From 28cc8c7980007c2f0d51e44c4723a89638658b90 Mon Sep 17 00:00:00 2001 From: tinosulzer Date: Wed, 17 Apr 2024 04:04:50 +0000 Subject: [PATCH] Generated from sources --- ...TimeBuildModelLithiumPlating.time_setup_model.json | 2 +- ...BuildModelLossActiveMaterial.time_setup_model.json | 2 +- ...tions.TimeBuildModelParticle.time_setup_model.json | 2 +- ...el_options.TimeBuildModelSEI.time_setup_model.json | 2 +- ...ns.TimeBuildModelSurfaceForm.time_setup_model.json | 2 +- ...ptions.TimeBuildModelThermal.time_setup_model.json | 2 +- ...ions.TimeSolveLithiumPlating.time_solve_model.json | 2 +- ....TimeSolveLossActiveMaterial.time_solve_model.json | 2 +- ...el_options.TimeSolveParticle.time_solve_model.json | 2 +- ...t_model_options.TimeSolveSEI.time_solve_model.json | 2 +- ...options.TimeSolveSurfaceForm.time_solve_model.json | 2 +- ...del_options.TimeSolveThermal.time_solve_model.json | 2 +- ...FNSimulationCCCV.mem_setup_DFN_simulationCCCV.json | 2 +- ...FNSimulationGITT.mem_setup_DFN_simulationGITT.json | 2 +- ...PMSimulationCCCV.mem_setup_SPM_simulationCCCV.json | 2 +- ...PMSimulationGITT.mem_setup_SPM_simulationGITT.json | 2 +- ...rks.MemCreateExpression.mem_create_expression.json | 2 +- ...arks.MemDiscretiseModel.mem_create_expression.json | 2 +- ..._benchmarks.MemDiscretiseModel.mem_discretise.json | 2 +- ...enchmarks.MemDiscretiseModel.mem_parameterise.json | 2 +- ...ks.MemParameteriseModel.mem_create_expression.json | 2 +- ...chmarks.MemParameteriseModel.mem_parameterise.json | 2 +- ...enchmarks.MemSolveModel.mem_create_expression.json | 2 +- ..._unit_benchmarks.MemSolveModel.mem_discretise.json | 2 +- ...nit_benchmarks.MemSolveModel.mem_parameterise.json | 2 +- ...emory_unit_benchmarks.MemSolveModel.mem_solve.json | 2 +- .../scikit-fem/sympy/tqdm/wget/summary.json | 2 +- ...p_models_and_sims.TimeBuildDFN.time_setup_DFN.json | 2 +- ...eBuildDFNSimulation.time_setup_DFN_simulation.json | 2 +- ...p_models_and_sims.TimeBuildSPM.time_setup_SPM.json | 2 +- ...eBuildSPMSimulation.time_setup_SPM_simulation.json | 2 +- ...models_and_sims.TimeBuildSPMe.time_setup_SPMe.json | 2 +- ...uildSPMeSimulation.time_setup_SPMe_simulation.json | 2 +- ...me_sims_experiments.TimeSimulation.time_setup.json | 2 +- ...me_sims_experiments.TimeSimulation.time_solve.json | 2 +- ...me_solve_models.TimeSolveDFN.time_solve_model.json | 2 +- ...me_solve_models.TimeSolveSPM.time_solve_model.json | 2 +- ...e_solve_models.TimeSolveSPMe.time_solve_model.json | 2 +- ...s.TimeCreateExpression.time_create_expression.json | 2 +- ...ks.TimeDiscretiseModel.time_create_expression.json | 2 +- ...enchmarks.TimeDiscretiseModel.time_discretise.json | 2 +- ...chmarks.TimeDiscretiseModel.time_parameterise.json | 2 +- ....TimeParameteriseModel.time_create_expression.json | 2 +- ...marks.TimeParameteriseModel.time_parameterise.json | 2 +- ...chmarks.TimeSolveModel.time_create_expression.json | 2 +- ...nit_benchmarks.TimeSolveModel.time_discretise.json | 2 +- ...t_benchmarks.TimeSolveModel.time_parameterise.json | 2 +- .../unit_benchmarks.TimeSolveModel.time_solve.json | 2 +- ...TimeBuildModelLithiumPlating.time_setup_model.json | 2 +- ...BuildModelLossActiveMaterial.time_setup_model.json | 2 +- ...tions.TimeBuildModelParticle.time_setup_model.json | 2 +- ...el_options.TimeBuildModelSEI.time_setup_model.json | 2 +- ...ns.TimeBuildModelSurfaceForm.time_setup_model.json | 2 +- ...ptions.TimeBuildModelThermal.time_setup_model.json | 2 +- ...ions.TimeSolveLithiumPlating.time_solve_model.json | 2 +- ....TimeSolveLossActiveMaterial.time_solve_model.json | 2 +- ...el_options.TimeSolveParticle.time_solve_model.json | 2 +- ...t_model_options.TimeSolveSEI.time_solve_model.json | 2 +- ...options.TimeSolveSurfaceForm.time_solve_model.json | 2 +- ...del_options.TimeSolveThermal.time_solve_model.json | 2 +- ...FNSimulationCCCV.mem_setup_DFN_simulationCCCV.json | 2 +- ...FNSimulationGITT.mem_setup_DFN_simulationGITT.json | 2 +- ...PMSimulationCCCV.mem_setup_SPM_simulationCCCV.json | 2 +- ...PMSimulationGITT.mem_setup_SPM_simulationGITT.json | 2 +- ...rks.MemCreateExpression.mem_create_expression.json | 2 +- ...arks.MemDiscretiseModel.mem_create_expression.json | 2 +- ..._benchmarks.MemDiscretiseModel.mem_discretise.json | 2 +- ...enchmarks.MemDiscretiseModel.mem_parameterise.json | 2 +- ...ks.MemParameteriseModel.mem_create_expression.json | 2 +- ...chmarks.MemParameteriseModel.mem_parameterise.json | 2 +- ...enchmarks.MemSolveModel.mem_create_expression.json | 2 +- ..._unit_benchmarks.MemSolveModel.mem_discretise.json | 2 +- ...nit_benchmarks.MemSolveModel.mem_parameterise.json | 2 +- ...emory_unit_benchmarks.MemSolveModel.mem_solve.json | 2 +- .../scikit-fem/sympy/tqdm/wget/summary.json | 2 +- ...p_models_and_sims.TimeBuildDFN.time_setup_DFN.json | 2 +- ...eBuildDFNSimulation.time_setup_DFN_simulation.json | 2 +- ...p_models_and_sims.TimeBuildSPM.time_setup_SPM.json | 2 +- ...eBuildSPMSimulation.time_setup_SPM_simulation.json | 2 +- ...models_and_sims.TimeBuildSPMe.time_setup_SPMe.json | 2 +- ...uildSPMeSimulation.time_setup_SPMe_simulation.json | 2 +- ...me_sims_experiments.TimeSimulation.time_setup.json | 2 +- ...me_sims_experiments.TimeSimulation.time_solve.json | 2 +- ...me_solve_models.TimeSolveDFN.time_solve_model.json | 2 +- ...me_solve_models.TimeSolveSPM.time_solve_model.json | 2 +- ...e_solve_models.TimeSolveSPMe.time_solve_model.json | 2 +- ...s.TimeCreateExpression.time_create_expression.json | 2 +- ...ks.TimeDiscretiseModel.time_create_expression.json | 2 +- ...enchmarks.TimeDiscretiseModel.time_discretise.json | 2 +- ...chmarks.TimeDiscretiseModel.time_parameterise.json | 2 +- ....TimeParameteriseModel.time_create_expression.json | 2 +- ...marks.TimeParameteriseModel.time_parameterise.json | 2 +- ...chmarks.TimeSolveModel.time_create_expression.json | 2 +- ...nit_benchmarks.TimeSolveModel.time_discretise.json | 2 +- ...t_benchmarks.TimeSolveModel.time_parameterise.json | 2 +- .../unit_benchmarks.TimeSolveModel.time_solve.json | 2 +- ...TimeBuildModelLithiumPlating.time_setup_model.json | 2 +- ...BuildModelLossActiveMaterial.time_setup_model.json | 2 +- ...tions.TimeBuildModelParticle.time_setup_model.json | 2 +- ...el_options.TimeBuildModelSEI.time_setup_model.json | 2 +- ...ns.TimeBuildModelSurfaceForm.time_setup_model.json | 2 +- ...ptions.TimeBuildModelThermal.time_setup_model.json | 2 +- ...ions.TimeSolveLithiumPlating.time_solve_model.json | 2 +- ....TimeSolveLossActiveMaterial.time_solve_model.json | 2 +- ...el_options.TimeSolveParticle.time_solve_model.json | 2 +- ...t_model_options.TimeSolveSEI.time_solve_model.json | 2 +- ...options.TimeSolveSurfaceForm.time_solve_model.json | 2 +- ...del_options.TimeSolveThermal.time_solve_model.json | 2 +- ...FNSimulationCCCV.mem_setup_DFN_simulationCCCV.json | 2 +- ...FNSimulationGITT.mem_setup_DFN_simulationGITT.json | 2 +- ...PMSimulationCCCV.mem_setup_SPM_simulationCCCV.json | 2 +- ...PMSimulationGITT.mem_setup_SPM_simulationGITT.json | 2 +- ...rks.MemCreateExpression.mem_create_expression.json | 2 +- ...arks.MemDiscretiseModel.mem_create_expression.json | 2 +- ..._benchmarks.MemDiscretiseModel.mem_discretise.json | 2 +- ...enchmarks.MemDiscretiseModel.mem_parameterise.json | 2 +- ...ks.MemParameteriseModel.mem_create_expression.json | 2 +- ...chmarks.MemParameteriseModel.mem_parameterise.json | 2 +- ...enchmarks.MemSolveModel.mem_create_expression.json | 2 +- ..._unit_benchmarks.MemSolveModel.mem_discretise.json | 2 +- ...nit_benchmarks.MemSolveModel.mem_parameterise.json | 2 +- ...emory_unit_benchmarks.MemSolveModel.mem_solve.json | 2 +- ...p_models_and_sims.TimeBuildDFN.time_setup_DFN.json | 2 +- ...eBuildDFNSimulation.time_setup_DFN_simulation.json | 2 +- ...p_models_and_sims.TimeBuildSPM.time_setup_SPM.json | 2 +- ...eBuildSPMSimulation.time_setup_SPM_simulation.json | 2 +- ...models_and_sims.TimeBuildSPMe.time_setup_SPMe.json | 2 +- ...uildSPMeSimulation.time_setup_SPMe_simulation.json | 2 +- ...me_sims_experiments.TimeSimulation.time_setup.json | 2 +- ...me_sims_experiments.TimeSimulation.time_solve.json | 2 +- ...me_solve_models.TimeSolveDFN.time_solve_model.json | 2 +- ...me_solve_models.TimeSolveSPM.time_solve_model.json | 2 +- ...e_solve_models.TimeSolveSPMe.time_solve_model.json | 2 +- ...s.TimeCreateExpression.time_create_expression.json | 2 +- ...ks.TimeDiscretiseModel.time_create_expression.json | 2 +- ...enchmarks.TimeDiscretiseModel.time_discretise.json | 2 +- ...chmarks.TimeDiscretiseModel.time_parameterise.json | 2 +- ....TimeParameteriseModel.time_create_expression.json | 2 +- ...marks.TimeParameteriseModel.time_parameterise.json | 2 +- ...chmarks.TimeSolveModel.time_create_expression.json | 2 +- ...nit_benchmarks.TimeSolveModel.time_discretise.json | 2 +- ...t_benchmarks.TimeSolveModel.time_parameterise.json | 2 +- .../unit_benchmarks.TimeSolveModel.time_solve.json | 2 +- index.json | 2 +- info.json | 2 +- regressions.json | 2 +- regressions.xml | 11 +---------- 147 files changed, 147 insertions(+), 156 deletions(-) diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLithiumPlating.time_setup_model.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLithiumPlating.time_setup_model.json index 84a14b512..e53124bd9 100644 --- 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newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model.json index d9476503d..abbd0a61c 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model.json +++ 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b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV.json index 681db9ab6..67bb29862 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV.json @@ -1 +1 @@ -[[17188, [768.0, 768.0]], [17217, [768.0, 768.0]], [17236, [768.0, 768.0]], [17246, [768.0, 768.0]]] \ No newline at end of file +[[17176, [768.0, 768.0]], [17205, [768.0, 768.0]], [17223, [768.0, 768.0]], [17229, [768.0, 768.0]]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT.json index 681db9ab6..67bb29862 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT.json @@ -1 +1 @@ -[[17188, [768.0, 768.0]], [17217, [768.0, 768.0]], [17236, [768.0, 768.0]], [17246, [768.0, 768.0]]] \ No newline at end of file +[[17176, [768.0, 768.0]], [17205, [768.0, 768.0]], [17223, [768.0, 768.0]], [17229, [768.0, 768.0]]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemCreateExpression.mem_create_expression.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemCreateExpression.mem_create_expression.json index 60062defc..3cc0f12dd 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemCreateExpression.mem_create_expression.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemCreateExpression.mem_create_expression.json @@ -1 +1 @@ -[[17188, 344.0], [17217, 344.0], [17236, 344.0], [17246, 344.0]] \ No newline at end of file +[[17176, 344.0], [17205, 344.0], [17223, 344.0], [17229, 344.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_create_expression.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_create_expression.json index 60062defc..3cc0f12dd 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_create_expression.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_create_expression.json @@ -1 +1 @@ -[[17188, 344.0], [17217, 344.0], [17236, 344.0], [17246, 344.0]] \ No newline at end of file +[[17176, 344.0], [17205, 344.0], [17223, 344.0], [17229, 344.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json index 04ddd05eb..3a46be463 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json @@ -1 +1 @@ -[[17188, 328.0], [17217, 328.0], [17236, 328.0], [17246, 328.0]] \ No newline at end of file +[[17176, 328.0], [17205, 328.0], [17223, 328.0], [17229, 328.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_parameterise.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_parameterise.json index 24c94e3cc..c79ec8229 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_parameterise.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemDiscretiseModel.mem_parameterise.json @@ -1 +1 @@ -[[17188, 320.0], [17217, 320.0], [17236, 320.0], [17246, 320.0]] \ No newline at end of file +[[17176, 320.0], [17205, 320.0], [17223, 320.0], [17229, 320.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemParameteriseModel.mem_create_expression.