From d5b879eb9998e3a6efb6d15ac0af04b6521cdb3b Mon Sep 17 00:00:00 2001 From: tinosulzer Date: Tue, 3 Oct 2023 04:08:35 +0000 Subject: [PATCH] Generated from sources --- ...l_options.TimeBuildModelLithiumPlating.time_setup_model.json | 2 +- ...tions.TimeBuildModelLossActiveMaterial.time_setup_model.json | 2 +- ...t_model_options.TimeBuildModelParticle.time_setup_model.json | 2 +- ...ferent_model_options.TimeBuildModelSEI.time_setup_model.json | 2 +- ...odel_options.TimeBuildModelSurfaceForm.time_setup_model.json | 2 +- ...nt_model_options.TimeBuildModelThermal.time_setup_model.json | 2 +- ..._model_options.TimeSolveLithiumPlating.time_solve_model.json | 2 +- ...el_options.TimeSolveLossActiveMaterial.time_solve_model.json | 2 +- ...ferent_model_options.TimeSolveParticle.time_solve_model.json | 2 +- .../different_model_options.TimeSolveSEI.time_solve_model.json | 2 +- ...ent_model_options.TimeSolveSurfaceForm.time_solve_model.json | 2 +- ...fferent_model_options.TimeSolveThermal.time_solve_model.json | 2 +- ..._sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV.json | 2 +- ..._sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT.json | 2 +- ..._sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV.json | 2 +- ..._sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT.json | 2 +- ...it_benchmarks.MemCreateExpression.mem_create_expression.json | 2 +- ...emory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json | 2 +- ...y_unit_benchmarks.MemParameteriseModel.mem_parameterise.json | 2 +- .../wget/memory_unit_benchmarks.MemSolveModel.mem_solve.json | 2 +- .../pybtex/python-3.8/scikit-fem/sympy/tqdm/wget/summary.json | 2 +- .../time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN.json | 2 +- ...d_sims.TimeBuildDFNSimulation.time_setup_DFN_simulation.json | 2 +- .../time_setup_models_and_sims.TimeBuildSPM.time_setup_SPM.json | 2 +- ...d_sims.TimeBuildSPMSimulation.time_setup_SPM_simulation.json | 2 +- ...ime_setup_models_and_sims.TimeBuildSPMe.time_setup_SPMe.json | 2 +- ...sims.TimeBuildSPMeSimulation.time_setup_SPMe_simulation.json | 2 +- .../wget/time_sims_experiments.TimeSimulation.time_setup.json | 2 +- .../wget/time_sims_experiments.TimeSimulation.time_solve.json | 2 +- .../wget/time_solve_models.TimeSolveDFN.time_solve_model.json | 2 +- .../wget/time_solve_models.TimeSolveSPM.time_solve_model.json | 2 +- .../wget/time_solve_models.TimeSolveSPMe.time_solve_model.json | 2 +- ..._benchmarks.TimeCreateExpression.time_create_expression.json | 2 +- .../unit_benchmarks.TimeDiscretiseModel.time_discretise.json | 2 +- ...unit_benchmarks.TimeParameteriseModel.time_parameterise.json | 2 +- .../tqdm/wget/unit_benchmarks.TimeSolveModel.time_solve.json | 2 +- ...l_options.TimeBuildModelLithiumPlating.time_setup_model.json | 2 +- ...tions.TimeBuildModelLossActiveMaterial.time_setup_model.json | 2 +- ...t_model_options.TimeBuildModelParticle.time_setup_model.json | 2 +- ...ferent_model_options.TimeBuildModelSEI.time_setup_model.json | 2 +- ...odel_options.TimeBuildModelSurfaceForm.time_setup_model.json | 2 +- ...nt_model_options.TimeBuildModelThermal.time_setup_model.json | 2 +- ..._model_options.TimeSolveLithiumPlating.time_solve_model.json | 2 +- ...el_options.TimeSolveLossActiveMaterial.time_solve_model.json | 2 +- ...ferent_model_options.TimeSolveParticle.time_solve_model.json | 2 +- .../different_model_options.TimeSolveSEI.time_solve_model.json | 2 +- ...ent_model_options.TimeSolveSurfaceForm.time_solve_model.json | 2 +- ...fferent_model_options.TimeSolveThermal.time_solve_model.json | 2 +- ..._sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV.json | 2 +- ..._sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT.json | 2 +- ..._sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV.json | 2 +- ..._sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT.json | 2 +- ...it_benchmarks.MemCreateExpression.mem_create_expression.json | 2 +- ...emory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json | 2 +- ...y_unit_benchmarks.MemParameteriseModel.mem_parameterise.json | 2 +- .../summary/memory_unit_benchmarks.MemSolveModel.mem_solve.json | 2 +- .../time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN.json | 2 +- ...d_sims.TimeBuildDFNSimulation.time_setup_DFN_simulation.json | 2 +- .../time_setup_models_and_sims.TimeBuildSPM.time_setup_SPM.json | 2 +- ...d_sims.TimeBuildSPMSimulation.time_setup_SPM_simulation.json | 2 +- ...ime_setup_models_and_sims.TimeBuildSPMe.time_setup_SPMe.json | 2 +- ...sims.TimeBuildSPMeSimulation.time_setup_SPMe_simulation.json | 2 +- .../time_sims_experiments.TimeSimulation.time_setup.json | 2 +- .../time_sims_experiments.TimeSimulation.time_solve.json | 2 +- .../time_solve_models.TimeSolveDFN.time_solve_model.json | 2 +- .../time_solve_models.TimeSolveSPM.time_solve_model.json | 2 +- .../time_solve_models.TimeSolveSPMe.time_solve_model.json | 2 +- ..._benchmarks.TimeCreateExpression.time_create_expression.json | 2 +- .../unit_benchmarks.TimeDiscretiseModel.time_discretise.json | 2 +- ...unit_benchmarks.TimeParameteriseModel.time_parameterise.json | 2 +- graphs/summary/unit_benchmarks.TimeSolveModel.time_solve.json | 2 +- index.json | 2 +- info.json | 2 +- regressions.json | 2 +- 74 files changed, 74 insertions(+), 74 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-3.8/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-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeBuildModelLithiumPlating.time_setup_model.json index 5039dd69a..820a76ebc 100644 --- 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--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-3.8/scikit-fem/sympy/tqdm/wget/different_model_options.TimeSolveLossActiveMaterial.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.TimeSolveLossActiveMaterial.time_solve_model.json index 5aa777de0..9d27cc3ea 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.TimeSolveLossActiveMaterial.time_solve_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.TimeSolveParticle.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.TimeSolveParticle.time_solve_model.json index fe6d8c29b..03011d5a2 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.TimeSolveParticle.time_solve_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.TimeSolveSEI.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.TimeSolveSEI.time_solve_model.json @@ -1 +1 @@ -[[14269, [0.036269864500070526, 0.0668448520000311, 0.03619106999985888, 0.06718044049983973, 0.053084287499927996, 0.08791181599997344, 0.039042701499965915, 0.07275582350001741, 0.05291973349994805, 0.08943364749995908, 0.05265080699990676, 0.08599598299997524, 0.05457614750002904, 0.08655613450002875, 0.5471998515001815, 0.40287206849984614, 0.602867516999936, 0.5751344150000932, 0.6627573000000666, 0.5640937264998342, 0.6500037429998429, 0.551624312999877, 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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/memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_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-3.8/scikit-fem/sympy/tqdm/wget/memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV.json @@ -1 +1 @@ -[[14269, [952.0, 952.0]], [14286, [952.0, 952.0]], [14316, [952.0, 952.0]], [14343, [952.0, 952.0]], [14361, [952.0, 952.0]], [14372, [952.0, 952.0]], [14386, [952.0, 952.0]], [14399, [952.0, 952.0]], [14415, [952.0, 952.0]], [14421, [952.0, 952.0]], [14441, [952.0, 952.0]], [14455, [952.0, 952.0]], [14481, [952.0, 952.0]], [14504, [952.0, 952.0]], [14533, [952.0, 952.0]], [14550, [952.0, 952.0]], [14587, [952.0, 952.0]], [14613, [952.0, 952.0]], [14643, 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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/memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT.json index f619022ed..addd83163 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/memory_sims.MemDFNSimulationGITT.mem_setup_DFN_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-3.8/scikit-fem/sympy/tqdm/wget/memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT.json @@ -1 +1 @@ -[[14269, [952.0, 952.0]], [14286, [952.0, 952.0]], [14316, [952.0, 952.0]], [14343, [952.0, 952.0]], [14361, [952.0, 952.0]], [14372, [952.0, 952.0]], [14386, 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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/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-3.8/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV.json index f619022ed..addd83163 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/memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV.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/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-3.8/scikit-fem/sympy/tqdm/wget/memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT.json @@ -1 +1 @@ -[[14269, [952.0, 952.0]], [14286, [952.0, 952.0]], [14316, [952.0, 952.0]], [14343, [952.0, 952.0]], [14361, [952.0, 952.0]], [14372, [952.0, 952.0]], [14386, [952.0, 952.0]], [14399, [952.0, 952.0]], [14415, [952.0, 952.0]], [14421, [952.0, 952.0]], [14441, [952.0, 952.0]], [14455, [952.0, 952.0]], [14481, [952.0, 952.0]], [14504, [952.0, 952.0]], [14533, [952.0, 952.0]], [14550, [952.0, 952.0]], [14587, [952.0, 952.0]], [14613, [952.0, 952.0]], [14643, 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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/memory_unit_benchmarks.MemCreateExpression.mem_create_expression.json index 7b96e88ae..051b11b2f 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/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-3.8/scikit-fem/sympy/tqdm/wget/memory_unit_benchmarks.MemCreateExpression.mem_create_expression.json @@ -1 +1 @@ -[[14269, 448.0], [14286, 448.0], [14316, 448.0], [14343, 448.0], [14361, 448.0], [14372, 448.0], [14386, 448.0], [14399, 448.0], [14415, 448.0], [14421, 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a/graphs/summary/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json b/graphs/summary/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json index 9f600e970..567ed3269 100644 --- a/graphs/summary/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json +++ b/graphs/summary/memory_unit_benchmarks.MemDiscretiseModel.mem_discretise.json @@ -1 +1 @@ -[[10863, 192.0], [10873, 192.0], [10886, 192.0], [10900, 192.0], [10907, 192.0], [10928, 192.0], [10950, 192.0], [10976, 192.0], [10978, 192.0], [11003, 192.0], [11022, 192.0], [11030, 192.0], [11052, 192.0], [11069, 192.0], [11100, 192.0], [11125, 192.0], [11127, 192.0], [11131, 192.0], [11155, 192.0], [11175, 192.0], [11207, 192.0], [11219, 192.0], [11259, 192.0], [11272, 192.0], [11300, 192.0], [11317, 192.0], [11342, 192.0], [11350, 192.0], [11373, 192.0], [11406, 192.0], [11408, 192.0], [11417, 192.0], [11452, 192.0], [11454, 192.0], [11468, 192.0], [11486, 192.0], [11522, 192.0], [11525, 192.0], [11558, 192.0], 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"env-LD_LIBRARY_PATH": "/home/runner/.local/lib", "branch": "develop", "anytree": null, "autograd": null, "scikit-fem": null, "imageio": null, "pybtex": null, "sympy": null, "bpx": null, "tqdm": null, "matplotlib": null}], "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)", "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": "9f3dfe67f8a8a4383ed41454515e96f36fbd859c7a8c86ee1b80ed0fe446c02c", "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)", "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": "92f39a892bcc5c7db147e87ef2cdd1a8fbfbb90ed1ee5a8907203ba6c7d2aecf", "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)", "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": "c32b56d8b7abd0d68c004e6e8fbe9de0acd1d71b5b0d0b1682f648bc8a39b391", "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)", "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": "d712bc9a59370612798cbb7043cd2ef7477b9ee7df0546cac38242bd598ca18d", "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)", "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": "1aa4c86af11cae5b0d40de18d782c6556c39a2c3b4359e25a29b0ff8bfce3de2", "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)", "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": "498f169375ada7271622b725ddc648abd90553aa621b17a11893b6fbcf1a3c7f", "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 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": "a7e921423ff12485f9191cadd13947c31710cf832f17da13ad68c5de2d0602ae", "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 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": "c1dff76d9e08da716685373107680084f50ebfb24c147064023ae3dacb502e06", "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 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": "ac0ac4e14582d06dfa824e725b3727a5180a44001c838a983c6c41458c0f1027", "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 