itkGaussianDistribution.h

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/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         https://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
 *
 *=========================================================================*/
#ifndef itkGaussianDistribution_h
#define itkGaussianDistribution_h
 
#include "itkProbabilityDistribution.h"
#include "ITKStatisticsExport.h"
 
namespace itk::Statistics
{
class ITKStatistics_EXPORT GaussianDistribution : public ProbabilityDistribution
{
public:
  ITK_DISALLOW_COPY_AND_MOVE(GaussianDistribution);

  using Self = GaussianDistribution;
  using Superclass = ProbabilityDistribution;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;

  itkOverrideGetNameOfClassMacro(GaussianDistribution);

  itkNewMacro(Self);

  SizeValueType
  GetNumberOfParameters() const override
  {
    return 2;
  }

  double
  EvaluatePDF(double x) const override;

  double
  EvaluatePDF(double x, const ParametersType &) const override;

  virtual double
  EvaluatePDF(double x, double mean, double variance) const;

  double
  EvaluateCDF(double x) const override;

  double
  EvaluateCDF(double x, const ParametersType &) const override;

  virtual double
  EvaluateCDF(double x, double mean, double variance) const;

  double
  EvaluateInverseCDF(double p) const override;

  double
  EvaluateInverseCDF(double p, const ParametersType &) const override;

  virtual double
  EvaluateInverseCDF(double p, double mean, double variance) const;

  virtual void
  SetMean(double);

  double
  GetMean() const override;

  bool
  HasMean() const override
  {
    return true;
  }

  virtual void
  SetVariance(double);

  double
  GetVariance() const override;

  bool
  HasVariance() const override
  {
    return true;
  }

  static double
  PDF(double x);

  static double
  PDF(double x, const ParametersType &);

  static double
  PDF(double x, double mean, double variance);

  static double
  CDF(double x);

  static double
  CDF(double x, const ParametersType &);

  static double
  CDF(double x, double mean, double variance);

  static double
  InverseCDF(double p);

  static double
  InverseCDF(double p, const ParametersType &);

  static double
  InverseCDF(double p, double mean, double variance);
 
protected:
  GaussianDistribution();
  ~GaussianDistribution() override = default;
 
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
}; // end of class
} // namespace itk::Statistics
 
#endif