[bug #25084] Running Model_Free on multi processors Fedora 20 complications

[Troels E. Linnet]

Update of bug #25084 (project relax):

 Open/Closed:Open => Closed 

___

Follow-up Comment #10:

Message from user. Problem solved.

I was able to get relax working on a multi-processor platform finally. I tried
using the mpich instead of openmpi. 
module load mpi/mpich-x86_64
mpirun -np 7 ./relax --multi='mpi4py' 

and it loaded up relax with 1 master and 7 slaves. I don't exactly understand
why openmpi doesn't work. I have gotten both from the package list, and
installed them directly., and I have mpi4py for both mpich and openmpi (I also
got these from the package list and installed directly), but this seemed to
finally get it to work. 


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[bug #25084] Running Model_Free on multi processors Fedora 20 complications

[Troels E. Linnet]

Update of bug #25084 (project relax):

 Open/Closed:  Closed => Open   

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Follow-up Comment #6:

Opening bug again.

Trying to write a script to get system information regarding openmpi.

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[bug #25084] Running Model_Free on multi processors Fedora 20 complications

[Troels E. Linnet]

Update of bug #25084 (project relax):

Priority:  5 - Normal => 1 - Later  
Severity:  3 - Normal => 2 - Minor  
  Status:None => External bug   
 Assigned to:None => tlinnet
 Open/Closed:Open => Closed 

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Follow-up Comment #4:

Closing this bug, as it not possible to inspect the users system.

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[bug #25084] Running Model_Free on multi processors Fedora 20 complications

[Troels E. Linnet]

Follow-up Comment #3, bug #25084 (project relax):

Try make a run script like this and copy it some where to your PATH 

myrelax
--
#!/bin/tcsh -fe
 
# Set the relax version used for this script.
set RELAX=/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/relax
 
# Set number of available CPUs.
set NPROC=`nproc`
set NP=`echo $NPROC + 0 | bc `
 
echo "Running relax with NP=$NP in multi-processor mode"
 
# Run relax in multi processor mode.
mpirun -np $NP $RELAX --multi='mpi4py' $argv

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[bug #25084] Running Model_Free on multi processors Fedora 20 complications

[Troels E. Linnet]

Follow-up Comment #2, bug #25084 (project relax):

I suspect there is a mismatch between two installations of relax.

One version of 2.x and one local of 4.x.

Try adding the full path to relax 

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[bug #25084] Running Model_Free on multi processors Fedora 20 complications

[Troels E. Linnet]

Follow-up Comment #1, bug #25084 (project relax):

Please upgrade!

Name   InstalledVersion Current version
minfx  True 1.0.41.0.12

relax information:
Version: 2.2.5 4.0.2



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[bug #25054] Running scripts for model free

[Troels E. Linnet]

Update of bug #25054 (project relax):

  Status:None => Invalid
 Assigned to:None => tlinnet
 Open/Closed:Open => Closed 

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Follow-up Comment #2:

I close this bug as invalid.

It is not a bug, it is a user error.

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[bug #25054] Running scripts for model free

[Troels E. Linnet]

Follow-up Comment #1, bug #25054 (project relax):

You have to read the output.

It says there is an error:

RelaxError: The spin ID '#hRGS7:12' corresponds to multiple spins, including
'#hRGS7:12@N' and '#hRGS7:12@H'. 


When relax makes an error. The program exits.

You have not labelled your data correct.

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[task #7882] Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals

[Troels E. Linnet]

Update of task #7882 (project relax):

 Open/Closed:Open => Closed 


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[bug #23642] When deleting all spins for a residue, an empty placeholder is where select=True

[Troels E. Linnet]

Update of bug #23642 (project relax):

  Status:None = Fixed  
 Open/Closed:Open = Closed 


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[bug #23644] monte_carlo.error_analysis() does not update the mean value/expectation value from simulations

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?23644

 Summary: monte_carlo.error_analysis() does not update the
mean value/expectation value from simulations
 Project: relax
Submitted by: tlinnet
Submitted on: Mon 15 Jun 2015 09:32:07 UTC
Category: None
Specific analysis category: None
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

When performing a monte_carlo.error_analysis(), the error for each parameter
is estimated by the Standard deviation for all the simulated values.

But the mean of these simulated values is not used to update parameter value.

Therefore, this leads to a rather weird situation, where the described
parameter error is from the width of a simulated distribution, and and the
expectation value is not updated.

Some few histograms is added to show this.



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File Attachments:


---
Date: Mon 15 Jun 2015 09:32:07 UTC  Name: figure1.png  Size: 32kB   By:
tlinnet

http://gna.org/bugs/download.php?file_id=24577
---
Date: Mon 15 Jun 2015 09:32:07 UTC  Name: figure3.png  Size: 35kB   By:
tlinnet

http://gna.org/bugs/download.php?file_id=24578
---
Date: Mon 15 Jun 2015 09:32:07 UTC  Name: figure2.png  Size: 36kB   By:
tlinnet

http://gna.org/bugs/download.php?file_id=24579

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[bug #23642] When deleting all spins for a residue, an empty placeholder is where select=True

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?23642

 Summary: When deleting all spins for a residue, an empty
placeholder is where select=True
 Project: relax
Submitted by: tlinnet
Submitted on: Sat 13 Jun 2015 11:53:52 UTC
Category: None
Specific analysis category: All analyses
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

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Details:

When deleting all spins for a residue, an empty placeholder is where
select=True

This is not very convenient, when one afterwards do spin_loop, where the empty
spins shows up.




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[bug #23618] queuing system for multi processors is not well designed.

[Troels E. Linnet]

Update of bug #23618 (project relax):

  Status:None = Invalid
 Assigned to:None = tlinnet
 Open/Closed:Open = Closed 

___

Follow-up Comment #7:

This problem is maybe more related to missing printout of progress in for
multi core monte-carlo simulations.

If 500 montecarlo simulations is spread out on 10 processors, each job gets 50
MC to handle.
But the processors does not report back, before all 50 MC is completed, and
this can take some time.

Therefore, it will for the user seems like that relax is stuck, when using
10 processors.

For a uni-processor setup, each MC simulation is handled, and reported back
when completed. This gives a better feeling with the process.




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[bug #23619] Stored chi2 sim values from Monte-Carlo simulations does not equal normal chi2 values

[Troels E. Linnet]

Update of bug #23619 (project relax):

  Status:None = Invalid
 Open/Closed:Open = Closed 

___

Follow-up Comment #2:

This bug is invalid.

The problem can be solved by selecting another distribution to draw the errors
from.

Before, the fitted chi2 was: 6249.52554918

A sample of 500 MC fitted chi2 was then:
926.6754336751644, 964.0109732186118, 1025.9989433716908, 1043.960525627065,
1001.5430340126602, 1011.4727841212358, 980.6200561189471, 1009.6621226424397,
977.0688338566254, 

By chosing to draw errors from the overall fit, instead of individual errors:
monte_carlo.create_data(distribution='red_chi2')

A sample of the 500 MC fittede chi2 is now:
6015.742665115796, 6735.870964603169, 6699.677733437879, 6336.189620385313,
5949.360127468063, 6264.302556809358, 6949.976694308039, 6220.975080541431,
6294.342637959295, 

This shows, that the loaded errors for the intensities is properly to low. The
loaded intensity errors is based on the noise RMSD of the spectra.

Therefore, this problem is not related to relax, but is related to the data
quality.


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[bug #23619] Stored chi2 sim values from Monte-Carlo simulations does not equal normal chi2 values

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?23619

 Summary: Stored chi2 sim values from Monte-Carlo simulations
does not equal normal chi2 values
 Project: relax
Submitted by: tlinnet
Submitted on: Thu 28 May 2015 02:02:25 PM UTC
Category: relax's source code
Specific analysis category: None
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: tlinnet
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

The stored chi2 sim values from Monte-Carlo simulations does not equal normal
chi2 values.

When looking at the spin.chi2_sim list, the values are very much different
from spin.chi2.




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[bug #23618] queuing system for multi processors is not well designed.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?23618

 Summary: queuing system for multi processors is not well
designed.
 Project: relax
Submitted by: tlinnet
Submitted on: Wed 27 May 2015 12:10:57 AM UTC
Category: relax's source code
Specific analysis category: None
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

There queuing system for multi processors appears not to be designed well.

This has been detected in dispersion analysis.
A clustered fit of 74 spins, doing 100 monte carlo simulations.

The test has been where a number of multi processors is 10, with 1 CPU as
master.

The problem seems to reside in:
multi.processor.run_queue()
multi.multi_processor.chunk_queue()

The current queuing system will take the 100 monte carlo simulations, and
chunk them up in pieces of 10, and distribute each of these chunks to each
CPU.

Each CPU thus have 10 simulations to handle.

The problem is, that not each simulations is equally fast to be solved.
Thus, a CPU will hang until all simulations has finished.
This will block the possibility to assign CPU power for other tasks, until
all simulations has finished.

A suggestion for a first fix, is not to chunk up the queue, 
but let each simulation be handled independently.

In multi/processor.py
--
-lqueue = self.chunk_queue(self.command_queue)
-self.run_command_queue(lqueue)
+#lqueue = self.chunk_queue(self.command_queue)
+self.run_command_queue(self.command_queue)
-

This does seem to improve the timing much, but give a better overview in the
process.

It appears that the queuing system can even be enhanced more.
The list of Running set is not replenished before all jobs in Running set
is completed.

This influences the solving time.



Only 20 monte carlo simulations is runned for comparison.
/usr/bin/time -p relax_multi bug.py

The running time for 1 CPU, no multi processor:
real 510.94
user 5903.01
sys 133.96

The running time for 1 CPU, 4 multi processor:
real 214.89
user 1786.39
sys 37.09

The running time for 1 CPU, 10 multi processor:
real 108.39
user 1930.21
sys 44.45


The running time for 1 CPU, 4 multi processor with first fix:
real 235.46
user 1892.20
sys 38.58

The running time for 1 CPU, 10 multi processor with first fix
real 110.50
user 1957.99
sys 43.60




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Date: Wed 27 May 2015 12:10:57 AM UTC  Name: bug.bz2  Size: 301kB   By:
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http://gna.org/bugs/download.php?file_id=24545

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[bug #23618] queuing system for multi processors is not well designed.

[Troels E. Linnet]

Follow-up Comment #1, bug #23618 (project relax):

Fix 2, where the Running set is continuously replenished when a job
finishes.

The running time for 1 CPU, 4 multi processor with second fix: 
real 206.19
user 1740.53
sys 38.38

The running time for 1 CPU, 10 multi processor with second fix 
real 106.74
user 1915.35
sys 43.71

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[bug #23618] queuing system for multi processors is not well designed.

[Troels E. Linnet]

Follow-up Comment #5, bug #23618 (project relax):

It is weird, that when calculations is not submitted, slave processors shows
100 %, and the master does it all.