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemParameteriseModel.mem_create_expression.json index 60062defc..3cc0f12dd 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemParameteriseModel.mem_create_expression.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemParameteriseModel.mem_create_expression.json @@ -1 +1 @@ -[[17188, 344.0], [17217, 344.0], [17236, 344.0], [17246, 344.0]] \ No newline at end of file +[[17176, 344.0], [17205, 344.0], [17223, 344.0], [17229, 344.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemParameteriseModel.mem_parameterise.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemParameteriseModel.mem_parameterise.json index 04ddd05eb..3a46be463 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemParameteriseModel.mem_parameterise.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemParameteriseModel.mem_parameterise.json @@ -1 +1 @@ -[[17188, 328.0], [17217, 328.0], [17236, 328.0], [17246, 328.0]] \ No newline at end of file +[[17176, 328.0], [17205, 328.0], [17223, 328.0], [17229, 328.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_create_expression.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_create_expression.json index 60062defc..3cc0f12dd 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_create_expression.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_create_expression.json @@ -1 +1 @@ -[[17188, 344.0], [17217, 344.0], [17236, 344.0], [17246, 344.0]] \ No newline at end of file +[[17176, 344.0], [17205, 344.0], [17223, 344.0], [17229, 344.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_discretise.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_discretise.json index 24c94e3cc..c79ec8229 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_discretise.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_discretise.json @@ -1 +1 @@ -[[17188, 320.0], [17217, 320.0], [17236, 320.0], [17246, 320.0]] \ No newline at end of file +[[17176, 320.0], [17205, 320.0], [17223, 320.0], [17229, 320.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_parameterise.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_parameterise.json index a0140ebc2..533f8c9d9 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_parameterise.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_parameterise.json @@ -1 +1 @@ -[[17188, 312.0], [17217, 312.0], [17236, 312.0], [17246, 312.0]] \ No newline at end of file +[[17176, 312.0], [17205, 312.0], [17223, 312.0], [17229, 312.0]] \ No newline at end of file diff --git a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_solve.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_solve.json index 04ddd05eb..3a46be463 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_solve.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemSolveModel.mem_solve.json @@ -1 +1 @@ -[[17188, 328.0], [17217, 328.0], [17236, 328.0], [17246, 328.0]] \ No newline at end of file +[[17176, 328.0], [17205, 328.0], [17223, 328.0], [17229, 328.0]] \ No newline at end of file diff --git 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a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model.json index 27cd03d06..b1c465f6e 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model.json +++ 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a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelParticle.time_setup_model.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelParticle.time_setup_model.json @@ -1 +1 @@ -[[15398, [0.27184407299989743, 0.2197918444999516, 0.2653036090001706, 0.3183539069999881, 0.5667603504999761, 0.48121249249993525, 0.5427005994999945, 0.5988689065000301]], [15442, [0.32375249049999866, 0.2623167505000481, 0.3159630910000999, 0.3820170424999958, 0.7006376504999139, 0.57325937600001, 0.6466166825000528, 0.7109174615000313]], [15463, [0.29971700900017595, 0.24326818299999786, 0.2951694309998061, 0.35027342049988874, 0.6375157314998887, 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b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelSEI.time_setup_model.json index a689014ab..c2e25b338 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelSEI.time_setup_model.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelSEI.time_setup_model.json @@ -1 +1 @@ -[[15398, [0.2731561840000154, 0.2785846335000599, 0.3346821055000362, 0.3110045315000036, 0.3301172854999379, 0.3325654025000233, 0.32614217500005793, 0.5699084139999684, 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a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelSurfaceForm.time_setup_model.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelSurfaceForm.time_setup_model.json @@ -1 +1 @@ -[[15398, [0.273789792499997, 0.30861247050000884, 0.3069511414999795, 0.5707040180000149, 0.6717837254998358, 0.6684384845000011]], [15442, [0.33495842249976704, 0.37094103550001023, 0.370630766500085, 0.7051513560000444, 0.8337150349998979, 0.8240536870000028]], [15463, [0.2975092195001139, 0.3342495949997897, 0.3332001544999912, 0.6359118250001075, 0.7483993394999402, 0.7386435170001278]], [15515, [0.2949162615000205, 0.33300194150012885, 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a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelThermal.time_setup_model.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelThermal.time_setup_model.json @@ -1 +1 @@ -[[15398, [0.2726794639999639, 0.3199617234999437, 0.4783512729999302, 0.5678154519999623, 0.7251484090000417, 0.8099721019999606]], [15442, [0.333792026999987, 0.3878636959998403, 0.5815348754999832, 0.7029235824999205, 0.907140561999995, 1.0007782975000055]], [15463, [0.29857798949996095, 0.34918661449995625, 0.5266823460000865, 0.6357761415000596, 0.8150398135001069, 0.9094091495001067]], [15515, [0.2932503370000177, 0.34426334949989723, 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a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveSurfaceForm.time_solve_model.json +++ b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveSurfaceForm.time_solve_model.json @@ -1 +1 @@ -[[15398, [0.022476321249996545, 0.06872174950007093, 0.05455259649988875, null, 0.07903517349996037, 0.09172162300001219, 0.5291165980000869, 0.43086898149982744, 0.38466521099996953, 0.4955349815001, 0.5853230244999281, 0.49863712900003065]], [15442, [0.04097628450006141, 0.07523676800002477, 0.06580863250002267, null, 0.0923170690000461, 0.10135951649994013, 0.6155192209999427, 0.4591861400000994, 0.46291249799998013, 0.5449895784998944, 0.6979732464999984, 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a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveThermal.time_solve_model.json b/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveThermal.time_solve_model.json index da4ec8c06..46e07c707 100644 --- a/graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveThermal.time_solve_model.json +++ 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at end of file diff --git a/graphs/summary/different_model_options.TimeBuildModelSEI.time_setup_model.json b/graphs/summary/different_model_options.TimeBuildModelSEI.time_setup_model.json index 0807ace38..a47a34f66 100644 --- a/graphs/summary/different_model_options.TimeBuildModelSEI.time_setup_model.json +++ b/graphs/summary/different_model_options.TimeBuildModelSEI.time_setup_model.json @@ -1 +1 @@ -[[15398, 0.4422316925398338], [15442, 0.5324600727175383], [15463, 0.4809472638218702], [15515, 0.4794947688526726], [15544, 0.37931405307074345], [15598, 0.7188386687642467], [15606, 0.3828007925363346], [15619, 0.37402725935407044], [15638, 0.38049490342819614], [15655, 0.38054466045633634], [15677, 0.37544101997179785], [15683, 0.3834568146336364], [15737, 0.3721711172563058], [15767, 0.3745291580894995], [15781, 0.38092670105256493], [15821, 0.3792614905240597], [15835, 0.37419055802913087], [15849, 0.3804909550551579], [15890, 0.38235256873255236], [15902, 0.3766529192771421], 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b/graphs/summary/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json index 35035861c..ac344c1d5 100644 --- a/graphs/summary/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json +++ b/graphs/summary/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json @@ -1 +1 @@ -[[15398, 192.0], [15442, 192.0], [15463, 192.0], [15515, 192.0], [15544, 192.0], [15598, 192.0], [15606, 192.0], [15619, 192.0], [15638, 192.0], [15655, 192.0], [15677, 192.0], [15683, 192.0], [15737, 192.0], [15767, 192.0], [15781, 192.0], [15821, 192.0], [15835, 192.0], [15849, 192.0], [15890, 192.0], [15902, 192.0], [15904, 192.0], [15909, 192.0], [15939, 192.0], [15966, 192.0], [16011, 192.0], [16016, 192.0], [16026, 192.0], [16069, 192.0], [16072, 192.0], [16081, 192.0], [16083, 192.0], [16103, 192.0], [16134, 192.0], [16140, 192.0], [16146, 192.0], [16164, 192.0], [16165, 192.0], [16182, 192.0], [16203, 192.0], [16257, 192.0], [16278, 192.0], [16304, 192.0], [16346, 192.0], [16351, 192.0], 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"branch": ["develop"]}, "graph_param_list": [{"machine": "GitHubRunner", "python": "3.8", "numpy": "", "casadi": "", "wget": "", "cmake": "", "anytree": "", "autograd": "", "scikit-fem": "", "imageio": "", "pybtex": "", "sympy": "", "bpx": "", "tqdm": "", "matplotlib": "", "env-LD_LIBRARY_PATH": "/home/runner/.local/lib", "branch": "develop"}, {"machine": "GitHubRunner", "python": "3.12", "numpy": "", "casadi": "", "wget": "", "cmake": "", "anytree": "", "autograd": "", "scikit-fem": "", "imageio": "", "pybtex": "", "sympy": "", "bpx": "", "tqdm": "", "matplotlib": "", "env-LD_LIBRARY_PATH": "/home/runner/.local/lib", "branch": "develop"}], "benchmarks": {"different_model_options.TimeBuildModelLithiumPlating.time_setup_model": {"code": "class TimeBuildModelLithiumPlating:\n def time_setup_model(self, model, params):\n build_model(\"OKane2022\", model, \"lithium plating\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelLithiumPlating.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'none'", "'irreversible'", "'reversible'", "'partially reversible'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b7715f9cd1f28f249a74a4036dff5452cde2f077c92024efae0ebb5545c3edc0", "warmup_time": -1}, "different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model": {"code": "class TimeBuildModelLossActiveMaterial:\n def time_setup_model(self, model, params):\n build_model(\"Ai2020\", model, \"loss of active material\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'none'", "'stress-driven'", "'reaction-driven'", "'stress and reaction-driven'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "478c22dec000f10359afc36541c1e78f5e93eaaddf53c542d8b86433b7bb0faa", "warmup_time": -1}, "different_model_options.TimeBuildModelParticle.time_setup_model": {"code": "class TimeBuildModelParticle:\n def time_setup_model(self, model, params):\n build_model(\"Marquis2019\", model, \"particle\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelParticle.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'Fickian diffusion'", "'uniform profile'", "'quadratic profile'", "'quartic profile'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "7a2b728d79432d8ed22c8c8680ee758da0ceffe378a6235c09e3614caf624ba6", "warmup_time": -1}, "different_model_options.TimeBuildModelSEI.time_setup_model": {"code": "class TimeBuildModelSEI:\n def time_setup_model(self, model, params):\n build_model(\"Marquis2019\", model, \"SEI\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelSEI.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'none'", "'constant'", "'reaction limited'", "'solvent-diffusion limited'", "'electron-migration limited'", "'interstitial-diffusion limited'", "'ec reaction limited'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "72052d17c62d75ef9abff93a57e2fe2b8776f153d13317ba41c9304374cf3241", "warmup_time": -1}, "different_model_options.TimeBuildModelSurfaceForm.time_setup_model": {"code": "class TimeBuildModelSurfaceForm:\n def time_setup_model(self, model, params):\n build_model(\"Marquis2019\", model, \"surface form\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelSurfaceForm.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'false'", "'differential'", "'algebraic'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "0ae12c41f1ed5675d959bbc049a400985cf3ede740ee73c11075d7aa10f34e49", "warmup_time": -1}, "different_model_options.TimeBuildModelThermal.time_setup_model": {"code": "class TimeBuildModelThermal:\n def time_setup_model(self, model, params):\n build_model(\"Marquis2019\", model, \"thermal\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelThermal.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'isothermal'", "'lumped'", "'x-full'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "a350e87e4e8a8f35aeb9951c78518a60da6177951f7d81d09f3d3088ec055cfd", "warmup_time": -1}, "different_model_options.TimeSolveLithiumPlating.time_solve_model": {"code": "class TimeSolveLithiumPlating:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(\n self, \"OKane2022\", model, \"lithium plating\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveLithiumPlating.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'none'", "'irreversible'", "'reversible'", "'partially reversible'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b1d66b1656476391fd4f4a356b350bff995917103286317dffc403f2b8a90fbe", "warmup_time": -1}, "different_model_options.TimeSolveLossActiveMaterial.time_solve_model": {"code": "class TimeSolveLossActiveMaterial:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(\n self, \"Ai2020\", model, \"loss of active material\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveLossActiveMaterial.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'none'", "'stress-driven'", "'reaction-driven'", "'stress and reaction-driven'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "d5e240fe84c4acc6966e4a3c4fd3b541659eb242ea36508a92c57a0ed958ceb7", "warmup_time": -1}, "different_model_options.TimeSolveParticle.time_solve_model": {"code": "class TimeSolveParticle:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(\n self, \"Marquis2019\", model, \"particle\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveParticle.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'Fickian diffusion'", "'uniform profile'", "'quadratic profile'", "'quartic profile'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "0fb24c2046b35533f49c825e1f5dbc32c30266f30c6ffc64504048df0f6182f7", "warmup_time": -1}, "different_model_options.TimeSolveSEI.time_solve_model": {"code": "class TimeSolveSEI:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(self, \"Marquis2019\", model, \"SEI\", params, solver_class)", "min_run_count": 2, "name": "different_model_options.TimeSolveSEI.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'none'", "'constant'", "'reaction limited'", "'solvent-diffusion limited'", "'electron-migration limited'", "'interstitial-diffusion limited'", "'ec reaction limited'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "53dd91bc8ea837141f3ff3ec6ae6fc8310b0ebfae08e6bbd8a1f692efb7d2f57", "warmup_time": -1}, "different_model_options.TimeSolveSurfaceForm.time_solve_model": {"code": "class TimeSolveSurfaceForm:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n if (model, params, solver_class) == (\n pybamm.lithium_ion.SPM,\n \"differential\",\n pybamm.IDAKLUSolver,\n ):\n raise NotImplementedError\n SolveModel.solve_setup(\n self, \"Marquis2019\", model, \"surface form\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveSurfaceForm.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'false'", "'differential'", "'algebraic'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b025abdf6ccd9f47388fd29f0bfc0fc5490bc48eb9c277ba6172b8064339cd15", "warmup_time": -1}, "different_model_options.TimeSolveThermal.time_solve_model": {"code": "class TimeSolveThermal:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(\n self, \"Marquis2019\", model, \"thermal\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveThermal.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'isothermal'", "'lumped'", "'x-full'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b8015ca16fbe5a13c5d7b34926d92538382b9575c674f2ef78d923e8e603f5cb", "warmup_time": -1}, "memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV": {"code": "class MemDFNSimulationCCCV:\n def mem_setup_DFN_simulationCCCV(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.DFN()\n exp = pybamm.Experiment(\n [\n \"Discharge at C/5 for 10 hours or until 3.3 V\",\n \"Rest for 1 hour\",\n \"Charge at 1 A until 4.1 V\",\n \"Hold at 4.1 V until 10 mA\",\n \"Rest for 1 hour\",\n ]\n )\n self.sim = pybamm.Simulation(\n self.model, parameter_values=self.param, experiment=exp\n )\n return self.sim\n\n def setup(self, _params):\n set_random_seed()", "name": "memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "51ef613d1be3b3c97e5cff911f9a71ebfec58bb3741293e2b387b6aec0c55d88"}, "memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT": {"code": "class MemDFNSimulationGITT:\n def mem_setup_DFN_simulationGITT(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n exp = pybamm.Experiment(\n [(\"Discharge at C/20 for 1 hour\", \"Rest for 1 hour\")] * 20\n )\n self.sim = pybamm.Simulation(\n self.model, parameter_values=self.param, experiment=exp\n )\n return self.sim\n\n def setup(self, _params):\n set_random_seed()", "name": "memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "d4b526c693f63c0dca2afa82bc58c24d52b7884ae618e298aff74e44864d84e4"}, "memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV": {"code": "class MemSPMSimulationCCCV:\n def mem_setup_SPM_simulationCCCV(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n exp = pybamm.Experiment(\n [\n \"Discharge at C/5 for 10 hours or until 3.3 V\",\n \"Rest for 1 hour\",\n \"Charge at 1 A until 4.1 V\",\n \"Hold at 4.1 V until 10 mA\",\n \"Rest for 1 hour\",\n ]\n )\n self.sim = pybamm.Simulation(\n self.model, parameter_values=self.param, experiment=exp\n )\n return self.sim\n\n def setup(self, _params):\n set_random_seed()", "name": "memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "29109fbfa71fad4a6f5d5b2f57bb2c9d364602f218e44f5f537529aae441a717"}, "memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT": {"code": "class MemSPMSimulationGITT:\n def mem_setup_SPM_simulationGITT(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n exp = pybamm.Experiment(\n [(\"Discharge at C/20 for 1 hour\", \"Rest for 1 hour\")] * 20\n )\n self.sim = pybamm.Simulation(\n self.model, parameter_values=self.param, experiment=exp\n )\n return self.sim\n\n def setup(self, _params):\n set_random_seed()", "name": "memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "c00f20a28b027b21fcddb41e38f4b6414026233b5484c1bc7a1ad2810fc0475f"}, "memory_unit_benchmarks.MemCreateExpression.mem_create_expression": {"code": "class MemCreateExpression:\n def mem_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n return self.model\n\n def setup(self):\n set_random_seed()", "name": "memory_unit_benchmarks.MemCreateExpression.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "3d6830c6c8132d74fbf54e206a2f784c514c86ad079aac662a24cb151775927f"}, "memory_unit_benchmarks.MemDiscretiseModel.mem_create_expression": {"code": "class MemCreateExpression:\n def mem_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n return self.model\n\nclass MemDiscretiseModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)", "name": "memory_unit_benchmarks.MemDiscretiseModel.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "1e1265e6812795c6b4638a8861b57dc14e9b3e21d54786009ba2f6ea6526eb99"}, "memory_unit_benchmarks.MemDiscretiseModel.mem_discretise": {"code": "class MemDiscretiseModel:\n def mem_discretise(self):\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n var_pts = {self.r: 20}\n mesh = pybamm.Mesh(self.geometry, submesh_types, var_pts)\n \n spatial_methods = {\"negative particle\": pybamm.FiniteVolume()}\n disc = pybamm.Discretisation(mesh, spatial_methods)\n disc.process_model(self.model)\n return disc\n\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)", "name": "memory_unit_benchmarks.MemDiscretiseModel.mem_discretise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "495195cd9a6ece265ad424338ffde8465bff6b401aff98f26bf908c480b58724"}, "memory_unit_benchmarks.MemDiscretiseModel.mem_parameterise": {"code": "class MemParameteriseModel:\n def mem_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n return param\n\nclass MemDiscretiseModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)", "name": "memory_unit_benchmarks.MemDiscretiseModel.mem_parameterise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "3193180de8abb381c009afe51426f5d20e7347c3b9761d1663a98425cce0c663"}, "memory_unit_benchmarks.MemParameteriseModel.mem_create_expression": {"code": "class MemCreateExpression:\n def mem_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n return self.model\n\nclass MemParameteriseModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)", "name": "memory_unit_benchmarks.MemParameteriseModel.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "862863fcd24f0545f40184ecdebd166445846c611afed20dcf90f68765c3cc0b"}, "memory_unit_benchmarks.MemParameteriseModel.mem_parameterise": {"code": "class MemParameteriseModel:\n def mem_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n return param\n\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)", "name": "memory_unit_benchmarks.MemParameteriseModel.mem_parameterise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "edad12bc03295b4e89366fc5cfb1ed396d7bb91d3f3c81c80c58aa1302e875c5"}, "memory_unit_benchmarks.MemSolveModel.mem_create_expression": {"code": "class MemCreateExpression:\n def mem_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n return self.model\n\nclass MemSolveModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n MemDiscretiseModel.mem_discretise(self)", "name": "memory_unit_benchmarks.MemSolveModel.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "16091c4e58d10d32014c88300ed1dcaf80b55cf5b10e264a66a1ea2b8837581e"}, "memory_unit_benchmarks.MemSolveModel.mem_discretise": {"code": "class MemDiscretiseModel:\n def mem_discretise(self):\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n var_pts = {self.r: 20}\n mesh = pybamm.Mesh(self.geometry, submesh_types, var_pts)\n \n spatial_methods = {\"negative particle\": pybamm.FiniteVolume()}\n disc = pybamm.Discretisation(mesh, spatial_methods)\n disc.process_model(self.model)\n return disc\n\nclass MemSolveModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n MemDiscretiseModel.mem_discretise(self)", "name": "memory_unit_benchmarks.MemSolveModel.mem_discretise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "34cbd7a52ecdcb0e943a83665c930436c4d296729f856ac0c74a38ebe551e0f9"}, "memory_unit_benchmarks.MemSolveModel.mem_parameterise": {"code": "class MemParameteriseModel:\n def mem_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n return param\n\nclass MemSolveModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n MemDiscretiseModel.mem_discretise(self)", "name": "memory_unit_benchmarks.MemSolveModel.mem_parameterise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "e4f639e8ddfb46ec7daa72247577a6c466daa157bef63aa013c20264f9da6a73"}, "memory_unit_benchmarks.MemSolveModel.mem_solve": {"code": "class MemSolveModel:\n def mem_solve(self):\n solver = pybamm.ScipySolver()\n t = np.linspace(0, 3600, 600)\n solver.solve(self.model, t)\n return solver\n\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n MemDiscretiseModel.mem_discretise(self)", "name": "memory_unit_benchmarks.MemSolveModel.mem_solve", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "a7b39a512b545d84bd7d5f0a6ed4d6901e6dc414da7e50ed43c6afa3abd62f0a"}, "time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN": {"code": "class TimeBuildDFN:\n def time_setup_DFN(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.DFN()\n self.param.process_model(self.model)\n compute_discretisation(self.model, self.param).process_model(self.model)\n\n def setup(self, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN", "number": 0, "param_names": ["parameter"], "params": [["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "0eee82eaa2ed6557bb7cec497b21c1595f4e2ab7f17c33cf98baa7acc53e6ef7", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildDFNSimulation.time_setup_DFN_simulation": {"code": "class