KratosMultiphysics · riccardotosi · Jul 26, 2021 · May 11, 2021 · May 11, 2021 · May 11, 2021
diff --git a/multilevel_monte_carlo/use_cases/compressible_potential_flow/README.md b/multilevel_monte_carlo/use_cases/compressible_potential_flow/README.md
@@ -4,9 +4,9 @@
 
 **Kratos version:** 8.1
 
-**XMC version:** 2.0
+**XMC version:** Kratos default version
 
-**PyCOMPSs version:** 2.7
+**PyCOMPSs version:** Kratos default version to run in serial, >2.8 to run with `runcompss`
 
 **Source files:** [Asynchronous Monte Carlo and Asynchronous Multilevel Monte Carlo](source)
 

diff --git a/..._monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/materials.json b/..._monte_carlo/use_cases/compressible_potential_flow/source/problem_settings/materials.json
@@ -0,0 +1,13 @@
+{
+    "properties" : [{
+        "model_part_name" : "model",
+        "properties_id"   : 1,
+        "Material"        : {
+            "Variables"        : {
+                "DENSITY"       : 1.225
+            },
+            "Tables"           : {}
+        }
+    }]
+}
+
diff --git a/...s/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev0.json b/...s/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev0.json
@@ -14,6 +14,9 @@
             "input_type"     : "mdpa",
             "input_filename" : "problem_settings/naca0012Mesh4"
         },
+        "material_import_settings": {
+            "materials_filename": "problem_settings/materials.json"
+        },
         "formulation"  : {
             "element_type": "compressible"
         },

diff --git a/...s/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev1.json b/...s/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev1.json
@@ -14,6 +14,9 @@
             "input_type"     : "mdpa",
             "input_filename" : "problem_settings/CPS_MONTECARLO_MeshInterpError1e-2"
         },
+        "material_import_settings": {
+            "materials_filename": "problem_settings/materials.json"
+        },
         "formulation"  : {
             "element_type": "compressible"
         },

diff --git a/...s/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev2.json b/...s/compressible_potential_flow/source/problem_settings/parameters_potential_naca_lev2.json
@@ -14,6 +14,9 @@
             "input_type"     : "mdpa",
             "input_filename" : "problem_settings/CPS_MONTECARLO_MeshInterpError5e-3"
         },
+        "material_import_settings": {
+            "materials_filename": "problem_settings/materials.json"
+        },
         "formulation"  : {
             "element_type": "compressible"
         },

diff --git a/.../use_cases/compressible_potential_flow/source/problem_settings/parameters_refinement.json b/.../use_cases/compressible_potential_flow/source/problem_settings/parameters_refinement.json
@@ -1,5 +1,5 @@
 {
-    "hessian_metric": {
+    "metric": {
 		"hessian_strategy_parameters"              :{
 				"metric_variable"				           : ["VELOCITY_X,VELOCITY_Y"],
 				"estimate_interpolation_error"     : false,
@@ -11,7 +11,7 @@
 		"anisotropy_remeshing"              : true,
 		"enforce_anisotropy_relative_variable" : false
     },
-    "refinement_mmg" : {
+    "remeshing" : {
         "initialize_entities"              : false,
         "echo_level"                       : 0
     }

