mailr23259 - in /branches/disp_speed: pipe_control/minimise.py target_functions/relax_disp.py


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Posted by tlinnet on May 20, 2014 - 14:55:
Author: tlinnet
Date: Tue May 20 14:55:11 2014
New Revision: 23259

URL: http://svn.gna.org/viewcvs/relax?rev=23259&view=rev
Log:
Reverted r23250-23248 as the correct fix was done in fixing bug 22055.

bug #22055 (https://gna.org/bugs/?22055) The processor.run_queue() does not 
clean up in uni_processor - chain-reaction failures in the test suite.

The command used was:
svn merge -r23250:r23247 .

.....
    r23250 | tlinnet | 2014-05-20 02:02:19 +0200 (Tue, 20 May 2014) | 1 line

    Fix for variable num_points not set.
    ------------------------------------------------------------------------
    r23249 | tlinnet | 2014-05-20 01:47:37 +0200 (Tue, 20 May 2014) | 4 lines

    An attempt to fix the pipe_control/minimisy.py minimise() call to 
processor.run_queue().

    It was thought that I was modifying the address of array class(back_calc).
    But this does not seem to be the problem.
    ------------------------------------------------------------------------
    r23248 | tlinnet | 2014-05-20 01:47:34 +0200 (Tue, 20 May 2014) | 11 lines

    Turned of processor.run_queue() when using calc().

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

    A weird behaviour was found when running the test-suite.

    Somehow, queued jobs from the last test suite was not flushed and done.
    Running the test-suite gave errors on almost all tests.

    Inspecting systemtest which only used calc() for the dispersion API, 
showed that no jobs was queued
    in the calculate() method, and the call to processor.run_queue(), was 
turned off, solving the problem.
.....

Modified:
    branches/disp_speed/pipe_control/minimise.py
    branches/disp_speed/target_functions/relax_disp.py

Modified: branches/disp_speed/pipe_control/minimise.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_speed/pipe_control/minimise.py?rev=23259&r1=23258&r2=23259&view=diff
==============================================================================
--- branches/disp_speed/pipe_control/minimise.py        (original)
+++ branches/disp_speed/pipe_control/minimise.py        Tue May 20 14:55:11 
2014
@@ -80,8 +80,7 @@
         api.calculate(verbosity=verbosity)
 
     # Execute any queued commands.
-    # No processes has been queued in the calc function().
-    #processor.run_queue()
+    processor.run_queue()
 
 
 def grid_search(lower=None, upper=None, inc=None, constraints=True, 
verbosity=1):

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=23259&r1=23258&r2=23259&view=diff
==============================================================================
--- branches/disp_speed/target_functions/relax_disp.py  (original)
+++ branches/disp_speed/target_functions/relax_disp.py  Tue May 20 14:55:11 
2014
@@ -484,14 +484,7 @@
                 dw_frq = dw[si] * self.frqs[0][si][mi]
 
                 # Back calculate the R2eff values.
-                r2eff = r2eff_CR72(r20a=R20A[r20_index], 
r20b=R20B[r20_index], pA=pA, dw=dw_frq, kex=kex, 
cpmg_frqs=self.cpmg_frqs[0][mi][0], 
num_points=self.num_disp_points[0][si][mi][0])
-
-                # Now do the fastest way to copy data from array r2eff to 
array class(back_calc), without modifying the address of array 
class(back_calc).
-                # This is to prevent pointer to class object array that 
cannot change. Should be equivalent to numpy.copyto (v. 1.7).
-                #self.back_calc[0][si][mi][0][:] = r2eff
-                # Parse back the value to update the back_calc class object.
-                for i in range(self.num_disp_points[0][si][mi][0]):
-                    self.back_calc[0][si][mi][0][i] = r2eff[i]
+                self.back_calc[0][si][mi][0] = 
r2eff_CR72(r20a=R20A[r20_index], r20b=R20B[r20_index], pA=pA, dw=dw_frq, 
kex=kex, cpmg_frqs=self.cpmg_frqs[0][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]):




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