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": "ae8aaf2c307ac32961fa5042f713258828cc71346da90c2364f4adb7320b2c2e", "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 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": "b284405e56214e750ff79f8a73ba2af17787ac9f6621fceb93eabd94f54146d8", "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 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": "e13856f7f828f5e2f68e83317010aca0c728a0fbb5fb953b73da8739b742a12a", "warmup_time": -1}, "memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV": {"code": "class MemDFNSimulationCCCV:\n def mem_setup_DFN_simulationCCCV(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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", "name": "memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "dcfa286e2ee441d8889df80a96e4bc08a19dce1b0dcc06cff67db8871dde214c"}, "memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT": {"code": "class MemDFNSimulationGITT:\n def mem_setup_DFN_simulationGITT(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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", "name": "memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "19cf3b39382834a8cb86fab71ae7457cb9784ff4be59085c9fbef9fef541601f"}, "memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV": {"code": "class MemSPMSimulationCCCV:\n def mem_setup_SPM_simulationCCCV(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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", "name": "memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "4d487b81ebe806e06b74c7e8a4e5adf7d2d193a65b9904033b32df9b546a400b"}, "memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT": {"code": "class MemSPMSimulationGITT:\n def mem_setup_SPM_simulationGITT(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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", "name": "memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "e795149bf5ef6de3f6a22e7aae87dee586fcfb2ad48f5567048499f946f84f6e"}, "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", "name": "memory_unit_benchmarks.MemCreateExpression.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "051d7dd69db532340a54137adc47187cb7fc1788330eeb474f50641a2202c9ff"}, "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 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": "161d1e865768e388bedfc8f24eec7c376ac9fef84acf0bdbcdaa583aca95ab68"}, "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 MemCreateExpression.mem_create_expression(self)", "name": "memory_unit_benchmarks.MemParameteriseModel.mem_parameterise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "d219da44966aae64a4ce98e5cfde0a0acedae4fdac3bcff12064b8d77fc7ef1a"}, "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 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": "0098dfcd1304100f58897a06d62ad61d924a646365de3706e91294f8d89943d3"}, "time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN": {"code": "class TimeBuildDFN:\n def time_setup_DFN(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "5294948f9d12b08e0ca91e872f066e08b04cc20a728431d490a7f389fb25d4cb", "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, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "bec1ef0368e5b10eb69f23a0228764e22ba74a9ce379a2d632fe081d9b554772", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPM.time_setup_SPM": {"code": "class TimeBuildSPM:\n def time_setup_SPM(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "9cc0fc69309859c6bf4b82d51013e8fe94dd813b79bac34773123bfbe9575b69", "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, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "dcc0e5a798b16647676f9beb1311bd07fcbd43b5f1445721dee62457345f84f0", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPMe.time_setup_SPMe": {"code": "class TimeBuildSPMe:\n def time_setup_SPMe(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "42f066a302b7c7c0b8678546b480bc896e28faa8487a3ada7570e4b587d592db", "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, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "fa33f32dc52b29c7d15644fc09b82fa83412d56629204948b3a5291eb4d299d7", "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 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": "70bb63e00480334e8fb1ebab75ebd483d2e781180b0c106d2217583902b2f268", "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 