/*
 * Copyright (C) 2005-2022 Centre National d'Etudes Spatiales (CNES)
 *
 * This file is part of Orfeo Toolbox
 *
 *     https://www.orfeo-toolbox.org/
 *
 * 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
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * 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 otbNormalizeVectorImageFilter_h
#define otbNormalizeVectorImageFilter_h

#include <vnl/vnl_math.h>

#include <itkMacro.h>
#include <otbVectorImage.h>
#include <otbUnaryFunctorVectorImageFilter.h>

#include <otbStreamingStatisticsVectorImageFilter.h>

namespace otb
{
namespace Functor
{
/** \brief NormalizeVectorImageFunctor
 * \brief this functor performs affine transformation on VariableLengthVectors
 */
template <class TInput, class TOutput>
class NormalizeVectorImageFunctor
{
public:
  NormalizeVectorImageFunctor()
  {
  }
  virtual ~NormalizeVectorImageFunctor()
  {
  }

  typedef typename itk::NumericTraits<TInput>::RealType                             RealVectorType;
  typedef typename itk::NumericTraits<typename RealVectorType::ValueType>::RealType RealType;

  TOutput operator()(const TInput& input)
  {
    unsigned int length = input.Size();
    TOutput      output(length);
    for (unsigned int i = 0; i < length; ++i)
    {
      output[i] = static_cast<typename TOutput::ValueType>((static_cast<RealType>(input[i]) - m_Mean[i]) / m_StdDev[i]);
    }
    return output;
  }

  template <class T>
  void SetMean(const itk::VariableLengthVector<T>& m)
  {
    m_Mean.SetSize(m.Size());
    for (unsigned int i = 0; i < m_Mean.Size(); ++i)
      m_Mean[i]         = static_cast<RealType>(m[i]);
  }

  RealVectorType GetMean() const
  {
    return this->m_Mean;
  }

  template <class T>
  void SetStdDev(const itk::VariableLengthVector<T>& sigma)
  {
    m_StdDev.SetSize(sigma.Size());
    for (unsigned int i = 0; i < m_StdDev.Size(); ++i)
    {
      m_StdDev[i] = static_cast<RealType>(sigma[i]);
      if (m_StdDev[i] == itk::NumericTraits<RealType>::Zero)
      {
        throw itk::ExceptionObject(__FILE__, __LINE__, "Cannot divide by zero !", ITK_LOCATION);
      }
    }
  }

  template <class T>
  void SetVariance(const itk::VariableLengthVector<T>& var)
  {
    m_StdDev.SetSize(var.Size());
    for (unsigned int i = 0; i < m_StdDev.Size(); ++i)
    {
      m_StdDev[i] = std::sqrt(static_cast<RealType>(var[i]));
      if (m_StdDev[i] == itk::NumericTraits<RealType>::Zero)
      {
        throw itk::ExceptionObject(__FILE__, __LINE__, "Cannot divide by zero !", ITK_LOCATION);
      }
    }
  }

  RealVectorType GetStdDev() const
  {
    return this->m_StdDev;
  }

protected:
  RealVectorType m_Mean;
  RealVectorType m_StdDev;
}; // end of class NormalizeVectorImageFunctor

} // end of namespace Functor


/** \class NormalizeVectorImageFilter
 * \brief Normalize an VectorImage by setting its mean to zero and possibly variance to one (band by band).
 *
 * NormalizeVectorImageFilter shifts and scales an image so that the pixels in the image
 * have a zero mean and unit variance.
 *
 * This filter uses StreamingStatisticsVectorImageFilter to compute the mean and variance of
 * the input and then applies the dedicated functor.
 *
 * \sa StreamingStatisticsVectorImageFilter
 *
 * \ingroup OTBStatistics
 */
template <class TInputImage, class TOutputImage>
class ITK_EXPORT NormalizeVectorImageFilter
    : public UnaryFunctorVectorImageFilter<TInputImage, TOutputImage,
                                           Functor::NormalizeVectorImageFunctor<typename TInputImage::PixelType, typename TOutputImage::PixelType>>
{
public:
  /** Standard class typedefs */
  typedef NormalizeVectorImageFilter Self;
  typedef UnaryFunctorVectorImageFilter<TInputImage, TOutputImage,
                                        Functor::NormalizeVectorImageFunctor<typename TInputImage::PixelType, typename TOutputImage::PixelType>>
                                        Superclass;
  typedef itk::SmartPointer<Self>       Pointer;
  typedef itk::SmartPointer<const Self> ConstPointer;

  /** Method for creation through the object factory. */
  itkNewMacro(Self);

  /** Creation through object factory macro */
  itkTypeMacro(NormalizeVectorImageFilter, ImageToImageFilter);

  typedef TInputImage  InputImageType;
  typedef TOutputImage OutputImageType;

  typedef typename itk::NumericTraits<typename TInputImage::PixelType>::RealType    RealVectorType;
  typedef typename itk::NumericTraits<typename RealVectorType::ValueType>::RealType RealType;

  typedef StreamingStatisticsVectorImageFilter<InputImageType> CovarianceEstimatorFilterType;
  typedef typename CovarianceEstimatorFilterType::Pointer      CovarianceEstimatorFilterPointerType;

  itkGetConstMacro(CovarianceEstimator, CovarianceEstimatorFilterType*);

  template <class T>
  void SetMean(const itk::VariableLengthVector<T>& m)
  {
    this->GetFunctor().SetMean(m);
    m_IsGivenMean = true;
    m_UseMean     = true;
    this->Modified();
  }

  template <class T>
  void SetStdDev(const itk::VariableLengthVector<T>& sigma)
  {
    this->GetFunctor().SetStdDev(sigma);
    m_IsGivenStdDev = true;
    m_UseStdDev     = true;
    this->Modified();
  }

  template <class T>
  void SetVariance(const itk::VariableLengthVector<T>& var)
  {
    this->GetFunctor().SetVariance(var);
    m_IsGivenStdDev = true;
    m_UseStdDev     = true;
    this->Modified();
  }


  itkSetMacro(UseMean, bool);
  itkSetMacro(UseStdDev, bool);

protected:
  NormalizeVectorImageFilter();
  ~NormalizeVectorImageFilter() override
  {
  }

  void GenerateOutputInformation() override;


private:
  NormalizeVectorImageFilter(const Self&);
  void operator=(const Self&);

  bool m_IsGivenMean;
  bool m_IsGivenStdDev;

  bool m_UseMean;
  bool m_UseStdDev;

  CovarianceEstimatorFilterPointerType m_CovarianceEstimator;

}; // end of class NormalizeVectorImageFilter

} // end of namespace otb

#ifndef OTB_MANUAL_INSTANTIATION
#include "otbNormalizeVectorImageFilter.hxx"
#endif

#endif // otbNormalizeVectorImageFilter_h
