Re: Model-Free Results Output

[Tyler R. <TR...@da...>]

Yes


Quoting Edward d'Auvergne <ed...@do...>:

> Oh, was this the minfx bug that was fixed?
>
>
> On Wed, Nov 5, 2008 at 9:30 PM, Tyler Reddy <TR...@da...> wrote:
>> I thought we already worked this one out?
>>
>>
>> Quoting Edward d'Auvergne <ed...@do...>:
>>
>>> Maybe this is again an edge case of an insanely difficult optimisation
>>> surface caused by underestimated errors.  I would recommend creating a
>>> bug report for this.  And if you could create a mini randomised data
>>> set which triggers this error (that could be added to the test suite
>>> as well), that would really help with the debugging the minfx code at
>>> the moment.
>>>
>>> Cheers,
>>>
>>> Edward
>>>
>>>
>>> On Fri, Oct 24, 2008 at 2:12 PM, Tyler Reddy <TR...@da...> wrote:
>>>> Thanks Seb.
>>>>
>>>> It looks like my 'prolate' iterations in the 2nd round are maxing out and
>>>> this
>>>> is causing an error output (even though the first round seemed okay):
>>>>
>>>>
>>>> k: 311     xk: array([  2.60992216e-11,   5.00000957e+02])
>>>>   fk: 2254.7254621187344
>>>> Entering sub-algorithm.
>>>>
>>>>       Newton minimisation
>>>>       ~~~~~~~~~~~~~~~~~~~
>>>>       Line search:  Backtracking line search.
>>>>       Hessian modification:  The Gill, Murray, and Wright modified 
>>>> Cholesky
>>>> algorithm.
>>>>
>>>>       k: 0       xk: array([  2.60992216e-11,   5.00000957e+02])
>>>>         fk: 2254.7254621187344
>>>>       k: 100     xk: array([  2.60992216e-11,   5.00000958e+02])
>>>>         fk: 2254.7254579164155
>>>>       k: 200     xk: array([  2.60992216e-11,   5.00000958e+02])
>>>>         fk: 2254.7254537140993
>>>>       k: 300     xk: array([  2.60992216e-11,   5.00000959e+02])
>>>>         fk: 2254.7254495117813
>>>>       k: 400     xk: array([  2.60992216e-11,   5.00000959e+02])
>>>>         fk: 2254.7254453094624
>>>>
>>>>       Parameter values: array([  2.60992216e-11,   5.00000960e+02])
>>>>       Function value:   2254.7254411071449
>>>>       Iterations:       500
>>>>       Function calls:   1001
>>>>       Gradient calls:   501
>>>>       Hessian calls:    500
>>>>       Warning:          Maximum number of iterations reached
>>>>
>>>>
>>>> k: 312     xk: array([  2.60992216e-11,   5.00000960e+02])
>>>>   fk: 2254.7254411071449
>>>> Entering sub-algorithm.
>>>>
>>>>       Newton minimisation
>>>>       ~~~~~~~~~~~~~~~~~~~
>>>>       Line search:  Backtracking line search.
>>>>       Hessian modification:  The Gill, Murray, and Wright modified 
>>>> Cholesky
>>>> algorithm.
>>>>
>>>>       k: 0       xk: array([  2.60992216e-11,   5.00000960e+02])
>>>>         fk: 2254.7254411071449
>>>>       k: 100     xk: array([  2.60992216e-11,   5.00000961e+02])
>>>>         fk: 2254.7254369048283
>>>>       k: 200     xk: array([  2.60992216e-11,   5.00000961e+02])
>>>>         fk: 2254.7254327025107
>>>>       k: 300     xk: array([  2.60992216e-11,   5.00000962e+02])
>>>>         fk: 2254.7254285001914
>>>>       k: 400     xk: array([  2.60992216e-11,   5.00000963e+02])
>>>>         fk: 2254.7254242978743
>>>>
>>>>       Parameter values: array([  2.60992216e-11,   5.00000963e+02])
>>>>       Function value:   2254.7254200955554
>>>>       Iterations:       500
>>>>       Function calls:   1001
>>>>       Gradient calls:   501
>>>>       Hessian calls:    500
>>>>       Warning:          Maximum number of iterations reached
>>>>
>>>>
>>>> Parameter values: array([  2.60992216e-11,   5.00000963e+02])
>>>> Function value:   2254.7254200955554
>>>> Iterations:       156500
>>>> Function calls:   313313
>>>> Gradient calls:   156813
>>>> Hessian calls:    156500
>>>> Warning:          Mu too small.
>>>>
>>>>
>>>>
>>>> Fitting to spin ':258&:LEU@N'
>>>> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>>>>
>>>>
>>>> Method of Multipliers
>>>> ~~~~~~~~~~~~~~~~~~~~~
>>>>
>>>> k: 0       xk: array([ 0.,  0.])
>>>>   fk: 3163.7013439706825
>>>> Entering sub-algorithm.
>>>>
>>>>       Newton minimisation
>>>>       ~~~~~~~~~~~~~~~~~~~
>>>>       Line search:  Backtracking line search.
>>>>       Hessian modification:  The Gill, Murray, and Wright modified 
>>>> Cholesky
>>>> algorithm.
>>>>
>>>>       k: 0       xk: array([ 0.,  0.])