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": "5581bd492a800415d9c6a1a381d87fcbc56564996b9d82ebe0f0c9b7518cc948", "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 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": "2f249ee7769f90524c47792571e7fe7ffdbef508d9090cc00ede84a16dc8d177", "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 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": "585652f5d88e12033cb4a7e8624f0289ddbc9e33d255c8022ff613a2e1acdf74", "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 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": "29fa52398e50081bc33cbf7c010649649e82aa3b26e967430dba19d70ca80712", "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 }", "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": "d50f4d23b4da39a89763df3a16060d53690898d238986a03d1867d86fdd8baf6", "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 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": "4fbfe1ce99553daa3ea65f929308b968644f29f5a930c12c92505465fb85c788", "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 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": "58d52171a131f2e05d1ca3d07e0a65d958c048aa8fe7d01aa04959f95800017d", "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 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": "f55331e31db8421a38d5fc1cae40690d1af2dfe4dbbcfbbcf716519cf3ff2946", "warmup_time": -1}}, "machines": {"GitHubRunner": {"machine": "GitHubRunner", "version": 1}}, "tags": {"v0.1.0": 3639, "v0.2.0": 4986, "v0.2.1": 5324, "v0.2.2": 6039, "v0.2.3": 6486, "v0.2.4": 6849, "v0.3.0": 7408, "v0.3.0-beta": 7345, "v0.4.0": 8469, "v21.08": 9273, "v21.10": 9559, "v21.11": 9930, "v21.12": 10079, "v21.9": 9445, "v22.1": 10291, "v22.10": 11984, "v22.11": 12362, "v22.11.1": 12493, "v22.12": 12559, "v22.2": 10351, "v22.3": 10478, "v22.4": 10571, "v22.5": 10732, "v22.6": 10873, "v22.7": 11201, "v22.8": 11417, "v22.9": 11660, "v23.1": 12708, "v23.2": 12991, "v23.3": 13327, "v23.4": 13477, "v23.4.1": 13489, "v23.5": 14069, "v23.5rc0": 13890}, "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": {"3639": "8afc8f94f75b6f0b51928f43819f9894d2b91020", "4986": "801492b250a6637554d99a4662a0d85c3354ceea", "5324": "105714c9748f7c7f3824411240ab583ac6c4973a", "6039": "eff587b12cd3e41b911c4665909f3d4ab8a8f50f", "6486": "09a3c082833f876bd5f4962306340886d29fa116", "6849": "f00b8d11ec0c4169c53d6fb1e0cd58e71009e924", "7345": "e408c41c6c3c432da7fc9a49263e4fc3b454ca45", "7408": "d1d6af04c5083b6c413fe30b1af4f4add1b222e3", "8469": "0a99ea46b37bedd729f75d8d1e101122c27bb6d8", "8742": "f6cb07aa40ec406ba9eba3f90c09ccf0c5feb539", "8995": 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1696094703000, "15217": 1696247241000}, "params": {"machine": ["GitHubRunner"], "python": ["3.8"], "numpy": ["", null], "casadi": ["", null], "wget": ["", null], "cmake": ["", null], "anytree": ["", null], "autograd": ["", null], "scikit-fem": ["", null], "imageio": ["", null], "pybtex": ["", null], "sympy": ["", null], "bpx": ["", null], "tqdm": ["", null], "matplotlib": ["", null], "env-LD_LIBRARY_PATH": ["/home/runner/.local/lib", null], "branch": ["develop"]}, "graph_param_list": [{"machine": "GitHubRunner", "python": "3.8", "branch": "develop", "numpy": null, "casadi": null, "wget": null, "cmake": null, "anytree": null, "autograd": null, "scikit-fem": null, "imageio": null, "pybtex": null, "sympy": null, "bpx": null, "tqdm": null, "matplotlib": null, "env-LD_LIBRARY_PATH": null}, {"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": "3.8", "numpy": "", "casadi": "", "wget": "", "cmake": "", "env-LD_LIBRARY_PATH": "/home/runner/.local/lib", "branch": "develop", "anytree": null, "autograd": null, "scikit-fem": null, "imageio": null, "pybtex": null, "sympy": null, "bpx": null, "tqdm": null, "matplotlib": null}], "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)", "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": "9f3dfe67f8a8a4383ed41454515e96f36fbd859c7a8c86ee1b80ed0fe446c02c", "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)", "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": "92f39a892bcc5c7db147e87ef2cdd1a8fbfbb90ed1ee5a8907203ba6c7d2aecf", "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)", "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": "c32b56d8b7abd0d68c004e6e8fbe9de0acd1d71b5b0d0b1682f648bc8a39b391", "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)", "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": "d712bc9a59370612798cbb7043cd2ef7477b9ee7df0546cac38242bd598ca18d", "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)", "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": "1aa4c86af11cae5b0d40de18d782c6556c39a2c3b4359e25a29b0ff8bfce3de2", "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)", "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": "498f169375ada7271622b725ddc648abd90553aa621b17a11893b6fbcf1a3c7f", "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 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": "a7e921423ff12485f9191cadd13947c31710cf832f17da13ad68c5de2d0602ae", "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 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": "c1dff76d9e08da716685373107680084f50ebfb24c147064023ae3dacb502e06", "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 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": "ac0ac4e14582d06dfa824e725b3727a5180a44001c838a983c6c41458c0f1027", "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 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": "ae8aaf2c307ac32961fa5042f713258828cc71346da90c2364f4adb7320b2c2e", "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 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": "b284405e56214e750ff79f8a73ba2af17787ac9f6621fceb93eabd94f54146d8", "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 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": "e13856f7f828f5e2f68e83317010aca0c728a0fbb5fb953b73da8739b742a12a", "warmup_time": -1}, "memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV": {"code": "class MemDFNSimulationCCCV:\n def mem_setup_DFN_simulationCCCV(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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", "name": "memory_sims.MemDFNSimulationCCCV.mem_setup_DFN_simulationCCCV", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "dcfa286e2ee441d8889df80a96e4bc08a19dce1b0dcc06cff67db8871dde214c"}, "memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT": {"code": "class MemDFNSimulationGITT:\n def mem_setup_DFN_simulationGITT(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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", "name": "memory_sims.MemDFNSimulationGITT.mem_setup_DFN_simulationGITT", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "19cf3b39382834a8cb86fab71ae7457cb9784ff4be59085c9fbef9fef541601f"}, "memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV": {"code": "class MemSPMSimulationCCCV:\n def mem_setup_SPM_simulationCCCV(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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", "name": "memory_sims.MemSPMSimulationCCCV.mem_setup_SPM_simulationCCCV", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "4d487b81ebe806e06b74c7e8a4e5adf7d2d193a65b9904033b32df9b546a400b"}, "memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT": {"code": "class MemSPMSimulationGITT:\n def mem_setup_SPM_simulationGITT(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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", "name": "memory_sims.MemSPMSimulationGITT.mem_setup_SPM_simulationGITT", "param_names": ["parameter"], "params": [["'Marquis2019'", "'Chen2020'"]], "type": "memory", "unit": "bytes", "version": "e795149bf5ef6de3f6a22e7aae87dee586fcfb2ad48f5567048499f946f84f6e"}, "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", "name": "memory_unit_benchmarks.MemCreateExpression.mem_create_expression", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "051d7dd69db532340a54137adc47187cb7fc1788330eeb474f50641a2202c9ff"}, "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 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": "161d1e865768e388bedfc8f24eec7c376ac9fef84acf0bdbcdaa583aca95ab68"}, "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 MemCreateExpression.mem_create_expression(self)", "name": "memory_unit_benchmarks.MemParameteriseModel.mem_parameterise", "param_names": [], "params": [], "type": "memory", "unit": "bytes", "version": "d219da44966aae64a4ce98e5cfde0a0acedae4fdac3bcff12064b8d77fc7ef1a"}, "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 