mailr23272 - in /branches/disp_speed: lib/dispersion/dpl94.py target_functions/relax_disp.py


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Posted by tlinnet on May 20, 2014 - 22:29:
Author: tlinnet
Date: Tue May 20 22:29:43 2014
New Revision: 23272

URL: http://svn.gna.org/viewcvs/relax?rev=23272&view=rev
Log:
Math-domain catching for model DPL94.

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

This is to implement catching of math domain errors, before they occur.
These can be found via the --numpy-raise function to the systemtests.

To make the code look clean, the class object "back_calc" is no longer
being updated per time point, but is updated in the relax_disp target 
function in
one go.

Modified:
    branches/disp_speed/lib/dispersion/dpl94.py
    branches/disp_speed/target_functions/relax_disp.py

Modified: branches/disp_speed/lib/dispersion/dpl94.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_speed/lib/dispersion/dpl94.py?rev=23272&r1=23271&r2=23272&view=diff
==============================================================================
--- branches/disp_speed/lib/dispersion/dpl94.py (original)
+++ branches/disp_speed/lib/dispersion/dpl94.py Tue May 20 22:29:43 2014
@@ -63,10 +63,10 @@
 """
 
 # Python module imports.
-from numpy import array, cos, isfinite, sin, sum
+from numpy import abs, array, cos, isfinite, min, sin, sum
 
 
-def r1rho_DPL94(r1rho_prime=None, phi_ex=None, kex=None, theta=None, R1=0.0, 
spin_lock_fields2=None, back_calc=None, num_points=None):
+def r1rho_DPL94(r1rho_prime=None, phi_ex=None, kex=None, theta=None, R1=0.0, 
spin_lock_fields2=None, num_points=None):
     """Calculate the R1rho values for the DPL94 model.
 
     See the module docstring for details.
@@ -84,9 +84,7 @@
     @type R1:                   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 back_calc:         The array for holding the back calculated 
R1rho values.  Each element corresponds to one of the spin-lock fields.
-    @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.
+    @keyword num_points:        The number of points on the dispersion 
curve, equal to the length of the spin_lock_fields.
     @type num_points:           int
     """
 
@@ -103,6 +101,13 @@
     # Denominator.
     denom = kex2 + spin_lock_fields2
 
+    # Catch math domain error of dividing with 0.
+    # This is when denom =0.
+    if min(abs(denom)) == 0:
+        R1rho = array([1e100]*num_points)
+
+        return R1rho
+
     # R1rho calculation.
     R1rho = R1_R2 + numer / denom
 
@@ -111,6 +116,4 @@
     if not isfinite(sum(R1rho)):
         R1rho = array([1e100]*num_points)
 
-    # Parse back the value to update the back_calc class object.
-    for i in range(num_points):
-        back_calc[i] = R1rho[i]
+    return 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=23272&r1=23271&r2=23272&view=diff
==============================================================================
--- branches/disp_speed/target_functions/relax_disp.py  (original)
+++ branches/disp_speed/target_functions/relax_disp.py  Tue May 20 22:29:43 
2014
@@ -965,7 +965,7 @@
                 # Loop over the offsets.
                 for oi in range(self.num_offsets[0][si][mi]):
                     # Back calculate the R2eff values.
-                    r1rho_DPL94(r1rho_prime=R20[r20_index], 
phi_ex=phi_ex_scaled, kex=kex, theta=self.tilt_angles[0][si][mi][oi], 
R1=self.r1[si, mi], 
spin_lock_fields2=self.spin_lock_omega1_squared[0][mi][oi], 
back_calc=self.back_calc[0][si][mi][oi], 
num_points=self.num_disp_points[0][si][mi][oi])
+                    self.back_calc[0][si][mi][oi] = 
r1rho_DPL94(r1rho_prime=R20[r20_index], phi_ex=phi_ex_scaled, kex=kex, 
theta=self.tilt_angles[0][si][mi][oi], R1=self.r1[si, mi], 
spin_lock_fields2=self.spin_lock_omega1_squared[0][mi][oi], 
num_points=self.num_disp_points[0][si][mi][oi])
 
                     # 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][oi]):




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