mailRe: r24100 - /branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_ns_r1rho_2site.py


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Posted by Edward d'Auvergne on June 18, 2014 - 17:24:
I'm re-re-re-re-re-re-running the super profiling script now and
everything is now ok.  I'll let it complete and commit the log file in
~30 min.  Then I'm off on holidays and won't be back until Monday.  By
then it looks like there will be timing statistics for all dispersion
models in relax!

Regards,

Edward


On 18 June 2014 17:14, Edward d'Auvergne <edward@xxxxxxxxxxxxx> wrote:
Very good question.  It must be a version mix up.  My current
profiling looks like:

Execution iteration 1

$ python profiling_cr72.py
    10000    0.070    0.000    1.750    0.000 
relax_disp.py:938(func_CR72_full)
      100    0.001    0.000    0.111    0.001 
relax_disp.py:938(func_CR72_full)
$ python /data/relax/tags/3.2.2/profiling_cr72.py /data/relax/tags/3.2.2
    10000    0.022    0.000    3.103    0.000 
relax_disp.py:907(func_CR72_full)
      100    0.000    0.000    3.070    0.031 
relax_disp.py:907(func_CR72_full)
$ python profiling_tsmfk01.py
    10000    0.106    0.000    0.732    0.000 
relax_disp.py:1803(func_TSMFK01)
      100    0.003    0.000    0.039    0.000 
relax_disp.py:1803(func_TSMFK01)
$ python /data/relax/tags/3.2.2/profiling_tsmfk01.py /data/relax/tags/3.2.2
    10000    0.270    0.000    1.635    0.000 
relax_disp.py:1892(func_TSMFK01)
      100    0.260    0.003    1.606    0.016 
relax_disp.py:1892(func_TSMFK01)
$ python profiling_b14.py
    10000    0.073    0.000    3.776    0.000 
relax_disp.py:884(func_B14_full)
      100    0.001    0.000    0.500    0.005 
relax_disp.py:884(func_B14_full)
$ python /data/relax/tags/3.2.2/profiling_b14.py /data/relax/tags/3.2.2
    10000    0.023    0.000    5.680    0.001 
relax_disp.py:854(func_B14_full)
      100    0.000    0.000    5.652    0.057 
relax_disp.py:854(func_B14_full)
$ python profiling_ns_cpmg_2site_expanded.py
    10000    0.187    0.000    4.473    0.000
relax_disp.py:1400(func_ns_cpmg_2site_expanded)
      100    0.027    0.000    0.677    0.007
relax_disp.py:1400(func_ns_cpmg_2site_expanded)
$ python /data/relax/tags/3.2.2/profiling_ns_cpmg_2site_expanded.py
/data/relax/tags/3.2.2
    10000    0.429    0.000    7.947    0.001
relax_disp.py:1445(func_ns_cpmg_2site_expanded)
      100    0.419    0.004    8.022    0.080
relax_disp.py:1445(func_ns_cpmg_2site_expanded)
$ python profiling_ns_cpmg_2site_3D.py
     1000    0.009    0.000   12.672    0.013
relax_disp.py:1375(func_ns_cpmg_2site_3D_full)
       10    0.000    0.000   12.703    1.270
relax_disp.py:1375(func_ns_cpmg_2site_3D_full)
$ python /data/relax/tags/3.2.2/profiling_ns_cpmg_2site_3D.py
/data/relax/tags/3.2.2
     1000    0.003    0.000   23.173    0.023
relax_disp.py:1421(func_ns_cpmg_2site_3D_full)
       10    0.000    0.000   23.549    2.355
relax_disp.py:1421(func_ns_cpmg_2site_3D_full)
$ python profiling_dpl94.py
    10000    0.116    0.000    1.076    0.000 relax_disp.py:966(func_DPL94)
      100    0.006    0.000    0.142    0.001 relax_disp.py:966(func_DPL94)
$ python /data/relax/tags/3.2.2/profiling_dpl94.py /data/relax/tags/3.2.2
    10000    1.834    0.000   22.603    0.002 relax_disp.py:934(func_DPL94)
      100    1.901    0.019   22.805    0.228 relax_disp.py:934(func_DPL94)
$ python profiling_ns_r1rho_2site.py
     1000    0.012    0.000    0.109    0.000 relax_disp.py:966(func_DPL94)
       10    0.001    0.000    0.015    0.001 relax_disp.py:966(func_DPL94)
$ python /data/relax/tags/3.2.2/profiling_ns_r1rho_2site.py
/data/relax/tags/3.2.2
     1000    0.178    0.000    2.240    0.002 relax_disp.py:934(func_DPL94)
       10    0.188    0.019    2.268    0.227 relax_disp.py:934(func_DPL94)

Regards,

Edward


On 18 June 2014 17:08, Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx> wrote:
How?

MODEL_NS_R1RHO_2SITE
self.model.func_ns_r1rho_2site(params)

Best
Troels


2014-06-18 17:04 GMT+02:00 Edward d'Auvergne <edward@xxxxxxxxxxxxx>:

Hi Troels,

I'm guessing that you already know this, but this is still executing
the DPL94 model rather than NS R1rho 2-site model.

Regards,

Edward



On 18 June 2014 16:48,  <tlinnet@xxxxxxxxxxxxx> wrote:
Author: tlinnet
Date: Wed Jun 18 16:48:50 2014
New Revision: 24100

URL: http://svn.gna.org/viewcvs/relax?rev=24100&view=rev
Log:
Added profiling script for NS R1rho 2site.

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

Modified:

branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_ns_r1rho_2site.py

Modified:
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_ns_r1rho_2site.py
URL:
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_ns_r1rho_2site.py?rev=24100&r1=24099&r2=24100&view=diff

==============================================================================
---
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_ns_r1rho_2site.py
(original)
+++
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_ns_r1rho_2site.py
Wed Jun 18 16:48:50 2014
@@ -63,7 +63,7 @@
 def main():
     if True:
         # Nr of iterations.
-        nr_iter = 1000
+        nr_iter = 10

         # Print statistics.
         verbose = True
@@ -523,11 +523,11 @@
         """

         # Return chi2 value.
-        chi2 = self.model.func_DPL94(params)
+        chi2 = self.model.func_ns_r1rho_2site(params)
         return chi2


-def single(num_spins=1, model=MODEL_DPL94, iter=None):
+def single(num_spins=1, model=MODEL_NS_R1RHO_2SITE, iter=None):
     """Calculate for a single spin.

     @keyword num_spins:     Number of spins in the cluster.
@@ -541,7 +541,7 @@
     """

     # Instantiate class
-    C1 = Profile(num_spins=num_spins, model=model, r2=5.0, phi_ex=1.0,
kex=5000.0, spins_params=['r2', 'phi_ex', 'kex'])
+    C1 = Profile(num_spins=num_spins, model=model, r2=5.0, dw=1.0,
pA=0.9, kex=5000.0, spins_params=['r2', 'dw', 'pA', 'kex'])

     # Loop 100 times for each spin in the clustered analysis (to make
the timing numbers equivalent).
     for spin_index in xrange(100):
@@ -551,7 +551,7 @@
     print("chi2 single:", chi2)


-def cluster(num_spins=100, model=MODEL_DPL94, iter=None):
+def cluster(num_spins=100, model=MODEL_NS_R1RHO_2SITE, iter=None):
     """Calculate for a number of clustered spins.

     @keyword num_spins:     Number of spins in the cluster.
@@ -565,7 +565,7 @@
     """

     # Instantiate class
-    C1 = Profile(num_spins=num_spins, model=model, r2=5.0, phi_ex=1.0,
kex=5000.0, spins_params=['r2', 'phi_ex', 'kex'])
+    C1 = Profile(num_spins=num_spins, model=model, r2=5.0, dw=1.0,
pA=0.9, kex=5000.0, spins_params=['r2', 'dw', 'pA', 'kex'])

     # Repeat the function call, to simulate minimisation.
     for i in xrange(iter):


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