r20697 - /branches/relax_disp/target_functions/relax_disp.py -- August 27, 2013 - 12:40

Author: bugman
Date: Tue Aug 27 12:40:51 2013
New Revision: 20697

URL: http://svn.gna.org/viewcvs/relax?rev=20697&view=rev
Log:
The dispersion target function class now handles R1 relaxation data.

This data is essential for the off-resonance R1rho models.


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=20697&r1=20696&r2=20697&view=diff
==============================================================================
--- branches/relax_disp/target_functions/relax_disp.py (original)
+++ branches/relax_disp/target_functions/relax_disp.py Tue Aug 27 12:40:51 
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, chemical_shifts=None, 
spin_lock_offsets=None, tilt_angles=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, chemical_shifts=None, 
spin_lock_offsets=None, tilt_angles=None, r1=None, relax_time=None, 
scaling_matrix=None):
         """Relaxation dispersion target functions for optimisation.
 
         Models
@@ -103,6 +103,8 @@
         @type spin_lock_offsets:    numpy rank-3 float array
         @keyword tilt_angles:       The spin-lock rotating frame tilt angle 
for each spin.  This is only used for off-resonance R1rho models.  The first 
dimension is that of the spin cluster (each element corresponds to a 
different spin in the block), the second dimension is the spectrometer field 
strength, and the third is the dispersion points.
         @type tilt_angles:          numpy rank-3 float array
+        @keyword r1:                The R1 relaxation rates for each spin 
and field strength.  This is only used for off-resonance R1rho models.
+        @type r1:                   numpy rank-2 float array.
         @keyword relax_time:        The fixed time period for relaxation (in 
seconds).
         @type relax_time:           float
         @keyword scaling_matrix:    The square and diagonal scaling matrix.
@@ -118,8 +120,11 @@
             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.")
+        if model in [MODEL_DPL94, MODEL_TP02]:
+            if chemical_shifts == None:
+                raise RelaxError("Chemical shifts must be supplied for the 
'%s' R1rho off-resonance dispersion model." % model)
+            if r1 == None:
+                raise RelaxError("R1 relaxation rates must be supplied for 
the '%s' R1rho off-resonance dispersion model." % model)
 
         # Store the arguments.
         self.num_params = num_params
@@ -135,6 +140,7 @@
         self.chemical_shifts = chemical_shifts
         self.spin_lock_offsets = spin_lock_offsets
         self.tilt_angles = tilt_angles
+        self.r1 = r1
         self.relax_time = relax_time
         self.scaling_matrix = scaling_matrix
 
@@ -959,7 +965,7 @@
                 dw_frq = dw[spin_index] * self.frqs[spin_index, frq_index]
 
                 # Back calculate the R1rho values.
-                r1rho_TP02(r1rho_prime=R20[r20_index], 
omega=self.chemical_shifts[spin_index, frq_index], pA=pA, pB=pB, dw=dw_frq, 
kex=kex, theta=self.tilt_angles[spin_index, frq_index], 
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], 
omega=self.chemical_shifts[spin_index, frq_index], pA=pA, pB=pB, dw=dw_frq, 
kex=kex, theta=self.tilt_angles[spin_index, frq_index], 
R1=self.r1[spin_index, frq_index], 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):