r22975 - /trunk/lib/dispersion/b14.py -- May 05, 2014 - 20:18

Author: tlinnet
Date: Mon May  5 20:18:38 2014
New Revision: 22975

URL: http://svn.gna.org/viewcvs/relax?rev=22975&view=rev
Log:
Pretty up code, by moving comments up on line.

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

Modified: trunk/lib/dispersion/b14.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/lib/dispersion/b14.py?rev=22975&r1=22974&r2=22975&view=diff
==============================================================================
--- trunk/lib/dispersion/b14.py (original)
+++ trunk/lib/dispersion/b14.py Mon May  5 20:18:38 2014
@@ -154,27 +154,62 @@
     g3 = 1/sqrt(2) * sqrt(g2 + sqrt(g1**2 + g2**2))   #trig faster than 
square roots
     g4 = 1/sqrt(2) * sqrt(-g2 + sqrt(g1**2 + g2**2))   #trig faster than 
square roots
     #########################################################################
-    #time independent factors
-    N = complex(kge + g3 - kge, g4)            #N = oG + oE
+    #Time independent factors.
+    #N = oG + oE.
+    N = complex(kge + g3 - kge, g4)
+
     NNc = (g3**2 + g4**2)
-    f0 = (dw**2 + g3**2) / NNc              #f0
-    f2 = (dw**2 - g4**2) / NNc              #f2
-    #t1 = (-dw + g4) * (complex(-dw, -g3)) / NNc #t1
-    t2 = (dw + g4) * (complex(dw, -g3)) / NNc #t2
-    t1pt2 = complex(2 * dw**2,g1)/ NNc     #t1 + t2
-    oGt2 = complex((-deltaR2 + keg - kge - g3), (dw - g4)) * t2  #-2 * oG * 
t2
-    Rpre = (r20a + r20b + kex) / 2.0   #-1/Trel * log(LpreDyn)
-    E0 =  2.0 * tcp * g3  #derived from relaxation       #E0 = -2.0 * tcp * 
(f00R - f11R)
-    E2 =  2.0 * tcp * g4  #derived from chemical shifts  #E2 = 
complex(0,-2.0 * tcp * (f00I - f11I))
-    E1 = (complex(g3, -g4)) * tcp    #mixed term (complex) (E0 - iE2)/2
-    ex0b = (f0 * numpy.cosh(E0) - f2 * numpy.cos(E2))               #real
-    ex0c = (f0 * numpy.sinh(E0) - f2 * numpy.sin(E2) * complex(0, 1.0)) 
#complex
-    ex1c = numpy.sinh(E1)                                   #complex
-    v3 = numpy.sqrt(ex0b**2 - 1)  #exact result for v2v3
+
+    # f0.
+    f0 = (dw**2 + g3**2) / NNc
+
+    # f2.
+    f2 = (dw**2 - g4**2) / NNc
+
+    # t1 = (-dw + g4) * (complex(-dw, -g3)) / NNc #t1.
+
+    # t2.
+    t2 = (dw + g4) * (complex(dw, -g3)) / NNc
+
+    # t1 + t2.
+    t1pt2 = complex(2 * dw**2,g1)/ NNc
+
+    # -2 * oG * t2.
+    oGt2 = complex((-deltaR2 + keg - kge - g3), (dw - g4)) * t2
+
+    # -1/Trel * log(LpreDyn).
+    Rpre = (r20a + r20b + kex) / 2.0
+
+    # Derived from relaxation.
+    # E0 = -2.0 * tcp * (f00R - f11R).
+    E0 =  2.0 * tcp * g3
+
+    # Derived from chemical shifts  #E2 = complex(0,-2.0 * tcp * (f00I - 
f11I)).
+    E2 =  2.0 * tcp * g4
+
+    # Mixed term (complex) (E0 - iE2)/2.
+    E1 = (complex(g3, -g4)) * tcp    
+
+    # Real.
+    ex0b = (f0 * numpy.cosh(E0) - f2 * numpy.cos(E2))
+
+    # Complex.
+    ex0c = (f0 * numpy.sinh(E0) - f2 * numpy.sin(E2) * complex(0, 1.0))
+
+    # Complex.
+    ex1c = numpy.sinh(E1)
+
+    # Exact result for v2v3.
+    v3 = numpy.sqrt(ex0b**2 - 1)
+
     y = numpy.power((ex0b - v3) / (ex0b + v3), ncyc)
-    v2pPdN = (( complex(-deltaR2 + kex, dw) ) * ex0c + (-oGt2 - kge * t1pt2) 
* 2 * ex1c)        #off diagonal common factor. sinh fuctions
+
+    # Off diagonal common factor. sinh fuctions.
+    v2pPdN = (( complex(-deltaR2 + kex, dw) ) * ex0c + (-oGt2 - kge * t1pt2) 
* 2 * ex1c)
     Tog = (((1 + y)/2 + (1 - y)/(2 * v3) * v2pPdN / N))
-    Minty = Rpre - ncyc/(Trel) * numpy.arccosh((ex0b).real) - 1/Trel * 
numpy.log((Tog.real))  #estimate R2eff
+
+    # Estimate R2eff.
+    Minty = Rpre - ncyc/(Trel) * numpy.arccosh((ex0b).real) - 1/Trel * 
numpy.log((Tog.real))
 
     # Loop over the time points, back calculating the R2eff values.
     for i in range(num_points):