r23751 - /branches/disp_spin_speed/lib/dispersion/cr72.py -- June 09, 2014 - 00:49

Author: tlinnet
Date: Mon Jun  9 00:49:15 2014
New Revision: 23751

URL: http://svn.gna.org/viewcvs/relax?rev=23751&view=rev
Log:
Changed all calls to numpy np.X functions to just the numpy function in 
lib/dispersion/cr72.py.

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=23751&r1=23750&r2=23751&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/cr72.py     (original)
+++ branches/disp_spin_speed/lib/dispersion/cr72.py     Mon Jun  9 00:49:15 
2014
@@ -93,7 +93,7 @@
 
 # Python module imports.
 import numpy as np
-from numpy import arccosh, array, cos, cosh, isfinite, min, max, sqrt, sum
+from numpy import allclose, arccosh, array, cos, cosh, isfinite, min, max, 
ndarray, ones, sqrt, sum, zeros
 
 # Repetitive calculations (to speed up calculations).
 eta_scale = 2.0**(-3.0/2.0)
@@ -124,7 +124,7 @@
 
     # Determine if calculating in numpy rank-1 float array, of higher 
dimensions.
     rank_1 = True
-    if isinstance(num_points, np.ndarray):
+    if isinstance(num_points, 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).
@@ -135,7 +135,7 @@
             return
     # For higher dimensions, return same structure.
     else:
-        if np.allclose(dw, np.zeros(dw.shape)) or np.allclose(pA, 
np.ones(dw.shape)) or np.allclose(kex, np.zeros(dw.shape)):
+        if allclose(dw, zeros(dw.shape)) or allclose(pA, ones(dw.shape)) or 
allclose(kex, zeros(dw.shape)):
             back_calc[:] = r20a
             return
 
@@ -149,7 +149,7 @@
     k_AB = pB * kex
 
     # The Psi and zeta values.
-    if not np.allclose(r20a, r20b):
+    if not allclose(r20a, r20b):
         fact = r20a - r20b - k_BA + k_AB
         Psi = fact**2 - dw2 + 4.0*pA*pB*kex**2
         zeta = 2.0*dw * fact
@@ -199,6 +199,6 @@
         if rank_1:
             R2eff = array([1e100]*num_points)
         else:
-            R2eff = np.ones(R2eff.shape) * 1e100
+            R2eff = ones(R2eff.shape) * 1e100
 
     back_calc[:] = R2eff