Renamed NegativeBinomial in favor of Polya. Fixes openturns#2708

ChangeLog

@@ -23,6 +23,7 @@
  * Removed deprecated OptimizationResult.getEvaluationNumber
  * Deprecated BayesDistribution in favor of JointByConditioningDistribution
  * Deprecated ConditionalDistribution in favor of DeconditionedDistribution
+ * Deprecated NegativeBinomial in favor of Polya
 
 === Documentation ===
  * Copy button for code blocks

lib/src/Uncertainty/Algorithm/OrthogonalBasis/MeixnerFactory.cxx

@@ -20,7 +20,7 @@
  */
 #include "openturns/MeixnerFactory.hxx"
 #include "openturns/PersistentObjectFactory.hxx"
-#include "openturns/NegativeBinomial.hxx"
+#include "openturns/Polya.hxx"
 #include "openturns/Exception.hxx"
 
 BEGIN_NAMESPACE_OPENTURNS
@@ -35,18 +35,18 @@ static const Factory<MeixnerFactory> Factory_MeixnerFactory;
 
 /* Default constructor, associated with the default Negative Binomial distribution of parameter 1, 1/2. */
 MeixnerFactory::MeixnerFactory()
-  : OrthogonalUniVariatePolynomialFactory(NegativeBinomial()),
+  : OrthogonalUniVariatePolynomialFactory(Polya()),
     r_(1.0),
     p_(0.5)
 {
   initializeCache();
 }
 
 
-/* Parameter constructor: lambda is the order of the generalized Meixner polynomial, associated with the NegativeBinomial(r, p) distribution */
+/* Parameter constructor: lambda is the order of the generalized Meixner polynomial, associated with the Polya(r, p) distribution */
 MeixnerFactory::MeixnerFactory(const Scalar r,
                                const Scalar p)
-  : OrthogonalUniVariatePolynomialFactory( NegativeBinomial(r, p) ),
+  : OrthogonalUniVariatePolynomialFactory( Polya(r, p) ),
     r_(r),
     p_(p)
 {

lib/src/Uncertainty/Algorithm/OrthogonalBasis/StandardDistributionPolynomialFactory.cxx

@@ -127,7 +127,7 @@ void StandardDistributionPolynomialFactory::checkSpecificFamily()
       hasSpecificFamily_ = true;
       return;
     }
-    if (measureType == "NegativeBinomial")
+    if (measureType == "Polya")
     {
       specificFamily_ = MeixnerFactory(parameter[0], parameter[1]);
       LOGDEBUG(OSS() << "measureType=" << measureType << ", specificFamily=" << specificFamily_);

lib/src/Uncertainty/Algorithm/OrthogonalBasis/openturns/MeixnerFactory.hxx

@@ -43,7 +43,7 @@ public:
   /** Default constructor, associated with the default Negative Binomial distribution of parameter 1, 1/2. */
   MeixnerFactory();
 
-  /** Parameter constructor: lambda is the order of the generalized Meixner polynomial, associated with the NegativeBinomial(r, p) distribution */
+  /** Parameter constructor: lambda is the order of the generalized Meixner polynomial, associated with the Polya(r, p) distribution */
   MeixnerFactory(const Scalar r,
                  const Scalar p);
 

lib/src/Uncertainty/Distribution/CMakeLists.txt

@@ -118,7 +118,7 @@ ot_add_source_file (MixedHistogramUserDefined.cxx)
 ot_add_source_file (Mixture.cxx)
 ot_add_source_file (Multinomial.cxx)
 ot_add_source_file (MultinomialFactory.cxx)
-ot_add_source_file (NegativeBinomial.cxx)
+ot_add_source_file (Polya.cxx)
 ot_add_source_file (NegativeBinomialFactory.cxx)
 ot_add_source_file (NonCentralChiSquare.cxx)
 ot_add_source_file (NonCentralStudent.cxx)
@@ -293,7 +293,7 @@ ot_install_header_file (MixedHistogramUserDefined.hxx)
 ot_install_header_file (Mixture.hxx)
 ot_install_header_file (MultinomialFactory.hxx)
 ot_install_header_file (Multinomial.hxx)
-ot_install_header_file (NegativeBinomial.hxx)
+ot_install_header_file (Polya.hxx)
 ot_install_header_file (NegativeBinomialFactory.hxx)
 ot_install_header_file (NonCentralChiSquare.hxx)
 ot_install_header_file (NonCentralStudent.hxx)

lib/src/Uncertainty/Distribution/NegativeBinomialFactory.cxx

@@ -1,6 +1,6 @@
 //                                               -*- C++ -*-
 /**
- *  @brief Factory for NegativeBinomial distribution
+ *  @brief Factory for Polya distribution
  *
  *  Copyright 2005-2024 Airbus-EDF-IMACS-ONERA-Phimeca
  *
@@ -91,21 +91,21 @@ Distribution NegativeBinomialFactory::build() const
   return buildAsNegativeBinomial().clone();
 }
 
