valgrind possible fix #25078

idaholab · Aug 2, 2023 · d4cb597 · d4cb597
1 parent 4219f80
commit d4cb597
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Showing 17 changed files with 186 additions and 2,734 deletions.
diff --git a/modules/stochastic_tools/test/include/reporters/TestLikelihood.h b/modules/stochastic_tools/test/include/reporters/TestLikelihood.h
@@ -35,4 +35,13 @@ class TestLikelihood : public GeneralReporter, public LikelihoodInterface
 
   /// model prediction values
   const std::vector<Real> & _model_pred;
+
+  /// Transfer the right outputs to the file
+  std::vector<Real> & _model_pred_required;
+
+  /// The MCMC sampler
+  Sampler & _sampler;
+
+  /// Communicator that was split based on samples that have rows
+  libMesh::Parallel::Communicator & _local_comm;
 };
diff --git a/modules/stochastic_tools/test/src/reporters/TestLikelihood.C b/modules/stochastic_tools/test/src/reporters/TestLikelihood.C
@@ -8,6 +8,7 @@
 //* https://www.gnu.org/licenses/lgpl-2.1.html
 
 #include "TestLikelihood.h"
+#include "Sampler.h"
 
 registerMooseObject("StochasticToolsTestApp", TestLikelihood);
 
@@ -21,14 +22,22 @@ TestLikelihood::validParams()
       "function", "function", "Value of the density or mass function.");
   params.addRequiredParam<std::vector<UserObjectName>>("likelihoods", "Names of likelihoods.");
   params.addRequiredParam<ReporterName>("model_pred", "Reporter with the model predictions.");
+  params.addParam<ReporterValueName>(
+      "model_pred_required",
+      "model_pred_required",
+      "Modified value of the model output from this reporter class.");
+  params.addRequiredParam<SamplerName>("sampler", "The sampler object.");
   return params;
 }
 
 TestLikelihood::TestLikelihood(const InputParameters & parameters)
   : GeneralReporter(parameters),
     LikelihoodInterface(parameters),
     _function(declareValue<std::vector<Real>>("function")),
-    _model_pred(getReporterValue<std::vector<Real>>("model_pred"))
+    _model_pred(getReporterValue<std::vector<Real>>("model_pred", REPORTER_MODE_DISTRIBUTED)),
+    _model_pred_required(declareValue<std::vector<Real>>("model_pred_required")),
+    _sampler(getSampler("sampler")),
+    _local_comm(_sampler.getLocalComm())
 {
   for (const UserObjectName & name : getParam<std::vector<UserObjectName>>("likelihoods"))
     _likelihoods.push_back(getLikelihoodFunctionByName(name));
@@ -39,6 +48,8 @@ TestLikelihood::TestLikelihood(const InputParameters & parameters)
 void
 TestLikelihood::execute()
 {
+  _model_pred_required = _model_pred;
+  _local_comm.allgather(_model_pred_required);
   for (unsigned i = 0; i < _function.size(); ++i)
-    _function[i] = _likelihoods[i]->function(_model_pred);
+    _function[i] = _likelihoods[i]->function(_model_pred_required);
 }
diff --git a/modules/stochastic_tools/test/tests/likelihoods/gaussian_derived/gold/extremevalue.json b/modules/stochastic_tools/test/tests/likelihoods/gaussian_derived/gold/extremevalue.json
@@ -22,6 +22,9 @@
             "values": {
                 "function": {
                     "type": "std::vector<double>"
+                },
+                "model_pred_required": {
+                    "type": "std::vector<double>"
                 }
             }
         },
@@ -49,7 +52,8 @@
             "likelihoodtest": {
                 "function": [
                     0.0
-                ]
+                ],
+                "model_pred_required": []
             },
             "noise_specified": {
                 "noise_specified": 0.2
@@ -70,7 +74,12 @@
             },
             "likelihoodtest": {
                 "function": [
-                    -13.226275095227445
+                    1.6266368748117197
+                ],
+                "model_pred_required": [
+                    -0.5769720319127907,
+                    0.4873549495108542,
+                    -0.6411786542848692
                 ]
             },
             "noise_specified": {

