r23732 - /branches/disp_spin_speed/lib/dispersion/cr72.py -- June 08, 2014 - 19:48

Author: tlinnet
Date: Sun Jun  8 19:48:25 2014
New Revision: 23732

URL: http://svn.gna.org/viewcvs/relax?rev=23732&view=rev
Log:
Re-inserted safety checks in lin/dispersion/cr72.py file.

This is re-inserted for the rank_1 cases.

This makes the unit-tests pass again.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion 
models for Clustered analysis.

Modified:
    branches/disp_spin_speed/lib/dispersion/cr72.py

Modified: branches/disp_spin_speed/lib/dispersion/cr72.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/cr72.py?rev=23732&r1=23731&r2=23732&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/cr72.py     (original)
+++ branches/disp_spin_speed/lib/dispersion/cr72.py     Sun Jun  8 19:48:25 
2014
@@ -122,10 +122,16 @@
     @type num_points:       int
     """
 
+    # Determine if calculating in numpy rank-1 float array, of higher 
dimensions.
+    rank_1 = True
+    if isinstance(num_points, np.ndarray):
+        rank_1 = False
+
     # Catch parameter values that will result in no exchange, returning flat 
R2eff = R20 lines (when kex = 0.0, k_AB = 0.0).
-    #if dw == 0.0 or pA == 1.0 or kex == 0.0:
-    #    back_calc[:] = array([r20a]*num_points)
-    #    return
+    if rank_1:
+        if dw == 0.0 or pA == 1.0 or kex == 0.0:
+            back_calc[:] = array([r20a]*num_points)
+            return
 
     # The B population.
     pB = 1.0 - pA
@@ -159,22 +165,25 @@
 
     # Catch math domain error of cosh(val > 710).
     # This is when etapos > 710.
-    #if max(etapos) > 700:
-    #    back_calc[:] = array([r20a]*num_points)
-    #    return
+    if rank_1:
+        if max(etapos) > 700:
+            back_calc[:] = array([r20a]*num_points)
+            return
 
     # The arccosh argument - catch invalid values.
     fact = Dpos * cosh(etapos) - Dneg * cos(etaneg)
-    #if min(fact) < 1.0:
-    #    back_calc[:] = array([r20_kex]*num_points)
-    #    return
+    if rank_1:
+        if min(fact) < 1.0:
+            back_calc[:] = array([r20_kex]*num_points)
+            return
 
     # Calculate R2eff.
     R2eff = r20_kex - cpmg_frqs * arccosh( fact )
 
     # 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(R2eff)):
-    #    R2eff = array([1e100]*num_points)
+    if rank_1:
+        if not isfinite(sum(R2eff)):
+            R2eff = array([1e100]*num_points)
 
     back_calc[:] = R2eff