-NegativeBinomial NegativeBinomialFactory::buildAsNegativeBinomial(const Sample & sample) const
+Polya NegativeBinomialFactory::buildAsNegativeBinomial(const Sample & sample) const
 {
   const UnsignedInteger size = sample.getSize();
-  if (size < 2) throw InvalidArgumentException(HERE) << "Error: cannot build a NegativeBinomial distribution from a sample of size < 2";
-  if (sample.getDimension() != 1) throw InvalidArgumentException(HERE) << "Error: can build a NegativeBinomial distribution only from a sample of dimension 1, here dimension=" << sample.getDimension();
+  if (size < 2) throw InvalidArgumentException(HERE) << "Error: cannot build a Polya distribution from a sample of size < 2";
+  if (sample.getDimension() != 1) throw InvalidArgumentException(HERE) << "Error: can build a Polya distribution only from a sample of dimension 1, here dimension=" << sample.getDimension();
   Scalar mean = 0.0;
   Scalar var = 0.0;
   const Scalar supportEpsilon = ResourceMap::GetAsScalar("DiscreteDistribution-SupportEpsilon");
   for (UnsignedInteger i = 0; i < size; ++i)
   {
     const Scalar x = sample(i, 0);
-    if (!SpecFunc::IsNormal(x)) throw InvalidArgumentException(HERE) << "Error: cannot build a NegativeBinomial distribution if data contains NaN or Inf";
+    if (!SpecFunc::IsNormal(x)) throw InvalidArgumentException(HERE) << "Error: cannot build a Polya distribution if data contains NaN or Inf";
     const int iX(static_cast<int>(round(x)));
     // The sample must be made of nonnegative integral values
-    if (std::abs(x - iX) > supportEpsilon || (iX < 0)) throw InvalidArgumentException(HERE) << "Error: can build a NegativeBinomial distribution only from a sample made of nonnegative integers, here x=" << x;
+    if (std::abs(x - iX) > supportEpsilon || (iX < 0)) throw InvalidArgumentException(HERE) << "Error: can build a Polya distribution only from a sample made of nonnegative integers, here x=" << x;
     var = i * var / (i + 1.0) + (1.0 - 1.0 / (i + 1.0)) * (mean - x) * (mean - x) / (i + 1.0);
     mean = (x + i * mean) / (i + 1.0);
   }
@@ -139,28 +139,28 @@ NegativeBinomial NegativeBinomialFactory::buildAsNegativeBinomial(const Sample &
   const Scalar r = solver.solve(f, 0.0, a, b, fA, fB);
   // Corresponding p estimate
   const Scalar p = 1.0 / (r / mean + 1.0);
-  NegativeBinomial result(r, p);
+  Polya result(r, p);
   result.setDescription(sample.getDescription());
   return result;
 }
 
-NegativeBinomial NegativeBinomialFactory::buildAsNegativeBinomial(const Point & parameters) const
+Polya NegativeBinomialFactory::buildAsNegativeBinomial(const Point & parameters) const
 {
   try
   {
-    NegativeBinomial distribution;
+    Polya distribution;
     distribution.setParameter(parameters);
     return distribution;
   }
   catch (const InvalidArgumentException &)
   {
-    throw InvalidArgumentException(HERE) << "Error: cannot build a NegativeBinomial distribution from the given parameters";
+    throw InvalidArgumentException(HERE) << "Error: cannot build a Polya distribution from the given parameters";
   }
 }
 
-NegativeBinomial NegativeBinomialFactory::buildAsNegativeBinomial() const
+Polya NegativeBinomialFactory::buildAsNegativeBinomial() const
 {
-  return NegativeBinomial();
+  return Polya();
 }
 
 END_NAMESPACE_OPENTURNS