1- % arPEtabSelect (venvActPath, yaml, limit, estimRoutine)
1+ % arPEtabSelect_old (venvActPath, yaml, limit, estimRoutine)
22%
33% Run model selection using PEtab-select (https://github.com/PEtab-dev/petab_select)
4- % Requires installation of the petab_select Python3 package. arPEtabSelect
4+ % Requires installation of the petab_select Python3 package. arPEtabSelect_old
55% uses the command line interface (CLI).
66%
77% [venvActPath] Path to a python virtual environment (venv) activation
2424% initial guess for all estimated parameters and additionally perform
2525% multi-start optimization with 20 runs:
2626%
27- % arPEtabSelect ('~/d2d_python_venv/bin/activate', ...
27+ % arPEtabSelect_old ('~/d2d_python_venv/bin/activate', ...
2828% '~/test_cases/0001/petab_select_problem',...
2929% 3,
3030% 'ar.p(ar.qFit == 1) = 0.3; arFit; arFitLHS(20)')
3333% (Leave empty initialModel & iterationCtr. Those are internal arguments
3434% to allow for recursive function call)
3535
36- function arPEtabSelect (venvActPath , yaml , limit , estimRoutine , initialModel , iterationCtr )
36+ function arPEtabSelect_old (venvActPath , yaml , limit , estimRoutine , initialModel , iterationCtr )
3737if ~exist(' iterationCtr' ) || isempty(iterationCtr )
3838 iterationCtr = 1 ;
3939end
@@ -85,7 +85,7 @@ function arPEtabSelect(venvActPath, yaml, limit, estimRoutine, initialModel, ite
8585end
8686
8787%% Call PEtab-select to generate candidate models
88- fprintf(' arPEtabSelect : Generating candidate models...\n ' )
88+ fprintf(' arPEtabSelect_old : Generating candidate models...\n ' )
8989syscom = [initstr ,...
9090 ' petab_select candidates ' , ...
9191 ' -y ' , yaml , ...
@@ -112,11 +112,11 @@ function arPEtabSelect(venvActPath, yaml, limit, estimRoutine, initialModel, ite
112112nModels = size(CandidateModels ,2 );
113113
114114if nModels < 1
115- fprintf(' arPEtabSelect : Finished after iteration %i - no (more) candidate models found.\n ' , iterationCtr - 1 )
115+ fprintf(' arPEtabSelect_old : Finished after iteration %i - no (more) candidate models found.\n ' , iterationCtr - 1 )
116116 terminateFlag = 1 ;
117117end
118118if terminateFlag == 0
119- fprintf(' arPEtabSelect : Calibrating candidate models...\n ' )
119+ fprintf(' arPEtabSelect_old : Calibrating candidate models...\n ' )
120120
121121 for jModel = 1 : nModels
122122 % Load & compile
@@ -214,7 +214,7 @@ function arPEtabSelect(venvActPath, yaml, limit, estimRoutine, initialModel, ite
214214 currentItCrit = currentIt .criteria.(SelectionProblem .criterion );
215215
216216 if round(currentItCrit ,4 ) > round(prevItCrit ,4 )
217- fprintf(' arPEtabSelect : Finished after iteration %i - criterion worse than in iteration %i .\n ' , iterationCtr , iterationCtr - 1 )
217+ fprintf(' arPEtabSelect_old : Finished after iteration %i - criterion worse than in iteration %i .\n ' , iterationCtr , iterationCtr - 1 )
218218 terminateFlag = 1 ;
219219 end
220220 end
@@ -238,6 +238,6 @@ function arPEtabSelect(venvActPath, yaml, limit, estimRoutine, initialModel, ite
238238end
239239
240240%% Next iteration
241- fprintf(' arPEtabSelect : Iteration %i complete. Continuing with next iteration\n ' ,iterationCtr )
242- arPEtabSelect (venvActPath , yaml , limit , estimRoutine , CalibYamlOut ,iterationCtr+1)
241+ fprintf(' arPEtabSelect_old : Iteration %i complete. Continuing with next iteration\n ' ,iterationCtr )
242+ arPEtabSelect_old (venvActPath , yaml , limit , estimRoutine , CalibYamlOut ,iterationCtr+1)
243243end
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