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Posted by tlinnet on May 29, 2014 - 11:35:
Author: tlinnet
Date: Thu May 29 11:35:35 2014
New Revision: 23582

URL: http://svn.gna.org/viewcvs/relax?rev=23582&view=rev
Log:
Converting back to having back_calc as a function argument to model M61b:

This is to clean up the API.
There can be bo no partial measures/implementations in the relax trunk.

The problem is, that many numerical models can't be optimised further, since 
they
evolve the spin-magnetisation in a matrix.  That spin evolvement can't be put 
into
a larger numpy array.

This is related to: task #7793: (https://gna.org/task/?7793) Speed-up of 
dispersion models.

Modified:
    branches/disp_speed/lib/dispersion/m61b.py
    branches/disp_speed/target_functions/relax_disp.py
    branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_m61b.py

Modified: branches/disp_speed/lib/dispersion/m61b.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_speed/lib/dispersion/m61b.py?rev=23582&r1=23581&r2=23582&view=diff
==============================================================================
--- branches/disp_speed/lib/dispersion/m61b.py  (original)
+++ branches/disp_speed/lib/dispersion/m61b.py  Thu May 29 11:35:35 2014
@@ -62,7 +62,7 @@
 # Python module imports.
 from numpy import abs, array, isfinite, min, sum
 
-def r1rho_M61b(r1rho_prime=None, pA=None, dw=None, kex=None, 
spin_lock_fields2=None, num_points=None):
+def r1rho_M61b(r1rho_prime=None, pA=None, dw=None, kex=None, 
spin_lock_fields2=None, back_calc=None, num_points=None):
     """Calculate the R1rho values for the M61 skew model.
 
     See the module docstring for details.
@@ -78,7 +78,9 @@
     @type kex:                  float
     @keyword spin_lock_fields2: The R1rho spin-lock field strengths squared 
(in rad^2.s^-2).
     @type spin_lock_fields2:    numpy rank-1 float array
-    @keyword num_points:        The number of points on the dispersion 
curve, equal to the length of the spin_lock_fields.
+    @keyword back_calc:         The array for holding the back calculated 
R1rho values.  Each element corresponds to the combination of spin lock field.
+    @type back_calc:            numpy rank-1 float array
+    @keyword num_points:        The number of points on the dispersion 
curve, equal to the length of the spin_lock_fields and back_calc arguments.
     @type num_points:           int
     """
 
@@ -95,7 +97,8 @@
     # Catch zeros (to avoid pointless mathematical operations).
     # This will result in no exchange, returning flat lines.
     if numer == 0.0:
-        return array([r1rho_prime]*num_points)
+        back_calc[:] = array([r1rho_prime]*num_points)
+        return
 
     # Denominator.
     denom = kex2_pA2dw2 + spin_lock_fields2
@@ -103,7 +106,8 @@
     # Catch math domain error of dividing with 0.
     # This is when denom=0.
     if min(abs(denom)) == 0:
-        return array([1e100]*num_points)
+        back_calc[:] = array([1e100]*num_points)
+        return
 
 
     # R1rho calculation.
@@ -112,6 +116,6 @@
     # Catch errors, taking a sum over array is the fastest way to check for
     # +/- inf (infinity) and nan (not a number).
     if not isfinite(sum(R1rho)):
-        return array([1e100]*num_points)
+        R1rho = array([1e100]*num_points)
 
-    return R1rho
+    back_calc[:] = R1rho

Modified: branches/disp_speed/target_functions/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_speed/target_functions/relax_disp.py?rev=23582&r1=23581&r2=23582&view=diff
==============================================================================
--- branches/disp_speed/target_functions/relax_disp.py  (original)
+++ branches/disp_speed/target_functions/relax_disp.py  Thu May 29 11:35:35 
2014
@@ -1210,7 +1210,7 @@
                 dw_frq = dw[si] * self.frqs[0][si][mi]
 
                 # Back calculate the R1rho values.
-                self.back_calc[0][si][mi][0] = 
r1rho_M61b(r1rho_prime=R20[r20_index], pA=pA, dw=dw_frq, kex=kex, 
spin_lock_fields2=self.spin_lock_omega1_squared[0][mi][0], 
num_points=self.num_disp_points[0][si][mi][0])
+                r1rho_M61b(r1rho_prime=R20[r20_index], pA=pA, dw=dw_frq, 
kex=kex, spin_lock_fields2=self.spin_lock_omega1_squared[0][mi][0], 
back_calc=self.back_calc[0][si][mi][0], 
num_points=self.num_disp_points[0][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[0][si][mi][0]):

Modified: 
branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_m61b.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_m61b.py?rev=23582&r1=23581&r2=23582&view=diff
==============================================================================
--- branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_m61b.py   
  (original)
+++ branches/disp_speed/test_suite/unit_tests/_lib/_dispersion/test_m61b.py   
  Thu May 29 11:35:35 2014
@@ -53,6 +53,7 @@
 
         # Required data structures.
         self.num_points = 11
+        self.R1rho = zeros(self.num_points, float64)
 
 
     def calc_r1rho(self):
@@ -62,16 +63,16 @@
         phi_ex_scaled, dw_frq, spin_lock_omega1_squared = 
self.param_conversion(pA=self.pA, dw=self.dw, sfrq=self.sfrq, 
spin_lock_nu1=self.spin_lock_nu1)
 
         # Calculate the R1rho values.
-        R1rho = r1rho_M61b(r1rho_prime=self.r1rho_prime, pA=self.pA, 
dw=dw_frq, kex=self.kex, spin_lock_fields2=spin_lock_omega1_squared, 
num_points=self.num_points)
+        R1rho = r1rho_M61b(r1rho_prime=self.r1rho_prime, pA=self.pA, 
dw=dw_frq, kex=self.kex, spin_lock_fields2=spin_lock_omega1_squared, 
back_calc=self.R1rho, num_points=self.num_points)
 
 
         # Check all R1rho values.
         if self.kex > 1.e5:
             for i in range(self.num_points):
-                self.assertAlmostEqual(R1rho[i], self.r1rho_prime, 2)
+                self.assertAlmostEqual(self.R1rho[i], self.r1rho_prime, 2)
         else:
             for i in range(self.num_points):
-                self.assertAlmostEqual(R1rho[i], self.r1rho_prime)
+                self.assertAlmostEqual(self.R1rho[i], self.r1rho_prime)
 
 
     def param_conversion(self, pA=None, dw=None, sfrq=None, 
spin_lock_nu1=None):




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