Hi Ed.

You can just grep for "out" or "einsum" in lib/dispersion.

Best
Troels

2014-06-27 14:15 GMT+02:00 Edward d'Auvergne <edw...@nmr-relax.com>:
> Hi Troels,
>
> I think if would be better if we caught this earlier, specifically the
> select_model() method of the specific_analyses.relax_disp.uf module if
> the user chooses a model which is not supported by their numpy
> version.  Such a check with a RelaxError would only be two lines of
> code, plus a comment (which could include the current version in
> numpy.version.version).  It would be very useful to add the models to
> a list variable in specific_analyses.relax_disp.variables so that I
> can replicate the checks in the GUI.  Even better would be to add the
> 2 line check to a function in specific_analyses.relax_disp.checks to
> allow for consistent checking in all user interfaces.  There could
> even be two separate tests, one for the numpy.einsum and one for the
> numpy out argument, each with their own model lists, if you wish.
>
> Cheers,
>
> Edward
>
>
>
>
>
>
> On 27 June 2014 12:58,  <tlin...@nmr-relax.com> wrote:
>> Author: tlinnet
>> Date: Fri Jun 27 12:58:22 2014
>> New Revision: 24336
>>
>> URL: http://svn.gna.org/viewcvs/relax?rev=24336&view=rev
>> Log:
>> Added to target function that experiment_type_setup() should not be 
>> initiated, if numpy.einsum is missing.
>>
>> Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion 
>> models for Clustered analysis.
>>
>> Modified:
>>     branches/disp_spin_speed/target_functions/relax_disp.py
>>
>> Modified: branches/disp_spin_speed/target_functions/relax_disp.py
>> URL: 
>> http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/target_functions/relax_disp.py?rev=24336&r1=24335&r2=24336&view=diff
>> ==============================================================================
>> --- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
>> +++ branches/disp_spin_speed/target_functions/relax_disp.py     Fri Jun 27 
>> 12:58:22 2014
>> @@ -365,8 +365,10 @@
>>          # This is to make sure, that the chi2 values is not affected by 
>> missing values.
>>          self.mask_replace_blank = masked_equal(self.missing, 1.0)
>>
>> -        # Check the experiment types, simplifying the data structures as 
>> needed.
>> -        self.experiment_type_setup()
>> +        # Check if eisum is available for numerical models.
>> +        if dep_check.einsum_module:
>> +            # Check the experiment types, simplifying the data structures 
>> as needed.
>> +            self.experiment_type_setup()
>>
>>          # Scaling initialisation.
>>          self.scaling_flag = False
>>
>>
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