TimeBuildDFNSimulation:\n def time_setup_DFN_simulation(self, with_experiment, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.DFN()\n if with_experiment:\n exp = pybamm.Experiment(\n [\n \"Discharge at 0.1C until 3.105 V\",\n ]\n )\n pybamm.Simulation(self.model, parameter_values=self.param, experiment=exp)\n else:\n pybamm.Simulation(self.model, parameter_values=self.param, C_rate=1)\n\n def setup(self, _with_experiment, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildDFNSimulation.time_setup_DFN_simulation", "number": 0, "param_names": ["with experiment", "parameter"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "041d84cc1adf4753d7f9652306ad60d0d6364fcc290e4736429f8e7c3c675a12", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPM.time_setup_SPM": {"code": "class TimeBuildSPM:\n def time_setup_SPM(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n self.param.process_model(self.model)\n compute_discretisation(self.model, self.param).process_model(self.model)\n\n def setup(self, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildSPM.time_setup_SPM", "number": 0, "param_names": ["parameter"], "params": [["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "d5778345d68fd67c043a3241f1764d8b6e007490765cb577f15dd6fe38347cad", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPMSimulation.time_setup_SPM_simulation": {"code": "class TimeBuildSPMSimulation:\n def time_setup_SPM_simulation(self, with_experiment, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n if with_experiment:\n exp = pybamm.Experiment(\n [\n \"Discharge at 0.1C until 3.105 V\",\n ]\n )\n pybamm.Simulation(self.model, parameter_values=self.param, experiment=exp)\n else:\n pybamm.Simulation(self.model, parameter_values=self.param, C_rate=1)\n\n def setup(self, _with_experiment, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildSPMSimulation.time_setup_SPM_simulation", "number": 0, "param_names": ["with experiment", "parameter"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "4af04a0ebcb83401d42904cefe3d57346161aa348bdafe191f95ec33fff21cec", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPMe.time_setup_SPMe": {"code": "class TimeBuildSPMe:\n def time_setup_SPMe(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPMe()\n self.param.process_model(self.model)\n compute_discretisation(self.model, self.param).process_model(self.model)\n\n def setup(self, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildSPMe.time_setup_SPMe", "number": 0, "param_names": ["parameter"], "params": [["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "970230e78bb53f069b2e13856e844504c8a106f98359e1d7ad09161d6d03c083", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPMeSimulation.time_setup_SPMe_simulation": {"code": "class TimeBuildSPMeSimulation:\n def time_setup_SPMe_simulation(self, with_experiment, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPMe()\n if with_experiment:\n exp = pybamm.Experiment(\n [\n \"Discharge at 0.1C until 3.105 V\",\n ]\n )\n pybamm.Simulation(self.model, parameter_values=self.param, experiment=exp)\n else:\n pybamm.Simulation(self.model, parameter_values=self.param, C_rate=1)\n\n def setup(self, _with_experiment, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildSPMeSimulation.time_setup_SPMe_simulation", "number": 0, "param_names": ["with experiment", "parameter"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "6f76c516f3fa71f22c3c769426712e12bc3c63681def5407f510a3d24fe28ebf", "warmup_time": -1}, "time_sims_experiments.TimeSimulation.time_setup": {"code": "class TimeSimulation:\n def time_setup(self, experiment, parameters, model_class, solver_class):\n param = pybamm.ParameterValues(parameters)\n model = model_class()\n solver = solver_class()\n exp = pybamm.Experiment(self.experiment_descriptions[experiment])\n pybamm.Simulation(model, parameter_values=param, experiment=exp, solver=solver)\n\n def setup(self, experiment, parameters, model_class, solver_class):\n set_random_seed()\n if (experiment, parameters, model_class, solver_class) == (\n \"GITT\",\n \"Marquis2019\",\n pybamm.lithium_ion.DFN,\n pybamm.CasadiSolver,\n ):\n raise NotImplementedError\n self.param = pybamm.ParameterValues(parameters)\n self.model = model_class()\n self.solver = solver_class()\n self.exp = pybamm.Experiment(self.experiment_descriptions[experiment])\n self.sim = pybamm.Simulation(\n self.model,\n parameter_values=self.param,\n experiment=self.exp,\n solver=self.solver,\n )", "min_run_count": 2, "name": "time_sims_experiments.TimeSimulation.time_setup", "number": 0, "param_names": ["experiment", "parameter", "model_class", "solver_class"], "params": [["'CCCV'", "'GITT'"], ["'Marquis2019'", "'Chen2020'"], ["", ""], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "f919a29c04da89b51fb66aa41294744b714b2d640df50debeff76b55023af868", "warmup_time": -1}, "time_sims_experiments.TimeSimulation.time_solve": {"code": "class TimeSimulation:\n def time_solve(self, _experiment, _parameters, _model_class, _solver_class):\n self.sim.solve()\n\n def setup(self, experiment, parameters, model_class, solver_class):\n set_random_seed()\n if (experiment, parameters, model_class, solver_class) == (\n \"GITT\",\n \"Marquis2019\",\n pybamm.lithium_ion.DFN,\n pybamm.CasadiSolver,\n ):\n raise NotImplementedError\n self.param = pybamm.ParameterValues(parameters)\n self.model = model_class()\n self.solver = solver_class()\n self.exp = pybamm.Experiment(self.experiment_descriptions[experiment])\n self.sim = pybamm.Simulation(\n self.model,\n parameter_values=self.param,\n experiment=self.exp,\n solver=self.solver,\n )", "min_run_count": 2, "name": "time_sims_experiments.TimeSimulation.time_solve", "number": 0, "param_names": ["experiment", "parameter", "model_class", "solver_class"], "params": [["'CCCV'", "'GITT'"], ["'Marquis2019'", "'Chen2020'"], ["", ""], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "6832512fe2709d359717d531b49d57f9b07241e3af646c02a9865a7e7b4c96ac", "warmup_time": -1}, "time_solve_models.TimeSolveDFN.time_solve_model": {"code": "class TimeSolveDFN:\n def time_solve_model(self, _solve_first, _parameters, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, solve_first, parameters, solver_class):\n set_random_seed()\n if (parameters, solver_class) == (\n \"ORegan2022\",\n pybamm.CasadiSolver,\n ):\n raise NotImplementedError\n self.solver = solver_class()\n self.model = pybamm.lithium_ion.DFN()\n c_rate = 1\n tmax = 4000 / c_rate\n nb_points = 500\n self.t_eval = np.linspace(0, tmax, nb_points)\n geometry = self.model.default_geometry\n \n # load parameter values and process model and geometry\n param = pybamm.ParameterValues(parameters)\n param.process_model(self.model)\n param.process_geometry(geometry)\n \n # set mesh\n var_pts = {\n \"x_n\": 20,\n \"x_s\": 20,\n \"x_p\": 20,\n \"r_n\": 30,\n \"r_p\": 30,\n \"y\": 10,\n \"z\": 10,\n }\n mesh = pybamm.Mesh(geometry, self.model.default_submesh_types, var_pts)\n \n # discretise model\n disc = pybamm.Discretisation(mesh, self.model.default_spatial_methods)\n disc.process_model(self.model)\n if solve_first:\n solve_model_once(self.model, self.solver, self.t_eval)", "min_run_count": 2, "name": "time_solve_models.TimeSolveDFN.time_solve_model", "number": 0, "param_names": ["solve first", "parameter", "solver_class"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Chen2020'", "'Ecker2015'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "f6d7b52e57b2a72e7ebdf55b8998c7f7e4ee88848570e445a0f7bd967d6d14be", "warmup_time": -1}, "time_solve_models.TimeSolveSPM.time_solve_model": {"code": "class TimeSolveSPM:\n def time_solve_model(self, _solve_first, _parameters, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, solve_first, parameters, solver_class):\n set_random_seed()\n self.solver = solver_class()\n self.model = pybamm.lithium_ion.SPM()\n c_rate = 1\n tmax = 4000 / c_rate\n nb_points = 500\n self.t_eval = np.linspace(0, tmax, nb_points)\n geometry = self.model.default_geometry\n \n # load parameter values and process model and geometry\n param = pybamm.ParameterValues(parameters)\n param.process_model(self.model)\n param.process_geometry(geometry)\n \n # set mesh\n var_pts = {\n \"x_n\": 20,\n \"x_s\": 20,\n \"x_p\": 20,\n \"r_n\": 30,\n \"r_p\": 30,\n \"y\": 10,\n \"z\": 10,\n }\n mesh = pybamm.Mesh(geometry, self.model.default_submesh_types, var_pts)\n \n # discretise model\n disc = pybamm.Discretisation(mesh, self.model.default_spatial_methods)\n disc.process_model(self.model)\n if solve_first:\n solve_model_once(self.model, self.solver, self.t_eval)", "min_run_count": 2, "name": "time_solve_models.TimeSolveSPM.time_solve_model", "number": 0, "param_names": ["solve first", "parameter", "solver_class"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ramadass2004'", "'Chen2020'", "'Ecker2015'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "f329b803e6760b144e33d59c3d34fa3d75fa6c26427168501d81c48156c62175", "warmup_time": -1}, "time_solve_models.TimeSolveSPMe.time_solve_model": {"code": "class TimeSolveSPMe:\n def time_solve_model(self, _solve_first, _parameters, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, solve_first, parameters, solver_class):\n set_random_seed()\n self.solver = solver_class()\n self.model = pybamm.lithium_ion.SPMe()\n c_rate = 1\n tmax = 4000 / c_rate\n nb_points = 500\n self.t_eval = np.linspace(0, tmax, nb_points)\n geometry = self.model.default_geometry\n \n # load parameter values and process model and geometry\n param = pybamm.ParameterValues(parameters)\n param.process_model(self.model)\n param.process_geometry(geometry)\n \n # set mesh\n var_pts = {\n \"x_n\": 20,\n \"x_s\": 20,\n \"x_p\": 20,\n \"r_n\": 30,\n \"r_p\": 30,\n \"y\": 10,\n \"z\": 10,\n }\n mesh = pybamm.Mesh(geometry, self.model.default_submesh_types, var_pts)\n \n # discretise model\n disc = pybamm.Discretisation(mesh, self.model.default_spatial_methods)\n disc.process_model(self.model)\n if solve_first:\n solve_model_once(self.model, self.solver, self.t_eval)", "min_run_count": 2, "name": "time_solve_models.TimeSolveSPMe.time_solve_model", "number": 0, "param_names": ["solve first", "parameter", "solver_class"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ramadass2004'", "'Chen2020'", "'Ecker2015'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "26110b628fab649e6153a529860b3104b379d3f288ca020d4321f489c8a38955", "warmup_time": -1}, "unit_benchmarks.TimeCreateExpression.time_create_expression": {"code": "class TimeCreateExpression:\n def time_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n\n def setup(self):\n set_random_seed()", "min_run_count": 2, "name": "unit_benchmarks.TimeCreateExpression.time_create_expression", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "79567e8fc10e82bb7efc93e89a5fa48101c5f63b2bcf09f9affa1daeaa660a7a", "warmup_time": -1}, "unit_benchmarks.TimeDiscretiseModel.time_create_expression": {"code": "class TimeCreateExpression:\n def time_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n\nclass TimeDiscretiseModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeDiscretiseModel.time_create_expression", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "53f64bb63b703ce09229d62a777fa5f21abf561c70430ff978cd6fce8363f76c", "warmup_time": -1}, "unit_benchmarks.TimeDiscretiseModel.time_discretise": {"code": "class TimeDiscretiseModel:\n def time_discretise(self):\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n var_pts = {self.r: 20}\n mesh = pybamm.Mesh(self.geometry, submesh_types, var_pts)\n \n spatial_methods = {\"negative particle\": pybamm.FiniteVolume()}\n disc = pybamm.Discretisation(mesh, spatial_methods)\n disc.process_model(self.model)\n\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeDiscretiseModel.time_discretise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "82d1028bb6552573a282aead5ecf23b4c233624a98d553f417f9b632904cf779", "warmup_time": -1}, "unit_benchmarks.TimeDiscretiseModel.time_parameterise": {"code": "class TimeParameteriseModel:\n def time_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n\nclass TimeDiscretiseModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeDiscretiseModel.time_parameterise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "ef8b306be418ea6cffb6df7d95c34e6e4c058556b81285cfe00a85a746364e11", "warmup_time": -1}, "unit_benchmarks.TimeParameteriseModel.time_create_expression": {"code": "class TimeCreateExpression:\n def time_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n\nclass TimeParameteriseModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeParameteriseModel.time_create_expression", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "c9c6590d7ea983ffd2ec4a0beb7198254c9872b5d79fafe982b5575dcbf533ea", "warmup_time": -1}, "unit_benchmarks.TimeParameteriseModel.time_parameterise": {"code": "class TimeParameteriseModel:\n def time_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeParameteriseModel.time_parameterise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "2db8360d2edcfa78dd7840bfc00d24c0e9649c847253c89fe402671c262b1338", "warmup_time": -1}, "unit_benchmarks.TimeSolveModel.time_create_expression": {"code": "class TimeCreateExpression:\n def time_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n\nclass TimeSolveModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n TimeDiscretiseModel.time_discretise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeSolveModel.time_create_expression", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "7d5ffee2c28dcaa231b44408496fce54271121737b80dc5a7498beb92ab2b159", "warmup_time": -1}, "unit_benchmarks.TimeSolveModel.time_discretise": {"code": "class TimeDiscretiseModel:\n def time_discretise(self):\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n var_pts = {self.r: 20}\n mesh = pybamm.Mesh(self.geometry, submesh_types, var_pts)\n \n spatial_methods = {\"negative particle\": pybamm.FiniteVolume()}\n disc = pybamm.Discretisation(mesh, spatial_methods)\n disc.process_model(self.model)\n\nclass TimeSolveModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n TimeDiscretiseModel.time_discretise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeSolveModel.time_discretise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "a4e41d181f7a8ac4c6c873e0aafa291f45deb155ad92dc625301917565fe6bdc", "warmup_time": -1}, "unit_benchmarks.TimeSolveModel.time_parameterise": {"code": "class TimeParameteriseModel:\n def time_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n\nclass TimeSolveModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n TimeDiscretiseModel.time_discretise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeSolveModel.time_parameterise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "14eb896be95381d740fa3f69396eb480514a09da23f2525bce6c81124247ca72", "warmup_time": -1}, "unit_benchmarks.TimeSolveModel.time_solve": {"code": "class TimeSolveModel:\n def time_solve(self):\n solver = pybamm.ScipySolver()\n t = np.linspace(0, 3600, 600)\n solver.solve(self.model, t)\n\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n TimeDiscretiseModel.time_discretise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeSolveModel.time_solve", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "3b060ae2823c304802df15803cd5d845699526f2b740e5e252d5890f61967a01", "warmup_time": -1}}, "machines": {"GitHubRunner": {"machine": "GitHubRunner", "version": 1}}, "tags": {"v0.1.0": 3608, "v0.2.0": 4954, "v0.2.1": 5277, "v0.2.2": 5978, "v0.2.3": 6424, "v0.2.4": 6787, "v0.3.0": 7341, "v0.3.0-beta": 7278, "v0.4.0": 8395, "v21.08": 9196, "v21.10": 9482, "v21.11": 9853, "v21.12": 10002, "v21.9": 9368, "v22.1": 10214, "v22.10": 11902, "v22.11": 12279, "v22.11.1": 12410, "v22.12": 12476, "v22.2": 10274, "v22.3": 10401, "v22.4": 10493, "v22.5": 10654, "v22.6": 10795, "v22.7": 11122, "v22.8": 11338, "v22.9": 11580, "v23.1": 12625, "v23.2": 12908, "v23.3": 13243, "v23.4": 13393, "v23.4.1": 13405, "v23.5": 13982, "v23.5rc0": 13803, "v23.9": 15663, "v23.9rc0": 15357, "v23.9rc1": 15609, "v24.1": 16527, "v24.1rc0": 16153, "v24.1rc1": 16302, "v24.1rc2": 16434}, "pages": [["", "Grid view", "Display as a agrid"], ["summarylist", "List view", "Display as a list"], ["regressions", "Show regressions", "Display information about recent regressions"]]} \ No newline at end of file +{"project": "PyBaMM", "project_url": "https://www.pybamm.org/", "show_commit_url": "#", "hash_length": 8, "revision_to_hash": {"3608": "8afc8f94f75b6f0b51928f43819f9894d2b91020", "4954": "801492b250a6637554d99a4662a0d85c3354ceea", "5277": "105714c9748f7c7f3824411240ab583ac6c4973a", "5978": "eff587b12cd3e41b911c4665909f3d4ab8a8f50f", "6424": 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"casadi": "", "wget": "", "cmake": "", "anytree": "", "autograd": "", "scikit-fem": "", "imageio": "", "pybtex": "", "sympy": "", "bpx": "", "tqdm": "", "matplotlib": "", "env-LD_LIBRARY_PATH": "/home/runner/.local/lib", "branch": "develop"}, {"machine": "GitHubRunner", "python": "3.12", "numpy": "", "casadi": "", "wget": "", "cmake": "", "anytree": "", "autograd": "", "scikit-fem": "", "imageio": "", "pybtex": "", "sympy": "", "bpx": "", "tqdm": "", "matplotlib": "", "env-LD_LIBRARY_PATH": "/home/runner/.local/lib", "branch": "develop"}], "benchmarks": {"different_model_options.TimeBuildModelLithiumPlating.time_setup_model": {"code": "class TimeBuildModelLithiumPlating:\n def time_setup_model(self, model, params):\n build_model(\"OKane2022\", model, \"lithium plating\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelLithiumPlating.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'none'", "'irreversible'", "'reversible'", "'partially reversible'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b7715f9cd1f28f249a74a4036dff5452cde2f077c92024efae0ebb5545c3edc0", "warmup_time": -1}, "different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model": {"code": "class TimeBuildModelLossActiveMaterial:\n def time_setup_model(self, model, params):\n build_model(\"Ai2020\", model, \"loss of active material\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelLossActiveMaterial.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'none'", "'stress-driven'", "'reaction-driven'", "'stress and reaction-driven'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "478c22dec000f10359afc36541c1e78f5e93eaaddf53c542d8b86433b7bb0faa", "warmup_time": -1}, "different_model_options.TimeBuildModelParticle.time_setup_model": {"code": "class TimeBuildModelParticle:\n def time_setup_model(self, model, params):\n build_model(\"Marquis2019\", model, \"particle\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelParticle.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'Fickian diffusion'", "'uniform profile'", "'quadratic profile'", "'quartic profile'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "7a2b728d79432d8ed22c8c8680ee758da0ceffe378a6235c09e3614caf624ba6", "warmup_time": -1}, "different_model_options.TimeBuildModelSEI.time_setup_model": {"code": "class TimeBuildModelSEI:\n def time_setup_model(self, model, params):\n build_model(\"Marquis2019\", model, \"SEI\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelSEI.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'none'", "'constant'", "'reaction limited'", "'solvent-diffusion limited'", "'electron-migration limited'", "'interstitial-diffusion limited'", "'ec reaction limited'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "72052d17c62d75ef9abff93a57e2fe2b8776f153d13317ba41c9304374cf3241", "warmup_time": -1}, "different_model_options.TimeBuildModelSurfaceForm.time_setup_model": {"code": "class TimeBuildModelSurfaceForm:\n def time_setup_model(self, model, params):\n build_model(\"Marquis2019\", model, \"surface form\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelSurfaceForm.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'false'", "'differential'", "'algebraic'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "0ae12c41f1ed5675d959bbc049a400985cf3ede740ee73c11075d7aa10f34e49", "warmup_time": -1}, "different_model_options.TimeBuildModelThermal.time_setup_model": {"code": "class TimeBuildModelThermal:\n def time_setup_model(self, model, params):\n build_model(\"Marquis2019\", model, \"thermal\", params)\n\n def setup(self, _model, _params):\n set_random_seed()", "min_run_count": 2, "name": "different_model_options.TimeBuildModelThermal.time_setup_model", "number": 0, "param_names": ["model", "model option"], "params": [["", ""], ["'isothermal'", "'lumped'", "'x-full'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "a350e87e4e8a8f35aeb9951c78518a60da6177951f7d81d09f3d3088ec055cfd", "warmup_time": -1}, "different_model_options.TimeSolveLithiumPlating.time_solve_model": {"code": "class TimeSolveLithiumPlating:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(\n self, \"OKane2022\", model, \"lithium plating\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveLithiumPlating.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'none'", "'irreversible'", "'reversible'", "'partially reversible'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b1d66b1656476391fd4f4a356b350bff995917103286317dffc403f2b8a90fbe", "warmup_time": -1}, "different_model_options.TimeSolveLossActiveMaterial.time_solve_model": {"code": "class TimeSolveLossActiveMaterial:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(\n self, \"Ai2020\", model, \"loss of active material\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveLossActiveMaterial.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'none'", "'stress-driven'", "'reaction-driven'", "'stress and reaction-driven'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "d5e240fe84c4acc6966e4a3c4fd3b541659eb242ea36508a92c57a0ed958ceb7", "warmup_time": -1}, "different_model_options.TimeSolveParticle.time_solve_model": {"code": "class TimeSolveParticle:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(\n self, \"Marquis2019\", model, \"particle\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveParticle.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'Fickian diffusion'", "'uniform profile'", "'quadratic profile'", "'quartic profile'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "0fb24c2046b35533f49c825e1f5dbc32c30266f30c6ffc64504048df0f6182f7", "warmup_time": -1}, "different_model_options.TimeSolveSEI.time_solve_model": {"code": "class TimeSolveSEI:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(self, \"Marquis2019\", model, \"SEI\", params, solver_class)", "min_run_count": 2, "name": "different_model_options.TimeSolveSEI.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'none'", "'constant'", "'reaction limited'", "'solvent-diffusion limited'", "'electron-migration limited'", "'interstitial-diffusion limited'", "'ec reaction limited'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "53dd91bc8ea837141f3ff3ec6ae6fc8310b0ebfae08e6bbd8a1f692efb7d2f57", "warmup_time": -1}, "different_model_options.TimeSolveSurfaceForm.time_solve_model": {"code": "class TimeSolveSurfaceForm:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n if (model, params, solver_class) == (\n pybamm.lithium_ion.SPM,\n \"differential\",\n pybamm.IDAKLUSolver,\n ):\n raise NotImplementedError\n SolveModel.solve_setup(\n self, \"Marquis2019\", model, \"surface form\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveSurfaceForm.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'false'", "'differential'", "'algebraic'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b025abdf6ccd9f47388fd29f0bfc0fc5490bc48eb9c277ba6172b8064339cd15", "warmup_time": -1}, "different_model_options.TimeSolveThermal.time_solve_model": {"code": "class TimeSolveThermal:\n def time_solve_model(self, _model, _params, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, model, params, solver_class):\n set_random_seed()\n SolveModel.solve_setup(\n self, \"Marquis2019\", model, \"thermal\", params, solver_class\n )", "min_run_count": 2, "name": "different_model_options.TimeSolveThermal.time_solve_model", "number": 0, "param_names": ["model", "model option", "solver class"], "params": [["", ""], ["'isothermal'", "'lumped'", "'x-full'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b8015ca16fbe5a13c5d7b34926d92538382b9575c674f2ef78d923e8e603f5cb", "warmup_time": -1}, "memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV": {"code": "class MemDFNSimulationCCCV:\n def mem_setup_DFN_simulationCCCV(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.DFN()\n exp = pybamm.Experiment(\n [\n \"Discharge at C/5 for 10 hours or until 3.3 V\",\n \"Rest for 1 hour\",\n \"Charge at 1 A until 4.1 V\",\n \"Hold at 4.1 V until 10 mA\",\n \"Rest for 1 hour\",\n ]\n )\n self.sim = pybamm.Simulation(\n self.model, parameter_values=self.param, experiment=exp\n )\n return self.sim\n\n def setup(self, _params):\n set_random_seed()", "name": "memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "51ef613d1be3b3c97e5cff911f9a71ebfec58bb3741293e2b387b6aec0c55d88"}, "memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT": {"code": "class MemDFNSimulationGITT:\n def mem_setup_DFN_simulationGITT(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n exp = pybamm.Experiment(\n [(\"Discharge at C/20 for 1 hour\", \"Rest for 1 hour\")] * 20\n )\n self.sim = pybamm.Simulation(\n self.model, parameter_values=self.param, experiment=exp\n )\n return self.sim\n\n def setup(self, _params):\n set_random_seed()", "name": "memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "d4b526c693f63c0dca2afa82bc58c24d52b7884ae618e298aff74e44864d84e4"}, "memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV": {"code": "class MemSPMSimulationCCCV:\n def mem_setup_SPM_simulationCCCV(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n exp = pybamm.Experiment(\n [\n \"Discharge at C/5 for 10 hours or until 3.3 V\",\n \"Rest for 1 hour\",\n \"Charge at 1 A until 4.1 V\",\n \"Hold at 4.1 V until 10 mA\",\n \"Rest for 1 hour\",\n ]\n )\n self.sim = pybamm.Simulation(\n self.model, parameter_values=self.param, experiment=exp\n )\n return self.sim\n\n def setup(self, _params):\n set_random_seed()", "name": "memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "29109fbfa71fad4a6f5d5b2f57bb2c9d364602f218e44f5f537529aae441a717"}, "memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT": {"code": "class MemSPMSimulationGITT:\n def mem_setup_SPM_simulationGITT(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n exp = pybamm.Experiment(\n [(\"Discharge at C/20 for 1 hour\", \"Rest for 1 hour\")] * 20\n )\n self.sim = pybamm.Simulation(\n self.model, parameter_values=self.param, experiment=exp\n )\n return self.sim\n\n def setup(self, _params):\n set_random_seed()", "name": "memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "c00f20a28b027b21fcddb41e38f4b6414026233b5484c1bc7a1ad2810fc0475f"}, "memory_unit_benchmarks.MemCreateExpression.mem_create_expression": {"code": "class MemCreateExpression:\n def mem_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n return self.model\n\n def setup(self):\n set_random_seed()", "name": "memory_unit_benchmarks.MemCreateExpression.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "3d6830c6c8132d74fbf54e206a2f784c514c86ad079aac662a24cb151775927f"}, "memory_unit_benchmarks.MemDiscretiseModel.mem_create_expression": {"code": "class MemCreateExpression:\n def mem_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n return self.model\n\nclass MemDiscretiseModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)", "name": "memory_unit_benchmarks.MemDiscretiseModel.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "1e1265e6812795c6b4638a8861b57dc14e9b3e21d54786009ba2f6ea6526eb99"}, "memory_unit_benchmarks.MemDiscretiseModel.mem_discretise": {"code": "class MemDiscretiseModel:\n def mem_discretise(self):\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n var_pts = {self.r: 20}\n mesh = pybamm.Mesh(self.geometry, submesh_types, var_pts)\n \n spatial_methods = {\"negative particle\": pybamm.FiniteVolume()}\n disc = pybamm.Discretisation(mesh, spatial_methods)\n disc.process_model(self.model)\n return disc\n\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)", "name": "memory_unit_benchmarks.MemDiscretiseModel.mem_discretise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "495195cd9a6ece265ad424338ffde8465bff6b401aff98f26bf908c480b58724"}, "memory_unit_benchmarks.MemDiscretiseModel.mem_parameterise": {"code": "class MemParameteriseModel:\n def mem_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n return param\n\nclass MemDiscretiseModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)", "name": "memory_unit_benchmarks.MemDiscretiseModel.mem_parameterise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "3193180de8abb381c009afe51426f5d20e7347c3b9761d1663a98425cce0c663"}, "memory_unit_benchmarks.MemParameteriseModel.mem_create_expression": {"code": "class MemCreateExpression:\n def mem_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n return self.model\n\nclass MemParameteriseModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)", "name": "memory_unit_benchmarks.MemParameteriseModel.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "862863fcd24f0545f40184ecdebd166445846c611afed20dcf90f68765c3cc0b"}, "memory_unit_benchmarks.MemParameteriseModel.mem_parameterise": {"code": "class MemParameteriseModel:\n def mem_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n return param\n\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)", "name": "memory_unit_benchmarks.MemParameteriseModel.mem_parameterise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "edad12bc03295b4e89366fc5cfb1ed396d7bb91d3f3c81c80c58aa1302e875c5"}, "memory_unit_benchmarks.MemSolveModel.mem_create_expression": {"code": "class MemCreateExpression:\n def mem_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n return self.model\n\nclass MemSolveModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n MemDiscretiseModel.mem_discretise(self)", "name": "memory_unit_benchmarks.MemSolveModel.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "16091c4e58d10d32014c88300ed1dcaf80b55cf5b10e264a66a1ea2b8837581e"}, "memory_unit_benchmarks.MemSolveModel.mem_discretise": {"code": "class MemDiscretiseModel:\n def mem_discretise(self):\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n var_pts = {self.r: 20}\n mesh = pybamm.Mesh(self.geometry, submesh_types, var_pts)\n \n spatial_methods = {\"negative particle\": pybamm.FiniteVolume()}\n disc = pybamm.Discretisation(mesh, spatial_methods)\n disc.process_model(self.model)\n return disc\n\nclass MemSolveModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n MemDiscretiseModel.mem_discretise(self)", "name": "memory_unit_benchmarks.MemSolveModel.mem_discretise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "34cbd7a52ecdcb0e943a83665c930436c4d296729f856ac0c74a38ebe551e0f9"}, "memory_unit_benchmarks.MemSolveModel.mem_parameterise": {"code": "class MemParameteriseModel:\n def mem_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n return param\n\nclass MemSolveModel:\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n MemDiscretiseModel.mem_discretise(self)", "name": "memory_unit_benchmarks.MemSolveModel.mem_parameterise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "e4f639e8ddfb46ec7daa72247577a6c466daa157bef63aa013c20264f9da6a73"}, "memory_unit_benchmarks.MemSolveModel.mem_solve": {"code": "class MemSolveModel:\n def mem_solve(self):\n solver = pybamm.ScipySolver()\n t = np.linspace(0, 3600, 600)\n solver.solve(self.model, t)\n return solver\n\n def setup(self):\n set_random_seed()\n MemCreateExpression.mem_create_expression(self)\n MemParameteriseModel.mem_parameterise(self)\n MemDiscretiseModel.mem_discretise(self)", "name": "memory_unit_benchmarks.MemSolveModel.mem_solve", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "a7b39a512b545d84bd7d5f0a6ed4d6901e6dc414da7e50ed43c6afa3abd62f0a"}, "time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN": {"code": "class TimeBuildDFN:\n def time_setup_DFN(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.DFN()\n self.param.process_model(self.model)\n compute_discretisation(self.model, self.param).process_model(self.model)\n\n def setup(self, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN", "number": 0, "param_names": ["parameter"], "params": [["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "0eee82eaa2ed6557bb7cec497b21c1595f4e2ab7f17c33cf98baa7acc53e6ef7", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildDFNSimulation.time_setup_DFN_simulation": {"code": "class TimeBuildDFNSimulation:\n def time_setup_DFN_simulation(self, with_experiment, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.DFN()\n if with_experiment:\n exp = pybamm.Experiment(\n [\n \"Discharge at 0.1C until 3.105 V\",\n ]\n )\n pybamm.Simulation(self.model, parameter_values=self.param, experiment=exp)\n else:\n pybamm.Simulation(self.model, parameter_values=self.param, C_rate=1)\n\n def setup(self, _with_experiment, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildDFNSimulation.time_setup_DFN_simulation", "number": 0, "param_names": ["with experiment", "parameter"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "041d84cc1adf4753d7f9652306ad60d0d6364fcc290e4736429f8e7c3c675a12", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPM.time_setup_SPM": {"code": "class TimeBuildSPM:\n def time_setup_SPM(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n self.param.process_model(self.model)\n compute_discretisation(self.model, self.param).process_model(self.model)\n\n def setup(self, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildSPM.time_setup_SPM", "number": 0, "param_names": ["parameter"], "params": [["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "d5778345d68fd67c043a3241f1764d8b6e007490765cb577f15dd6fe38347cad", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPMSimulation.time_setup_SPM_simulation": {"code": "class TimeBuildSPMSimulation:\n def time_setup_SPM_simulation(self, with_experiment, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPM()\n if with_experiment:\n exp = pybamm.Experiment(\n [\n \"Discharge at 0.1C until 3.105 V\",\n ]\n )\n pybamm.Simulation(self.model, parameter_values=self.param, experiment=exp)\n else:\n pybamm.Simulation(self.model, parameter_values=self.param, C_rate=1)\n\n def setup(self, _with_experiment, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildSPMSimulation.time_setup_SPM_simulation", "number": 0, "param_names": ["with experiment", "parameter"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "4af04a0ebcb83401d42904cefe3d57346161aa348bdafe191f95ec33fff21cec", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPMe.time_setup_SPMe": {"code": "class TimeBuildSPMe:\n def time_setup_SPMe(self, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPMe()\n self.param.process_model(self.model)\n compute_discretisation(self.model, self.param).process_model(self.model)\n\n def setup(self, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildSPMe.time_setup_SPMe", "number": 0, "param_names": ["parameter"], "params": [["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "970230e78bb53f069b2e13856e844504c8a106f98359e1d7ad09161d6d03c083", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPMeSimulation.time_setup_SPMe_simulation": {"code": "class TimeBuildSPMeSimulation:\n def time_setup_SPMe_simulation(self, with_experiment, params):\n self.param = pybamm.ParameterValues(params)\n self.model = pybamm.lithium_ion.SPMe()\n if with_experiment:\n exp = pybamm.Experiment(\n [\n \"Discharge at 0.1C until 3.105 V\",\n ]\n )\n pybamm.Simulation(self.model, parameter_values=self.param, experiment=exp)\n else:\n pybamm.Simulation(self.model, parameter_values=self.param, C_rate=1)\n\n def setup(self, _with_experiment, _params):\n set_random_seed()", "min_run_count": 2, "name": "time_setup_models_and_sims.TimeBuildSPMeSimulation.time_setup_SPMe_simulation", "number": 0, "param_names": ["with experiment", "parameter"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Mohtat2020'", "'Chen2020'", "'OKane2022'", "'Ecker2015'"]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "6f76c516f3fa71f22c3c769426712e12bc3c63681def5407f510a3d24fe28ebf", "warmup_time": -1}, "time_sims_experiments.TimeSimulation.time_setup": {"code": "class TimeSimulation:\n def time_setup(self, experiment, parameters, model_class, solver_class):\n param = pybamm.ParameterValues(parameters)\n model = model_class()\n solver = solver_class()\n exp = pybamm.Experiment(self.experiment_descriptions[experiment])\n pybamm.Simulation(model, parameter_values=param, experiment=exp, solver=solver)\n\n def setup(self, experiment, parameters, model_class, solver_class):\n set_random_seed()\n if (experiment, parameters, model_class, solver_class) == (\n \"GITT\",\n \"Marquis2019\",\n pybamm.lithium_ion.DFN,\n pybamm.CasadiSolver,\n ):\n raise NotImplementedError\n self.param = pybamm.ParameterValues(parameters)\n self.model = model_class()\n self.solver = solver_class()\n self.exp = pybamm.Experiment(self.experiment_descriptions[experiment])\n self.sim = pybamm.Simulation(\n self.model,\n parameter_values=self.param,\n experiment=self.exp,\n solver=self.solver,\n )", "min_run_count": 2, "name": "time_sims_experiments.TimeSimulation.time_setup", "number": 0, "param_names": ["experiment", "parameter", "model_class", "solver_class"], "params": [["'CCCV'", "'GITT'"], ["'Marquis2019'", "'Chen2020'"], ["", ""], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "f919a29c04da89b51fb66aa41294744b714b2d640df50debeff76b55023af868", "warmup_time": -1}, "time_sims_experiments.TimeSimulation.time_solve": {"code": "class TimeSimulation:\n def time_solve(self, _experiment, _parameters, _model_class, _solver_class):\n self.sim.solve()\n\n def setup(self, experiment, parameters, model_class, solver_class):\n set_random_seed()\n if (experiment, parameters, model_class, solver_class) == (\n \"GITT\",\n \"Marquis2019\",\n pybamm.lithium_ion.DFN,\n pybamm.CasadiSolver,\n ):\n raise NotImplementedError\n self.param = pybamm.ParameterValues(parameters)\n self.model = model_class()\n self.solver = solver_class()\n self.exp = pybamm.Experiment(self.experiment_descriptions[experiment])\n self.sim = pybamm.Simulation(\n self.model,\n parameter_values=self.param,\n experiment=self.exp,\n solver=self.solver,\n )", "min_run_count": 2, "name": "time_sims_experiments.TimeSimulation.time_solve", "number": 0, "param_names": ["experiment", "parameter", "model_class", "solver_class"], "params": [["'CCCV'", "'GITT'"], ["'Marquis2019'", "'Chen2020'"], ["", ""], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "6832512fe2709d359717d531b49d57f9b07241e3af646c02a9865a7e7b4c96ac", "warmup_time": -1}, "time_solve_models.TimeSolveDFN.time_solve_model": {"code": "class TimeSolveDFN:\n def time_solve_model(self, _solve_first, _parameters, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, solve_first, parameters, solver_class):\n set_random_seed()\n if (parameters, solver_class) == (\n \"ORegan2022\",\n pybamm.CasadiSolver,\n ):\n raise NotImplementedError\n self.solver = solver_class()\n self.model = pybamm.lithium_ion.DFN()\n c_rate = 1\n tmax = 4000 / c_rate\n nb_points = 500\n self.t_eval = np.linspace(0, tmax, nb_points)\n geometry = self.model.default_geometry\n \n # load parameter values and process model and geometry\n param = pybamm.ParameterValues(parameters)\n param.process_model(self.model)\n param.process_geometry(geometry)\n \n # set mesh\n var_pts = {\n \"x_n\": 20,\n \"x_s\": 20,\n \"x_p\": 20,\n \"r_n\": 30,\n \"r_p\": 30,\n \"y\": 10,\n \"z\": 10,\n }\n mesh = pybamm.Mesh(geometry, self.model.default_submesh_types, var_pts)\n \n # discretise model\n disc = pybamm.Discretisation(mesh, self.model.default_spatial_methods)\n disc.process_model(self.model)\n if solve_first:\n solve_model_once(self.model, self.solver, self.t_eval)", "min_run_count": 2, "name": "time_solve_models.TimeSolveDFN.time_solve_model", "number": 0, "param_names": ["solve first", "parameter", "solver_class"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'Prada2013'", "'Ai2020'", "'Ramadass2004'", "'Chen2020'", "'Ecker2015'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "f6d7b52e57b2a72e7ebdf55b8998c7f7e4ee88848570e445a0f7bd967d6d14be", "warmup_time": -1}, "time_solve_models.TimeSolveSPM.time_solve_model": {"code": "class TimeSolveSPM:\n def time_solve_model(self, _solve_first, _parameters, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, solve_first, parameters, solver_class):\n set_random_seed()\n self.solver = solver_class()\n self.model = pybamm.lithium_ion.SPM()\n c_rate = 1\n tmax = 4000 / c_rate\n nb_points = 500\n self.t_eval = np.linspace(0, tmax, nb_points)\n geometry = self.model.default_geometry\n \n # load parameter values and process model and geometry\n param = pybamm.ParameterValues(parameters)\n param.process_model(self.model)\n param.process_geometry(geometry)\n \n # set mesh\n var_pts = {\n \"x_n\": 20,\n \"x_s\": 20,\n \"x_p\": 20,\n \"r_n\": 30,\n \"r_p\": 30,\n \"y\": 10,\n \"z\": 10,\n }\n mesh = pybamm.Mesh(geometry, self.model.default_submesh_types, var_pts)\n \n # discretise model\n disc = pybamm.Discretisation(mesh, self.model.default_spatial_methods)\n disc.process_model(self.model)\n if solve_first:\n solve_model_once(self.model, self.solver, self.t_eval)", "min_run_count": 2, "name": "time_solve_models.TimeSolveSPM.time_solve_model", "number": 0, "param_names": ["solve first", "parameter", "solver_class"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ramadass2004'", "'Chen2020'", "'Ecker2015'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "f329b803e6760b144e33d59c3d34fa3d75fa6c26427168501d81c48156c62175", "warmup_time": -1}, "time_solve_models.TimeSolveSPMe.time_solve_model": {"code": "class TimeSolveSPMe:\n def time_solve_model(self, _solve_first, _parameters, _solver_class):\n self.solver.solve(self.model, t_eval=self.t_eval)\n\n def setup(self, solve_first, parameters, solver_class):\n set_random_seed()\n self.solver = solver_class()\n self.model = pybamm.lithium_ion.SPMe()\n c_rate = 1\n tmax = 4000 / c_rate\n nb_points = 500\n self.t_eval = np.linspace(0, tmax, nb_points)\n geometry = self.model.default_geometry\n \n # load parameter values and process model and geometry\n param = pybamm.ParameterValues(parameters)\n param.process_model(self.model)\n param.process_geometry(geometry)\n \n # set mesh\n var_pts = {\n \"x_n\": 20,\n \"x_s\": 20,\n \"x_p\": 20,\n \"r_n\": 30,\n \"r_p\": 30,\n \"y\": 10,\n \"z\": 10,\n }\n mesh = pybamm.Mesh(geometry, self.model.default_submesh_types, var_pts)\n \n # discretise model\n disc = pybamm.Discretisation(mesh, self.model.default_spatial_methods)\n disc.process_model(self.model)\n if solve_first:\n solve_model_once(self.model, self.solver, self.t_eval)", "min_run_count": 2, "name": "time_solve_models.TimeSolveSPMe.time_solve_model", "number": 0, "param_names": ["solve first", "parameter", "solver_class"], "params": [["False", "True"], ["'Marquis2019'", "'ORegan2022'", "'NCA_Kim2011'", "'Prada2013'", "'Ramadass2004'", "'Chen2020'", "'Ecker2015'"], ["", ""]], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "26110b628fab649e6153a529860b3104b379d3f288ca020d4321f489c8a38955", "warmup_time": -1}, "unit_benchmarks.TimeCreateExpression.time_create_expression": {"code": "class TimeCreateExpression:\n def time_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n\n def setup(self):\n set_random_seed()", "min_run_count": 2, "name": "unit_benchmarks.TimeCreateExpression.time_create_expression", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "79567e8fc10e82bb7efc93e89a5fa48101c5f63b2bcf09f9affa1daeaa660a7a", "warmup_time": -1}, "unit_benchmarks.TimeDiscretiseModel.time_create_expression": {"code": "class TimeCreateExpression:\n def time_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n\nclass TimeDiscretiseModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeDiscretiseModel.time_create_expression", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "53f64bb63b703ce09229d62a777fa5f21abf561c70430ff978cd6fce8363f76c", "warmup_time": -1}, "unit_benchmarks.TimeDiscretiseModel.time_discretise": {"code": "class TimeDiscretiseModel:\n def time_discretise(self):\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n var_pts = {self.r: 20}\n mesh = pybamm.Mesh(self.geometry, submesh_types, var_pts)\n \n spatial_methods = {\"negative particle\": pybamm.FiniteVolume()}\n disc = pybamm.Discretisation(mesh, spatial_methods)\n disc.process_model(self.model)\n\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeDiscretiseModel.time_discretise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "82d1028bb6552573a282aead5ecf23b4c233624a98d553f417f9b632904cf779", "warmup_time": -1}, "unit_benchmarks.TimeDiscretiseModel.time_parameterise": {"code": "class TimeParameteriseModel:\n def time_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n\nclass TimeDiscretiseModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeDiscretiseModel.time_parameterise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "ef8b306be418ea6cffb6df7d95c34e6e4c058556b81285cfe00a85a746364e11", "warmup_time": -1}, "unit_benchmarks.TimeParameteriseModel.time_create_expression": {"code": "class TimeCreateExpression:\n def time_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n\nclass TimeParameteriseModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeParameteriseModel.time_create_expression", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "c9c6590d7ea983ffd2ec4a0beb7198254c9872b5d79fafe982b5575dcbf533ea", "warmup_time": -1}, "unit_benchmarks.TimeParameteriseModel.time_parameterise": {"code": "class TimeParameteriseModel:\n def time_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeParameteriseModel.time_parameterise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "2db8360d2edcfa78dd7840bfc00d24c0e9649c847253c89fe402671c262b1338", "warmup_time": -1}, "unit_benchmarks.TimeSolveModel.time_create_expression": {"code": "class TimeCreateExpression:\n def time_create_expression(self):\n self.R = pybamm.Parameter(\"Particle radius [m]\")\n D = pybamm.Parameter(\"Diffusion coefficient [m2.s-1]\")\n j = pybamm.Parameter(\"Interfacial current density [A.m-2]\")\n F = pybamm.Parameter(\"Faraday constant [C.mol-1]\")\n c0 = pybamm.Parameter(\"Initial concentration [mol.m-3]\")\n self.model = pybamm.BaseModel()\n \n c = pybamm.Variable(\"Concentration [mol.m-3]\", domain=\"negative particle\")\n N = -D * pybamm.grad(c)\n dcdt = -pybamm.div(N)\n self.model.rhs = {c: dcdt}\n \n lbc = pybamm.Scalar(0)\n rbc = -j / F / D\n self.model.boundary_conditions = {\n c: {\"left\": (lbc, \"Neumann\"), \"right\": (rbc, \"Neumann\")}\n }\n \n self.model.initial_conditions = {c: c0}\n self.model.variables = {\n \"Concentration [mol.m-3]\": c,\n \"Surface concentration [mol.m-3]\": pybamm.surf(c),\n \"Flux [mol.m-2.s-1]\": N,\n }\n\nclass TimeSolveModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n TimeDiscretiseModel.time_discretise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeSolveModel.time_create_expression", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "7d5ffee2c28dcaa231b44408496fce54271121737b80dc5a7498beb92ab2b159", "warmup_time": -1}, "unit_benchmarks.TimeSolveModel.time_discretise": {"code": "class TimeDiscretiseModel:\n def time_discretise(self):\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n var_pts = {self.r: 20}\n mesh = pybamm.Mesh(self.geometry, submesh_types, var_pts)\n \n spatial_methods = {\"negative particle\": pybamm.FiniteVolume()}\n disc = pybamm.Discretisation(mesh, spatial_methods)\n disc.process_model(self.model)\n\nclass TimeSolveModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n TimeDiscretiseModel.time_discretise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeSolveModel.time_discretise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "a4e41d181f7a8ac4c6c873e0aafa291f45deb155ad92dc625301917565fe6bdc", "warmup_time": -1}, "unit_benchmarks.TimeSolveModel.time_parameterise": {"code": "class TimeParameteriseModel:\n def time_parameterise(self):\n param = pybamm.ParameterValues(\n {\n \"Particle radius [m]\": 10e-6,\n \"Diffusion coefficient [m2.s-1]\": 3.9e-14,\n \"Interfacial current density [A.m-2]\": 1.4,\n \"Faraday constant [C.mol-1]\": 96485,\n \"Initial concentration [mol.m-3]\": 2.5e4,\n }\n )\n \n self.r = pybamm.SpatialVariable(\n \"r\", domain=[\"negative particle\"], coord_sys=\"spherical polar\"\n )\n \n self.geometry = {\n \"negative particle\": {self.r: {\"min\": pybamm.Scalar(0), \"max\": self.R}}\n }\n param.process_model(self.model)\n param.process_geometry(self.geometry)\n\nclass TimeSolveModel:\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n TimeDiscretiseModel.time_discretise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeSolveModel.time_parameterise", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "14eb896be95381d740fa3f69396eb480514a09da23f2525bce6c81124247ca72", "warmup_time": -1}, "unit_benchmarks.TimeSolveModel.time_solve": {"code": "class TimeSolveModel:\n def time_solve(self):\n solver = pybamm.ScipySolver()\n t = np.linspace(0, 3600, 600)\n solver.solve(self.model, t)\n\n def setup(self):\n set_random_seed()\n TimeCreateExpression.time_create_expression(self)\n TimeParameteriseModel.time_parameterise(self)\n TimeDiscretiseModel.time_discretise(self)", "min_run_count": 2, "name": "unit_benchmarks.TimeSolveModel.time_solve", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "3b060ae2823c304802df15803cd5d845699526f2b740e5e252d5890f61967a01", "warmup_time": -1}}, "machines": {"GitHubRunner": {"machine": "GitHubRunner", "version": 1}}, "tags": {"v0.1.0": 3608, "v0.2.0": 4954, "v0.2.1": 5277, "v0.2.2": 5978, "v0.2.3": 6424, "v0.2.4": 6787, "v0.3.0": 7341, "v0.3.0-beta": 7278, "v0.4.0": 8395, "v21.08": 9196, "v21.10": 9482, "v21.11": 9853, "v21.12": 10002, "v21.9": 9368, "v22.1": 10214, "v22.10": 11902, "v22.11": 12279, "v22.11.1": 12410, "v22.12": 12476, "v22.2": 10274, "v22.3": 10401, "v22.4": 10493, "v22.5": 10654, "v22.6": 10795, "v22.7": 11122, "v22.8": 11338, "v22.9": 11580, "v23.1": 12625, "v23.2": 12908, "v23.3": 13243, "v23.4": 13393, "v23.4.1": 13405, "v23.5": 13982, "v23.5rc0": 13803, "v23.9": 15656, "v23.9rc0": 15350, "v23.9rc1": 15602, "v24.1": 16517, "v24.1rc0": 16143, "v24.1rc1": 16292, "v24.1rc2": 16424}, "pages": [["", "Grid view", "Display as a agrid"], ["summarylist", "List view", "Display as a list"], ["regressions", "Show regressions", "Display information about recent regressions"]]} \ No newline at end of file diff --git a/info.json b/info.json index d41727792..59ff6766c 100644 --- a/info.json +++ b/info.json @@ -1,4 +1,4 @@ { "asv-version": "0.6.3", - "timestamp": 1713239895292 + "timestamp": 1713326689400 } \ No newline at end of file diff --git a/regressions.json b/regressions.json index 49022adea..3a3d213b7 100644 --- a/regressions.json +++ b/regressions.json @@ -1 +1 @@ -{"regressions": [["different_model_options.TimeSolveLithiumPlating.time_solve_model(, 'irreversible', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLithiumPlating.time_solve_model.json", {"python": "3.8"}, 2, 0.03895995000004859, 0.022071712249982056, [[null, 15683, 0.022071712249982056, 0.03895995000004859]]], ["different_model_options.TimeSolveLithiumPlating.time_solve_model(, 'irreversible', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLithiumPlating.time_solve_model.json", {"python": "3.8"}, 3, 0.08572085699995569, 0.048980932999938886, [[null, 15683, 0.048980932999938886, 0.08572085699995569]]], ["different_model_options.TimeSolveLossActiveMaterial.time_solve_model(, 'stress-driven', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLossActiveMaterial.time_solve_model.json", {"python": "3.8"}, 10, 4.65005118549999, 4.167683744999977, [[15966, 16011, 4.167683744999977, 4.65005118549999]]], ["different_model_options.TimeSolveLossActiveMaterial.time_solve_model(, 'stress and reaction-driven', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLossActiveMaterial.time_solve_model.json", {"python": "3.8"}, 14, 4.6125043374998995, 4.164340683999967, [[15966, 16011, 4.164340683999967, 4.6125043374998995]]], ["time_sims_experiments.TimeSimulation.time_solve('CCCV', 'Marquis2019', , )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/time_sims_experiments.TimeSimulation.time_solve.json", {"python": "3.8"}, 2, 11.145895058499946, 3.2878285570000116, [[16958, 16973, 3.2878285570000116, 11.145895058499946]]], ["time_solve_models.TimeSolveSPM.time_solve_model(False, 'Prada2013', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/time_solve_models.TimeSolveSPM.time_solve_model.json", {"python": "3.12"}, 6, 0.016426642750047904, 0.0154010247499059, [[17188, 17217, 0.0154010247499059, 0.015722432750067128]]], ["time_solve_models.TimeSolveSPM.time_solve_model(False, 'Ramadass2004', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/time_solve_models.TimeSolveSPM.time_solve_model.json", {"python": "3.12"}, 8, 0.013465013250026914, 0.010543664500005434, [[17236, 17246, 0.010619252333337197, 0.013465013250026914]]], ["different_model_options.TimeSolveSEI.time_solve_model(, 'interstitial-diffusion limited', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.12/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveSEI.time_solve_model.json", {"python": "3.12"}, 24, 0.512316243999976, 0.4848571625000204, [[17236, 17246, 0.4866745710000373, 0.512316243999976]]]]} \ No newline at end of file +{"regressions": [["different_model_options.TimeSolveLithiumPlating.time_solve_model(, 'irreversible', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLithiumPlating.time_solve_model.json", {"python": "3.8"}, 2, 0.03895995000004859, 0.022071712249982056, [[null, 15676, 0.022071712249982056, 0.03895995000004859]]], ["different_model_options.TimeSolveLithiumPlating.time_solve_model(, 'irreversible', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLithiumPlating.time_solve_model.json", {"python": "3.8"}, 3, 0.08572085699995569, 0.048980932999938886, [[null, 15676, 0.048980932999938886, 0.08572085699995569]]], ["different_model_options.TimeSolveLossActiveMaterial.time_solve_model(, 'stress-driven', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLossActiveMaterial.time_solve_model.json", {"python": "3.8"}, 10, 4.65005118549999, 4.167683744999977, [[15956, 16001, 4.167683744999977, 4.65005118549999]]], ["different_model_options.TimeSolveLossActiveMaterial.time_solve_model(, 'stress and reaction-driven', )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLossActiveMaterial.time_solve_model.json", {"python": "3.8"}, 14, 4.6125043374998995, 4.164340683999967, [[15956, 16001, 4.164340683999967, 4.6125043374998995]]], ["time_sims_experiments.TimeSimulation.time_solve('CCCV', 'Marquis2019', , )", "graphs/anytree/autograd/bpx/branch-develop/casadi/cmake/env-LD_LIBRARY_PATH-_home_runner_.local_lib/imageio/machine-GitHubRunner/matplotlib/numpy/pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/time_sims_experiments.TimeSimulation.time_solve.json", {"python": "3.8"}, 2, 11.145895058499946, 3.2878285570000116, [[16948, 16963, 3.2878285570000116, 11.145895058499946]]]]} \ No newline at end of file diff --git a/regressions.xml b/regressions.xml index b6d950599..da5880250 100644 --- a/regressions.xml +++ b/regressions.xml @@ -1,14 +1,5 @@ -tag:PyBaMM.asv,1970-01-01:/7ab015bdc77d3e5ac42910029714d3af631ad7db1bbfd0219dda34a11473abadAirspeed VelocityPyBaMM performance regressions2024-04-16T03:55:15Ztag:PyBaMM.asv,2024-04-15:/39c0f2bf90ff8490b0b53a746cb26be0ee33b8322a43e5ba2d5b652638ff8fe826.80% time_solve_models.TimeSolveSPM.time_solve_model(False, 'Ramadass2004', <class 'pybamm.solvers.casadi_solver.CasadiSolver'>)2024-04-16T03:55:15Z<a href="index.html#time_solve_models.TimeSolveSPM.time_solve_model?python=3.12&p-solve+first=False&p-parameter=%27Ramadass2004%27&p-solver_class=%3Cclass+%27pybamm.solvers.casadi_solver.CasadiSolver%27%3E&commits=6b5f5b7fbff076a5abb6619b574e8c2c181381c2-cf09d5e3430b46e1d16848e17db9b923c42e30b4">26.80% regression</a> on 2024-04-15 21:09:32 in commits <a href="#6b5f5b7fbff076a5abb6619b574e8c2c181381c2">6b5f5b7f...cf09d5e3</a>.<br> - New value: 13.5ms, old value: 10.6ms.<br> - Latest value: 13.5ms (27.71% worse - than best value 10.5ms).tag:PyBaMM.asv,2024-04-15:/2341fefb322823844a554a6e0e2acb54b3523a64b13b0650049195996dec4fd65.27% different_model_options.TimeSolveSEI.time_solve_model(<class 'pybamm.models.full_battery_models.lithium_ion.dfn.DFN'>, 'interstitial-diffusion limited', <class 'pybamm.solvers.casadi_solver.CasadiSolver'>)2024-04-16T03:44:38Z<a href="index.html#different_model_options.TimeSolveSEI.time_solve_model?python=3.12&p-model=%3Cclass+%27pybamm.models.full_battery_models.lithium_ion.dfn.DFN%27%3E&p-model+option=%27interstitial-diffusion+limited%27&p-solver+class=%3Cclass+%27pybamm.solvers.casadi_solver.CasadiSolver%27%3E&commits=6b5f5b7fbff076a5abb6619b574e8c2c181381c2-cf09d5e3430b46e1d16848e17db9b923c42e30b4">5.27% regression</a> on 2024-04-15 21:09:32 in commits <a href="#6b5f5b7fbff076a5abb6619b574e8c2c181381c2">6b5f5b7f...cf09d5e3</a>.<br> - New value: 512ms, old value: 487ms.<br> - Latest value: 512ms (5.66% worse - than best value 485ms).tag:PyBaMM.asv,2024-04-12:/15d3648691367e06eaef7ac8db09b14753e5b2dcd5c58b821150787d710f9e7e2.09% time_solve_models.TimeSolveSPM.time_solve_model(False, 'Prada2013', <class 'pybamm.solvers.casadi_solver.CasadiSolver'>)2024-04-14T04:29:50Z<a href="index.html#time_solve_models.TimeSolveSPM.time_solve_model?python=3.12&p-solve+first=False&p-parameter=%27Prada2013%27&p-solver_class=%3Cclass+%27pybamm.solvers.casadi_solver.CasadiSolver%27%3E&commits=4cf09f36bb4afb42c661e8765e14b4527581eff7-09ee982ba84055ec2c56f73b4cc63742c2ca0721">2.09% regression</a> on 2024-04-12 20:45:14 in commits <a href="#4cf09f36bb4afb42c661e8765e14b4527581eff7">4cf09f36...09ee982b</a>.<br> - New value: 15.7ms, old value: 15.4ms.<br> - Latest value: 16.4ms (6.66% worse - than best value 15.4ms).tag:PyBaMM.asv,2024-03-26:/c4d1c30c41497de54850f76c84b8fb6205ef362112d66edf2ab2ce1adcf80f6d239.00% time_sims_experiments.TimeSimulation.time_solve('CCCV', 'Marquis2019', <class 'pybamm.models.full_battery_models.lithium_ion.dfn.DFN'>, <class 'pybamm.solvers.casadi_solver.CasadiSolver'>)2024-03-27T03:48:30Z<a href="index.html#time_sims_experiments.TimeSimulation.time_solve?python=3.8&p-experiment=%27CCCV%27&p-parameter=%27Marquis2019%27&p-model_class=%3Cclass+%27pybamm.models.full_battery_models.lithium_ion.dfn.DFN%27%3E&p-solver_class=%3Cclass+%27pybamm.solvers.casadi_solver.CasadiSolver%27%3E&commits=280da52baebb1d58627799b702e97e425805a499-cba763acc58972f9d8de878cd1115b8ad47b433d">239.00% regression</a> on 2024-03-26 21:12:32 in commits <a href="#280da52baebb1d58627799b702e97e425805a499">280da52b...cba763ac</a>.<br> +tag:PyBaMM.asv,1970-01-01:/7ab015bdc77d3e5ac42910029714d3af631ad7db1bbfd0219dda34a11473abadAirspeed VelocityPyBaMM performance regressions2024-03-27T03:48:30Ztag:PyBaMM.asv,2024-03-26:/c4d1c30c41497de54850f76c84b8fb6205ef362112d66edf2ab2ce1adcf80f6d239.00% time_sims_experiments.TimeSimulation.time_solve('CCCV', 'Marquis2019', <class 'pybamm.models.full_battery_models.lithium_ion.dfn.DFN'>, <class 'pybamm.solvers.casadi_solver.CasadiSolver'>)2024-03-27T03:48:30Z<a href="index.html#time_sims_experiments.TimeSimulation.time_solve?python=3.8&p-experiment=%27CCCV%27&p-parameter=%27Marquis2019%27&p-model_class=%3Cclass+%27pybamm.models.full_battery_models.lithium_ion.dfn.DFN%27%3E&p-solver_class=%3Cclass+%27pybamm.solvers.casadi_solver.CasadiSolver%27%3E&commits=280da52baebb1d58627799b702e97e425805a499-cba763acc58972f9d8de878cd1115b8ad47b433d">239.00% regression</a> on 2024-03-26 21:12:32 in commits <a href="#280da52baebb1d58627799b702e97e425805a499">280da52b...cba763ac</a>.<br> New value: 11.1s, old value: 3.29s.<br> Latest value: 11.1s (239.00% worse than best value 3.29s).tag:PyBaMM.asv,2023-12-19:/eee2368a071795f92de82596e7fee234e2fac78271a030cb8d682151cae7003711.57% different_model_options.TimeSolveLossActiveMaterial.time_solve_model(<class 'pybamm.models.full_battery_models.lithium_ion.dfn.DFN'>, 'stress-driven', <class 'pybamm.solvers.casadi_solver.CasadiSolver'>)2023-12-20T03:38:29Z<a href="index.html#different_model_options.TimeSolveLossActiveMaterial.time_solve_model?python=3.8&p-model=%3Cclass+%27pybamm.models.full_battery_models.lithium_ion.dfn.DFN%27%3E&p-model+option=%27stress-driven%27&p-solver+class=%3Cclass+%27pybamm.solvers.casadi_solver.CasadiSolver%27%3E&commits=256747c82e3a355fe20b8f577eb0b69480cad720-85d930a8b9d57f5df4b52ce9a667aa46986025e3">11.57% regression</a> on 2023-12-19 23:56:10 in commits <a href="#256747c82e3a355fe20b8f577eb0b69480cad720">256747c8...85d930a8</a>.<br>