13578 tlinnet   20   0 1315m 386m  25m R 133.6  1.6   1:08.73 python  

13584 tlinnet   20   0  784m  72m  21m R 100.2  0.3   1:03.22 python  

13579 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.23 python   

13580 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.25 python   

13581 tlinnet   20   0  784m  73m  21m R 99.9  0.3   1:03.20 python   

13582 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.22 python   

13583 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.21 python   

13585 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.21 python   

13586 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.23 python   

13587 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.24 python   

13588 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.20 python   

13589 tlinnet   20   0  784m  72m  21m R 99.9  0.3   1:03.20 python 

When jobs are submitted, they show 200 %

13579 tlinnet   20   0 1023m 150m  23m R 199.9  0.6   3:20.01 python  

13580 tlinnet   20   0 1023m 152m  23m R 199.9  0.6   3:19.77 python  

13582 tlinnet   20   0 1023m 152m  23m R 199.9  0.6   3:19.22 python  

13583 tlinnet   20   0 1023m 149m  23m R 199.9  0.6   3:18.93 python  

13584 tlinnet   20   0 1023m 151m  23m R 199.9  0.6   3:18.40 python  

13585 tlinnet   20   0 1023m 149m  23m R 199.9  0.6   3:18.12 python  

13586 tlinnet   20   0 1023m 149m  23m R 199.9  0.6   3:17.89 python  

13588 tlinnet   20   0 1023m 151m  23m R 199.9  0.6   3:17.32 python  

13589 tlinnet   20   0 1023m 151m  23m R 199.9  0.6   3:16.74 python  

13587 tlinnet   20   0 1023m 151m  23m R 199.5  0.6   3:17.60 python  

13581 tlinnet   20   0 1023m 150m  23m R 199.2  0.6   3:19.40 python  

13578 tlinnet   20   0 1638m 636m  26m R 99.9  2.6   3:49.60 python 


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[bug #23618] queuing system for multi processors is not well designed.

[Troels E. Linnet]

Follow-up Comment #2, bug #23618 (project relax):

Adding the test script

(file #24546)
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[sr #3210] relaxation experimental data and fitting curve plot

[Troels E. Linnet]

Follow-up Comment #6, sr #3210 (project relax):

Added help.py script, that will make graphs per spin with intepolated values.

put help.py in the same folder as r1.500.save.bz2.
Make sure that there is a folder called grace.

run the script by:
relax help.py

This will open the state file, and interpolate values.
Changes to xmgrace settings can be made manually

in grace folder, there is a grace2images.py file.
Execute this, to make all xmgrace files into png, or eps.

(file #23718, file #23719, file #23720)
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File name: int_51_T.agr   Size:2 KB
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[bug #23186] Error calculation of individual parameter dw from Monte-Carlo, is based on first spin.

[Troels E. Linnet]

Follow-up Comment #5, bug #23186 (project relax):

Hi Ed.

Do you have a suggestion how to fix this?

Best
Troels

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[task #7873] Write wrapper function to nmrglue, to read .ft2 files and process them.

[Troels E. Linnet]

Update of task #7873 (project relax):

  Status:  Gone walkabout = Ready For Test 
Percent Complete: 10% = 100%   
  Effort:   10.00 = 100

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Follow-up Comment #93:

This needs to be verified for python 3 and relax.

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[bug #22598] Back end of value.set does not respect force=False flag

[Troels E. Linnet]

Update of bug #22598 (project relax):

  Status:None = Fixed  
 Open/Closed:Open = Closed 

___

Follow-up Comment #3:

This has been fixed.

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[bug #23186] Error calculation of individual parameter dw from Monte-Carlo, is based on first spin.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?23186

 Summary: Error calculation of individual parameter dw from
Monte-Carlo, is based on first spin.
 Project: relax
Submitted by: tlinnet
Submitted on: Wed 14 Jan 2015 12:47:37 PM UTC
Category: None
Specific analysis category: Relaxation dispersion
Priority: 7 - High
Severity: 4 - Important
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

This was discovered in post:

http://thread.gmane.org/gmane.science.nmr.relax.user/1795

The problem is in:
specific_analyses.relax_disp/api.sim_return_param()

--
# Convert the parameter index.
if model_param:
param_name, si, mi = param_index_to_param_info(index=index,
spins=spins)
if not param_name in ['r2eff', 'i0']:
si = 0
else:
param_name = aux_params[index - total_param_num]
si = 0
mi = 0

...

# Model and auxiliary parameters.
else:
sim_data = getattr(spins[si], param_name + _sim)

--

Since si = 0, it takes dw values from initial spin, and uses this as error for
all spins.

This is not correct.





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[bug #23187] Deleting residue in GUI, and then open spin viewer crashes relax.

[Troels E. Linnet]

Follow-up Comment #3, bug #23187 (project relax):

def test_bug_23187_residue_delete_gui(self):
Catch U{bug #23187https://gna.org/bugs/?23187}, deleting residue
in GUI, and then open spin viewer crashes relax.

# Mf tab:  Simulate the new analysis wizard.
analysis = self.new_analysis_wizard(analysis_type='mf',
analysis_name='Mf test', pipe_name='mf', pipe_bundle='mf bundle')

self._execute_uf(uf_name='residue.create', res_num=1)
self._execute_uf(uf_name='residue.create', res_num=2)

# Launch the spin viewer window.
self.app.gui.show_tree()

# Close the spin viewer window.
self.app.gui.spin_viewer.handler_close()

# Delete spin,
self._execute_uf(uf_name='residue.delete', res_id=:2)

# Launch the spin viewer window.
self.app.gui.show_tree()


relax_tomat --gui-tests General.test_bug_23187_residue_delete_gui --time

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[bug #23187] Deleting residue in GUI, and then open spin viewer crashes relax.

[Troels E. Linnet]

Follow-up Comment #4, bug #23187 (project relax):

This will NOT catch the error.

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[task #7860] When dx_map is issued, create a parameter file which maps parameters to chi2 value.

[Troels E. Linnet]

Update of task #7860 (project relax):

Percent Complete:  0% = 100%   
 Open/Closed:Open = Closed 
  Effort:0.00 = 10.00  

___

Follow-up Comment #7:

This has been implemented.

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[task #7826] Write an python class for the repeated analysis of dispersion data.

[Troels E. Linnet]

Update of task #7826 (project relax):

Percent Complete:  0% = 80%

___

Follow-up Comment #73:

This has been completed.

The class though needs to be revised for repeated code, and cleaned up.

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[task #7873] Write wrapper function to nmrglue, to read .ft2 files and process them.

[Troels E. Linnet]

URL:
  http://gna.org/task/?7873

 Summary: Write wrapper function to nmrglue, to read .ft2
files and process them.
 Project: relax
Submitted by: tlinnet
Submitted on: Thu 27 Nov 2014 10:21:11 AM UTC
 Should Start On: Thu 27 Nov 2014 12:00:00 AM UTC
   Should be Finished on: Thu 27 Nov 2014 12:00:00 AM UTC
Category: relax's source code
Priority: 5 - Normal
  Status: In Progress
Percent Complete: 0%
 Assigned to: tlinnet
 Open/Closed: Open
 Discussion Lock: Any
  Effort: 0.00

___

Details:

nmrglue is a powerful Python module for working with NMR data.

The article describing nmrglue has been published in the Journal of
Biomolecular NMR.

J.J. Helmus, C.P. Jaroniec, Nmrglue: An open source Python package for the
analysis of multidimensional NMR data, J. Biomol. NMR 2013, 55, 355-367.
10.1007/s10858-013-9718-x.

The code is develop at Github.
https://github.com/jjhelmus/nmrglue/

With documentation and examples here:
http://jjhelmus.github.io/nmrglue/current/index.html

The License is covered here:
https://github.com/jjhelmus/nmrglue/blob/master/LICENSE.txt


The idea is to write some wrapper function to nmrglue, to quickly be able to
access the very useful functionality. 




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[task #7860] When dx_map is issued, create a parameter file which maps parameters to chi2 value.

[Troels E. Linnet]

URL:
  http://gna.org/task/?7860

 Summary: When dx_map is issued, create a parameter file which
maps parameters to chi2 value.
 Project: relax
Submitted by: tlinnet
Submitted on: Fri 10 Oct 2014 12:09:54 PM UTC
 Should Start On: Fri 10 Oct 2014 12:00:00 AM UTC
   Should be Finished on: Fri 10 Oct 2014 12:00:00 AM UTC
Category: None
Priority: 5 - Normal
  Status: In Progress
Percent Complete: 0%
 Assigned to: tlinnet
 Open/Closed: Open
 Discussion Lock: Any
  Effort: 0.00

___

Details:

During the creation of a dx_map, it would be highly valuable to store the
parameter values, which give rise to the chi2 values.

The file should contain colums of:

par_1   par_2   par_3  chi2

The columns could also be sorted, with chi2 values lowest first.




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[bug #22563] The NS MMQ 2-site dispersion model is running at 32-bit precision and not 64-bit as it should be.

[Troels E. Linnet]

Follow-up Comment #2, bug #22563 (project relax):

This bug was not introduced in the disp_spin_speed branch.
The 64-bit was present before that.

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[bug #22753] dx.map does not work when only 1 point is used.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22753

 Summary: dx.map does not work when only 1 point is used.
 Project: relax
Submitted by: tlinnet
Submitted on: Sun 05 Oct 2014 08:15:48 PM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: tlinnet
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:






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[bug #22753] dx.map does not work when only 1 point is used.

[Troels E. Linnet]

Update of bug #22753 (project relax):

  Status:None = Fixed  


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[bug #22753] dx.map does not work when only 1 point is used.

[Troels E. Linnet]

Update of bug #22753 (project relax):

 Open/Closed:Open = Closed 


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[bug #22754] The minimise.calculate() does not calculate chi2 value for clustered residues

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22754

 Summary: The minimise.calculate() does not calculate chi2
value for clustered residues
 Project: relax
Submitted by: tlinnet
Submitted on: Sun 05 Oct 2014 08:32:18 PM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: tlinnet
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

This affect the dx map, not making the chi2 surface correct for clustered
values.




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[bug #22754] The minimise.calculate() does not calculate chi2 value for clustered residues

[Troels E. Linnet]

Update of bug #22754 (project relax):

  Status:None = Fixed  
 Open/Closed:Open = Closed 


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[task #7858] Make it possible to submit CPMG experiments for BMRB

[Troels E. Linnet]

URL:
  http://gna.org/task/?7858

 Summary: Make it possible to submit CPMG experiments for BMRB
 Project: relax
Submitted by: tlinnet
Submitted on: Fri 03 Oct 2014 01:40:31 PM UTC
 Should Start On: Fri 03 Oct 2014 12:00:00 AM UTC
   Should be Finished on: Fri 03 Oct 2014 12:00:00 AM UTC
Category: None
Priority: 5 - Normal
  Status: In Progress
Percent Complete: 0%
 Assigned to: tlinnet
 Open/Closed: Open
 Discussion Lock: Any
  Effort: 0.00

___

Details:

Implement API for BMRB submission of CPMG data.




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[task #7858] Make it possible to submit CPMG experiments for BMRB

[Troels E. Linnet]

Update of task #7858 (project relax):

  Status: In Progress = Gone walkabout 

___

Follow-up Comment #6:

This feature will not be implemented, as it requires a large re-write of data
structures.
   
To implement the funvtion, it would require a re-write of the relax_data
bmrb_write(star) function, and proper handling of cdp.ri_ids.
It was also not readily possible to find examples of submitted CPMG data in
the BMRB database.
This makes it hard to develop, and even ensure that BMRB would accept the
format.