diff --git a/..._potential_flow/source/problem_settings/parameters_xmc_asynchronous_mc_potentialFlow.json b/..._potential_flow/source/problem_settings/parameters_xmc_asynchronous_mc_potentialFlow.json
@@ -7,10 +7,6 @@
         "tolerancesForHierarchy": [0],
         "positionMaxNumberIterationsCriterion": 2
     },
-    "costEstimatorInputDictionary": {
-        "indexSetDimension": 0,
-        "order": 1
-    },
     "hierarchyOptimiserInputDictionary": {
         "defaultHierarchy": [[[],5]],
         "indexSpace": [1,1],
@@ -20,9 +16,17 @@
     },
     "monteCarloIndexInputDictionary": {
         "costEstimator": "xmc.momentEstimator.MomentEstimator",
+        "costEstimatorInputDictionary": {
+            "indexSetDimension": 0, "order": 1, "updatedPowerSums":"xmc.methodDefs_momentEstimator.updatePowerSums.updatePowerSumsOrder2Dimension0", "centralMomentComputer":"xmc.methodDefs_momentEstimator.computeCentralMoments.centralMomentWrapper", "centralMomentErrorComputer":"xmc.methodDefs_momentEstimator.computeErrorEstimation.centralMomentErrorWrapper"
+        },
         "indexValue": null,
-        "qoiEstimator": ["xmc.momentEstimator.MomentEstimator"],
-        "combinedEstimator": ["xmc.momentEstimator.CombinedMomentEstimator"],
+        "qoiEstimator": [
+            "xmc.momentEstimator.MomentEstimator",
+            "xmc.momentEstimator.MultiMomentEstimator"
+        ],
+        "qoiEstimatorInputDictionary": [
+            {"indexSetDimension": 0,"order": 5,"updatedPowerSums":"xmc.methodDefs_momentEstimator.updatePowerSums.updatePowerSumsOrder10Dimension0","centralMomentComputer":"xmc.methodDefs_momentEstimator.computeCentralMoments.centralMomentWrapper","centralMomentErrorComputer":"xmc.methodDefs_momentEstimator.computeErrorEstimation.centralMomentErrorWrapper"},
+            {"variableDimension": 3432,"order": 1, "isEstimationParallel": false}],
         "sampler": "xmc.sampleGenerator.SampleGenerator",
         "eventGroupSize": 5
     },
@@ -36,14 +40,6 @@
         "qoiPredictor": [],
         "initialNumberBatches": 1
     },
-    "qoiEstimatorInputDictionary": {
-        "indexSetDimension": 0,
-        "order": 5
-    },
-    "combinedEstimatorInputDictionary": {
-        "indexSetDimension": 0,
-        "order": 5
-    },
     "randomGeneratorInputDictionary": {
         "generator": "xmc.methodDefs_randomGeneratorWrapper.generator.returnUniformAndTwoNormal",
         "parameters": [0,4294967295,0.3,0.003,-0.035,0.00035]
@@ -55,36 +51,35 @@
     },
     "solverWrapperInputDictionary": {
         "adaptiveRefinementJumpToFinestLevel": false,
+        "analysisStage": "simulation_definition.SimulationScenario",
         "asynchronous": true,
         "fakeRandomVariable": [0,0.3,0.0],
         "index": [],
         "mappingOutputQuantities": false,
         "numberContributionsPerInstance": 1,
-        "numberQoI": 3433,
-        "numberCombinedQoi": 0,
-        "outputBatchSize": 1717,
+        "outputBatchSize": 1,
         "parameters": null,
         "printToFile": true,
-        "problemId": "problem_airfoil",
         "projectParametersPath": "problem_settings/parameters_potential_naca_lev2.json",
         "refinementParametersPath": "problem_settings/parameters_refinement.json",
         "refinementStrategy": "stochastic_adaptive_refinement",
+        "sizeMultiXMomentEstimator": 3432,
         "taskAllAtOnce": true
     },
     "monoCriteriaInpuctDictionary" :{
         "statisticalError": {
             "criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isLowerThanOrEqualTo",
-            "tolerance": [0.01],
+            "tolerance": 0.01,
             "input": "error0"
         },
         "minNumberIterations": {
             "criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isGreaterThanOrEqualTo",
-            "tolerance": [0],
+            "tolerance": 0.0,
             "input": "algorithmCost"
         },
         "maxNumberIterations": {
             "criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isGreaterThanOrEqualTo",
-            "tolerance": [0],
+            "tolerance": 0.0,
             "input": "algorithmCost"
         }
     },

