Merge pull request #2142 from jschueller/misc1

misc 2

ChangeLog

@@ -33,6 +33,8 @@
  * Deprecated Distribution::getCenteredMoment in favor of getCentralMoment
  * Deprecated IterativeMoments::getCenteredMoments in favor of getCentralMoments
  * Deprecated GeneralLinearModelAlgorithm | KrigingAlgorithm ctors using collection of basis
+ * Deprecated Drawable.draw|clean & Graph.draw|clean|getRCommand methods for legacy R graphs
+ * Deprecated GaussianProcess.GIBBS in favor of GaussianProcess.GALLIGAOGIBBS
 
 === Documentation ===
  * Added example galleries at the end of API doc pages

TODO

@@ -10,3 +10,5 @@ Remove (Process)Sample::computeCenteredMoment
 Remove Distribution::getCenteredMoment
 Remove IterativeMoments::getCenteredMoments
 Drop deprecated GeneralLinearModelAlgorithm | KrigingAlgorithm ctors for 1.21
+Drop deprecated Drawable.draw|clean & Graph.draw|clean|getRCommand|makeR*|GetExtensionMap methods
+Drop deprecated GaussianProcess.GIBBS

lib/src/Base/Algo/KarhunenLoeveP1Algorithm.cxx

@@ -445,7 +445,7 @@ void KarhunenLoeveP1Algorithm::run()
     selectedVariance += eigenValues[K];
     ++ K;
   }
-  while ((K < nbModesMax) && (selectedVariance < (1.0 - threshold_) * cumulatedVariance));
+  while ((K < nbModesMax) && (selectedVariance <= (1.0 - threshold_) * cumulatedVariance));
   LOGINFO(OSS() << "Selected " << K << " eigenvalues out of " << eigenValues.getSize() << " computed");
 
   // Reduce and rescale the eigenvectors

lib/src/Base/Func/MarginalEvaluation.cxx

@@ -41,9 +41,9 @@ MarginalEvaluation::MarginalEvaluation()
 /* Default constructor */
 MarginalEvaluation::MarginalEvaluation(const EvaluationImplementation & evaluation,
                                        const Indices & indices)
-  : EvaluationImplementation()
+  : MarginalEvaluation(evaluation.clone(), indices)
 {
-  *this = MarginalEvaluation(evaluation.clone(), indices);
+  // Nothing to do
 }
 
 /* Default constructor */

lib/src/Base/Func/MarginalGradient.cxx

@@ -41,9 +41,9 @@ MarginalGradient::MarginalGradient()
 /* Parameter constructor */
 MarginalGradient::MarginalGradient(const GradientImplementation & gradient,
                                    const Indices & indices)
-  : GradientImplementation()
+  : MarginalGradient(gradient.clone(), indices)
 {
-  *this = MarginalGradient(gradient.clone(), indices);
+  // Nothing to do
 }
 
 /* Parameters constructor */

lib/src/Base/Func/MarginalHessian.cxx

@@ -41,9 +41,9 @@ MarginalHessian::MarginalHessian()
 /* Parameter constructor */
 MarginalHessian::MarginalHessian(const HessianImplementation & hessian,
                                  const Indices & indices)
-  : HessianImplementation()
+  : MarginalHessian(hessian.clone(), indices)
 {
-  *this = MarginalHessian(hessian.clone(), indices);
+  // Nothing to do
 }
 
 /* Parameters constructor */

lib/src/Base/Func/SymbolicFunction.cxx

@@ -49,9 +49,9 @@ SymbolicFunction::SymbolicFunction ()
 /* Parameter constructor */
 SymbolicFunction::SymbolicFunction (const String & inputVariablesName,
                                     const String & formula)
-  : Function()
+  : SymbolicFunction(Description(1, inputVariablesName), Description(1, formula))
 {
-  *this = SymbolicFunction(Description(1, inputVariablesName), Description(1, formula));
+  // Nothing to do
 }
 
 

lib/src/Base/Graph/GraphImplementation.cxx

@@ -529,6 +529,8 @@ void GraphImplementation::draw(const String & file,
                                const Scalar height,
                                SignedInteger drawingFormat)
 {
+  LOGWARN(OSS() << "Graph.draw is deprecated");
+
   // Override format base on extension
   size_t pos = file.find_last_of(".");
   Bool matchedExtension = false;

lib/src/Base/Graph/openturns/Drawable.hxx

@@ -139,13 +139,13 @@ public:
   /** Accessor for data */
   Sample getData() const;
 