>>>>         fk: 3163.7013439706825
>>>> Traceback (most recent call last):
>>>>  File "/Applications/relax-1.3.1/relax-1.3/relax", line 414, in <module>
>>>>   Relax()
>>>>  File "/Applications/relax-1.3.1/relax-1.3/relax", line 131, in __init__
>>>>   self.interpreter.run(self.script_file)
>>>>  File "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py", 
>>>> line 270,
>>>> in
>>>> run
>>>>   return run_script(intro=self.__intro_string, local=self.local,
>>>> script_file=script_file, quit=self.__quit_flag,
>>>> show_script=self.__show_script,
>>>> raise_relax_error=self.__raise_relax_error)
>>>>  File "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py", 
>>>> line 531,
>>>> in
>>>> run_script
>>>>   return console.interact(intro, local, script_file, quit,
>>>> show_script=show_script, raise_relax_error=raise_relax_error)
>>>>  File "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py", 
>>>> line 427,
>>>> in
>>>> interact_script
>>>>   execfile(script_file, local)
>>>>  File "full_analysis.py", line 673, in <module>
>>>>   Main(self.relax)
>>>>  File "full_analysis.py", line 300, in __init__
>>>>   self.multi_model()
>>>>  File "full_analysis.py", line 665, in multi_model
>>>>   minimise(MIN_ALGOR)
>>>>  File "/Applications/relax-1.3.1/relax-1.3/prompt/minimisation.py", line
>>>> 362,
>>>> in minimise
>>>> minimise.minimise(min_algor=min_algor, min_options=min_options,
>>>> func_tol=func_tol, grad_tol=grad_tol, max_iterations=max_iterations,
>>>> constraints=constraints, scaling=scaling, verbosity=verbosity)
>>>>  File "/Applications/relax-1.3.1/relax-1.3/generic_fns/minimise.py", line
>>>> 239,
>>>> in minimise
>>>>   minimise(min_algor=min_algor, min_options=min_options, 
>>>> func_tol=func_tol,
>>>> grad_tol=grad_tol, max_iterations=max_iterations, constraints=constraints,
>>>> scaling=scaling, verbosity=verbosity)
>>>>  File
>>>> "/Applications/relax-1.3.1/relax-1.3/specific_fns/model_free/mf_minimise.py",
>>>> line 987, in minimise
>>>>   results = generic_minimise(func=self.mf.func, dfunc=self.mf.dfunc,
>>>> d2func=self.mf.d2func, args=(), x0=param_vector, min_algor=min_algor,
>>>> min_options=min_options, func_tol=func_tol, grad_tol=grad_tol,
>>>> maxiter=max_iterations, A=A, b=b, full_output=
>>>> ag=verbosity)
>>>>  File
>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/generic.py",
>>>> line 412, in generic_minimise
>>>>   results = method_of_multipliers(func=func, dfunc=dfunc, d2func=d2func,
>>>> args=args, x0=x0, min_options=min_options, A=A, b=b, l=l, u=u, c=c, dc=dc,
>>>> d2c=d2c, func_tol=func_tol, grad_tol=grad_tol, maxiter=maxiter,
>>>> full_output=full_output, print_flag=
>>>>  File
>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/method_of_multipliers.py",
>>>> line 143, in method_of_multipliers
>>>>   results = min.minimise()
>>>>  File
>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/method_of_multipliers.py",
>>>> line 403, in minimise
>>>>   results = self.generic_minimise(func=self.func_LA, dfunc=self.func_dLA,
>>>> d2func=self.func_d2LA, args=self.args, x0=self.xk, 
>>>> min_algor=self.min_algor,
>>>> min_options=self.min_options, func_tol=None, grad_tol=self.tk,
>>>> maxiter=maxiter,
>>>> full_output=1, pr
>>>> b_print_flag, print_prefix="\t")
>>>>  File
>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/generic.py",
>>>> line 343, in generic_minimise
>>>>   results = newton(func=func, dfunc=dfunc, d2func=d2func, 
>>>> args=args, x0=x0,
>>>> min_options=min_options, func_tol=func_tol, grad_tol=grad_tol,
>>>> maxiter=maxiter,
>>>> full_output=full_output, print_flag=print_flag, print_prefix=print_prefix)
>>>>  File
>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/newton.py",
>>>> line 44, in newton
>>>>   results = min.minimise()
>>>>  File
>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/base_classes.py",
>>>> line 233, in minimise
>>>>   self.new_param_func()
>>>>  File
>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/newton.py",
>>>> line 166, in new_param_func
>>>>   self.line_search()
>>>>  File
>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/base_classes.py",
>>>> line 339, in backline
>>>>   self.alpha, fc = backtrack(self.func, self.args, self.xk, self.fk,
>>>> self.dfk,
>>>> self.pk, a_init=self.a0)
>>>> TypeError: 'NoneType' object is not iterable
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> Quoting Edward d'Auvergne <edw...@do...>:
>>>>
>>>>> :S  It overwrites a pre-existing file!  And the important script of
>>>>> all things!!!  That'll have to be fixed.  Seb, could you submit a bug
>>>>> report for that?
>>>>>
>>>>> Cheers,
>>>>>
>>>>> Edward
>>>>>
>>>>>
>>>>> On Fri, Oct 24, 2008 at 2:12 PM, Sébastien Morin
>>>>> <seb...@do...> wrote:
>>>>>>
>>>>>> Oh... Sorry... It's still early in the morning here (Quebec City)...
>>>>>>
>>>>>> ...
