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 <[EMAIL PROTECTED]> 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 <[EMAIL PROTECTED]>:
>
>> On Mon, Oct 20, 2008 at 5:12 PM, Tyler Reddy <[EMAIL PROTECTED]> 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
>>
>
>
>
>
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