-  /** Generate R commands for plotting the graphic */
+  /** @deprecated Generate R commands for plotting the graphic */
   String draw() const;
 
   /** Get R point code from key */
   UnsignedInteger getPointCode(const String key) const;
 
-  /** Clean all the temporary data created by draw() method */
+  /** @deprecated Clean all the temporary data created by draw() method */
   void clean() const;
 
   /** Give the colors name */

lib/src/Base/Graph/openturns/DrawableImplementation.hxx

@@ -149,10 +149,10 @@ public:
   /** Bounding box accessor */
   virtual Interval getBoundingBox() const;
 
-  /** R command generating method, for plotting through R */
+  /** @deprecated R command generating method, for plotting through R */
   virtual String draw() const;
 
-  /** Clean all the temporary data created by draw() method */
+  /** @deprecated Clean all the temporary data created by draw() method */
   virtual void clean() const;
 
   /** Clone method */

lib/src/Base/Graph/openturns/Graph.hxx

@@ -141,16 +141,16 @@ public:
   String getTitle() const;
   void setTitle(const String & title);
 
-  /** The method that generates the graphic files */
+  /** @deprecated The method that generates the graphic files */
   void draw(const String & file,
             const Scalar width = ResourceMap::GetAsUnsignedInteger("Graph-DefaultWidth"),
             const Scalar height = ResourceMap::GetAsUnsignedInteger("Graph-DefaultHeight"),
             SignedInteger format = GraphImplementation::ALL);
 
-  /** Get the R command corresponding to the graph */
+  /** @deprecated Get the R command corresponding to the graph */
   String getRCommand() const;
 
-  /** Clean temporary files */
+  /** @deprecated Clean temporary files */
   void clean();
 
   /** Margin accessor */

lib/src/Base/Graph/openturns/GraphImplementation.hxx

@@ -137,16 +137,16 @@ public:
   virtual String getTitle() const;
   void setTitle(const String & title);
 
-  /** The method that generates the graphic files */
+  /** @deprecated The method that generates the graphic files */
   void draw(const String & file,
             const Scalar width = ResourceMap::GetAsUnsignedInteger("Graph-DefaultWidth"),
             const Scalar height = ResourceMap::GetAsUnsignedInteger("Graph-DefaultHeight"),
             SignedInteger format = ALL);
 
-  /** Get the R command corresponding to the graph */
+  /** @deprecated Get the R command corresponding to the graph */
   String getRCommand() const;
 
-  /** Clean temporary files */
+  /** @deprecated Clean temporary files */
   void clean();
 
   /** Margin accessor */

lib/src/Base/Stat/CMakeLists.txt

@@ -140,18 +140,20 @@ ot_install_header_file (IsotropicCovarianceModel.hxx)
 # Build on the fly source files
 if (BISON_FOUND AND FLEX_FOUND)
   ot_add_build_dir_to_include_dirs (${CMAKE_CURRENT_BINARY_DIR})
-  add_custom_command(OUTPUT  ${CMAKE_CURRENT_BINARY_DIR}/csv_parser.cc ${CMAKE_CURRENT_BINARY_DIR}/csv_parser.hh
+  set (BISON_FLAGS "-Wno-deprecated" CACHE STRING "bison flags")
+  separate_arguments(BISON_FLAGS)
+  add_custom_command(OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/csv_parser.cc ${CMAKE_CURRENT_BINARY_DIR}/csv_parser.hh
                       MAIN_DEPENDENCY ${CMAKE_CURRENT_SOURCE_DIR}/csv_parser.yy
                       COMMAND ${BISON_EXECUTABLE}
-                      ARGS    -Wno-deprecated
+                      ARGS    ${BISON_FLAGS}
                               -o ${CMAKE_CURRENT_BINARY_DIR}/csv_parser.cc
                                  ${CMAKE_CURRENT_SOURCE_DIR}/csv_parser.yy
                       COMMENT "CSV parser generation"
                    )
   ot_add_built_source_file (${CMAKE_CURRENT_BINARY_DIR}/csv_parser.cc)
   add_custom_target (generate_csv_parser DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/csv_parser.cc)
 
