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Merge pull request #86 from KratosMultiphysics/mlmc-update-examples
[MLMC] Update CPF example
2 parents d4922da + 495d549 commit df1aed7

11 files changed

Lines changed: 93 additions & 103 deletions

‎multilevel_monte_carlo/use_cases/compressible_potential_flow/README.md‎

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**Kratos version:** 8.1
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**XMC version:** 2.0
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**XMC version:** Kratos default version
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**PyCOMPSs version:** 2.7
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**PyCOMPSs version:** Kratos default version to run in serial, >2.8 to run with `runcompss`
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**Source files:** [Asynchronous Monte Carlo and Asynchronous Multilevel Monte Carlo](source)
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‎multilevel_monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/materials.json‎

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{
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"properties" : [{
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"model_part_name" : "model",
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"properties_id" : 1,
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"Material" : {
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"Variables" : {
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"DENSITY" : 1.225
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},
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"Tables" : {}
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}
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}]
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}
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‎multilevel_monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev0.json‎

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"input_type" : "mdpa",
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"input_filename" : "problem_settings/naca0012Mesh4"
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},
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"material_import_settings": {
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"materials_filename": "problem_settings/materials.json"
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},
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"formulation" : {
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"element_type": "compressible"
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},

‎multilevel_monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev1.json‎

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"input_type" : "mdpa",
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"input_filename" : "problem_settings/CPS_MONTECARLO_MeshInterpError1e-2"
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},
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"material_import_settings": {
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"materials_filename": "problem_settings/materials.json"
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},
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"formulation" : {
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"element_type": "compressible"
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},

‎multilevel_monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev2.json‎

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"input_type" : "mdpa",
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"input_filename" : "problem_settings/CPS_MONTECARLO_MeshInterpError5e-3"
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},
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"material_import_settings": {
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"materials_filename": "problem_settings/materials.json"
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},
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"formulation" : {
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"element_type": "compressible"
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},

‎multilevel_monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/parameters_refinement.json‎

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{
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"hessian_metric": {
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"metric": {
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"hessian_strategy_parameters" :{
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"metric_variable" : ["VELOCITY_X,VELOCITY_Y"],
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"estimate_interpolation_error" : false,
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"anisotropy_remeshing" : true,
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"enforce_anisotropy_relative_variable" : false
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},
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"refinement_mmg" : {
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"remeshing" : {
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"initialize_entities" : false,
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"echo_level" : 0
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}

‎multilevel_monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/parameters_xmc_asynchronous_mc_potentialFlow.json‎

