SMCRA: Drop getInitialResultCollection

openturns · Oct 18, 2023 · 0283739 · 0283739
1 parent 43d96d6
commit 0283739
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Showing 6 changed files with 5 additions and 46 deletions.
diff --git a/lib/src/SequentialMonteCarloRobustAlgorithm.cxx b/lib/src/SequentialMonteCarloRobustAlgorithm.cxx
@@ -236,13 +236,6 @@ SequentialMonteCarloRobustAlgorithm::OptimizationResultCollection SequentialMont
   return resultCollection_;
 }
 
-/* Initial results accessor */
-SequentialMonteCarloRobustAlgorithm::OptimizationResultCollection SequentialMonteCarloRobustAlgorithm::getInitialResultCollection() const
-{
-  return initialResultCollection_;
-}
-
-
 Sample SequentialMonteCarloRobustAlgorithm::getInitialStartingPoints() const
 {
   return initialStartingPoints_;
@@ -256,8 +249,7 @@ String SequentialMonteCarloRobustAlgorithm::__repr__() const
       << ", initialSamplingSize=" << initialSamplingSize_
       << ", initialSearch=" << initialSearch_
       << ", resultCollection=" << resultCollection_
-      << ", initialStartingPoints=" << initialStartingPoints_
-      << ", initialResultCollection=" << initialResultCollection_;
+      << ", initialStartingPoints=" << initialStartingPoints_;
   return oss;
 }
 
@@ -269,7 +261,6 @@ void SequentialMonteCarloRobustAlgorithm::save(Advocate & adv) const
   adv.saveAttribute("initialSearch_", initialSearch_);
   adv.saveAttribute("resultCollection_", resultCollection_);
   adv.saveAttribute("initialStartingPoints_", initialStartingPoints_);
-  adv.saveAttribute("initialResultCollection_", initialResultCollection_);
 }
 
 /* Method load() reloads the object from the StorageManager */
@@ -280,7 +271,6 @@ void SequentialMonteCarloRobustAlgorithm::load(Advocate & adv)
   adv.loadAttribute("initialSearch_", initialSearch_);
   adv.loadAttribute("resultCollection_", resultCollection_);
   adv.loadAttribute("initialStartingPoints_", initialStartingPoints_);
-  adv.loadAttribute("initialResultCollection_", initialResultCollection_);
 }
 
 

diff --git a/lib/src/otrobopt/SequentialMonteCarloRobustAlgorithm.hxx b/lib/src/otrobopt/SequentialMonteCarloRobustAlgorithm.hxx
@@ -73,9 +73,6 @@ public:
   /** Initial starting points accessor */
   OT::Sample getInitialStartingPoints() const;
 
-  /** Initial optimization results accessor */
-  OptimizationResultCollection getInitialResultCollection() const;
-
   /** String converter */
   OT::String __repr__() const override;
 
@@ -99,9 +96,6 @@ private:
   // Initial starting points
   OT::Sample initialStartingPoints_;
 
-  // Initial problem results
-  OptimizationResultPersistentCollection initialResultCollection_;
-
 }; /* class SequentialMonteCarloRobustAlgorithm */
 
 } /* namespace OTROBOPT */

diff --git a/python/src/SequentialMonteCarloRobustAlgorithm.i b/python/src/SequentialMonteCarloRobustAlgorithm.i
@@ -2,21 +2,9 @@
 
 %{
 #include "otrobopt/SequentialMonteCarloRobustAlgorithm.hxx"
-#include "openturns/PythonWrappingFunctions.hxx"
-
-namespace OT {
-template <>
-struct traitsPythonType< OT::OptimizationResult >
-{
-  typedef _PyObject_ Type;
-};
-
-}
 %}
 
 %include SequentialMonteCarloRobustAlgorithm_doc.i
 
-%template(OptimizationResultCollection) OT::Collection<OT::OptimizationResult>;
-
+%copyctor OTROBOPT::SequentialMonteCarloRobustAlgorithm;
 %include otrobopt/SequentialMonteCarloRobustAlgorithm.hxx
-namespace OTROBOPT { %extend SequentialMonteCarloRobustAlgorithm { SequentialMonteCarloRobustAlgorithm(const SequentialMonteCarloRobustAlgorithm & other) { return new OTROBOPT::SequentialMonteCarloRobustAlgorithm(other); } } }
diff --git a/python/src/SequentialMonteCarloRobustAlgorithm_doc.i.in b/python/src/SequentialMonteCarloRobustAlgorithm_doc.i.in
@@ -105,18 +105,6 @@ initialSearch : int, 0 by default (no multi-start)
 
 // ---------------------------------------------------------------------
 
-%feature("docstring") OTROBOPT::SequentialMonteCarloRobustAlgorithm::getInitialResultCollection
-"Multi-start optimization results accessor.
-
-Optimization results during the initial search phase.
-
-Returns
--------
-resultColl : sequence of :class:`openturns.OptimizationResult`
-    List of optimization results"
-
-// ---------------------------------------------------------------------
-
 %feature("docstring") OTROBOPT::SequentialMonteCarloRobustAlgorithm::getInitialStartingPoints
 "Multi-start optimization starting points accessor.
 

diff --git a/python/test/t_SequentialMonteCarloRobustAlgorithm_std.py b/python/test/t_SequentialMonteCarloRobustAlgorithm_std.py
@@ -52,6 +52,5 @@
     result = algo.getResult()
     print('x*=', result.getOptimalPoint(), 'J(x*)=',
           result.getOptimalValue(), 'iteration=', result.getIterationNumber())
-    # print (algo.getInitialResultCollection())
-    # print (algo.getInitialStartingPoints())
-    # print (algo.getResultCollection())
+    assert len(algo.getInitialStartingPoints()) == 1000
+    assert len(algo.getResultCollection()) > 10
diff --git a/python/test/t_saveload.expout b/python/test/t_saveload.expout
@@ -8,4 +8,4 @@ measure=  class=QuantileMeasure alpha=0.99
 measure=  class=AggregatedMeasure collection=[class=MeasureEvaluation implementation=class=MeanMeasure,class=MeasureEvaluation implementation=class=VarianceMeasure,class=MeasureEvaluation implementation=class=WorstCaseMeasure minimization=false,class=MeasureEvaluation implementation=class=JointChanceMeasure alpha=0.95,class=MeasureEvaluation implementation=class=IndividualChanceMeasure alpha=class=Point name=Unnamed dimension=1 values=[0.95],class=MeasureEvaluation implementation=class=MeanStandardDeviationTradeoffMeasure alpha=class=Point name=Unnamed dimension=1 values=[0.8],class=MeasureEvaluation implementation=class=QuantileMeasure alpha=0.99]
 measureFunction=  class=MeanMeasure
 problem=  class=RobustOptimizationProblem robustnessMeasure=class=MeasureEvaluation implementation=class=MeanMeasure reliabilityMeasure=class=MeasureEvaluation implementation=class=JointChanceMeasure alpha=0.9
-algo=  class=SequentialMonteCarloRobustAlgorithm, initialSamplingSize=2, initialSearch=1000, resultCollection=[], initialStartingPoints=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=0 dimension=1 data=[], initialResultCollection=[]
+algo=  class=SequentialMonteCarloRobustAlgorithm, initialSamplingSize=2, initialSearch=1000, resultCollection=[], initialStartingPoints=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=0 dimension=1 data=[]