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[bug #22598] Back end of value.set does not respect force=False flag

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22598

 Summary: Back end of value.set does not respect force=False
flag
 Project: relax
Submitted by: tlinnet
Submitted on: Mon 08 Sep 2014 03:43:38 PM UTC
Category: None
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

When using back-end of value.set, the function does not respect setting the
force flag to False.

This was discovered, by using relax_disp.r20_from_min_r2eff and setting
grid_inc to None.

Here r20 was overwritten.




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[bug #22568] The 'arrow' up in the GUI relax prompt does not bring up the last command.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22568

 Summary: The 'arrow' up in the GUI relax prompt does not
bring up the last command.
 Project: relax
Submitted by: tlinnet
Submitted on: Thu 04 Sep 2014 08:09:16 AM UTC
Category: relax's source code
Specific analysis category: None
Priority: 3 - Low
Severity: 1 - Wish
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: 64-bit GNU/Linux

___

Details:

When using the relax prompt in the GUI, one often want's to re-run a command.

But the arrow 'up' does not bring the last command.
The curser go up in the text.

This was observed on a mac.




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[task #7826] Write an python class for the repeated analysis of dispersion data.

[Troels E. Linnet]

URL:
  http://gna.org/task/?7826

 Summary: Write an python class for the repeated analysis of
dispersion data.
 Project: relax
Submitted by: tlinnet
Submitted on: Wed 03 Sep 2014 12:10:14 PM UTC
 Should Start On: Wed 03 Sep 2014 12:00:00 AM UTC
   Should be Finished on: Wed 03 Sep 2014 12:00:00 AM UTC
Category: relax's source code
Priority: 2
  Status: In Progress
Percent Complete: 0%
 Assigned to: tlinnet
 Open/Closed: Open
 Discussion Lock: Any
  Effort: 0.00

___

Details:

I would like to make a protocol, which can repeatability analyses dispersion
data.

The range of dispersion data is similar, so the setup of the system is equal.

But the intensities will vary. 




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[bug #22557] Monte-Carlo simulations for R1rho dispersion analysis, does not include randomization of R1.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22557

 Summary: Monte-Carlo simulations for R1rho dispersion
analysis, does not include randomization of R1.
 Project: relax
Submitted by: tlinnet
Submitted on: Mon 01 Sep 2014 10:28:33 AM UTC
Category: relax's source code
Specific analysis category: None
Priority: 6
Severity: 4 - Important
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Branches
 Discussion Lock: Any
Operating System: All systems

___

Details:

Please see:
http://thread.gmane.org/gmane.science.nmr.relax.devel/6969

The Monte-Carlo simulations only randomize data for R1rho prime.
It does not randomize for R1.

This is a bug.

It would then be possible to compare to error estimation from Co-variance
matrix.
Example DPL94:
One would first get the error for R1_ex, and then for Rex.
R1rho = R1_ex + Rex = R1 * cos(theta)**2 + (R1rho_p + ( (phi_ex * kex) /
(kex**2 + we**2) ) ) * sin(theta)**2.

Get the error from the covariance of R1_ex, and then for Rex.

J1: of R1 * cos(theta)**2 
J2: of (R1rho_p + ( (phi_ex * kex) / (kex**2 + we**2) ) ) * sin(theta)**2.

Then Covar of J1, Covar of J2.

Then
STD(DPL94) = sqrt(diag(cov_J1)) + sqrt(diag(cov_J2))

This follows for standard rule of error propagation.

This error should approx correspond to the error for 10.000 Monte-Carlo
simulations.

My statements here should be checked thoroughly before implementation.

There is maybe a shortcut:
Uncertainty in a Function of Several Variables
Page 75, An Introduction to Error Analysis
http://www.uscibooks.com/taylornb.htm

std(q) = sqrt  ( (dq/dx *std(x))**2 + (dq/dz *std(z))**2  )

where x, z are R1 and R1rho_prime, and q is DPL94.





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[task #7824] Model parameter ERROR estimation from Jacobian and Co-variance matrix of dispersion models.

[Troels E. Linnet]

URL:
  http://gna.org/task/?7824

 Summary: Model parameter ERROR estimation from Jacobian and
Co-variance matrix of dispersion models.
 Project: relax
Submitted by: tlinnet
Submitted on: Mon 01 Sep 2014 02:31:47 PM UTC
 Should Start On: Mon 01 Sep 2014 12:00:00 AM UTC
   Should be Finished on: Mon 01 Sep 2014 12:00:00 AM UTC
Category: relax's source code
Priority: 3 - Low
  Status: In Progress
Percent Complete: 0%
 Assigned to: tlinnet
 Open/Closed: Open
 Discussion Lock: Any
  Effort: 0.00

___

Details:

In theory, one can get the Model parameter ERROR, from Jacobian and
Co-variance matrix of dispersion models.

The error of the dispersion points R2eff, stems from error on signal
intensity.

The R2eff and error points are used in the dispersion models.

If one knows the derivative of a function, one can get the estimated errors as
well.

http://www.orbitals.com/self/least/least.htm

This could get compared to a large number of Monte-Carlo simulations.

I relax, Monte-Carlo simulations are made by assuming an gaussian distribution
of R2eff points.

Estimating the errors from the Jacobian, is essential the same, since the
Co-variance matrix is made by populating the weight matrix with the R2eff
errors.

Therefore, the end result should in principle be the same.

The Jacobian matrix are easy to derive for the analytical models.
For the numerical solutions, it is a little different, since we then need to
take the derivative of a matrix. That can get tricky. In this situation, a
numerical gradient solution would probably be better.




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[bug #22552] Chi2 value returned from C-code Curve-fitting return 0.0 for wrong parameters - Expected influence on Monte-Carlo sim

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22552

 Summary: Chi2 value returned from C-code Curve-fitting return
0.0 for wrong parameters - Expected influence on Monte-Carlo sim
 Project: relax
Submitted by: tlinnet
Submitted on: Sun 31 Aug 2014 10:51:18 AM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 9 - Immediate
Severity: 4 - Important
  Status: Need Info
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

The Chi2 value returned from C-code Curve-fitting return 0.0 for wrong
parameters.

This is expected to influence Monte-Carlo simulations, where minfx can take a
wrong step.

This is inserted as systemtest:
relax -s Relax_disp.test_finite_value -d

R = - 500.
I0 = 1000.
params = [R, I0]
chi2 = func(params)
= Returns 0.0

This shows, that restraints should be set on, for keeping control over steps
not been taking wrong.




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[bug #22552] Chi2 value returned from C-code Curve-fitting return 0.0 for wrong parameters - Expected influence on Monte-Carlo sim

[Troels E. Linnet]

Update of bug #22552 (project relax):

Priority:   9 - Immediate = 5 - Normal 
Severity:   4 - Important = 2 - Minor  

___

Follow-up Comment #1:

Corrections to this statement.

The C-code was not initialized with function values.
Therefore a return with 0.0

from target_functions.relax_fit import jacobian, jacobian_chi2, setup
from specific_analyses.relax_fit.optimisation import func_wrapper,
dfunc_wrapper, d2func_wrapper
func = func_wrapper

times = array([ 0.7,  1. ,  0.8,  0.4,  0.9])
I = array([ 476.76174875,  372.43328777,  454.20339981, 656.87936253, 
419.16726341])
errors = array([  9.48032653,  11.34093541,   9.35149017,  10.84867928, 
12.17590736])

scaling_list = [1.0, 1.0]
setup(num_params=2, num_times=len(times), values=I, sd=errors,
relax_times=times, scaling_matrix=scaling_list)

R = - 500.
I0 = 1000.
params = [R, I0]

chi2 = func(params)

The question is, if minfx can handle inf values?


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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22554

 Summary: The distribution of intensity with errors in
Monte-Carlo simulations are markedly more narrow than expected.
 Project: relax
Submitted by: tlinnet
Submitted on: Sun 31 Aug 2014 07:03:07 PM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 9 - Immediate
Severity: 4 - Important
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

It seems that relax draw a lot more narrow distribution of Intensity with
errors, than python module random.
This has an influence on estimated parameter error.

This is a potential huge error in relax.
A possible example of a catastrophic implementation of Monte-Carlo
simulations.

See:
http://thread.gmane.org/gmane.science.nmr.relax.scm/23239
http://thread.gmane.org/gmane.science.nmr.relax.scm/23238

Attached image that show distribution narrowing for Monte-Carlo simulations in
relax.

Also attached 2 images, that show there is perfect correlation for estimation
of errors between boot strapping and from Co-variance matrix.




___

File Attachments:


---
Date: Sun 31 Aug 2014 07:03:07 PM UTC  Name:
estimate_errors_analyse_relax.py.png  Size: 47kB   By: tlinnet

http://gna.org/bugs/download.php?file_id=21975
---
Date: Sun 31 Aug 2014 07:03:07 PM UTC  Name: estimate_errors_data_nt5.png 
Size: 73kB   By: tlinnet

http://gna.org/bugs/download.php?file_id=21976
---
Date: Sun 31 Aug 2014 07:03:07 PM UTC  Name: estimate_errors_data_nt10.png 
Size: 74kB   By: tlinnet

http://gna.org/bugs/download.php?file_id=21977

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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #1, bug #22554 (project relax):

This shows that the created intensities are totally off the true intensity.

(file #21978)
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Additional Item Attachment:

File name: estimate_errors_analyse_relax_intensity.png Size:46 KB


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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #2, bug #22554 (project relax):

It seems there is a difference in implementation.

Relax will do an average on all the simulated intensities before sending to
minimisation.

Boot strap method will send to minimisation for arrays of intensities, and
collect R and I0, and then make a standard deviation of those values.

This is an idea,
From the relax method, there should then be calculated a standard deviation
for all the simulated intensities, and this should be used as weights instead?

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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #3, bug #22554 (project relax):

Correction for last statement.

The API loops over simulations.

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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #4, bug #22554 (project relax):

Printing the param_array in monte carlo error analysis shows some error:

[{'r1rho_800.1000_120.000_1000.000': 1.0347010103451084},
{'r1rho_800.1000_120.000_1000.000': 1.0341836551964643},
{'r1rho_800.1000_120.000_1000.000': 1.0326624700588243}]

[{'r1rho_800.1000_120.000_1000.000': 2056.6507689335872},
{'r1rho_800.1000_120.000_1000.000': 2038.7365902565855},
{'r1rho_800.1000_120.000_1000.000': 2055.035231223037}]

The 2000 should be 1000 ?

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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #5, bug #22554 (project relax):

A print in optimisation.minimise_r2eff shows:

(array([  1.033736979857547e+00,   2.042543396198080e+03]),
1.3185441226817112, 12, 42, 13, 12, None)
Simulation 1
(array([  1.030188575574683e+00,   2.048713605406381e+03]),
1.2165923486568535, 8, 25, 9, 8, None)
Simulation 2
(array([  1.041327082929338e+00,   2.051083000120404e+03]), 2.746923212190992,
8, 27, 9, 8, None)
Simulation 3


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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #6, bug #22554 (project relax):

Even with constraints on, and simplex as minimisation it seems that simplex
takes a catastophic step, and get inf from the C-code.