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"tolerancesForHierarchy": [0],
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"positionMaxNumberIterationsCriterion": 2
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},
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"costEstimatorInputDictionary": {
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"indexSetDimension": 0,
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"order": 1
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},
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"hierarchyOptimiserInputDictionary": {
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"defaultHierarchy": [[[],5]],
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"indexSpace": [1,1],
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},
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"monteCarloIndexInputDictionary": {
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"costEstimator": "xmc.momentEstimator.MomentEstimator",
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"costEstimatorInputDictionary": {
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"indexSetDimension": 0, "order": 1, "updatedPowerSums":"xmc.methodDefs_momentEstimator.updatePowerSums.updatePowerSumsOrder2Dimension0", "centralMomentComputer":"xmc.methodDefs_momentEstimator.computeCentralMoments.centralMomentWrapper", "centralMomentErrorComputer":"xmc.methodDefs_momentEstimator.computeErrorEstimation.centralMomentErrorWrapper"
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},
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"indexValue": null,
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"qoiEstimator": ["xmc.momentEstimator.MomentEstimator"],
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"combinedEstimator": ["xmc.momentEstimator.CombinedMomentEstimator"],
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"qoiEstimator": [
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"xmc.momentEstimator.MomentEstimator",
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"xmc.momentEstimator.MultiMomentEstimator"
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],
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"qoiEstimatorInputDictionary": [
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{"indexSetDimension": 0,"order": 5,"updatedPowerSums":"xmc.methodDefs_momentEstimator.updatePowerSums.updatePowerSumsOrder10Dimension0","centralMomentComputer":"xmc.methodDefs_momentEstimator.computeCentralMoments.centralMomentWrapper","centralMomentErrorComputer":"xmc.methodDefs_momentEstimator.computeErrorEstimation.centralMomentErrorWrapper"},
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{"variableDimension": 3432,"order": 1, "isEstimationParallel": false}],
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"sampler": "xmc.sampleGenerator.SampleGenerator",
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"eventGroupSize": 5
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},
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"qoiPredictor": [],
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"initialNumberBatches": 1
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},
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"qoiEstimatorInputDictionary": {
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"indexSetDimension": 0,
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"order": 5
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},
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"combinedEstimatorInputDictionary": {
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"indexSetDimension": 0,
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"order": 5
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},
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"randomGeneratorInputDictionary": {
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"generator": "xmc.methodDefs_randomGeneratorWrapper.generator.returnUniformAndTwoNormal",
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"parameters": [0,4294967295,0.3,0.003,-0.035,0.00035]
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},
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"solverWrapperInputDictionary": {
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"adaptiveRefinementJumpToFinestLevel": false,
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"analysisStage": "simulation_definition.SimulationScenario",
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"asynchronous": true,
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"fakeRandomVariable": [0,0.3,0.0],
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"index": [],
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"mappingOutputQuantities": false,
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"numberContributionsPerInstance": 1,
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"numberQoI": 3433,
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"numberCombinedQoi": 0,
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"outputBatchSize": 1717,
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"outputBatchSize": 1,
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"parameters": null,
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"printToFile": true,
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"problemId": "problem_airfoil",
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"projectParametersPath": "problem_settings/parameters_potential_naca_lev2.json",
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"refinementParametersPath": "problem_settings/parameters_refinement.json",
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"refinementStrategy": "stochastic_adaptive_refinement",
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"sizeMultiXMomentEstimator": 3432,
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"taskAllAtOnce": true
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},
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"monoCriteriaInpuctDictionary" :{
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"statisticalError": {
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"criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isLowerThanOrEqualTo",
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"tolerance": [0.01],
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"tolerance": 0.01,
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"input": "error0"
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},
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"minNumberIterations": {
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"criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isGreaterThanOrEqualTo",
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"tolerance": [0],
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"tolerance": 0.0,
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"input": "algorithmCost"
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},
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"maxNumberIterations": {
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"criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isGreaterThanOrEqualTo",
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"tolerance": [0],
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"tolerance": 0.0,
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"input": "algorithmCost"
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}
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},

‎multilevel_monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/parameters_xmc_asynchronous_mlmc_potentialFlow.json‎

