Hi Troels,
I don't agree on this order:
expected_result = [MODEL_R2EFF, MODEL_NOREX_R1RHO_FIT_R1,
MODEL_MP05_FIT_R1, MODEL_TAP03_FIT_R1, MODEL_TP02_FIT_R1,
MODEL_DPL94_FIT_R1, MODEL_NS_R1RHO_2SITE_FIT_R1]
as the TP02 model should be before MP05. The TP02 parameters could be
used as the starting point for the MP05 model (though I doubt anyone
will optimise both of these models at the same time, it might happen).
MP05 should be before the numeric model, as it is. And the rest I
would not use nesting for, so the order is unimportant. Though I
don't see why DPL94 comes after all of the Palmer models.
Regards,
Edward
On 12 August 2014 10:55, <[email protected]> wrote:
> Author: tlinnet
> Date: Tue Aug 12 10:55:04 2014
> New Revision: 24996
>
> URL: http://svn.gna.org/viewcvs/relax?rev=24996&view=rev
> Log:
> Added unit test, to test the expected sorting of models for auto analyses.
>
> sr #3135(https://gna.org/support/?3135): Optimisation of the R1 relaxation
> rate for the off-resonance R1rho relaxation dispersion models.
>
> Modified:
>
> branches/R1_fitting/test_suite/unit_tests/_specific_analyses/_relax_disp/test_variables.py
>
> Modified:
> branches/R1_fitting/test_suite/unit_tests/_specific_analyses/_relax_disp/test_variables.py
> URL:
> http://svn.gna.org/viewcvs/relax/branches/R1_fitting/test_suite/unit_tests/_specific_analyses/_relax_disp/test_variables.py?rev=24996&r1=24995&r2=24996&view=diff
> ==============================================================================
> ---
> branches/R1_fitting/test_suite/unit_tests/_specific_analyses/_relax_disp/test_variables.py
> (original)
> +++
> branches/R1_fitting/test_suite/unit_tests/_specific_analyses/_relax_disp/test_variables.py
> Tue Aug 12 10:55:04 2014
> @@ -20,7 +20,7 @@
>
> ###############################################################################
>
> # relax module imports.
> -from specific_analyses.relax_disp.variables import nesting_model
> +from specific_analyses.relax_disp.variables import nesting_model, sort_models
> from specific_analyses.relax_disp.variables import MODEL_B14,
> MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94_FIT_R1, MODEL_IT99,
> MODEL_MMQ_CR72, MODEL_LM63, MODEL_LM63_3SITE, MODEL_MP05_FIT_R1, MODEL_NOREX,
> MODEL_NOREX_R1RHO_FIT_R1, MODEL_NS_CPMG_2SITE_3D,
> MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED,
> MODEL_NS_CPMG_2SITE_STAR, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE,
> MODEL_NS_MMQ_3SITE, MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_R1RHO_2SITE,
> MODEL_NS_R1RHO_2SITE_FIT_R1, MODEL_NS_R1RHO_3SITE,
> MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_R2EFF, MODEL_TAP03_FIT_R1,
> MODEL_TP02_FIT_R1, MODEL_TSMFK01
> from specific_analyses.relax_disp.variables import MODEL_EXP_TYPE, MODEL_EQ,
> MODEL_PARAMS, MODEL_SITES, MODEL_YEAR
> from test_suite.unit_tests.base_classes import UnitTestCase
> @@ -294,3 +294,40 @@
>
> # Test the return.
> self.assertEqual(nesting_model(self_models=self_models,
> model=model)[1].model, MODEL_DPL94_FIT_R1)
> +
> +
> + def test_sort_models(self):
> + """Unit test of function sort_models, which determine how to sort
> models for auto analyses."""
> +
> + ## Test sort of models, when models are all R1rho models with fitted
> R1.
> + # Define all the models tested in the analysis.
> + self_models = [MODEL_R2EFF, MODEL_NOREX_R1RHO_FIT_R1,
> MODEL_DPL94_FIT_R1, MODEL_TP02_FIT_R1, MODEL_TAP03_FIT_R1, MODEL_MP05_FIT_R1,
> MODEL_NS_R1RHO_2SITE_FIT_R1]
> + expected_result = [MODEL_R2EFF, MODEL_NOREX_R1RHO_FIT_R1,
> MODEL_MP05_FIT_R1, MODEL_TAP03_FIT_R1, MODEL_TP02_FIT_R1, MODEL_DPL94_FIT_R1,
> MODEL_NS_R1RHO_2SITE_FIT_R1]
> +
> + # Test the return.
> + self.assertEqual(sort_models(models=self_models), expected_result)
> +
> + ## Test sort of models, when models are all CPMG models.
> + # Define all the models tested in the analysis.
> + self_models = [MODEL_R2EFF, MODEL_NOREX, MODEL_CR72,
> MODEL_CR72_FULL, MODEL_IT99, MODEL_TSMFK01, MODEL_B14, MODEL_B14_FULL,
> MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_3D,
> MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_STAR,
> MODEL_NS_CPMG_2SITE_STAR_FULL]
> + expected_result = [MODEL_R2EFF, MODEL_NOREX,
> MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_B14, MODEL_B14_FULL, MODEL_TSMFK01,
> MODEL_IT99, MODEL_CR72, MODEL_CR72_FULL, MODEL_NS_CPMG_2SITE_3D,
> MODEL_NS_CPMG_2SITE_STAR, MODEL_NS_CPMG_2SITE_3D_FULL,
> MODEL_NS_CPMG_2SITE_STAR_FULL]
> +
> + # Test the return.
> + self.assertEqual(sort_models(models=self_models), expected_result)
> +
> + ## Test sort of models, when models are all CPMG MMQ models.
> + # Define all the models tested in the analysis.
> + self_models = [MODEL_R2EFF, MODEL_NOREX, MODEL_NS_MMQ_3SITE,
> MODEL_NS_MMQ_2SITE, MODEL_MMQ_CR72, MODEL_NS_MMQ_3SITE_LINEAR]
> + expected_result = [MODEL_R2EFF, MODEL_NOREX, MODEL_MMQ_CR72,
> MODEL_NS_MMQ_2SITE, MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_MMQ_3SITE]
> +
> + # Test the return.
> + self.assertEqual(sort_models(models=self_models), expected_result)
> +
> + ## Test sort of models, when models are mix of CPMG and CPMG MMQ
> models.
> + # Define all the models tested in the analysis.
> + self_models = [MODEL_R2EFF, MODEL_NOREX, MODEL_NS_MMQ_3SITE,
> MODEL_NS_MMQ_2SITE, MODEL_MMQ_CR72, MODEL_CR72, MODEL_B14,
> MODEL_NS_MMQ_3SITE_LINEAR]
> + expected_result = [MODEL_R2EFF, MODEL_NOREX, MODEL_B14, MODEL_CR72,
> MODEL_MMQ_CR72, MODEL_NS_MMQ_2SITE, MODEL_NS_MMQ_3SITE_LINEAR,
> MODEL_NS_MMQ_3SITE]
> +
> + ## Test the return.
> + self.assertEqual(sort_models(models=self_models), expected_result)
> +
>
>
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