It is known, that minfx cannot handle 'inf' values, and terminates right
away.


x0 [1.035066856592987  1022.443240712164652]
[  1.017439782586841e+00   2.029754497891464e+03] 0.840053982988 846 1907 0 0
None Log barrier [[ 1.  0.]
 [-1.  0.]
 [ 0.  1.]] [   0. -200.0.]
Simulation 1
x0 [1.035066856592987  1022.443240712164652]
[  1.037245769846418e+00   2.041876765235998e+03] 1.24717371552 743 1722 0 0
None Log barrier [[ 1.  0.]
 [-1.  0.]
 [ 0.  1.]] [   0. -200.0.]
Simulation 2
x0 [1.035066856592987  1022.443240712164652]
[  1.037824582507327e+00   2.047667399532010e+03] 4.2070590787 738 1675 0 0
None Log barrier [[ 1.  0.]
 [-1.  0.]
 [ 0.  1.]] [   0. -200.0.]
Simulation 3



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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #7, bug #22554 (project relax):

Something weird is happening:

relax minimise.execute(min_algor='simplex', line_search=None,
hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None,
max_iter=1000, constraints=True, scaling=True, verbosity=0)
Resetting the minimisation statistics.
None [921.558089761, 748.6864, 553.35411824, 496.3042145605,
360.04328976]
[1.035066857518701  1022.4432409176693  ] 0.245202137454 824 1886 0 0 None
Log barrier [[ 1.  0.]
 [-1.  0.]
 [ 0.  1.]] [   0. -200.0.]

relax relax_disp.plot_exp_curves(file='tmpk97wh8', dir='/tmp', force=True,
norm=True)
Opening the file '/tmp/tmpk97wh8' for writing.
Grace intensity file is: /tmp/tmpk97wh8 in /tmp for file tmpk97wh8

relax monte_carlo.setup(number=3)

relax monte_carlo.create_data(method='back_calc')

relax monte_carlo.initial_values()

relax minimise.execute(min_algor='simplex', line_search=None,
hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None,
max_iter=1000, constraints=True, scaling=True, verbosity=1)
0 [1834.4491491416306, 1499.1489275070198, 1095.6716334946577,
976.5259731096135, 722.563060550292]
[  1.040684047922508e+00   2.039705568780987e+03] 1.49429853793 758 1773 0 0
None Log barrier [[ 1.  0.]
 [-1.  0.]
 [ 0.  1.]] [   0. -200.0.]
Simulation 1
1 [1852.4875603169571, 1499.1457457370575, 1110.1771381462654,
993.2545336219156, 735.9938965401652]
[  1.028974809246774e+00   2.049155739845578e+03] 1.07542416653 788 1759 0 0
None Log barrier [[ 1.  0.]
 [-1.  0.]
 [ 0.  1.]] [   0. -200.0.]
Simulation 2
2 [1835.5770994281788, 1495.4938169679149, 1120.8445034726096,
1003.99837753052, 721.8551762167374]
[  1.016225469398227e+00   2.033590055983061e+03] 4.61464104601 778 1749 0 0
None Log barrier [[ 1.  0.]
 [-1.  0.]
 [ 0.  1.]] [   0. -200.0.]
Simulation 3


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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #8, bug #22554 (project relax):

SIGH.

It just take one line of code to ruin it all.
This is a else if statement going wrong.

# Loop over the replicates.
for i in range(len(int_keys)):
# Simulation intensity data.
if sim_index != None:
# Error checking.
if not int_keys[i] in spin.peak_intensity_sim:
raise RelaxError(The peak intensity simulation data is missing
the key '%s'. % int_keys[i])

# Sum.
intensity += spin.peak_intensity_sim[int_keys[i]][sim_index]
print spin.peak_intensity_sim[int_keys[i]][sim_index]

# Error intensity data.
if error:
# Error checking.
if not hasattr(spin, 'peak_intensity_err') or not int_keys[i] in
spin.peak_intensity_err:
raise RelaxError(The peak intensity errors are missing the key
'%s'. % int_keys[i])

# Sum.
intensity += spin.peak_intensity_err[int_keys[i]]**2

# Normal intensity data.
else:
# Error checking.
if not int_keys[i] in spin.peak_intensity:
raise RelaxError(The peak intensity data is missing the key
'%s'. % int_keys[i])

# Sum.
intensity += spin.peak_intensity[int_keys[i]]
print spin.peak_intensity[int_keys[i]]

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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Update of bug #22554 (project relax):

 Open/Closed:Open = Closed 


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[bug #22552] Chi2 value returned from C-code Curve-fitting return 0.0 for wrong parameters - Expected influence on Monte-Carlo sim

[Troels E. Linnet]

Update of bug #22552 (project relax):

  Status:   Need Info = Invalid
 Open/Closed:Open = Closed 

___

Follow-up Comment #3:

This is invalid.

exp(x) in C-code gives inf values for extreme values of x.

This should be handled in minfx.

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[bug #22554] The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected.

[Troels E. Linnet]

Follow-up Comment #13, bug #22554 (project relax):

This is how it looks after getting fixed.

(file #21979, file #21980)
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Additional Item Attachment:

File name: figure_1.png   Size:43 KB
File name: figure_2.png   Size:46 KB


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[task #7822] Implement user function to estimate R2eff and associated errors for exponential curve fitting.

[Troels E. Linnet]

Update of task #7822 (project relax):

  Status: In Progress = Completed  
Percent Complete:  0% = 100%   
 Open/Closed:Open = Closed 
  Effort:0.00 = 100


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[bug #22461] NS R1rho 2-site_fit_r1 has extremely high chi2 value in systemtest Relax_disp.test_r1rho_kjaergaard_missing_r1

[Troels E. Linnet]

Update of bug #22461 (project relax):

  Status: In Progress = Fixed  
 Assigned to:None = tlinnet
 Open/Closed:Open = Closed 

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Follow-up Comment #18:

This is now complete.

The error was a wrong passing of time point to the target function.

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[bug #22540] The Relax Controller does not follow output when doing Monte-Carlo simulations.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22540

 Summary: The Relax Controller does not follow output when
doing Monte-Carlo simulations.
 Project: relax
Submitted by: tlinnet
Submitted on: Thu 28 Aug 2014 12:28:17 PM UTC
Category: relax's source code
Specific analysis category: None
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: Mac OS X

___

Details:

Hi Edward.

I just tried running the GUI.

When the analysis is done, and Monte Carlo simulations is performed, the
Relax Controller does not follow the output.

It is not a bug problem, but hard to see if something new is happening.

Best

See:
http://thread.gmane.org/gmane.science.nmr.relax.devel/6892




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[bug #22540] The Relax Controller does not follow output when doing Monte-Carlo simulations.

[Troels E. Linnet]

Follow-up Comment #1, bug #22540 (project relax):

The Controllor actually totally blocks up the whole view of the system when
running.

On Linux, there is Grey boxes, and everything gets blocked.

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[bug #22541] The R1 fit flag does not work in the GUI.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22541

 Summary: The R1 fit flag does not work in the GUI.
 Project: relax
Submitted by: tlinnet
Submitted on: Thu 28 Aug 2014 12:41:51 PM UTC
Category: None
Specific analysis category: None
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: None

___

Details:

How to reproduce.

1) Go to:
relax_trunk/test_suite/shared_data/dispersion/Kjaergaard_et_al_2013

2) Start relax
relax -g

3) Start Relaxation dispersion analysis.

4) User function. script
Open: 1_setup_r1rho_GUI.py

5) User function: deselect.all

6) User function: select.spin ':52@N'

7) Model: R2eff, No Rex, DPL94

6) Set 10 MC for both exp and model

7) Toogle R1 fit

8) Execute

relax minimise.grid_search(lower=None, upper=None, inc=21, verbosity=1,
constraints=True, skip_preset=True)
Exception raised in thread.

Traceback (most recent call last):
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/execute.py,
line 87, in run
self.run_analysis()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/auto_relax_disp.py,
line 725, in run_analysis
Relax_disp(pipe_name=self.data.pipe_name,
pipe_bundle=self.data.pipe_bundle, results_dir=self.data.save_dir,
models=self.data.models, grid_inc=self.data.inc,
mc_sim_num=self.data.mc_sim_num, exp_mc_sim_num=self.data.exp_mc_sim_num,
pre_run_dir=self.data.pre_run_dir,
mc_sim_all_models=self.data.mc_sim_all_models,
insignificance=self.data.insignificance, numeric_only=self.data.numeric_only,
r1_fit=self.data.r1_fit)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/auto_analyses/relax_disp.py,
line 136, in __init__
self.run()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/auto_analyses/relax_disp.py,
line 627, in run
self.optimise(model=model, model_path=model_path)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/auto_analyses/relax_disp.py,
line 411, in optimise
self.interpreter.minimise.grid_search(inc=self.grid_inc)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/prompt/uf_objects.py, line
223, in __call__
self._backend(*new_args, **uf_kargs)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/minimise.py,
line 171, in grid_search
model_lower, model_upper, model_inc = grid_setup(lower, upper, inc,
verbosity=verbosity, skip_preset=skip_preset)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/minimise.py,
line 248, in grid_setup
values = api.get_param_values(model_info)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/specific_analyses/relax_disp/api.py,
line 463, in get_param_values
values.append(get_value(spins=spins, sim_index=sim_index,
param_name=param_name, spin_index=si, r20_key=r20_key))
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/specific_analyses/relax_disp/parameters.py,
line 393, in get_value
obj = getattr(spins[spin_index], param_name)
AttributeError: 'SpinContainer' object has no attribute 'r1'




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[bug #22542] NS R1rho 2-site seems to be wrong implemented.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22542

 Summary: NS R1rho 2-site seems to be wrong implemented.
 Project: relax
Submitted by: tlinnet
Submitted on: Thu 28 Aug 2014 01:22:12 PM UTC
Category: None
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Branches
 Discussion Lock: Any
Operating System: All systems

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Details:

See http://thread.gmane.org/gmane.science.nmr.relax.devel/6594




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[task #7822] Implement user function to estimate R2eff and associated errors for exponential curve fitting.

[Troels E. Linnet]

URL:
  http://gna.org/task/?7822

 Summary: Implement user function to estimate R2eff and
associated errors for exponential curve fitting.
 Project: relax
Submitted by: tlinnet
Submitted on: Sun 24 Aug 2014 03:56:36 PM UTC
 Should Start On: Sun 24 Aug 2014 12:00:00 AM UTC
   Should be Finished on: Sun 24 Aug 2014 12:00:00 AM UTC
Category: relax's source code
Priority: 5 - Normal
  Status: In Progress
Percent Complete: 0%
 Assigned to: tlinnet
 Open/Closed: Open
 Discussion Lock: Any
  Effort: 0.00

___

Details:

A verification script, showed that using scipy.optimize.leastsq reaches the
exact same parameters as minfx for exponential curve fitting.

The verification script is in:
test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py
test_suite/shared_data/curve_fitting/profiling/verify_error.py

The profiling script shows that a 10 X increase in speed can be reached by
removing
the linear constraints when using minfx.

The profiling also shows that scipy.optimize.leastsq is 10X as fast as using
minfx, even without linear constraints.

scipy.optimize.leastsq is a wrapper around wrapper around MINPACK's lmdif and
lmder algorithms.

MINPACK is a FORTRAN90 library which solves systems of nonlinear equations, or
carries out the least squares minimization of the residual of a set of linear
or nonlinear equations.

 The verification script also shows, that a very heavy and time consuming
monte carlo simulation of 2000 steps, reaches the same errors as the errors
reported by scipy.optimize.leastsq.