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"tolerancesForHierarchy": [0],
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"positionMaxNumberIterationsCriterion": 2
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},
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"costEstimatorInputDictionary": {
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"indexSetDimension": 0,
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"order": 1
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},
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"hierarchyOptimiserInputDictionary": {
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"defaultHierarchy": [[[0],5],[[1],5],[[2],5]],
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"indexSpace": [10],
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"toleranceSplittingBounds": [0.5,0.5]
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},
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"monteCarloIndexInputDictionary": {
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"combinedEstimator": ["xmc.momentEstimator.CombinedMomentEstimator"],
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"costEstimator": "xmc.momentEstimator.MomentEstimator",
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"costEstimatorInputDictionary": {
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"indexSetDimension": 0,
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"order": 1,
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"updatedPowerSums":"xmc.methodDefs_momentEstimator.updatePowerSums.updatePowerSumsOrder2Dimension0",
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"centralMomentComputer":"xmc.methodDefs_momentEstimator.computeCentralMoments.centralMomentWrapper",
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"centralMomentErrorComputer":"xmc.methodDefs_momentEstimator.computeErrorEstimation.centralMomentErrorWrapper"
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},
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"indexValue": null,
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"qoiEstimator": ["xmc.momentEstimator.MomentEstimator"],
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"qoiEstimator": [
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"xmc.momentEstimator.MomentEstimator",
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"xmc.momentEstimator.MultiMomentEstimator"
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],
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"qoiEstimatorInputDictionary": [
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{"indexSetDimension": 1,"order": 1,"updatedPowerSums":"xmc.methodDefs_momentEstimator.updatePowerSums.updatePowerSumsOrder2Dimension1","centralMomentComputer":"xmc.methodDefs_momentEstimator.computeCentralMoments.centralMomentWrapper","centralMomentErrorComputer":"xmc.methodDefs_momentEstimator.computeErrorEstimation.centralMomentErrorWrapper"},
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{"variableDimension": 204,"order": 1, "isEstimationParallel": false}
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],
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"sampler": "xmc.sampleGenerator.SampleGenerator",
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"eventGroupSize": 5
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},
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"qoiPredictor": [],
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"initialNumberBatches": 1
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},
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"qoiEstimatorInputDictionary": {
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"indexSetDimension": 1,
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"order": 1
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},
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"combinedEstimatorInputDictionary": {
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"indexSetDimension": 1,
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"order": 1
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},
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"randomGeneratorInputDictionary": {
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"generator": "xmc.methodDefs_randomGeneratorWrapper.generator.returnUniformAndTwoNormal",
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"parameters": [0,4294967295,0.3,0.03,0.0,0.0087]
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},
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"solverWrapperInputDictionary": {
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"adaptiveRefinementJumpToFinestLevel": false,
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"analysisStage": "simulation_definition.SimulationScenario",
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"asynchronous": true,
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"fakeRandomVariable": [0,0.3,0.0],
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"index": [],
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"mappingOutputQuantities": true,
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"numberContributionsPerInstance": 1,
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"numberQoI": 205,
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"numberCombinedQoi": 0,
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"outputBatchSize": 1,
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"parameters": null,
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"printToFile": false,
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"problemId": "problem_airfoil",
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"projectParametersPath": ["problem_settings/parameters_potential_naca_lev0.json","problem_settings/parameters_potential_naca_lev1.json","problem_settings/parameters_potential_naca_lev2.json"],
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"refinementParametersPath": "problem_settings/parameters_refinement.json",
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"refinementStrategy": "reading_from_file",
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"sizeMultiXMomentEstimator": 204,
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"taskAllAtOnce": true
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},
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"monoCriteriaInpuctDict" :{
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"statisticalError": {
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"criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isLowerThanOrEqualTo",
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"tolerance": [0.15],
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"tolerance": 0.15,
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"input": "error0"
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},
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"minNumberIterations": {
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"criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isGreaterThanOrEqualTo",
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"tolerance": [0],
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"tolerance": 0.0,
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"input": "algorithmCost"
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},
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"maxNumberIterations": {
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"criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isGreaterThanOrEqualTo",
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"tolerance": [0],
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"tolerance": 0.0,
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"input": "algorithmCost"
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}
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},

‎multilevel_monte_carlo/use_cases/compressible_potential_flow/source/run_mc_Kratos.py‎