-  add_custom_command(OUTPUT  ${CMAKE_CURRENT_BINARY_DIR}/csv_lexer.cc ${CMAKE_CURRENT_BINARY_DIR}/csv_lexer.h
+  add_custom_command(OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/csv_lexer.cc ${CMAKE_CURRENT_BINARY_DIR}/csv_lexer.h
                       MAIN_DEPENDENCY ${CMAKE_CURRENT_SOURCE_DIR}/csv_lexer.ll
                       COMMAND ${FLEX_EXECUTABLE}
                       ARGS    -o ${CMAKE_CURRENT_BINARY_DIR}/csv_lexer.cc

lib/src/Uncertainty/Algorithm/MetaModel/FunctionalChaos/openturns/IntegrationStrategy.hxx

@@ -69,15 +69,6 @@ public:
   /** String converter */
   String __repr__() const override;
 
-  /** Compute the components alpha_k_p_ by projecting the model on the partial L2 basis */
-  void computeCoefficients(const Function & function,
-                           const FunctionCollection & basis,
-                           const Indices & indices,
-                           const Indices & addedRanks,
-                           const Indices & conservedRanks,
-                           const Indices & removedRanks,
-                           const UnsignedInteger marginalIndex = 0) override;
-
   /** Method save() stores the object through the StorageManager */
   void save(Advocate & adv) const override;
 
@@ -86,7 +77,14 @@ public:
 
 
 protected:
-
+  /** Compute the components alpha_k_p_ by projecting the model on the partial L2 basis */
+  void computeCoefficients(const Function & function,
+                           const FunctionCollection & basis,
+                           const Indices & indices,
+                           const Indices & addedRanks,
+                           const Indices & conservedRanks,
+                           const Indices & removedRanks,
+                           const UnsignedInteger marginalIndex = 0) override;
 private:
 
 } ; /* class IntegrationStrategy */

lib/src/Uncertainty/Algorithm/MetaModel/FunctionalChaos/openturns/LeastSquaresStrategy.hxx

@@ -76,6 +76,13 @@ public:
   /** String converter */
   String __repr__() const override;
 
+  /** Method save() stores the object through the StorageManager */
+  void save(Advocate & adv) const override;
+
+  /** Method load() reloads the object from the StorageManager */
+  void load(Advocate & adv) override;
+
+protected:
   /** Compute the components alpha_k_p_ by projecting the model on the partial L2 basis */
   void computeCoefficients(const Function & function,
                            const FunctionCollection & basis,
@@ -84,16 +91,6 @@ public:
                            const Indices & conservedRanks,
                            const Indices & removedRanks,
                            const UnsignedInteger marginalIndex = 0) override;
-
-  /** Method save() stores the object through the StorageManager */
-  void save(Advocate & adv) const override;
-
-  /** Method load() reloads the object from the StorageManager */
-  void load(Advocate & adv) override;
-
-
-protected:
-
 private:
   /** Factory to build an ApproximationAlgorithmImplementation */
   ApproximationAlgorithmImplementationFactoryImplementation p_approximationAlgorithmImplementationFactory_;

lib/src/Uncertainty/Algorithm/MetaModel/FunctionalChaos/openturns/ProjectionStrategy.hxx

@@ -38,6 +38,11 @@ class OT_API ProjectionStrategy
   : public TypedInterfaceObject<ProjectionStrategyImplementation>
 {
   CLASSNAME
+
+  // Make the FunctionalChaosAlgorithm class a friend of the ProjectionStrategyImplementation class
+  // as this last class is in charge of managing data that are part of the FunctionalChaosAlgorithm
+  // state
+  friend class FunctionalChaosAlgorithm;
 public:
 
   typedef ProjectionStrategyImplementation::FunctionCollection FunctionCollection;
@@ -79,6 +84,13 @@ public:
   virtual void setExperiment(const WeightedExperiment & weightedExperiment);
   virtual WeightedExperiment getExperiment() const;
 
+  /** String converter */
+  String __repr__() const override;
+
+  /** String converter */
+  String __str__(const String & offset = "") const override;
+
+protected:
   /** Compute the components alpha_k_p_ by projecting the model on the partial L2 basis */
   void computeCoefficients(const Function & function,
                            const FunctionCollection & basis,
@@ -87,15 +99,6 @@ public:
                            const Indices & conservedRanks,
                            const Indices & removedRanks,
                            const UnsignedInteger marginalIndex = 0);
-
-  /** String converter */
-  String __repr__() const override;
-
-  /** String converter */
-  String __str__(const String & offset = "") const override;
-
-protected:
-
 private:
 