The return from scipy.optimize.leastsq, gives the estimated co-variance.
Taking the square root of the co-variance corresponds with 2X error reported
by minfx after 2000 Monte-Carlo simulations.

This could be an extremely time saving step, when performing model fitting in
R1rho, where the errors of the R2eff values, are estimated by Monte-Carlo
simulations.

The following setup illustrates the problem.
This was analysed on a: MacBook Pro, 13-inch, Late 2011.
With no multi-core setup.

Script running is:
test_suite/shared_data/dispersion/Kjaergaard_et_al_2013/2_pre_run_r2eff.py

This script analyses just the R2eff values for 15 residues.
It estimates the errors of R2eff based on 2000 Monte Carlo simulations.
For each residues, there is 14 exponential graphs.

The script was broken after 35 simulations.
This was measured to 20 minutes.
So 500 simulations would take about 4.8 Hours.

The R2eff values and errors can by scipy.optimize.leastsq can instead be
calculated in: 15 residues * 0.02 seconds = 0.3 seconds.




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[bug #22501] Close all analyses raises error

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22501

 Summary: Close all analyses raises error
 Project: relax
Submitted by: tlinnet
Submitted on: Thu 21 Aug 2014 03:39:22 PM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: 64-bit GNU/Linux

___

Details:

Clicking on:

Close all analyses raises an error.

How to reproduce:
 relax -g
 New Analysis
 Relaxation dispersion
 User functions. Results - read - results.bz
 Click Close all analyses


Traceback (most recent call last):
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 409, in menu_close_all
self.delete_all()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 193, in delete_all
self.delete_analysis(self._num_analyses-1)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 258, in delete_analysis
pipes.delete(pipe)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/pipes.py, line
283, in delete
status.observers.pipe_alteration.notify()
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/status.py, line 417,
in notify
self._callback[key]()
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/controller.py,
line 399, in update_controller
name = self.gui.analysis.current_analysis_name()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 149, in current_analysis_name
return ds.relax_gui.analyses[self._current].analysis_name
IndexError: list index out of range




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[bug #22501] Close all analyses raises error

[Troels E. Linnet]

Follow-up Comment #1, bug #22501 (project relax):

If one starts an auto analyses.

Set something up.
Closes all, and then start a new:

Traceback (most recent call last):
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 409, in menu_close_all
self.delete_all()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 193, in delete_all
self.delete_analysis(self._num_analyses-1)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 258, in delete_analysis
pipes.delete(pipe)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/pipes.py, line
283, in delete
status.observers.pipe_alteration.notify()
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/status.py, line 417,
in notify
self._callback[key]()
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/controller.py,
line 399, in update_controller
name = self.gui.analysis.current_analysis_name()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 149, in current_analysis_name
return ds.relax_gui.analyses[self._current].analysis_name
IndexError: list index out of range
Traceback (most recent call last):
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 438, in menu_new
self.new_analysis(analysis_type, analysis_name, pipe_name, pipe_bundle,
uf_exec)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 510, in new_analysis
analysis = classes[analysis_type](parent=self.notebook, id=-1,
gui=self.gui, analysis_name=analysis_name, pipe_name=pipe_name,
pipe_bundle=pipe_bundle, uf_exec=uf_exec, data_index=index)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/auto_relax_disp.py,
line 102, in __init__
self.gui.interpreter.apply('pipe.create', pipe_name=pipe_name,
pipe_type='relax_disp', bundle=pipe_bundle)
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/interpreter.py,
line 109, in apply
apply(fn, args, kwds)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/pipes.py, line
192, in create
ds.add(pipe_name=pipe_name, pipe_type=pipe_type, bundle=bundle,
switch=switch)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/data_store/__init__.py,
line 386, in add
status.observers.pipe_alteration.notify()
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/status.py, line 417,
in notify
self._callback[key]()
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/controller.py,
line 399, in update_controller
name = self.gui.analysis.current_analysis_name()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 149, in current_analysis_name
return ds.relax_gui.analyses[self._current].analysis_name
IndexError: list index out of range

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[bug #22501] Close all analyses raises error

[Troels E. Linnet]

Follow-up Comment #2, bug #22501 (project relax):

To reproduce:

 relax -g
 New Analysis
 Relaxation dispersion
 Click Close all analyses 

Traceback (most recent call last):
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 409, in menu_close_all
self.delete_all()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 193, in delete_all
self.delete_analysis(self._num_analyses-1)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 258, in delete_analysis
pipes.delete(pipe)
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/pipes.py, line
283, in delete
status.observers.pipe_alteration.notify()
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/status.py, line 417,
in notify
self._callback[key]()
  File /sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/controller.py,
line 399, in update_controller
name = self.gui.analysis.current_analysis_name()
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/gui/analyses/__init__.py,
line 149, in current_analysis_name
return ds.relax_gui.analyses[self._current].analysis_name
IndexError: list index out of range


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[sr #3121] Support request for replacing space in header files for the value.write functions

[Troels E. Linnet]

Update of sr #3121 (project relax):

 Open/Closed:  Closed = Open   

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Follow-up Comment #5:

It seems, that something is broken when writing out files.

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[sr #3121] Support request for replacing space in header files for the value.write functions

[Troels E. Linnet]

Update of sr #3121 (project relax):

 Open/Closed:Open = Closed 


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[bug #22477] Not possible to perform grace.write() on k_AB parameter for mixed CPMG analysis.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22477

 Summary: Not possible to perform grace.write() on k_AB
parameter for mixed CPMG analysis.
 Project: relax
Submitted by: tlinnet
Submitted on: Fri 15 Aug 2014 01:48:36 PM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

Issuing:
grace.write(x_data_type='res_num', y_data_type=param)

  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/grace.py, line
274, in write
write_xy_data(data, file=file, graph_type=graph_type, norm=[norm])
  File
/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/lib/software/grace.py, line
181, in write_xy_data
error = point[2]

This is possible because, that the final round can have a mix of model CR72
and TSMFK01, where the Monte-Carlo simulations is only estimated for TSMK01,
and k_AB is calculated for CR72.




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[bug #22477] Not possible to perform grace.write() on k_AB parameter for mixed CPMG analysis.

[Troels E. Linnet]

Update of bug #22477 (project relax):

  Status:None = Fixed  
 Assigned to:None = tlinnet
 Open/Closed:Open = Closed 

___

Follow-up Comment #3:

If there is no error point, set it to None, and thereby 0.0.

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[bug #22470] value.set does not work for parameter r1_fit

[Troels E. Linnet]

Update of bug #22470 (project relax):

  Status:None = Fixed  
 Assigned to:None = tlinnet
 Open/Closed:Open = Closed 


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[bug #22470] value.set does not work for parameter r1_fit

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22470

 Summary: value.set does not work for parameter r1_fit
 Project: relax
Submitted by: tlinnet
Submitted on: Thu 14 Aug 2014 09:17:39 AM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

This will tricker an error, when using GRID_INC=None




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[sr #3135] Optimisation of the R1 relaxation rate for the off-resonance R1rho relaxation dispersion models.

[Troels E. Linnet]

Update of sr #3135 (project relax):

  Status:   Postponed = Done   
 Assigned to:None = tlinnet
 Open/Closed:Open = Closed 


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[bug #22440] The NOREX model is not covering R1rho models.

[Troels E. Linnet]

Update of bug #22440 (project relax):

  Status:None = Fixed  
 Assigned to:None = tlinnet
 Open/Closed:Open = Closed 


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[bug #22461] NS R1rho 2-site_fit_r1 has extremely high chi2 value in systemtest Relax_disp.test_r1rho_kjaergaard_missing_r1

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22461

 Summary: NS R1rho 2-site_fit_r1 has extremely high chi2 value
in systemtest Relax_disp.test_r1rho_kjaergaard_missing_r1
 Project: relax
Submitted by: tlinnet
Submitted on: Tue 12 Aug 2014 09:17:34 AM UTC
Category: None
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 4 - Important
  Status: In Progress
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

In systemtest Relax_disp.test_r1rho_kjaergaard_missing_r1

The model:
NS R1rho 2-site_fit_r1

has extremely high chi2 value. 




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[bug #22461] NS R1rho 2-site_fit_r1 has extremely high chi2 value in systemtest Relax_disp.test_r1rho_kjaergaard_missing_r1

[Troels E. Linnet]

Follow-up Comment #2, bug #22461 (project relax):

This error can be triggered by:

relax -s Relax_disp.test_r1rho_kjaergaard_missing_r1 --numpy-raise -d

The error is:
.
  File /Users/tlinnet/software/R1_fitting/target_functions/relax_disp.py,
line 314, in __init__
self.inv_relax_times[ei, si, mi, :] = 1.0 / relax_time
FloatingPointError: divide by zero encountered in double_scalars

The time reported is: [[ 0.]]
This is a division error with 0.0.

This is strange, since the print of time is:
in: specific_analyses/relax_disp/optimisation.py, line 561
print self.relax_times : [[ 0.]]
print cdp.relax_time_list : [0.0, 0.04, 0.1, 0.14, 0.2, 0.4]

The problem resides in:
specific_analyses/relax_disp/data.py in function 'return_r2eff_arrays()'.

The relax times is expected to have indices [ei][mi].