>>>>>>
>>>>>> Dont' forget to specify a log file...
>>>>>>
>>>>>> LOG   ->   relax -l LOG script.py
>>>>>>
>>>>>> TEE   ->   relax -t LOG script.py
>>>>>>
>>>>>> If you just specify the script, the script will be erased by the log...
>>>>>>
>>>>>> Cheers,
>>>>>>
>>>>>>
>>>>>> Séb
>>>>>>
>>>>>>
>>>>>> Sébastien Morin wrote:
>>>>>>>
>>>>>>> Hi Tyler,
>>>>>>>
>>>>>>> If you want all output from relax to go to a log file, use the option
>>>>>>> '-l'... (relax -l script.py)
>>>>>>>
>>>>>>> If you want all output from relax to go to a file AND the terminal
>>>>>>> (display), use the option '-t'... (relax -t script.py)
>>>>>>>
>>>>>>> These options are visible when typing : ./relax --help  (or relax -h)
>>>>>>>
>>>>>>> Good luck !
>>>>>>>
>>>>>>>
>>>>>>> Séb  :)
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Tyler Reddy wrote:
>>>>>>>
>>>>>>>> Okay, I submitted the report. Let me know if there's more information
>>>>>>>> you need
>>>>>>>> or a better way to submit bug reports in general.. haven't done this
>>>>>>>> before.
>>>>>>>> Also, I had to manually copy/paste the output, and while it 
>>>>>>>> looks fine,
>>>>>>>> if
>>>>>>>> there is a problem with the same pdb structure getting read twice or
>>>>>>>> something
>>>>>>>> that's probably just my pasting error from the unix terminal to the
>>>>>>>> browser.
>>>>>>>>
>>>>>>>> On that note, how can I fix this command:
>>>>>>>>
>>>>>>>> relax full_analysis.py > STDOUT.txt 2> STDERR.txt
>>>>>>>> tcsh: Ambiguous output redirect.
>>>>>>>>
>>>>>>>> Or better yet, can I merge all the output streams to a single 
>>>>>>>> text file
>>>>>>>> and
>>>>>>>> display the output in the terminal at the same time as well (maybe I'm
>>>>>>>> getting
>>>>>>>> too ambitious there..)?
>>>>>>>>
>>>>>>>> Also, I do get the same output for 'ellipsoid' as well, as Seb asked.
>>>>>>>>
>>>>>>>> Yours,
>>>>>>>>
>>>>>>>> Tyler
>>>>>>>>
>>>>>>>>
>>>>>>>> Quoting Edward d'Auvergne <ed...@do...>:
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>> Hi,
>>>>>>>>>
>>>>>>>>> This issue looks like a problem with the loaded PDB structure.  The
>>>>>>>>> 'local_tm' and 'sphere' optimisations do not utilise structural
>>>>>>>>> information, but the 'oblate' and 'prolate' spheroids, and the
>>>>>>>>> 'ellipsoid' all require this info.  Normally relax will catch this
>>>>>>>>> problem and deselect the spins without XH bond vectors, but 
>>>>>>>>> this seems
>>>>>>>>> to be broken in the 1.3 versions hence you get the original cryptic
>>>>>>>>> Python error.  As this is a real bug with the relax source code (and
>>>>>>>>> not a yet-to-be converted feature or a sample script), would you be
>>>>>>>>> able to submit a bug report for this issue?  The relax bug tracker is
>>>>>>>>> located at https://gna.org/bugs/?group=relax and the link at
>>>>>>>>> https://gna.org/bugs/?func=additem&group=relax allows you to create a
>>>>>>>>> report.  That would be much appreciated.
>>>>>>>>>
>>>>>>>>> The bug report will be useful for having this error caught by the
>>>>>>>>> relax test suite - if I can replicate the bug there then I can play
>>>>>>>>> with the bug and fix it.  Note the the actual problem 
>>>>>>>>> occurred earlier
>>>>>>>>> starting with the loading of the PDB file at the structure.read_pdb()
>>>>>>>>> user function.  So if you could include all print out from that user
>>>>>>>>> function to the end of the traceback error message, that 
>>>>>>>>> would be very
>>>>>>>>> useful.
>>>>>>>>>
>>>>>>>>> Cheers,
>>>>>>>>>
>>>>>>>>> Edward
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On Wed, Oct 22, 2008 at 3:17 AM, Tyler Reddy <TR...@da...> wrote:
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>> Hi Seb,
>>>>>>>>>>
>>>>>>>>>> I just tested 'oblate' and it produces the same error output.
>>>>>>>>>>
>>>>>>>>>> Tyler
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Quoting Sébastien Morin <seb...@do...>:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>> Hi Tyler,
>>>>>>>>>>>
>>>>>>>>>>> Do you get the same error when trying the 'oblate' or 'ellipsoid'
>>>>>>>>>>> diffusion tensors ?
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Sébastien
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Tyler Reddy wrote:
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>> I'm having an issue with the full_analysis.py script. It seems to
>>>>>>>>>>>> work
>>>>>>>>>>>> fine when
>>>>>>>>>>>> DIFF_MODEL = 'local_tm' or 'sphere' (converges on 4th round) but
>>>>>>>>>>>> for
>>>>>>>>>>>> 'prolate'
>>>>>>>>>>>> I get the following output:
>>>>>>>>>>>>
>>>>>>>>>>>> Grid search
>>>>>>>>>>>> ~~~~~~~~~~~
>>>>>>>>>>>>
>>>>>>>>>>>> Searching the grid.