diff --git a/...otential_flow/source/problem_settings/parameters_xmc_asynchronous_mlmc_potentialFlow.json b/...otential_flow/source/problem_settings/parameters_xmc_asynchronous_mlmc_potentialFlow.json
@@ -7,10 +7,6 @@
         "tolerancesForHierarchy": [0],
         "positionMaxNumberIterationsCriterion": 2
     },
-    "costEstimatorInputDictionary": {
-        "indexSetDimension": 0,
-        "order": 1
-    },
     "hierarchyOptimiserInputDictionary": {
         "defaultHierarchy": [[[0],5],[[1],5],[[2],5]],
         "indexSpace": [10],
@@ -19,10 +15,23 @@
         "toleranceSplittingBounds": [0.5,0.5]
     },
     "monteCarloIndexInputDictionary": {
-        "combinedEstimator": ["xmc.momentEstimator.CombinedMomentEstimator"],
         "costEstimator": "xmc.momentEstimator.MomentEstimator",
+        "costEstimatorInputDictionary": {
+            "indexSetDimension": 0,
+            "order": 1,
+            "updatedPowerSums":"xmc.methodDefs_momentEstimator.updatePowerSums.updatePowerSumsOrder2Dimension0",
+            "centralMomentComputer":"xmc.methodDefs_momentEstimator.computeCentralMoments.centralMomentWrapper",
+            "centralMomentErrorComputer":"xmc.methodDefs_momentEstimator.computeErrorEstimation.centralMomentErrorWrapper"
+        },
         "indexValue": null,
-        "qoiEstimator": ["xmc.momentEstimator.MomentEstimator"],
+        "qoiEstimator": [
+            "xmc.momentEstimator.MomentEstimator",
+            "xmc.momentEstimator.MultiMomentEstimator"
+        ],
+        "qoiEstimatorInputDictionary": [
+            {"indexSetDimension": 1,"order": 1,"updatedPowerSums":"xmc.methodDefs_momentEstimator.updatePowerSums.updatePowerSumsOrder2Dimension1","centralMomentComputer":"xmc.methodDefs_momentEstimator.computeCentralMoments.centralMomentWrapper","centralMomentErrorComputer":"xmc.methodDefs_momentEstimator.computeErrorEstimation.centralMomentErrorWrapper"},
+            {"variableDimension": 204,"order": 1, "isEstimationParallel": false}
+        ],
         "sampler": "xmc.sampleGenerator.SampleGenerator",
         "eventGroupSize": 5
     },
@@ -36,14 +45,6 @@
         "qoiPredictor": [],
         "initialNumberBatches": 1
     },
-    "qoiEstimatorInputDictionary": {
-        "indexSetDimension": 1,
-        "order": 1
-    },
-    "combinedEstimatorInputDictionary": {
-        "indexSetDimension": 1,
-        "order": 1
-    },
     "randomGeneratorInputDictionary": {
         "generator": "xmc.methodDefs_randomGeneratorWrapper.generator.returnUniformAndTwoNormal",
         "parameters": [0,4294967295,0.3,0.03,0.0,0.0087]
@@ -55,36 +56,35 @@
     },
     "solverWrapperInputDictionary": {
         "adaptiveRefinementJumpToFinestLevel": false,
+        "analysisStage": "simulation_definition.SimulationScenario",
         "asynchronous": true,
         "fakeRandomVariable": [0,0.3,0.0],
         "index": [],
         "mappingOutputQuantities": true,
         "numberContributionsPerInstance": 1,
-        "numberQoI": 205,
-        "numberCombinedQoi": 0,
         "outputBatchSize": 1,
         "parameters": null,
         "printToFile": false,
-        "problemId": "problem_airfoil",
         "projectParametersPath": ["problem_settings/parameters_potential_naca_lev0.json","problem_settings/parameters_potential_naca_lev1.json","problem_settings/parameters_potential_naca_lev2.json"],
         "refinementParametersPath": "problem_settings/parameters_refinement.json",
         "refinementStrategy": "reading_from_file",
+        "sizeMultiXMomentEstimator": 204,
         "taskAllAtOnce": true
     },
     "monoCriteriaInpuctDict" :{
         "statisticalError": {
             "criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isLowerThanOrEqualTo",
-            "tolerance": [0.15],
+            "tolerance": 0.15,
             "input": "error0"
         },
         "minNumberIterations": {
             "criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isGreaterThanOrEqualTo",
-            "tolerance": [0],
+            "tolerance": 0.0,
             "input": "algorithmCost"
         },
         "maxNumberIterations": {
             "criteria": "xmc.methodDefs_monoCriterion.criterionFunctions.isGreaterThanOrEqualTo",
-            "tolerance": [0],
+            "tolerance": 0.0,
             "input": "algorithmCost"
         }
     },

diff --git a/multilevel_monte_carlo/use_cases/compressible_potential_flow/source/run_mc_Kratos.py b/multilevel_monte_carlo/use_cases/compressible_potential_flow/source/run_mc_Kratos.py
@@ -11,7 +11,8 @@
 import KratosMultiphysics.MultilevelMonteCarloApplication
 import xmc
 import xmc.methodDefs_momentEstimator.computeCentralMoments as mdccm
-from exaqute.ExaquteTaskLocal import *
+from exaqute import get_value_from_remote
+
 
 if __name__ == "__main__":
 