diff --git a/modules/stochastic_tools/test/tests/likelihoods/gaussian_derived/gold/likelihood_scalar.json b/modules/stochastic_tools/test/tests/likelihoods/gaussian_derived/gold/likelihood_scalar.json
@@ -22,6 +22,9 @@
             "values": {
                 "function": {
                     "type": "std::vector<double>"
+                },
+                "model_pred_required": {
+                    "type": "std::vector<double>"
                 }
             }
         },
@@ -49,7 +52,8 @@
             "likelihoodtest": {
                 "function": [
                     0.0
-                ]
+                ],
+                "model_pred_required": []
             },
             "noise_specified": {
                 "noise_specified": 0.2
@@ -70,7 +74,12 @@
             },
             "likelihoodtest": {
                 "function": [
-                    0.09019318612685807
+                    6.453480006168816
+                ],
+                "model_pred_required": [
+                    -0.5769720319127907,
+                    0.4873549495108542,
+                    -0.6411786542848692
                 ]
             },
             "noise_specified": {

diff --git a/...s/stochastic_tools/test/tests/likelihoods/gaussian_derived/gold/loglikelihood_scalar.json b/...s/stochastic_tools/test/tests/likelihoods/gaussian_derived/gold/loglikelihood_scalar.json
@@ -22,6 +22,9 @@
             "values": {
                 "function": {
                     "type": "std::vector<double>"
+                },
+                "model_pred_required": {
+                    "type": "std::vector<double>"
                 }
             }
         },
@@ -49,7 +52,8 @@
             "likelihoodtest": {
                 "function": [
                     0.0
-                ]
+                ],
+                "model_pred_required": []
             },
             "noise_specified": {
                 "noise_specified": 0.2
@@ -70,7 +74,12 @@
             },
             "likelihoodtest": {
                 "function": [
-                    -2.4058013965978287
+                    1.8646195211506778
+                ],
+                "model_pred_required": [
+                    -0.5769720319127907,
+                    0.4873549495108542,
+                    -0.6411786542848692
                 ]
             },
             "noise_specified": {

diff --git a/modules/stochastic_tools/test/tests/likelihoods/gaussian_derived/gold/truncatedgaussian.json b/modules/stochastic_tools/test/tests/likelihoods/gaussian_derived/gold/truncatedgaussian.json
@@ -22,6 +22,9 @@
             "values": {
                 "function": {
                     "type": "std::vector<double>"
+                },
+                "model_pred_required": {
+                    "type": "std::vector<double>"
                 }
             }
         },
@@ -49,7 +52,8 @@
             "likelihoodtest": {
                 "function": [
                     0.0
-                ]
+                ],
+                "model_pred_required": []
             },
             "noise_specified": {
                 "noise_specified": 0.2
@@ -70,7 +74,12 @@
             },
             "likelihoodtest": {
                 "function": [
-                    -2.3832432847464218
+                    1.9242540625981073
+                ],
+                "model_pred_required": [
+                    -0.5769720319127907,
+                    0.4873549495108542,
+                    -0.6411786542848692
                 ]
             },
             "noise_specified": {

diff --git a/modules/stochastic_tools/test/tests/likelihoods/gaussian_derived/main.i b/modules/stochastic_tools/test/tests/likelihoods/gaussian_derived/main.i
@@ -56,6 +56,7 @@
     type = TestLikelihood
     likelihoods = 'gaussian'
     model_pred = constant/reporter_transfer:average:value
+    sampler = sample
   []
 []
 

diff --git a/modules/stochastic_tools/test/tests/samplers/mcmc/confg.csv b/modules/stochastic_tools/test/tests/samplers/mcmc/confg.csv
@@ -1,8 +1,2 @@
 1.0
-2.0
-3.0
-4.0
-5.0
-6.0
-7.0
-8.0
+2.0
diff --git a/modules/stochastic_tools/test/tests/samplers/mcmc/exp_0_05.csv b/modules/stochastic_tools/test/tests/samplers/mcmc/exp_0_05.csv
@@ -1,8 +1,2 @@
 -0.6906555,
--0.48597421,
--0.3830987,
--0.35797811,
--0.1734234,
--0.14960162,
--0.07303159,
--0.15606178
+-0.48597421,