>>>>>>>>>>>> Traceback (most recent call last):
>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/relax", line 408, in
>>>>>>>>>>>> <module>
>>>>>>>>>>>>    Relax()
>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/relax", line 125, in
>>>>>>>>>>>> __init__
>>>>>>>>>>>>    self.interpreter.run(self.script_file)
>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>> line 270, in
>>>>>>>>>>>> run
>>>>>>>>>>>>    return run_script(intro=self.__intro_string, local=self.local,
>>>>>>>>>>>> script_file=script_file, quit=self.__quit_flag,
>>>>>>>>>>>> show_script=self.__show_script,
>>>>>>>>>>>> raise_relax_error=self.__raise_relax_er
>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>> line 531, in
>>>>>>>>>>>> run_script
>>>>>>>>>>>>    return console.interact(intro, local, script_file, quit,
>>>>>>>>>>>> show_script=show_script, raise_relax_error=raise_relax_error)
>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>> line 427, in
>>>>>>>>>>>> interact_script
>>>>>>>>>>>>    execfile(script_file, local)
>>>>>>>>>>>>  File "full_analysis.py", line 673, in <module>
>>>>>>>>>>>>    Main(self.relax)
>>>>>>>>>>>>  File "full_analysis.py", line 284, in __init__
>>>>>>>>>>>>    grid_search(inc=inc)
>>>>>>>>>>>>  File 
>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/prompt/minimisation.py",
>>>>>>>>>>>> line 152,
>>>>>>>>>>>> in grid_search
>>>>>>>>>>>>    minimise.grid_search(lower=lower, upper=upper, inc=inc,
>>>>>>>>>>>> constraints=constraints, verbosity=verbosity)
>>>>>>>>>>>>  File
>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/generic_fns/minimise.py", 
>>>>>>>>>>>> line
>>>>>>>>>>>> 185,
>>>>>>>>>>>> in grid_search
>>>>>>>>>>>>    grid_search(lower=lower, upper=upper, inc=inc,
>>>>>>>>>>>> constraints=constraints,
>>>>>>>>>>>> verbosity=verbosity)
>>>>>>>>>>>>  File
>>>>>>>>>>>>
>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/specific_fns/model_free/mf_minimise.py",
>>>>>>>>>>>> line 479, in grid_search
>>>>>>>>>>>>    self.minimise(min_algor='grid', lower=lower, upper=upper,
>>>>>>>>>>>> inc=inc,
>>>>>>>>>>>> constraints=constraints, verbosity=verbosity, sim_index=sim_index)
>>>>>>>>>>>>  File
>>>>>>>>>>>>
>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/specific_fns/model_free/mf_minimise.py",
>>>>>>>>>>>> line 987, in minimise
>>>>>>>>>>>>    results = generic_minimise(func=self.mf.func,
>>>>>>>>>>>> dfunc=self.mf.dfunc,
>>>>>>>>>>>> d2func=self.mf.d2func, args=(), x0=param_vector,
>>>>>>>>>>>> min_algor=min_algor,
>>>>>>>>>>>> min_options=min_options, func_tol=func_tol, g
>>>>>>>>>>>> l, maxiter=max_iterations, A=A, b=b, full_output=1,
>>>>>>>>>>>> print_flag=verbosity)
>>>>>>>>>>>>  File
>>>>>>>>>>>>
>>>>>>>>>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/generic.py",
>>>>>>>>>>>> line 319, in generic_minimise
>>>>>>>>>>>>    xk, fk, k = grid(func=func, args=args, grid_ops=min_options,
>>>>>>>>>>>> A=A, b=b, l=l,
>>>>>>>>>>>> u=u, c=c, print_flag=print_flag)
>>>>>>>>>>>>  File
>>>>>>>>>>>>
>>>>>>>>>>>> "/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/minfx/grid.py",
>>>>>>>>>>>> line 129, in grid
>>>>>>>>>>>>    f = func(*(params,)+args)
>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/maths_fns/mf.py", line
>>>>>>>>>>>> 506, in
>>>>>>>>>>>> func_diff
>>>>>>>>>>>>    self.diff_data.calc_di(data, self.diff_data)
>>>>>>>>>>>>  File
>>>>>>>>>>>>
>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/maths_fns/direction_cosine.py",
>>>>>>>>>>>> line
>>>>>>>>>>>> 64, in calc_spheroid_di
>>>>>>>>>>>>    data.dz = dot(data.xh_unit_vector, diff_data.dpar)
>>>>>>>>>>>> TypeError: unsupported operand type(s) for *: 'NoneType' and
>>>>>>>>>>>> 'float'
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> Quoting Edward d'Auvergne <ed...@do...>:
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>> Hi,
>>>>>>>>>>>>>
>>>>>>>>>>>>> For the bug you mention, I've fixed this and the changes are in
>>>>>>>>>>>>> the
>>>>>>>>>>>>> repository.  There were a few other issues to do with subsequent
>>>>>>>>>>>>> LaTeX
>>>>>>>>>>>>> compilation and these have been fixed too.  You can see the new
>>>>>>>>>>>>> sample
>>>>>>>>>>>>> script at:  http://svn.gna.org/viewcvs/relax/1.3/sample_scripts/
>>>>>>>>>>>>>
>>>>>>>>>>>>> Regards,
>>>>>>>>>>>>>
>>>>>>>>>>>>> Edward
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> On Tue, Oct 21, 2008 at 3:44 AM, Tyler Reddy <TR...@da...>
>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>> Hello,
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> 1) I changed that line and I'm still having a bit of 
>>>>>>>>>>>>>> trouble (see
>>>>>>>>>>>>>> output
>>>>>>>>>>>>>> below).
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> 2) The errors that I'm using are described as 'the standard
>>>>>>>>>>>>>> error for each
>>>>>>>>>>>>>> parameter... [which] is an easy calculation from the covariance
>>>>>>>>>>>>>> matrix.'
>>>>>>>>>>>>>> Paraphrasing from the author there--I'm guessing this isn't the
>>>>>>>>>>>>>> optimal
>>>>>>>>>>>>>> input?
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> 3) I'm not sure it's explicitly stated in the manual, but I'm
>>>>>>>>>>>>>> proceeding on
>>>>>>>>>>>>>> the
>>>>>>>>>>>>>> assumption that you run the multi-model script first and then
>>>>>>>>>>>>>> modsel to
>>>>>>>>>>>>>> decide
>>>>>>>>>>>>>> on the right model for each given residue. A few weeks ago I was
>>>>>>>>>>>>>> experimenting
>>>>>>>>>>>>>> with this and if I didn't leave the global correlation time as
>>>>>>>>>>>>>> fixed the
>>>>>>>>>>>>>> computation seemed to take a VERY long time (unclear if it was
>>>>>>>>>>>>>> ever going to
>>>>>>>>>>>>>> finish).
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Also, as a side note, since my peptide is actually in a micelle,
>>>>>>>>>>>>>> I'm not
>>>>>>>>>>>>>> sure if
>>>>>>>>>>>>>> there's anything extra I can do for diffusion tensor and
>>>>>>>>>>>>>> correlation time
>>>>>>>>>>>>>> type
>>>>>>>>>>>>>> stuff. I know some programs (i.e. the Mathematica notebooks by
>>>>>>>>>>>>>> Dr.
>>>>>>>>>>>>>> Spyracopoulos) read in PDB files for diffusion tensor
>>>>>>>>>>>>>> calculations, but I
>>>>>>>>>>>>>> suspect it's a bit of a mess when the system is more complicated
>>>>>>>>>>>>>> than the
>>>>>>>>>>>>>> structure in the PDB file would suggest.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Output:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Latex()
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> ----------------------------------------------------------------------------------------------------
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> relax> pipe.create(pipe_name='results', pipe_type='mf')
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> relax> results.read(file='results', dir=None)
>>>>>>>>>>>>>> Opening the file 'results' for reading.
>>>>>>>>>>>>>> Traceback (most recent call last):
>>>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/relax", line 408, in
>>>>>>>>>>>>>> <module>
>>>>>>>>>>>>>>  Relax()
>>>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/relax", line 125, in
>>>>>>>>>>>>>> __init__
>>>>>>>>>>>>>>  self.interpreter.run(self.script_file)
>>>>>>>>>>>>>>  File
>>>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>>>> line 270,
>>>>>>>>>>>>>> in
>>>>>>>>>>>>>> run
>>>>>>>>>>>>>>  return run_script(intro=self.__intro_string, local=self.local,
>>>>>>>>>>>>>> script_file=script_file, quit=self.__quit_flag,
>>>>>>>>>>>>>> show_script=self.__show_script,
>>>>>>>>>>>>>> raise_relax_error=self.__raise_relax_error)
>>>>>>>>>>>>>>  File
>>>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>>>> line 531,
>>>>>>>>>>>>>> in
>>>>>>>>>>>>>> run_script
>>>>>>>>>>>>>>  return console.interact(intro, local, script_file, quit,
>>>>>>>>>>>>>> show_script=show_script, raise_relax_error=raise_relax_error)
>>>>>>>>>>>>>>  File
>>>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>>>> line 427,
>>>>>>>>>>>>>> in
>>>>>>>>>>>>>> interact_script
>>>>>>>>>>>>>>  execfile(script_file, local)
>>>>>>>>>>>>>>  File "latex_mf_table.py", line 220, in <module>
>>>>>>>>>>>>>>  Latex()
>>>>>>>>>>>>>>  File "latex_mf_table.py", line 68, in __init__
>>>>>>>>>>>>>>  self.table_body()
>>>>>>>>>>>>>>  File "latex_mf_table.py", line 186, in table_body
>>>>>>>>>>>>>>  self.file.write("%9.3f & %9.3f & " % (spin.s2, spin.s2_err))
>>>>>>>>>>>>>> AttributeError: 'SpinContainer' object has no attribute 's2_err'
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Quoting Edward d'Auvergne <ed...@do...>:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Hi,
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Using a new system test, I found one more bug in the script.
>>>>>>>>>>>>>>>  This has
>>>>>>>>>>>>>>> been fixed in the 1.3 repository line.  If you haven't used
>>>>>>>>>>>>>>> subversion
>>>>>>>>>>>>>>> to check out (and update) the 1.3 line, then you can see the
>>>>>>>>>>>>>>> changes
>>>>>>>>>>>>>>> required in my commit at:
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> https://mail.gna.org/public/relax-commits/2008-10/msg00402.html
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Just change the line starting with '-' to the line 
>>>>>>>>>>>>>>> starting with
>>>>>>>>>>>>>>> '+'.
>>>>>>>>>>>>>>> Oh, it may take a few minutes for the link to be generated.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Regards,
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Edward
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> On Mon, Oct 20, 2008 at 10:12 PM, Edward d'Auvergne
>>>>>>>>>>>>>>> <ed...@do...> wrote:
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Hi,
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> That's a bug in the sample script.  Try adding a ':' character
>>>>>>>>>>>>>>>> to the
>>>>>>>>>>>>>>>> end of line 171 in your script.  I've fixed this in the 1.3
>>>>>>>>>>>>>>>> repository
>>>>>>>>>>>>>>>> line and will try to add a system test to the program 
>>>>>>>>>>>>>>>> to try to
>>>>>>>>>>>>>>>> catch
>>>>>>>>>>>>>>>> any bugs before you do ;)
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Cheers,
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Edward
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> On Mon, Oct 20, 2008 at 9:27 PM, Tyler Reddy <TR...@da...>
>>>>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> I've been trying to use the latex python script on the aic
>>>>>>>>>>>>>>>>> results file.
>>>>>>>>>>>>>>>>> I get
>>>>>>>>>>>>>>>>> the syntax error below. Not sure if I'm doing something wrong
>>>>>>>>>>>>>>>>> or if
>>>>>>>>>>>>>>>>> there's
>>>>>>>>>>>>>>>>> just a small problem with that line of code:
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> Latex()
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> ----------------------------------------------------------------------------------------------------
>>>>>>>>>>>>>>>>> Traceback (most recent call last):
>>>>>>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/relax", line 408,
>>>>>>>>>>>>>>>>> in
>>>>>>>>>>>>>>>>> <module>
>>>>>>>>>>>>>>>>>  Relax()
>>>>>>>>>>>>>>>>>  File "/Applications/relax-1.3.1/relax-1.3/relax", line 125,
>>>>>>>>>>>>>>>>> in
>>>>>>>>>>>>>>>>> __init__
>>>>>>>>>>>>>>>>>  self.interpreter.run(self.script_file)
>>>>>>>>>>>>>>>>>  File
>>>>>>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>>>>>>> line 270, in
>>>>>>>>>>>>>>>>> run
>>>>>>>>>>>>>>>>>  return run_script(intro=self.__intro_string,
>>>>>>>>>>>>>>>>> local=self.local,
>>>>>>>>>>>>>>>>> script_file=script_file, quit=self.__quit_flag,
>>>>>>>>>>>>>>>>> show_script=self.__show_script,
>>>>>>>>>>>>>>>>> raise_relax_error=self.__raise_relax_error)
>>>>>>>>>>>>>>>>>  File
>>>>>>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>>>>>>> line 531, in
>>>>>>>>>>>>>>>>> run_script
>>>>>>>>>>>>>>>>>  return console.interact(intro, local, script_file, quit,
>>>>>>>>>>>>>>>>> show_script=show_script, raise_relax_error=raise_relax_error)
>>>>>>>>>>>>>>>>>  File
>>>>>>>>>>>>>>>>> "/Applications/relax-1.3.1/relax-1.3/prompt/interpreter.py",
>>>>>>>>>>>>>>>>> line 427, in
>>>>>>>>>>>>>>>>> interact_script
>>>>>>>>>>>>>>>>>  execfile(script_file, local)
>>>>>>>>>>>>>>>>>  File "latex_mf_table.py", line 171
>>>>>>>>>>>>>>>>>  for spin, spin_id in spin_loop(return_id=True)
>>>>>>>>>>>>>>>>> SyntaxError: invalid syntax
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> Quoting Edward d'Auvergne <ed...@do...>:
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>> On Mon, Oct 20, 2008 at 5:12 PM, Tyler Reddy <TR...@da...>
>>>>>>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>> Hello,
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>> 1)
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>> I have been using the multi model and model selection
>>>>>>>>>>>>>>>>>>> scripts in
>>>>>>>>>>>>>>>>>>> relax 1.3.2 but
>>>>>>>>>>>>>>>>>>> I have trouble displaying the output in a tabulated format.
>>>>>>>>>>>>>>>>>>> Both
>>>>>>>>>>>>>>>>>>> scripts seem
>>>>>>>>>>>>>>>>>>> to produce an xml document with various headers that isn't
>>>>>>>>>>>>>>>>>>> easy to
>>>>>>>>>>>>>>>>>>> read. It
>>>>>>>>>>>>>>>>>>> looks like format='columnar' isn't supported. I wonder what
>>>>>>>>>>>>>>>>>>> other
>>>>>>>>>>>>>>>>>>> options I
>>>>>>>>>>>>>>>>>>> have to look at this data? For some reason, I don't recall
>>>>>>>>>>>>>>>>>>> having
>>>>>>>>>>>>>>>>>>> this problem
>>>>>>>>>>>>>>>>>>> on a Linux machine a few weeks ago (using a Mac OS 10.4 at
>>>>>>>>>>>>>>>>>>> the
>>>>>>>>>>>>>>>>>>> moment), but
>>>>>>>>>>>>>>>>>>> anyways it would be nice to get readable model-free output.