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import KratosMultiphysics.MultilevelMonteCarloApplication
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import xmc
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import xmc.methodDefs_momentEstimator.computeCentralMoments as mdccm
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from exaqute.ExaquteTaskLocal import *
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from exaqute import get_value_from_remote
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if __name__ == "__main__":
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with open(parametersPath,'r') as parameter_file:
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parameters = json.load(parameter_file)
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# add path of the problem folder to python path
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problem_id = parameters["solverWrapperInputDictionary"]["problemId"]
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sys.path.append(os.path.join("..","xmc","classDefs_solverWrapper","problemDefs_KratosMultiphysics",problem_id))
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# SolverWrapper
29+
parameters["solverWrapperInputDictionary"]["qoiEstimator"] = parameters["monteCarloIndexInputDictionary"]["qoiEstimator"]
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# SampleGenerator
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samplerInputDictionary = parameters["samplerInputDictionary"]
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monteCarloIndexInputDictionary = parameters["monteCarloIndexInputDictionary"]
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monteCarloIndexInputDictionary["samplerInputDictionary"] = samplerInputDictionary
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# Moment Estimators
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qoiEstimatorInputDictionary = parameters["qoiEstimatorInputDictionary"]
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combinedEstimatorInputDictionary = parameters["combinedEstimatorInputDictionary"]
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costEstimatorInputDictionary = parameters["costEstimatorInputDictionary"]
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# qoi estimators
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monteCarloIndexInputDictionary["qoiEstimator"] = [monteCarloIndexInputDictionary["qoiEstimator"][0] for _ in range (0,parameters["solverWrapperInputDictionary"]["numberQoI"])]
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monteCarloIndexInputDictionary["qoiEstimatorInputDictionary"] = [qoiEstimatorInputDictionary]*parameters["solverWrapperInputDictionary"]["numberQoI"]
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# combined estimators
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monteCarloIndexInputDictionary["combinedEstimator"] = [monteCarloIndexInputDictionary["combinedEstimator"][0] for _ in range (0,parameters["solverWrapperInputDictionary"]["numberCombinedQoi"])]
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monteCarloIndexInputDictionary["combinedEstimatorInputDictionary"] = [combinedEstimatorInputDictionary]*parameters["solverWrapperInputDictionary"]["numberCombinedQoi"]
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# cost estimator
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monteCarloIndexInputDictionary["costEstimatorInputDictionary"] = costEstimatorInputDictionary
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# MonoCriterion
5441
criteriaArray = []
5542
criteriaInputs = []
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153140
qoi_dict["qoi_id_"+str(qoi_counter)]["index_"+str(index)] = {"qoi_id":qoi_counter, "index": index, "instances": sample_counter, "S1": S1, "S2": S2, "S3": S3, "S4": S4, "S5": S5, "S6": S6, "S7": S7, "S8": S8, "S9": S9, "S10": S10, "h1": h1, "h2": h2,"type":"scalar_quantity","tag":"lift_coefficient"}
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# save pressure coefficient
143+
qoi_counter = qoi_counter + 1
144+
qoi_dict["qoi_id_"+str(qoi_counter)] = {"member_"+str(member): {} for member in range (algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter]._variableDimension)}
145+
member = 0
156146
for node in current_model.GetModelPart(model_part_of_interest).Nodes:
157-
qoi_counter = qoi_counter + 1
158-
qoi_dict["qoi_id_"+str(qoi_counter)] = {"index_"+str(index): {} for index in range (len(algo.monteCarloSampler.indices))}
147+
qoi_dict["qoi_id_"+str(qoi_counter)]["member_"+str(member)] = {"index_"+str(index): {} for index in range (len(algo.monteCarloSampler.indices))}
159148
for index in range (len(algo.monteCarloSampler.indices)):
160149
algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter] = get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter])
161150
sample_counter = algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter]._sampleCounter
162-
S1 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[0][0]))
163-
S2 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[1][0]))
164-
S3 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[2][0]))
165-
S4 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[3][0]))
166-
S5 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[4][0]))
167-
S6 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[5][0]))
168-
S7 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[6][0]))
169-
S8 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[7][0]))
170-
S9 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[8][0]))
171-
S10 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[9][0]))
151+
S1 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter]._powerSums["1"][member]))
152+
S2 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter]._powerSums["2"][member]))
172153
h1 = float(get_value_from_remote(mdccm.computeCentralMomentsOrderOneDimensionZero(S1,sample_counter)))
173154
h2 = float(get_value_from_remote(mdccm.computeCentralMomentsOrderTwoDimensionZero(S1,S2,sample_counter)))
174-
qoi_dict["qoi_id_"+str(qoi_counter)]["index_"+str(index)] = {"qoi_id":qoi_counter, "index": index, "instances": sample_counter, "S1": S1, "S2": S2, "S3": S3, "S4": S4, "S5": S5, "S6": S6, "S7": S7, "S8": S8, "S9": S9, "S10": S10, "h1": h1, "h2": h2,"type":"scalar_quantity","tag":"pressure coefficent","node_id":node.Id,"node_coordinates":[node.X,node.Y,node.Z]}
155+
qoi_dict["qoi_id_"+str(qoi_counter)]["member_"+str(member)]["index_"+str(index)] = {"qoi_id":qoi_counter, "member":member, "index": index, "instances": sample_counter, "S1": S1, "S2": S2, "S3": S3, "S4": S4, "S5": S5, "S6": S6, "S7": S7, "S8": S8, "S9": S9, "S10": S10, "h1": h1, "h2": h2,"type":"scalar_quantity","tag":"pressure coefficent","node_id":node.Id,"node_coordinates":[node.X,node.Y,node.Z]}
156+
member += 1
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176158
# save to file
177159
with open('power_sums_outputs/MC_asynchronous_power_sums_' +str(time.time()) + '.json', 'w') as f:

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