A print ei, mi, oi, di, relax_time in line 4392 in data.py shows:
0 0 0 0 0.0
0 0 0 0 0.04
0 0 0 0 0.1
0 0 0 0 0.2
0 0 0 1 0.0
0 0 0 1 0.04
0 0 0 1 0.1
0 0 0 1 0.2
0 0 0 1 0.4
0 0 0 2 0.0
0 0 0 2 0.04
0 0 0 2 0.1
0 0 0 2 0.2
0 0 0 2 0.4
0 0 0 2 0.0
0 0 0 2 0.04
0 0 0 2 0.1
0 0 0 2 0.2
0 0 0 2 0.4
0 0 0 2 0.0
0 0 0 2 0.04
0 0 0 2 0.1
0 0 0 2 0.2
0 0 0 2 0.4
0 0 0 3 0.0
0 0 0 3 0.04
0 0 0 3 0.1
0 0 0 3 0.2
0 0 0 3 0.4
0 0 0 4 0.0
0 0 0 4 0.04
0 0 0 4 0.1
0 0 0 4 0.2
0 0 0 4 0.4
0 0 0 4 0.0
0 0 0 4 0.04
0 0 0 4 0.1
0 0 0 4 0.2
0 0 0 4 0.4
0 0 0 4 0.0
0 0 0 4 0.04
0 0 0 4 0.1
0 0 0 4 0.2
0 0 0 4 0.4
0 0 0 4 0.0
0 0 0 4 0.04
0 0 0 4 0.1
0 0 0 4 0.2
0 0 0 4 0.4
0 0 0 4 0.0
0 0 0 4 0.04
0 0 0 4 0.1
0 0 0 4 0.2
0 0 0 4 0.4
0 0 0 4 0.0
0 0 0 4 0.04
0 0 0 4 0.1
0 0 0 4 0.2
0 0 0 4 0.4
0 0 0 5 0.0
0 0 0 5 0.04
0 0 0 5 0.1
0 0 0 5 0.14
0 0 0 5 0.2
0 0 0 5 0.0
0 0 0 5 0.04
0 0 0 5 0.1
0 0 0 5 0.14
0 0 0 5 0.2
0 0 1 0 0.0
0 0 1 0 0.04
0 0 1 0 0.1
0 0 1 0 0.2
0 0 1 0 0.4
0 0 1 0 0.0
0 0 1 0 0.04
0 0 1 0 0.1
0 0 1 0 0.2
0 0 1 0 0.4
0 0 1 0 0.0
0 0 1 0 0.04
0 0 1 0 0.1
0 0 1 0 0.2
0 0 1 0 0.4
0 0 1 0 0.0
0 0 1 0 0.04
0 0 1 0 0.1
0 0 1 0 0.2
0 0 1 0 0.4
0 0 1 0 0.0
0 0 1 0 0.04
0 0 1 0 0.1
0 0 1 0 0.2
0 0 1 0 0.4
0 0 1 0 0.0
0 0 1 0 0.04
0 0 1 0 0.1
0 0 1 0 0.2
0 0 1 0 0.4
0 0 2 0 0.0
0 0 2 0 0.04
0 0 2 0 0.1
0 0 2 0 0.2
0 0 2 0 0.4
0 0 2 0 0.0
0 0 2 0 0.04
0 0 2 0 0.1
0 0 2 0 0.2
0 0 2 0 0.4
0 0 2 0 0.0
0 0 2 0 0.04
0 0 2 0 0.1
0 0 2 0 0.2
0 0 2 0 0.4
0 0 2 1 0.0
0 0 2 1 0.04
0 0 2 1 0.1
0 0 2 1 0.2
0 0 2 1 0.4
0 0 2 1 0.0
0 0 2 1 0.04
0 0 2 1 0.1
0 0 2 1 0.2
0 0 2 1 0.4
0 0 2 1 0.0
0 0 2 1 0.04
0 0 2 1 0.1
0 0 2 1 0.2
0 0 2 1 0.4
0 0 2 1 0.0
0 0 2 1 0.04
0 0 2 1 0.1
0 0 2 1 0.2
0 0 2 1 0.4
0 0 2 1 0.0
0 0 2 1 0.04
0 0 2 1 0.1
0 0 2 1 0.2
0 0 2 1 0.4
0 0 2 1 0.0
0 0 2 1 0.04
0 0 2 1 0.1
0 0 2 1 0.2
0 0 2 1 0.4
0 0 2 2 0.0
0 0 2 2 0.04
0 0 2 2 0.1
0 0 2 2 0.14
0 0 2 2 0.2
0 0 2 2 0.0
0 0 2 2 0.04
0 0 2 2 0.1
0 0 2 2 0.14
0 0 2 2 0.2
0 0 3 0 0.0
0 0 3 0 0.04
0 0 3 0 0.1
0 0 3 0 0.2
0 0 3 0 0.4
0 0 3 0 0.0
0 0 3 0 0.04
0 0 3 0 0.1
0 0 3 0 0.2
0 0 3 0 0.4
0 0 3 0 0.0
0 0 3 0 0.04
0 0 3 0 0.1
0 0 3 0 0.2
0 0 3 0 0.4
0 0 3 1 0.0
0 0 3 1 0.04
0 0 3 1 0.1
0 0 3 1 0.2
0 0 3 1 0.4
0 0 3 1 0.0
0 0 3 1 0.04
0 0 3 1 0.1
0 0 3 1 0.2
0 0 3 1 0.4
0 0 3 1 0.0
0 0 3 1 0.04
0 0 3 1 0.1
0 0 3 1 0.2
0 0 3 1 0.4
0 0 3 1 0.0
0 0 3 1 0.04
0 0 3 1 0.1
0 0 3 1 0.2
0 0 3 1 0.4
0 0 3 1 0.0
0 0 3 1 0.04
0 0 3 1 0.1
0 0 3 1 0.2
0 0 3 1 0.4
0 0 3 1 0.0
0 0 3 1 0.04
0 0 3 1 0.1
0 0 3 1 0.2
0 0 3 1 0.4
0 0 4 0 0.0
0 0 4 0 0.04
0 0 4 0 0.1
0 0 4 0 0.2
0 0 4 0 0.4
0 0 4 0 0.0
0 0 4 0 0.04
0 0 4 0 0.1
0 0 4 0 0.2
0 0 4 0 0.4
0 0 4 0 0.0
0 0 4 0 0.04
0 0 4 0 0.1
0 0 4 0 0.2
0 0 4 0 0.4
0 0 4 0 0.0
0 0 4 0 0.04
0 0 4 0 0.1
0 0 4 0 0.2
0 0 4 0 0.4
0 0 4 0 0.0
0 0 4 0 0.04
0 0 4 0 0.1
0 0 4 0 0.2
0 0 4 0 0.4
0 0 4 0 0.0
0 0 4 0 0.04
0 0 4 0 0.1
0 0 4 0 0.2
0 0 4 0 0.4
0 0 5 0 0.0
0 0 5 0 0.04
0 0 5 0 0.1
0 0 5 0 0.2
0 0 5 0 0.4
0 0 5 0 0.0
0 0 5 0 0.04
0 0 5 0 0.1
0 0 5 0 0.2
0 0 5 0 0.4
0 0 5 0 0.0
0 0 5 0 0.04
0 0 5 0 0.1
0 0 5 0 0.2
0 0 5 0 0.4
0 0 5 0 0.0
0 0 5 0 0.04
0 0 5 0 0.1
0 0 5 0 0.2
0 0 5 0 0.4
0 0 5 0 0.0
0 0 5 0 0.04
0 0 5 0 0.1
0 0 5 0 0.2
0 0 5 0 0.4
0 0 5 0 0.0
0 0 5 0 0.04
0 0 5 0 0.1
0 0 5 0 0.2
0 0 5 0 0.4

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[bug #22440] The NOREX model is not covering R1rho models.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22440

 Summary: The NOREX model is not covering R1rho models.
 Project: relax
Submitted by: tlinnet
Submitted on: Mon 04 Aug 2014 10:14:05 AM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 7 - High
Severity: 4 - Important
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

The NOREX model is not covering R1rho models.

The target function for NOREX is calculated as:

back_calc = R20

R20 is for R1hro models equivalent to R1rho prime (R1rho'), which for example
in the model of DPL94 would mean:

R1rho = R1rho'

But for the NOREX case, the return should be

R1rho = R1 * cos^2(theta) + (R1rho' + 0) * sin^2(theta)

This affects all off-resonance model calculations.




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[task #7816] Document the relax_disp.plot_disp_curves() with the new R1rho graphs.

[Troels E. Linnet]

URL:
  http://gna.org/task/?7816

 Summary: Document the relax_disp.plot_disp_curves() with the
new R1rho graphs.
 Project: relax
Submitted by: tlinnet
Submitted on: Sat 02 Aug 2014 08:38:41 AM UTC
 Should Start On: Sat 02 Aug 2014 12:00:00 AM UTC
   Should be Finished on: Sat 02 Aug 2014 12:00:00 AM UTC
Category: Documentation
Priority: 3 - Low
  Status: Postponed
Percent Complete: 0%
 Assigned to: tlinnet
 Open/Closed: Open
 Discussion Lock: Any
  Effort: 0.00

___

Details:

Graphs are ready at:

test_suite/shared_data/dispersion/Kjaergaard_et_al_2013/check_graphs/mc_2000/final/

The question where this should reside in the manual:

In:
The basics - Introduction - Data visualisation
http://www.nmr-relax.com/manual/Data_visualisation.html

Or:
The specific analyses - Relaxation dispersion - Relaxation dispersion data
visualisation






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[bug #21788] Only Warning is raised for missing loading R1 relaxation rate for the off-resonance R1rho relaxation dispersion models.

[Troels E. Linnet]

Update of bug #21788 (project relax):

  Status:   Confirmed = Fixed  
 Assigned to:None = tlinnet
 Open/Closed:Open = Closed 
 Release:   3.1.6 = Repository: trunk  

___

Follow-up Comment #5:

This is now fixed.

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[bug #22408] Failing system tests for Model-Free analysis.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22408

 Summary: Failing system tests for Model-Free analysis.
 Project: relax
Submitted by: tlinnet
Submitted on: Wed 30 Jul 2014 06:29:19 PM UTC
Category: Test suite
Specific analysis category: Model-free analysis
Priority: 3 - Low
Severity: 1 - Wish
  Status: None
 Assigned to: None
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: 64-bit GNU/Linux

___

Details:

Following systemtest fail on my system.

E 0.30 s for Mf.test_bugs_12582_12591_12607
E75.77 s for Mf.test_omp_analysis
E 0.05 s for Mf.test_tylers_peptide

They are all related to:
UnboundLocalError: local variable 'min_params' referenced before assignment

Mf.test_bugs_12582_12591_12607
  File
/Users/tlinnet/software/relax_trunk/specific_analyses/model_free/optimisation.py,
line 602, in run
results = self.optimise()
  File
/Users/tlinnet/software/relax_trunk/specific_analyses/model_free/optimisation.py,
line 648, in optimise
results = grid_point_array(func=self.mf.func, args=(),
points=self.opt_params.subdivision, verbosity=self.opt_params.verbosity)
  File
/Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/minfx/grid.py,
line 376, in grid_point_array
return min_params, f_min, total_steps, None
UnboundLocalError: local variable 'min_params' referenced before assignment



Mf.test_omp_analysis
  File /Users/tlinnet/software/relax_trunk/multi/uni_processor.py, line 186,
in run_queue
command.run(self, completed)
  File
/Users/tlinnet/software/relax_trunk/specific_analyses/model_free/optimisation.py,
line 602, in run
results = self.optimise()
  File
/Users/tlinnet/software/relax_trunk/specific_analyses/model_free/optimisation.py,
line 648, in optimise
results = grid_point_array(func=self.mf.func, args=(),
points=self.opt_params.subdivision, verbosity=self.opt_params.verbosity)
  File
/Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/minfx/grid.py,
line 376, in grid_point_array
return min_params, f_min, total_steps, None
UnboundLocalError: local variable 'min_params' referenced before assignment




___

File Attachments:


---
Date: Wed 30 Jul 2014 06:29:19 PM UTC  Name: relax_info.txt  Size: 7kB   By:
tlinnet

http://gna.org/bugs/download.php?file_id=21598
---
Date: Wed 30 Jul 2014 06:29:19 PM UTC  Name: log.txt  Size: 367kB   By:
tlinnet

http://gna.org/bugs/download.php?file_id=21599

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[bug #22409] Minimisation of R1rho model give random results

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22409

 Summary: Minimisation of R1rho model give random results
 Project: relax
Submitted by: tlinnet
Submitted on: Wed 30 Jul 2014 09:21:29 PM UTC
Category: relax's source code
Specific analysis category: Relaxation dispersion
Priority: 5 - Normal
Severity: 4 - Important
  Status: None
 Assigned to: bugman
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

This was discussed in:
http://thread.gmane.org/gmane.science.nmr.relax.devel/6538


Systemtest Relax_disp.test_r1rho_kjaergaard_auto_check_graphs 
shows that the error value constantly are changing between each
run of analysis.

This is properly because the number of Monte-Carlo simulation is only set to
3.

This can sometimes happens if the base data are exponential curves, as then
the R2eff errors are determined by Monte Carlo simulations which are random. 


And because it is a test the number of simulations are low so the randomness
is quite large.  

This randomness will then be propagated into the higher models. 

Apart from the unique case of Monte Carlo simulations (or the unit tests for
a
few other functions which use the 'random' Python module), a test
should return the same result to machine precision every single time.
It must be identical.




