r23821 - /branches/disp_spin_speed/target_functions/relax_disp.py -- June 11, 2014 - 10:08

Author: tlinnet
Date: Wed Jun 11 10:08:08 2014
New Revision: 23821

URL: http://svn.gna.org/viewcvs/relax?rev=23821&view=rev
Log:
Reordered how the structures dw init structures are created.

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

Modified:
    branches/disp_spin_speed/target_functions/relax_disp.py

Modified: branches/disp_spin_speed/target_functions/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/target_functions/relax_disp.py?rev=23821&r1=23820&r2=23821&view=diff
==============================================================================
--- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
+++ branches/disp_spin_speed/target_functions/relax_disp.py     Wed Jun 11 
10:08:08 2014
@@ -440,10 +440,10 @@
             self.dw_struct = deepcopy(zeros_a)
 
             # Temporary storage to avoid memory allocations and garbage 
collection.
-            self.dw_temp = zeros([self.NS] + self.numpy_array_shape, float64)
+            self.dw_temp = deepcopy(zeros_a)
 
             # The structure for multiplication with dw to piecewise build up 
the full dw structure.
-            self.dw_mask = deepcopy(self.dw_temp)
+            self.dw_mask = zeros(tuple([self.NS] + self.numpy_array_shape), 
float64)
 
             # Loop over the experiment types.
             for ei in range(self.NE):
@@ -561,10 +561,10 @@
         # Loop over the dw elements (one per spin).
         for si in range(self.NS):
             # First multiply the spin specific dw with the spin specific 
frequency mask, using temporary storage.
-            multiply(dw[si], self.dw_mask[si], self.dw_temp[si])
+            multiply(dw[si], self.dw_mask[si], self.dw_temp)
 
             # Then add to the total, using temporary storage.
-            add(self.dw_struct, self.dw_temp[si], self.dw_struct)
+            add(self.dw_struct, self.dw_temp, self.dw_struct)
 
         # Reshape dw to per experiment and nr spins.
         dw_axis = asarray(dw).reshape(self.NE, self.NS)