tum merge branch #221
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tum merge branch #221
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- Stochastic optimization with stochastic constraints implementation - Tested it for "column simulation code". Graphs and other detailts in the shared document - ALso implemented a method to perform stochastic optimisation when design variables directly appear in the objective and it is not differntiable. (Variational Objective VO.py)
…ion part. Note that it is not modular completely. Just for ref.
…onSolver' into Calibration_Optimisation_HydrationSolver
# Conflicts: # environment.yml # lebedigital/simulation/precast_column.py # tests/demonstrator_scripts/test_column_simulation.py
…monstrator scripts updated
…corporated in the demonstrator_scripts and snakemake accordingly updated. The tests for the model learning/calibration routines are not properly tested yet. Same with optimization. Also the some scripts doesnt have docstring, plus testing lines here and there. Important thing is they work.
joergfunger
reviewed
Mar 20, 2024
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What would be the files to execute in order to see what is implemented (test files, examples?). I usually try to start a review by looking at those to see how I can use the code, but I struggle in the 120! new files to find the right entry point. Also, the test files in demonstrator_calibration are not passing, they are removed from the automatic tests, but do not pass on my machine either. As for the paper, we maybe do not need to compile the paper, but it would be great to have a pipeline that allows to understand how the results/figures have been created. Is there something like that implemented?
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Hello,
I merged with the main and added our scripts. Please complete the pull whenever time permits.