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[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Follow-up Comment #486, task #7807 (project relax):

This development branch is now complete, and I ask for merge to trunk.

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[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Follow-up Comment #325, task #7807 (project relax):

Storage of idea: NS CPMG 2site 3d

Skipping of the spin lloop

# Loop over the spins
#for si in range(NS):
## Loop over the spectrometer frequencies.
for mi in range(NM):
# Extract number of points.
num_points_si_mi = int(num_points[0, 0, mi, 0])

# Loop over the time points, back calculating the R2eff values.
for di in range(num_points_si_mi):
# Extract the values from the higher dimensional arrays.
inv_tcpmg_si_mi_di = inv_tcpmg[0, 0, mi, 0, di]
power_si_mi_di = int(power[0, 0, mi, 0, di])
#r20a_si_mi_di = r20a[0, 0, mi, 0, di]

# Initial magnetisation.
Mint_i = Mint_mat[:, :, mi, Ellipsis]

# This matrix is a propagator that will evolve the magnetization
with the matrix R for a delay tcp.
evolution_matrix_i = evolution_matrix_mat[:, :, mi, Ellipsis]

# Loop over the CPMG elements, propagating the magnetisation.
for j in range(power_si_mi_di):
Mint_i = einsum('...ij,...jk', evolution_matrix_i, Mint_i)

# Store the result.
Mint_mat[:, :, mi, Ellipsis] =  Mint_i


print Mint_mat[:, :, :, :, :, 1, 0]
print asd

# The next lines calculate the R2eff using a two-point approximation, i.e.
assuming that the decay is mono-exponential.
#Mx = Mint_i[1][0] / pA
# Extract data from ei, si, mi, oi, di, the [1][0]
Mx = Mint_mat[:, :, :, :, :, 1, 0] / pA

mask_inv = masked_invalid(Mx)
if any(mask_inv.mask):
Mx[mask_inv.mask] = r20a[mask_inv.mask]

back_calc[:] = Mx


#if Mx = 0.0 or isNaN(Mx):
#back_calc[0, si, mi, 0, di] = r20a_si_mi_di
#else:
#back_calc[0, si, mi, 0, di] = - inv_tcpmg_si_mi_di * log(Mx)

# Replace data in array.
# If dw is zero.
if t_dw_zero:
back_calc[mask_dw_zero.mask] = r20a[mask_dw_zero.mask]

# 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(back_calc)):
# Replaces nan, inf, etc. with fill value.
fix_invalid(back_calc, copy=False, fill_value=1e100)

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[bug #22212] Plotting of graphs in disp speed branch is broken

[Troels E. Linnet]

Update of bug #22212 (project relax):

  Status:None = Fixed  
 Open/Closed:Open = Closed 

___

Follow-up Comment #1:

This has been fixed, where the target class now have a function:
get_back_calc()

which will return the data in the correct expected order.

This is the back and forth conversion between the data structures implemented
when gathering the data,
and the data send to the library function of higher dimensionality.

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[bug #22220] Unpacking of parameters for global analysis in model IT99, is performed wrong.

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?0

 Summary: Unpacking of parameters for global analysis in model
IT99, is performed wrong.
 Project: relax
Submitted by: tlinnet
Submitted on: Wed 18 Jun 2014 05:58:06 PM UTC
Category: None
Specific analysis category: None
Priority: 7 - High
Severity: 3 - Normal
  Status: None
 Assigned to: tlinnet
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Repository: trunk
 Discussion Lock: Any
Operating System: All systems

___

Details:

It is not possible to perform a global analysis with IT99.




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[bug #22220] Unpacking of parameters for global analysis in model IT99, is performed wrong.

[Troels E. Linnet]

Update of bug #0 (project relax):

 Open/Closed:Open = Closed 


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[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Update of task #7807 (project relax):

Percent Complete:  0% = 100%   
 Open/Closed:Open = Closed 
  Effort:0.00 = 100

___

Follow-up Comment #263:

This now complete.

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[task #7801] Design interface between the user and the functional code is to perform comprehensive checks of input

[Troels E. Linnet]

Update of task #7801 (project relax):

  Status:None = Cancelled  
 Open/Closed:Open = Closed 

___

Follow-up Comment #3:

Relax accepts calculating for missing spins.

This can happen, if you have data from several spectrometer frequencies, but
have not resolved all the spins for each experiment.

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[task #7800] Calculate dispersion alpha value.

[Troels E. Linnet]

Update of task #7800 (project relax):

  Status:None = Postponed  


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[task #3930] Create the GNU/Linux development platform web page

[Troels E. Linnet]

Update of task #3930 (project relax):

  Status:None = Completed  
Percent Complete:  0% = 100%   
 Assigned to:None = tlinnet
  Effort:0.00 = 100

___

Follow-up Comment #1:

This is now mostly featured at:

http://wiki.nmr-relax.com/Category:Installation

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[task #3930] Create the GNU/Linux development platform web page

[Troels E. Linnet]

Update of task #3930 (project relax):

 Open/Closed:Open = Closed 


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[bug #21788] Only Warning is raised for missing loading R1 relaxation rate for the off-resonance R1rho relaxation dispersion models.

[Troels E. Linnet]

Follow-up Comment #2, bug #21788 (project relax):

Hi Ed.

Can we add this feature?

Ideally, I would like to implement fitting of R1.
This could be done, if no R1 data is loaded ?

Best
Troels

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[bug #22212] Plotting of graphs in disp speed branch is broken

[Troels E. Linnet]

URL:
  http://gna.org/bugs/?22212

 Summary: Plotting of graphs in disp speed branch is broken
 Project: relax
Submitted by: tlinnet
Submitted on: Tue 17 Jun 2014 07:46:04 PM UTC
Category: None
Specific analysis category: None
Priority: 5 - Normal
Severity: 3 - Normal
  Status: None
 Assigned to: tlinnet
 Originator Name: 
Originator Email: 
 Open/Closed: Open
 Release: Branches
 Discussion Lock: Any
Operating System: None

___

Details:

Something is wrong with the plotting of data



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File Attachments:


---
Date: Tue 17 Jun 2014 07:46:04 PM UTC  Name: disp_1_N.png  Size: 9kB   By:
tlinnet

http://gna.org/bugs/download.php?file_id=21070

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[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Follow-up Comment #72, task #7807 (project relax):

Timing now
Tue Jun 10 19:04:34 2014/tmp/tmpUgjuF0

 143893 function calls (143880 primitive calls) in 0.346 seconds

   Ordered by: cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.0000.3460.346 string:1(module)
10.0010.0010.3460.346 profiling_cr72.py:427(single)
 10000.0010.0000.3360.000 profiling_cr72.py:413(calc)
 10000.0080.0000.3350.000
relax_disp.py:992(func_CR72_full)
 10000.0240.0000.3230.000
relax_disp.py:526(calc_CR72_chi2)
 10030.0880.0000.2340.000 cr72.py:101(r2eff_CR72)
 20030.0340.0000.1190.000 numeric.py:2056(allclose)
100460.0510.0000.0510.000 {method 'reduce' of
'numpy.ufunc' objects}
 30000.0280.0000.0460.000 shape_base.py:761(tile)


   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.0001.5131.513 string:1(module)
10.0010.0011.5131.513 profiling_cr72.py:449(cluster)
 10000.0010.0001.4390.001 profiling_cr72.py:413(calc)
 10000.0100.0001.4380.001
relax_disp.py:992(func_CR72_full)
 10000.0520.0001.4200.001
relax_disp.py:526(calc_CR72_chi2)
 13000.9260.0011.2010.001 cr72.py:101(r2eff_CR72)
 23000.1000.0000.2220.000 numeric.py:2056(allclose)
 30000.0330.0000.1560.000 shape_base.py:761(tile)
 40000.1080.0000.1080.000 {method 'repeat' of
'numpy.ndarray' objects}
118280.0850.0000.0850.000 {method 'reduce' of
'numpy.ufunc' objects}
10.0000.0000.0730.073 profiling_cr72.py:106(__init__)
10.0120.0120.0570.057
profiling_cr72.py:173(return_r2eff_arrays)


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[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Follow-up Comment #56, task #7807 (project relax):

A 10x speed up on clustered analysis.


Checked on:
Hardware information:
Machine: x86_64
Processor:   x86_64
Processor name:  Intel(R) Core(TM) i5-3470 CPU @ 3.20GHz
Endianness:  little
Total RAM size:  3705 Mb
Total swap size: 3839 Mb

Operating system information:
System:  Linux
Release: 2.6.32-431.17.1.el6.x86_64
Version: #1 SMP Fri Apr 11 17:27:00 EDT 2014
GNU/Linux version:   Red Hat Enterprise Linux Client 6.5 Santiago
Distribution:redhat 6.5 Santiago
Full platform string:   
Linux-2.6.32-431.17.1.el6.x86_64-x86_64-with-redhat-6.5-Santiago


Timing for:
3 fields
('sfrq: ', 6.0, 'number of cpmg frq', 15, array([ 2., 6., 10., 14.,
18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58.])) 
('sfrq: ', 8.0, 'number of cpmg frq', 20, array([ 2., 6., 10., 14.,
18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58., 62., 66., 70., 74.,
78.])) 
('sfrq: ', 9.0, 'number of cpmg frq', 22, array([ 2., 6., 10., 14.,
18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58., 62., 66., 70., 74.,
78., 82., 86.])) 

iterations of function call: 1000

Timed for simulating 1 or 100 clustered spins.

##
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)


For disp_spin_speed r23759 #

1 spin:
10.0000.0000.4960.496 string:1(module)
10.0010.0010.4960.496 profiling_cr72.py:419(single)
 10000.0010.0000.4860.000 profiling_cr72.py:405(calc)
 10000.0090.0000.4850.000
relax_disp.py:995(func_CR72_full)
 10000.0380.0000.4720.000
relax_disp.py:524(calc_CR72_chi2)
 10030.0970.0000.3740.000 cr72.py:101(r2eff_CR72)
 40030.0710.0000.2420.000 numeric.py:2056(allclose)
160460.0810.0000.0810.000 {method 'reduce' of
'numpy.ufunc' objects}
 80150.0090.0000.0700.000 fromnumeric.py:1762(any)

100 spins:
10.0000.0002.0842.084 string:1(module)
10.0020.0022.0842.084 profiling_cr72.py:441(cluster)
 10000.0020.0002.0050.002 profiling_cr72.py:405(calc)
 10000.0340.0002.0030.002
relax_disp.py:995(func_CR72_full)
 10000.1410.0001.9600.002
relax_disp.py:524(calc_CR72_chi2)
 13001.1000.0011.6760.001 cr72.py:101(r2eff_CR72)
 43000.2450.0000.5070.000 numeric.py:2056(allclose)
 30000.0370.0000.1640.000 shape_base.py:761(tile)
178280.1260.0000.1260.000 {method 'reduce' of
'numpy.ufunc' objects}
 40000.1100.0000.1100.000 {method 'repeat' of
'numpy.ndarray' objects}
 86090.0110.0000.0860.000 fromnumeric.py:1762(any)



For trunk   r23753 #

1 spin:
10.0000.0000.3470.347 string:1(module)
10.0010.0010.3470.347 profiling_cr72.py:419(single)
 10000.0010.0000.3390.000 profiling_cr72.py:405(calc)
 10000.0080.0000.3380.000
relax_disp.py:908(func_CR72_full)
 10000.0320.0000.3260.000
relax_disp.py:456(calc_CR72_chi2)
 30030.1760.0000.2430.000 cr72.py:100(r2eff_CR72)
120360.0600.0000.0600.000 {method 'reduce' of
'numpy.ufunc' objects}
 30000.0250.0000.0490.000 chi2.py:32(chi2)
 60030.0080.0000.0480.000 fromnumeric.py:1621(sum)

100 spins:
10.0000.000   32.247   32.247 string:1(module)
10.0020.002   32.247   32.247 profiling_cr72.py:441(cluster)
 10000.0020.000   32.1960.032 profiling_cr72.py:405(calc)
 10000.0120.000   32.1940.032
relax_disp.py:908(func_CR72_full)
 10003.2910.003   32.1710.032
relax_disp.py:456(calc_CR72_chi2)
   300300   17.3610.000   23.8190.000 cr72.py:100(r2eff_CR72)
  12009275.7670.0005.7670.000 {method 'reduce' of
'numpy.ufunc' objects}
   302.5120.0004.8030.000 chi2.py:32(chi2)
   6003000.7500.0004.6360.000 fromnumeric.py:1621(sum)
   6003000.5900.0003.4100.000 _methods.py:23(_sum)
   3003000.2900.0002.1740.000 fromnumeric.py:2048(amax)
   3003000.2740.0001.9390.000 fromnumeric.py:2132(amin)


--

Python information:
Architecture:64bit ELF
Python version:  2.7.6
Python branch:   
Python build:default, Apr 11 2014 13:46:04
Python 

[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Follow-up Comment #12, task #7807 (project relax):

With the current implementation, the speed of a global analysis for 100 spins
is speeded up by a factor X2.

The unit tests though fail!

1000 iterations
100 spins
3 sfrq
('sfrq: ', 6.0, 'number of cpmg frq', 15, array([  2.,   6.,  10., 
14.,  18.,  22.,  26.,  30.,  34.,  38.,  42.,
46.,  50.,  54.,  58.]))
('sfrq: ', 8.0, 'number of cpmg frq', 20, array([  2.,   6.,  10., 
14.,  18.,  22.,  26.,  30.,  34.,  38.,  42.,
46.,  50.,  54.,  58.,  62.,  66.,  70.,  74.,  78.]))
('sfrq: ', 9.0, 'number of cpmg frq', 22, array([  2.,   6.,  10., 
14.,  18.,  22.,  26.,  30.,  34.,  38.,  42.,
46.,  50.,  54.,  58.,  62.,  66.,  70.,  74.,  78.,  82.,  86.]))
('chi2 cluster:', 0.0)

TRUNK
single spin
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.0000.5560.556 string:1(module)
10.0010.0010.5560.556 pf:418(single)
 10000.0020.0000.5480.001 pf:404(calc)
 10000.0070.0000.5460.001
relax_disp.py:908(func_CR72_full)
 10000.0520.0000.5330.001
relax_disp.py:456(calc_CR72_chi2)
 30030.3800.0000.4220.000 cr72.py:100(r2eff_CR72)
 30000.0410.0000.0560.000 chi2.py:32(chi2)

100 spins
10.0000.000   54.478   54.478 string:1(module)
10.0020.002   54.478   54.478 pf:440(cluster)
 10000.0040.000   54.3960.054 pf:404(calc)
 10000.0110.000   54.3920.054
relax_disp.py:908(func_CR72_full)
 10005.3040.005   54.3660.054
relax_disp.py:456(calc_CR72_chi2)
   300300   38.7330.000   43.0160.000 cr72.py:100(r2eff_CR72)
   304.1900.0005.7040.000 chi2.py:32(chi2)
   6003000.7000.0003.0290.000 fromnumeric.py:1379(sum)
   6003001.9310.0001.9310.000 {method 'sum' of 'numpy.ndarray'
objects}
   3003000.2670.0001.4630.000 fromnumeric.py:1774(amax)
   3003000.2380.0001.3050.000 fromnumeric.py:1836(amin)
   3003001.1960.0001.1960.000 {method 'max' of 'numpy.ndarray'
objects}
   3003001.0670.0001.0670.000 {method 'min' of 'numpy.ndarray'
objects}


NOW

single spin
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.0000.5910.591 string:1(module)
10.0010.0010.5910.591 pf:418(single)
 10000.0020.0000.5860.001 pf:404(calc)
 10000.0080.0000.5840.001
relax_disp.py:971(func_CR72_full)
 10000.1410.0000.5700.001
relax_disp.py:494(calc_CR72_chi2)
 10030.1390.0000.1860.000 cr72.py:101(r2eff_CR72)
170290.1840.0000.1840.000 {numpy.core.multiarray.array}
 30000.0420.0000.0570.000 chi2.py:32(chi2)
 10030.0300.0000.0470.000 numeric.py:1862(allclose)

100 spins
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.000   38.563   38.563 string:1(module)
10.0020.002   38.563   38.563 pf:440(cluster)
 10000.0040.000   38.4610.038 pf:404(calc)
 10000.0120.000   38.4570.038
relax_disp.py:971(func_CR72_full)
 1000   12.9070.013   38.4290.038
relax_disp.py:494(calc_CR72_chi2)
  1504108   18.2210.000   18.2210.000 {numpy.core.multiarray.array}
   304.0720.0005.5260.000 chi2.py:32(chi2)
 13001.2900.0011.4670.001 cr72.py:101(r2eff_CR72)
   300.3430.0001.4540.000 fromnumeric.py:1379(sum)
   300.9330.0000.9330.000 {method 'sum' of 'numpy.ndarray'
objects}
   5048180.3720.0000.3720.000 {range}
   300.1790.0000.1790.000 {isinstance}
 13000.1340.0000.1780.000 numeric.py:1862(allclose)

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[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Follow-up Comment #22, task #7807 (project relax):

System tests which fails

F20.55 s for Relax_disp.test_hansen_cpmg_data_missing_auto_analysis
F17.85 s for Relax_disp.test_sod1wt_t25_to_cr72

Checked on MacBook Pro
2.4 GHz Intel Core i5
8 GB 1067 Mhz DDR3 RAM.
Python Distribution -- Python 2.7.3 |EPD 7.3-2 (32-bit)| 

Timing for:
3 fields
('sfrq: ', 6.0, 'number of cpmg frq', 15, array([ 2., 6., 10., 14.,
18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58.])) 
('sfrq: ', 8.0, 'number of cpmg frq', 20, array([ 2., 6., 10., 14.,
18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58., 62., 66., 70., 74.,
78.])) 
('sfrq: ', 9.0, 'number of cpmg frq', 22, array([ 2., 6., 10., 14.,
18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58., 62., 66., 70., 74.,
78., 82., 86.])) 

iterations of function call: 1000

Timed for simulating 1 or 100 clustered spins.


For trunk: r23720


1 spin:
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.0000.5610.561 string:1(module)
10.0010.0010.5610.561 pf:419(single)
 10000.0020.0000.5570.001 pf:405(calc)
 10000.0080.0000.5540.001
relax_disp.py:908(func_CR72_full)
 10000.0530.0000.5410.001
relax_disp.py:456(calc_CR72_chi2)
 30030.3840.0000.4270.000 cr72.py:100(r2eff_CR72)
 30000.0420.0000.0570.000 chi2.py:32(chi2)


100 spins:
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.000   54.497   54.497 string:1(module)
10.0020.002   54.497   54.497 pf:441(cluster)
 10000.0040.000   54.4110.054 pf:405(calc)
 10000.0120.000   54.4070.054
relax_disp.py:908(func_CR72_full)
 10005.2410.005   54.3800.054
relax_disp.py:456(calc_CR72_chi2)
   300300   38.7430.000   43.0500.000 cr72.py:100(r2eff_CR72)
   304.2240.0005.7360.000 chi2.py:32(chi2)




For disp_spin_speed: r23739


1 spin:
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.0000.7940.794 string:1(module)
10.0010.0010.7930.793 pf:419(single)
 10000.0020.0000.7880.001 pf:405(calc)
 10000.0080.0000.7860.001
relax_disp.py:973(func_CR72_full)
 10000.1450.0000.7720.001
relax_disp.py:496(calc_CR72_chi2)
 10030.1630.0000.3760.000 cr72.py:101(r2eff_CR72)
230290.1950.0000.1950.000 {numpy.core.multiarray.array}
 40030.1230.0000.1890.000 numeric.py:1862(allclose)
 30000.0430.0000.0590.000 chi2.py:32(chi2)


100 spins:
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
10.0000.000   44.674   44.674 string:1(module)
10.0030.003   44.674   44.674 pf:441(cluster)
 10000.0040.000   44.5560.045 pf:405(calc)
 10000.0150.000   44.5510.045
relax_disp.py:973(func_CR72_full)
 1000   15.0910.015   44.5200.045
relax_disp.py:496(calc_CR72_chi2)
  1510108   20.4730.000   20.4730.000 {numpy.core.multiarray.array}
   304.7270.0006.4540.000 chi2.py:32(chi2)
 13001.4030.0012.1840.002 cr72.py:101(r2eff_CR72)

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[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Follow-up Comment #23, task #7807 (project relax):

The time spent in cr72.py goes from:

38.7430.000   43.0500.000 cr72.py:100(r2eff_CR72)
to
1.4030.0012.1840.002 cr72.py:101(r2eff_CR72).
This is awesome!

The time in:
5.2410.005   54.3800.054 relax_disp.py:456(calc_CR72_chi2)
15.0910.015   44.5200.045 relax_disp.py:496(calc_CR72_chi2)

This is triple time as much, which is probably related to the increased
looping, to get the disp point structures back.

The NEW time consumer is:
  1510108   20.4730.000   20.4730.000 {numpy.core.multiarray.array}.





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[task #7807] Speed-up of dispersion models for Clustered analysis

[Troels E. Linnet]

Follow-up Comment #24, task #7807 (project relax):

relax_disp_spin_speed -s
Relax_disp.test_hansen_cpmg_data_missing_auto_analysis --time -d

Optimised parameters:

ParameterValue (:4)   Value (:70)  Value (:71)

R2 (500 MHz) 1.60456873699084 6.97235130701478
4.98111647969012
R2 (800 MHz) 1.63225063409431 9.40988386796136  
0.0590835112910213
pA  0.5439095946687310.989856745034836   
0.996608013844177
dw   6.63536592789307e-13 5.60878828496508
4.34425685338434
kex  5.58192185204703e-09 1752.93345983946
1937.21776309767
chi2  26.735669529984 53.8382172686881
5.51703749012445

F17.18 s for Relax_disp.test_hansen_cpmg_data_missing_auto_analysis

==
FAIL: test_hansen_cpmg_data_missing_auto_analysis
(test_suite.system_tests.relax_disp.Relax_disp)
Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data
with parts missing.
--
Traceback (most recent call last):
  File
/Users/tlinnet/software/disp_spin_speed/test_suite/system_tests/relax_disp.py,
line 2237, in test_hansen_cpmg_data_missing_auto_analysis
self.assertAlmostEqual(spin4.pA, 0.899911303159742, 3)
AssertionError: 0.54390959466873079 != 0.899911303159742 within 3 places



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