 } ; /* class ProjectionStrategy */

lib/src/Uncertainty/Algorithm/MetaModel/FunctionalChaos/openturns/ProjectionStrategyImplementation.hxx

@@ -50,6 +50,7 @@ class OT_API ProjectionStrategyImplementation
   // as this last class is in charge of managing data that are part of the FunctionalChaosAlgorithm
   // state
   friend class FunctionalChaosAlgorithm;
+  friend class ProjectionStrategy;
 
 public:
 
@@ -108,6 +109,13 @@ public:
   virtual void setExperiment(const WeightedExperiment & weightedExperiment);
   virtual WeightedExperiment getExperiment() const;
 
+  /** Method save() stores the object through the StorageManager */
+  void save(Advocate & adv) const override;
+
+  /** Method load() reloads the object from the StorageManager */
+  void load(Advocate & adv) override;
+
+protected:
   /** Compute the components alpha_k_p_ by projecting the model on the partial L2 basis */
   virtual void computeCoefficients(const Function & function,
                                    const FunctionCollection & basis,
@@ -117,13 +125,6 @@ public:
                                    const Indices & removedRanks,
                                    const UnsignedInteger marginalIndex = 0);
 
-  /** Method save() stores the object through the StorageManager */
-  void save(Advocate & adv) const override;
-
-  /** Method load() reloads the object from the StorageManager */
-  void load(Advocate & adv) override;
-
-protected:
   /** The collection of Alpha_k coefficients */
   Point alpha_k_p_;
 

lib/src/Uncertainty/Algorithm/Simulation/SimulationSensitivityAnalysis.cxx

@@ -64,9 +64,9 @@ SimulationSensitivityAnalysis::SimulationSensitivityAnalysis(const RandomVector
 
 /* Standard constructor */
 SimulationSensitivityAnalysis::SimulationSensitivityAnalysis(const ProbabilitySimulationResult & result)
-  : PersistentObject()
+  : SimulationSensitivityAnalysis(result.getEvent())
 {
-  *this = SimulationSensitivityAnalysis(result.getEvent());
+  // Nothing to do
 }
 
 /* Standard constructor */

lib/src/Uncertainty/Bayesian/CalibrationAlgorithmImplementation.cxx

@@ -48,7 +48,9 @@ CalibrationAlgorithmImplementation::CalibrationAlgorithmImplementation(const Fun
   , parameterPrior_(parameterPrior)
   , result_()
 {
-  // Nothing to do
+  // Allow for a dim-0 sample but it should have the right size internally
+  if (!inputObservations_.getDimension())
+    inputObservations_ = Sample(outputObservations.getSize(), 0);
 }
 
 /* Performs the actual computation. Must be overloaded by the actual calibration algorithm */

lib/src/Uncertainty/Bayesian/GaussianLinearCalibration.cxx

@@ -58,11 +58,11 @@ GaussianLinearCalibration::GaussianLinearCalibration(const Function & model,
   const UnsignedInteger parameterDimension = candidate.getDimension();
   if (model.getParameterDimension() != parameterDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of parameter dimension=" << parameterDimension << ", got parameter dimension=" << model.getParameterDimension();
   if (parameterCovariance.getDimension() != parameterDimension) throw InvalidArgumentException(HERE) << "Error: expected a parameter covariance of dimension=" << parameterDimension << ", got dimension=" << parameterCovariance.getDimension();
-  const UnsignedInteger inputDimension = inputObservations.getDimension();
+  const UnsignedInteger inputDimension = inputObservations_.getDimension();
   if (model.getInputDimension() != inputDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of input dimension=" << inputDimension << ", got input dimension=" << model.getInputDimension();
   const UnsignedInteger outputDimension = outputObservations.getDimension();
   if (model.getOutputDimension() != outputDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of output dimension=" << outputDimension << ", got output dimension=" << model.getOutputDimension();
-  const UnsignedInteger size = inputObservations.getSize();
+  const UnsignedInteger size = outputObservations.getSize();
   if (outputObservations.getSize() != size) throw InvalidArgumentException(HERE) << "Error: expected an output sample of size=" << size << ", got size=" << outputObservations.getSize();
   globalErrorCovariance_ = errorCovariance.getDimension() != outputDimension;
   if (globalErrorCovariance_ && !(errorCovariance.getDimension() == outputDimension * size)) throw InvalidArgumentException(HERE) << "Error: expected an error covariance either of dimension=" << outputDimension << " or dimension=" << outputDimension * size << ", got dimension=" << errorCovariance.getDimension();