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>> The results file is now in XML format and the more readable
>>>>>>>>>>>>>>>>>> 'columnar'
>>>>>>>>>>>>>>>>>> format has been removed from the 1.3 line.  With the change
>>>>>>>>>>>>>>>>>> to the new
>>>>>>>>>>>>>>>>>> XML results file all the contents of a data pipe,
>>>>>>>>>>>>>>>>>> irrespective of what
>>>>>>>>>>>>>>>>>> that data is, is packaged.  So you can put data into this
>>>>>>>>>>>>>>>>>> pipe
>>>>>>>>>>>>>>>>>> yourself and it will save that information (for advanced
>>>>>>>>>>>>>>>>>> users,
>>>>>>>>>>>>>>>>>> complex python objects will need the to_xml() and from_xml()
>>>>>>>>>>>>>>>>>> methods
>>>>>>>>>>>>>>>>>> to package and unpackage the data).  The reason for removing
>>>>>>>>>>>>>>>>>> the
>>>>>>>>>>>>>>>>>> 'columnar' format was that it was considered too inflexible
>>>>>>>>>>>>>>>>>> for the
>>>>>>>>>>>>>>>>>> changes occuring in the 1.3 line, it contained duplicate
>>>>>>>>>>>>>>>>>> information,
>>>>>>>>>>>>>>>>>> had numerical precision issues, and there were alternatives
>>>>>>>>>>>>>>>>>> to easily
>>>>>>>>>>>>>>>>>> view this data.  You can use the value.display() and
>>>>>>>>>>>>>>>>>> value.write()
>>>>>>>>>>>>>>>>>> user functions to display and save the results for a single
>>>>>>>>>>>>>>>>>> parameter.
>>>>>>>>>>>>>>>>>> If needed, these user functions could be extended to accept
>>>>>>>>>>>>>>>>>> a list of
>>>>>>>>>>>>>>>>>> parameters.
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>> Then there is the sample_scripts/latex_mf_table.py sample
>>>>>>>>>>>>>>>>>> script which
>>>>>>>>>>>>>>>>>> will generate a LaTeX table of the model-free results.  This
>>>>>>>>>>>>>>>>>> file can
>>>>>>>>>>>>>>>>>> be copied and modified - this requires learning a bit of
>>>>>>>>>>>>>>>>>> python - to
>>>>>>>>>>>>>>>>>> format and display the results any way you wish.  
>>>>>>>>>>>>>>>>>> And finally
>>>>>>>>>>>>>>>>>> if
>>>>>>>>>>>>>>>>>> anyone really wants to, and has the skills to, they can
>>>>>>>>>>>>>>>>>> modify this
>>>>>>>>>>>>>>>>>> sample script to recreate a version of the 
>>>>>>>>>>>>>>>>>> 'columnar' format.
>>>>>>>>>>>>>>>>>>  This
>>>>>>>>>>>>>>>>>> could be added to the relax sample scripts, and if their
>>>>>>>>>>>>>>>>>> skills are
>>>>>>>>>>>>>>>>>> very advanced, then much code from the 1.2 relax 
>>>>>>>>>>>>>>>>>> versions can
>>>>>>>>>>>>>>>>>> be
>>>>>>>>>>>>>>>>>> recycled.
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>> 2)
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>> The error input for the relaxation rate parameters is
>>>>>>>>>>>>>>>>>>> currently my
>>>>>>>>>>>>>>>>>>> non-linear
>>>>>>>>>>>>>>>>>>> curve fitting standard deviation. I'm not sure if 
>>>>>>>>>>>>>>>>>>> that means
>>>>>>>>>>>>>>>>>>> subsequent
>>>>>>>>>>>>>>>>>>> analysis will be completely incorrect? I guess it 
>>>>>>>>>>>>>>>>>>> depends on
>>>>>>>>>>>>>>>>>>> the
>>>>>>>>>>>>>>>>>>> comparison of
>>>>>>>>>>>>>>>>>>> magnitude between these errors and the type of 
>>>>>>>>>>>>>>>>>>> error that is
>>>>>>>>>>>>>>>>>>> propagated by
>>>>>>>>>>>>>>>>>>> relax during its own curve-fitting (which I am unable to do
>>>>>>>>>>>>>>>>>>> at the
>>>>>>>>>>>>>>>>>>> moment).
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>> I'm guessing this is the sum of squared error value (SSE)
>>>>>>>>>>>>>>>>>> from the
>>>>>>>>>>>>>>>>>> fit.  Or is it a regression coefficient or a chi-squared
>>>>>>>>>>>>>>>>>> value?  Did
>>>>>>>>>>>>>>>>>> the fitting use a technique such as bootstrapping or
>>>>>>>>>>>>>>>>>> jackknife
>>>>>>>>>>>>>>>>>> simulations to estimate the parameter errors via
>>>>>>>>>>>>>>>>>> propagation?  Or did
>>>>>>>>>>>>>>>>>> it use the covariance matrix?  If it is the SSE, 
>>>>>>>>>>>>>>>>>> chi-squared,
>>>>>>>>>>>>>>>>>> or
>>>>>>>>>>>>>>>>>> regression coefficient then that value cannot be used.  This
>>>>>>>>>>>>>>>>>> will be
>>>>>>>>>>>>>>>>>> wildly wrong and cause massive failure in model selection.
>>>>>>>>>>>>>>>>>>  It will
>>>>>>>>>>>>>>>>>> cause big problems in optimisation, and if you are unlucky
>>>>>>>>>>>>>>>>>> and have
>>>>>>>>>>>>>>>>>> spaces with long, curved valleys or flat curved spaces
>>>>>>>>>>>>>>>>>> leading to the
>>>>>>>>>>>>>>>>>> minimum (that's model-free models m5 to m8 in most cases and
>>>>>>>>>>>>>>>>>> not so
>>>>>>>>>>>>>>>>>> uncommon in model m4) then the minimum can be squeezed and
>>>>>>>>>>>>>>>>>> appear in
>>>>>>>>>>>>>>>>>> another completely different region in the space.  It will
>>>>>>>>>>>>>>>>>> likely also
>>>>>>>>>>>>>>>>>> cause model failure issues, which although removed by the
>>>>>>>>>>>>>>>>>> eliminate()
>>>>>>>>>>>>>>>>>> user function, might discount the best solution.  I would
>>>>>>>>>>>>>>>>>> guess that
>>>>>>>>>>>>>>>>>> all of this will have a measurable affect on the final
>>>>>>>>>>>>>>>>>> diffusion
>>>>>>>>>>>>>>>>>> tensor as well and, if so, this will cause the appearance of
>>>>>>>>>>>>>>>>>> artificial motions (my 2007 JBNMR paper at
>>>>>>>>>>>>>>>>>> http://dx.doi.org/10.1039/b702202f explains these problems
>>>>>>>>>>>>>>>>>> in detail).
>>>>>>>>>>>>>>>>>> If one is not careful with the errors and they are
>>>>>>>>>>>>>>>>>> significantly off,
>>>>>>>>>>>>>>>>>> then the result is that the results may not be real.  So I
>>>>>>>>>>>>>>>>>> would only
>>>>>>>>>>>>>>>>>> use the error if it comes from an established error
>>>>>>>>>>>>>>>>>> propagation
>>>>>>>>>>>>>>>>>> technique (i.e. from data to parameter error propagation).
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>> Regards,
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>> Edward
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> _______________________________________________
>>>>>>>>>>>>>>>>> relax (http://nmr-relax.com)
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> This is the relax-users mailing list
>>>>>>>>>>>>>>>>> rel...@do...
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> To unsubscribe from this list, get a password
>>>>>>>>>>>>>>>>> reminder, or change your subscription options,
>>>>>>>>>>>>>>>>> visit the list information page at
>>>>>>>>>>>>>>>>> https://mail.gna.org/listinfo/relax-users
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>> _______________________________________________
>>>>>>>>>>>> relax (http://nmr-relax.com)
>>>>>>>>>>>>
>>>>>>>>>>>> This is the relax-users mailing list
>>>>>>>>>>>> rel...@do...
>>>>>>>>>>>>
>>>>>>>>>>>> To unsubscribe from this list, get a password
>>>>>>>>>>>> reminder, or change your subscription options,
>>>>>>>>>>>> visit the list information page at
>>>>>>>>>>>> https://mail.gna.org/listinfo/relax-users
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>> _______________________________________________
>>>>>>>>>>> relax (http://nmr-relax.com)
>>>>>>>>>>>
>>>>>>>>>>> This is the relax-users mailing list
>>>>>>>>>>> rel...@do...
>>>>>>>>>>>
>>>>>>>>>>> To unsubscribe from this list, get a password
>>>>>>>>>>> reminder, or change your subscription options,
>>>>>>>>>>> visit the list information page at
>>>>>>>>>>> https://mail.gna.org/listinfo/relax-users
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>> _______________________________________________
>>>>>>>>>> relax (http://nmr-relax.com)
>>>>>>>>>>
>>>>>>>>>> This is the relax-users mailing list
>>>>>>>>>> rel...@do...
>>>>>>>>>>
>>>>>>>>>> To unsubscribe from this list, get a password
>>>>>>>>>> reminder, or change your subscription options,
>>>>>>>>>> visit the list information page at
>>>>>>>>>> https://mail.gna.org/listinfo/relax-users
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>> _______________________________________________
>>>>>>>>> relax (http://nmr-relax.com)
>>>>>>>>>
>>>>>>>>> This is the relax-users mailing list
>>>>>>>>> rel...@do...
>>>>>>>>>
>>>>>>>>> To unsubscribe from this list, get a password
>>>>>>>>> reminder, or change your subscription options,
>>>>>>>>> visit the list information page at
>>>>>>>>> https://mail.gna.org/listinfo/relax-users
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> _______________________________________________
>>>>>>>> relax (http://nmr-relax.com)
>>>>>>>>
>>>>>>>> This is the relax-users mailing list
>>>>>>>> rel...@do...
>>>>>>>>
>>>>>>>> To unsubscribe from this list, get a password
>>>>>>>> reminder, or change your subscription options,
>>>>>>>> visit the list information page at
>>>>>>>> https://mail.gna.org/listinfo/relax-users
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>>
>>>>
>>>>
>>>
>>> _______________________________________________
>>> relax (http://nmr-relax.com)
>>>
>>> This is the relax-users mailing list
>>> rel...@do...
>>>
>>> To unsubscribe from this list, get a password
>>> reminder, or change your subscription options,
>>> visit the list information page at
>>> https://mail.gna.org/listinfo/relax-users
>>>
>>
>>
>>
>>
>> _______________________________________________
>> relax (http://nmr-relax.com)
>>
>> This is the relax-users mailing list
>> rel...@do...
>>
>> To unsubscribe from this list, get a password
>> reminder, or change your subscription options,
>> visit the list information page at
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>>
>