mailRe: r23005 - in /trunk: lib/dispersion/b14.py target_functions/relax_disp.py


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Posted by Edward d'Auvergne on May 06, 2014 - 17:30:
Hi,

If you revert the previous commit, this one might need reverting as well.

Cheers,

Edward



On 6 May 2014 17:22,  <tlinnet@xxxxxxxxxxxxx> wrote:
Author: tlinnet
Date: Tue May  6 17:22:40 2014
New Revision: 23005

URL: http://svn.gna.org/viewcvs/relax?rev=23005&view=rev
Log:
Pretty-up code. Re-ordered logic of r20 parameters, and exchange parameters 
in function call.

sr #3154: (https://gna.org/support/?3154) Implementation of Baldwin (2014) 
B14 model - 2-site exact solution model for all time scales.

This follows the tutorial for adding relaxation dispersion models at:
http://wiki.nmr-relax.com/Tutorial_for_adding_relaxation_dispersion_models_to_relax#Debugging


Modified:
    trunk/lib/dispersion/b14.py
    trunk/target_functions/relax_disp.py

Modified: trunk/lib/dispersion/b14.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/lib/dispersion/b14.py?rev=23005&r1=23004&r2=23005&view=diff
==============================================================================
--- trunk/lib/dispersion/b14.py (original)
+++ trunk/lib/dispersion/b14.py Tue May  6 17:22:40 2014
@@ -102,7 +102,7 @@
 from numpy import arccosh, cos, cosh, log, sin, sinh, sqrt, power


-def r2eff_B14(r20a=None, r20b=None, pA=None, pB=None, dw=None, kex=None, 
k_AB=None, k_BA=None, deltaR2=None, alpha_m=None, ncyc=None, 
inv_tcpmg=None, tcp=None, back_calc=None, num_points=None):
+def r2eff_B14(r20a=None, r20b=None, deltaR2=None, alpha_m=None, pA=None, 
pB=None, dw=None, kex=None, k_AB=None, k_BA=None, ncyc=None, 
inv_tcpmg=None, tcp=None, back_calc=None, num_points=None):
     """Calculate the R2eff values for the CR72 model.

     See the module docstring for details.
@@ -112,6 +112,10 @@
     @type r20a:             float
     @keyword r20b:          The R20 parameter value of state B (R2 with no 
exchange).
     @type r20b:             float
+    @keyword deltaR2:       The difference r20a - r20b.
+    @type deltaR2:          float
+    @keyword alpha_m:       The Carver and Richards (1972) alpha_minus 
short notation. alpha_m = deltaR2 + k_AB - k_BA = r20a - r20b + k_AB - k_BA.
+    @type alpha_m:          float
     @keyword pA:            The population of state A.
     @type pA:               float
     @keyword pB:            The population of state B.
@@ -124,10 +128,6 @@
     @type k_AB:             float
     @keyword k_BA:          The rate of exchange from site B to A (rad/s).
     @type k_BA:             float
-    @keyword deltaR2:       The difference r20a - r20b.
-    @type deltaR2:          float
-    @keyword alpha_m:       The Carver and Richards (1972) alpha_minus 
short notation. alpha_m = deltaR2 + k_AB - k_BA = r20a - r20b + k_AB - k_BA.
-    @type alpha_m:          float
     @keyword ncyc:          The matrix exponential power array. The number 
of CPMG blocks.
     @type ncyc:             numpy int16, rank-1 array
     @keyword inv_tcpmg:     The inverse of the total duration of the CPMG 
element (in inverse seconds).

Modified: trunk/target_functions/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/target_functions/relax_disp.py?rev=23005&r1=23004&r2=23005&view=diff
==============================================================================
--- trunk/target_functions/relax_disp.py        (original)
+++ trunk/target_functions/relax_disp.py        Tue May  6 17:22:40 2014
@@ -819,7 +819,7 @@
                         aliased_dw = dw_frq

                     # Back calculate the R2eff values.
-                    r2eff_B14(r20a=r20a, r20b=r20b, pA=pA, pB=pB, 
dw=dw_frq, kex=kex, k_AB=k_AB, k_BA=k_BA, deltaR2=deltaR2, alpha_m=alpha_m, 
ncyc=self.power[ei][mi], inv_tcpmg=self.inv_relax_times[ei][mi], 
tcp=self.tau_cpmg[ei][mi], back_calc=self.back_calc[ei][si][mi][0], 
num_points=self.num_disp_points[ei][si][mi][0])
+                    r2eff_B14(r20a=r20a, r20b=r20b, deltaR2=deltaR2, 
alpha_m=alpha_m, pA=pA, pB=pB, dw=dw_frq, kex=kex, k_AB=k_AB, k_BA=k_BA, 
ncyc=self.power[ei][mi], inv_tcpmg=self.inv_relax_times[ei][mi], 
tcp=self.tau_cpmg[ei][mi], back_calc=self.back_calc[ei][si][mi][0], 
num_points=self.num_disp_points[ei][si][mi][0])

                     # 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 di in range(self.num_disp_points[ei][si][mi][0]):


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