lib/src/Uncertainty/Bayesian/GaussianNonLinearCalibration.cxx

@@ -64,11 +64,11 @@ GaussianNonLinearCalibration::GaussianNonLinearCalibration(const Function & mode
   const UnsignedInteger parameterDimension = candidate.getDimension();
   if (model.getParameterDimension() != parameterDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of parameter dimension=" << parameterDimension << ", got parameter dimension=" << model.getParameterDimension();
   if (parameterCovariance.getDimension() != parameterDimension) throw InvalidArgumentException(HERE) << "Error: expected a parameter covariance of dimension=" << parameterDimension << ", got dimension=" << parameterCovariance.getDimension();
-  const UnsignedInteger inputDimension = inputObservations.getDimension();
+  const UnsignedInteger inputDimension = inputObservations_.getDimension();
   if (model.getInputDimension() != inputDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of input dimension=" << inputDimension << ", got input dimension=" << model.getInputDimension();
   const UnsignedInteger outputDimension = outputObservations.getDimension();
   if (model.getOutputDimension() != outputDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of output dimension=" << outputDimension << ", got output dimension=" << model.getOutputDimension();
-  const UnsignedInteger size = inputObservations.getSize();
+  const UnsignedInteger size = outputObservations.getSize();
   if (outputObservations.getSize() != size) throw InvalidArgumentException(HERE) << "Error: expected an output sample of size=" << size << ", got size=" << outputObservations.getSize();
   globalErrorCovariance_ = errorCovariance.getDimension() != outputDimension;
   if (globalErrorCovariance_ && !(errorCovariance.getDimension() == outputDimension * size)) throw InvalidArgumentException(HERE) << "Error: expected an error covariance either of dimension=" << outputDimension << " or dimension=" << outputDimension * size << ", got dimension=" << errorCovariance.getDimension();

lib/src/Uncertainty/Bayesian/LinearLeastSquaresCalibration.cxx

@@ -53,11 +53,11 @@ LinearLeastSquaresCalibration::LinearLeastSquaresCalibration(const Function & mo
   // Check the input
   const UnsignedInteger parameterDimension = candidate.getDimension();
   if (model.getParameterDimension() != parameterDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of parameter dimension=" << parameterDimension << ", got parameter dimension=" << model.getParameterDimension();
-  const UnsignedInteger inputDimension = inputObservations.getDimension();
+  const UnsignedInteger inputDimension = inputObservations_.getDimension();
   if (model.getInputDimension() != inputDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of input dimension=" << inputDimension << ", got input dimension=" << model.getInputDimension();
   const UnsignedInteger outputDimension = outputObservations.getDimension();
   if (model.getOutputDimension() != outputDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of output dimension=" << outputDimension << ", got output dimension=" << model.getOutputDimension();
-  const UnsignedInteger size = inputObservations.getSize();
+  const UnsignedInteger size = outputObservations.getSize();
   if (outputObservations.getSize() != size) throw InvalidArgumentException(HERE) << "Error: expected an output sample of size=" << size << ", got size=" << outputObservations.getSize();
 }
 

lib/src/Uncertainty/Bayesian/NonLinearLeastSquaresCalibration.cxx

@@ -57,11 +57,11 @@ NonLinearLeastSquaresCalibration::NonLinearLeastSquaresCalibration(const Functio
   , bootstrapSize_(ResourceMap::GetAsUnsignedInteger("NonLinearLeastSquaresCalibration-BootstrapSize"))
 {
   // Check the input
-  const UnsignedInteger inputDimension = inputObservations.getDimension();
+  const UnsignedInteger inputDimension = inputObservations_.getDimension();
   if (model.getInputDimension() != inputDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of input dimension=" << inputDimension << ", got input dimension=" << model.getInputDimension();
   const UnsignedInteger outputDimension = outputObservations.getDimension();
   if (model.getOutputDimension() != outputDimension) throw InvalidArgumentException(HERE) << "Error: expected a model of output dimension=" << outputDimension << ", got output dimension=" << model.getOutputDimension();
-  const UnsignedInteger size = inputObservations.getSize();
+  const UnsignedInteger size = outputObservations.getSize();
   if (outputObservations.getSize() != size) throw InvalidArgumentException(HERE) << "Error: expected an output sample of size=" << size << ", got size=" << outputObservations.getSize();
 
   // Now the automatic selection of the algorithm