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": "0098dfcd1304100f58897a06d62ad61d924a646365de3706e91294f8d89943d3"}, "time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN": {"code": "class TimeBuildDFN:\n def time_setup_DFN(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "5294948f9d12b08e0ca91e872f066e08b04cc20a728431d490a7f389fb25d4cb", "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, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "bec1ef0368e5b10eb69f23a0228764e22ba74a9ce379a2d632fe081d9b554772", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPM.time_setup_SPM": {"code": "class TimeBuildSPM:\n def time_setup_SPM(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "9cc0fc69309859c6bf4b82d51013e8fe94dd813b79bac34773123bfbe9575b69", "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, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "dcc0e5a798b16647676f9beb1311bd07fcbd43b5f1445721dee62457345f84f0", "warmup_time": -1}, "time_setup_models_and_sims.TimeBuildSPMe.time_setup_SPMe": {"code": "class TimeBuildSPMe:\n def time_setup_SPMe(self, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "42f066a302b7c7c0b8678546b480bc896e28faa8487a3ada7570e4b587d592db", "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, parameters):\n self.param = pybamm.ParameterValues(parameters)\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)", "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": "fa33f32dc52b29c7d15644fc09b82fa83412d56629204948b3a5291eb4d299d7", "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 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": "70bb63e00480334e8fb1ebab75ebd483d2e781180b0c106d2217583902b2f268", "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 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": "5581bd492a800415d9c6a1a381d87fcbc56564996b9d82ebe0f0c9b7518cc948", "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 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": "2f249ee7769f90524c47792571e7fe7ffdbef508d9090cc00ede84a16dc8d177", "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 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": "585652f5d88e12033cb4a7e8624f0289ddbc9e33d255c8022ff613a2e1acdf74", "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 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": "29fa52398e50081bc33cbf7c010649649e82aa3b26e967430dba19d70ca80712", "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 }", "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": "d50f4d23b4da39a89763df3a16060d53690898d238986a03d1867d86fdd8baf6", "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 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": "4fbfe1ce99553daa3ea65f929308b968644f29f5a930c12c92505465fb85c788", "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 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": "58d52171a131f2e05d1ca3d07e0a65d958c048aa8fe7d01aa04959f95800017d", "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 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": "f55331e31db8421a38d5fc1cae40690d1af2dfe4dbbcfbbcf716519cf3ff2946", "warmup_time": -1}}, "machines": {"GitHubRunner": {"machine": "GitHubRunner", "version": 1}}, "tags": {"v0.1.0": 3639, "v0.2.0": 4986, "v0.2.1": 5324, "v0.2.2": 6039, "v0.2.3": 6486, "v0.2.4": 6849, "v0.3.0": 7408, "v0.3.0-beta": 7345, "v0.4.0": 8469, "v21.08": 9273, "v21.10": 9559, "v21.11": 9930, "v21.12": 10079, "v21.9": 9445, "v22.1": 10291, "v22.10": 11984, "v22.11": 12362, "v22.11.1": 12493, "v22.12": 12559, "v22.2": 10351, "v22.3": 10478, "v22.4": 10571, "v22.5": 10732, "v22.6": 10873, "v22.7": 11201, "v22.8": 11417, "v22.9": 11660, "v23.1": 12708, "v23.2": 12991, "v23.3": 13327, "v23.4": 13477, "v23.4.1": 13489, "v23.5": 14069, "v23.5rc0": 13890}, "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 f590059f6..02fe91852 100644 --- a/info.json +++ b/info.json @@ -1,4 +1,4 @@ { "asv-version": "0.6.1", - "timestamp": 1696219633843 + "timestamp": 1696306114981 } \ No newline at end of file diff --git a/regressions.json b/regressions.json index a655ee18d..66b5701c2 100644 --- a/regressions.json +++ b/regressions.json @@ -1 +1 @@ -{"regressions": [["time_setup_models_and_sims.TimeBuildDFN.time_setup_DFN('Marquis2019')", 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