@@ -24,9 +25,8 @@
     with open(parametersPath,'r') as parameter_file:
             parameters = json.load(parameter_file)
 
-    # add path of the problem folder to python path
-    problem_id = parameters["solverWrapperInputDictionary"]["problemId"]
-    sys.path.append(os.path.join("..","xmc","classDefs_solverWrapper","problemDefs_KratosMultiphysics",problem_id))
+    # SolverWrapper
+    parameters["solverWrapperInputDictionary"]["qoiEstimator"] = parameters["monteCarloIndexInputDictionary"]["qoiEstimator"]
 
     # SampleGenerator
     samplerInputDictionary = parameters["samplerInputDictionary"]
@@ -37,19 +37,6 @@
     monteCarloIndexInputDictionary = parameters["monteCarloIndexInputDictionary"]
     monteCarloIndexInputDictionary["samplerInputDictionary"] = samplerInputDictionary
 
-    # Moment Estimators
-    qoiEstimatorInputDictionary = parameters["qoiEstimatorInputDictionary"]
-    combinedEstimatorInputDictionary = parameters["combinedEstimatorInputDictionary"]
-    costEstimatorInputDictionary = parameters["costEstimatorInputDictionary"]
-    # qoi estimators
-    monteCarloIndexInputDictionary["qoiEstimator"] = [monteCarloIndexInputDictionary["qoiEstimator"][0] for _ in range (0,parameters["solverWrapperInputDictionary"]["numberQoI"])]
-    monteCarloIndexInputDictionary["qoiEstimatorInputDictionary"] = [qoiEstimatorInputDictionary]*parameters["solverWrapperInputDictionary"]["numberQoI"]
-    # combined estimators
-    monteCarloIndexInputDictionary["combinedEstimator"] = [monteCarloIndexInputDictionary["combinedEstimator"][0] for _ in range (0,parameters["solverWrapperInputDictionary"]["numberCombinedQoi"])]
-    monteCarloIndexInputDictionary["combinedEstimatorInputDictionary"] = [combinedEstimatorInputDictionary]*parameters["solverWrapperInputDictionary"]["numberCombinedQoi"]
-    # cost estimator
-    monteCarloIndexInputDictionary["costEstimatorInputDictionary"] = costEstimatorInputDictionary
-
     # MonoCriterion
     criteriaArray = []
     criteriaInputs = []
@@ -153,25 +140,20 @@
             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"}
 
     # save pressure coefficient
+    qoi_counter = qoi_counter + 1
+    qoi_dict["qoi_id_"+str(qoi_counter)] = {"member_"+str(member): {} for member in range (algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter]._variableDimension)}
+    member = 0
     for node in current_model.GetModelPart(model_part_of_interest).Nodes:
-        qoi_counter = qoi_counter + 1
-        qoi_dict["qoi_id_"+str(qoi_counter)] = {"index_"+str(index): {} for index in range (len(algo.monteCarloSampler.indices))}
+        qoi_dict["qoi_id_"+str(qoi_counter)]["member_"+str(member)] = {"index_"+str(index): {} for index in range (len(algo.monteCarloSampler.indices))}
         for index in range (len(algo.monteCarloSampler.indices)):
             algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter] = get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter])
             sample_counter = algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter]._sampleCounter
-            S1 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[0][0]))
-            S2 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[1][0]))
-            S3 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[2][0]))
-            S4 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[3][0]))
-            S5 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[4][0]))
-            S6 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[5][0]))
-            S7 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[6][0]))
-            S8 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[7][0]))
-            S9 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[8][0]))
-            S10 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter].powerSums[9][0]))
+            S1 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter]._powerSums["1"][member]))
+            S2 = float(get_value_from_remote(algo.monteCarloSampler.indices[index].qoiEstimator[qoi_counter]._powerSums["2"][member]))
             h1 = float(get_value_from_remote(mdccm.computeCentralMomentsOrderOneDimensionZero(S1,sample_counter)))
             h2 = float(get_value_from_remote(mdccm.computeCentralMomentsOrderTwoDimensionZero(S1,S2,sample_counter)))
-            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]}
+            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]}
+        member += 1
 
     # save to file
     with open('power_sums_outputs/MC_asynchronous_power_sums_' +str(time.time()) + '.json', 'w') as f: