 
                 # Back calculate the R2eff values.
-                r1rho_DPL94(r1rho_prime=R20[r20_index], 
phi_ex=phi_ex_scaled, kex=kex, spin_lock_fields=self.spin_lock_nu1, 
back_calc=self.back_calc[spin_index, frq_index], 
num_points=self.num_disp_points)
+                r1rho_DPL94(r1rho_prime=R20[r20_index], 
w=self.chemical_shifts[spin_index, frq_index], phi_ex=phi_ex_scaled, kex=kex, 
spin_lock_fields=self.spin_lock_nu1, back_calc=self.back_calc[spin_index, 
frq_index], num_points=self.num_disp_points)
 
                 # 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):
@@ -948,7 +953,7 @@
                 dw_frq = dw[spin_index] * self.frqs[spin_index, frq_index]
 
                 # Back calculate the R1rho values.
-                r1rho_TP02(r1rho_prime=R20[r20_index], pA=pA, pB=pB, 
dw=dw_frq, kex=kex, spin_lock_fields=self.spin_lock_nu1, 
back_calc=self.back_calc[spin_index, frq_index], 
num_points=self.num_disp_points)
+                r1rho_TP02(r1rho_prime=R20[r20_index], 
w=self.chemical_shifts[spin_index, frq_index], pA=pA, pB=pB, dw=dw_frq, 
kex=kex, spin_lock_fields=self.spin_lock_nu1, 
back_calc=self.back_calc[spin_index, frq_index], 
num_points=self.num_disp_points)
 
                 # 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):