// Ceres Solver - A fast non-linear least squares minimizer

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// http://ceres-solver.org/

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// Author: strandmark@google.com (Petter Strandmark)

//

// Class for loading the data required for descibing a Fields of Experts (FoE)

// model.

#include "fields_of_experts.h"

#include <fstream>

#include <cmath>

#include "pgm_image.h"

namespace ceres {

namespace examples {

FieldsOfExpertsCost::FieldsOfExpertsCost(const std::vector<double>& filter)

    : filter_(filter) {

  set_num_residuals(1);

  for (int i = 0; i < filter_.size(); ++i) {

    mutable_parameter_block_sizes()->push_back(1);

  }

}

// This is a dot product between a the scalar parameters and a vector of filter

// coefficients.

bool FieldsOfExpertsCost::Evaluate(double const* const* parameters,

                                   double* residuals,

                                   double** jacobians) const {

  int num_variables = filter_.size();

  residuals[0] = 0;

  for (int i = 0; i < num_variables; ++i) {

    residuals[0] += filter_[i] * parameters[i][0];

  }

  if (jacobians != NULL) {

    for (int i = 0; i < num_variables; ++i) {

      if (jacobians[i] != NULL) {

        jacobians[i][0] = filter_[i];

      }

    }

  }

  return true;

}

// This loss function builds the FoE terms and is equal to

//

//   f(x) = alpha_i * log(1 + (1/2)s)

//

void FieldsOfExpertsLoss::Evaluate(double sq_norm, double rho[3]) const {

  const double c = 0.5;

  const double sum = 1.0 + sq_norm * c;

  const double inv = 1.0 / sum;

  // 'sum' and 'inv' are always positive, assuming that 's' is.

  rho[0] = alpha_ *  log(sum);

  rho[1] = alpha_ * c * inv;

  rho[2] = - alpha_ * c * c * inv * inv;

}

FieldsOfExperts::FieldsOfExperts()

    :  size_(0), num_filters_(0) {

}

bool FieldsOfExperts::LoadFromFile(const std::string& filename) {

  std::ifstream foe_file(filename.c_str());

  foe_file >> size_;

  foe_file >> num_filters_;

  if (size_ < 0 || num_filters_ < 0) {

    return false;

  }

  const int num_variables = NumVariables();

  x_delta_indices_.resize(num_variables);

  for (int i = 0; i < num_variables; ++i) {

    foe_file >> x_delta_indices_[i];

  }

  y_delta_indices_.resize(NumVariables());

  for (int i = 0; i < num_variables; ++i) {

    foe_file >> y_delta_indices_[i];

  }

  alpha_.resize(num_filters_);

  for (int i = 0; i < num_filters_; ++i) {

    foe_file >> alpha_[i];

  }

  filters_.resize(num_filters_);

  for (int i = 0; i < num_filters_; ++i) {

    filters_[i].resize(num_variables);

    for (int j = 0; j < num_variables; ++j) {

      foe_file >> filters_[i][j];

    }

  }

  // If any read failed, return failure.

  if (!foe_file) {

    size_ = 0;

    return false;

  }

  // There cannot be anything else in the file. Try reading another number and

  // return failure if that succeeded.

  double temp;

  foe_file >> temp;

  if (foe_file) {

    size_ = 0;

    return false;

  }

  return true;

}

ceres::CostFunction* FieldsOfExperts::NewCostFunction(int alpha_index) const {

  return new FieldsOfExpertsCost(filters_[alpha_index]);

}

ceres::LossFunction* FieldsOfExperts::NewLossFunction(int alpha_index) const {

  return new FieldsOfExpertsLoss(alpha_[alpha_index]);

}

}  // namespace examples

}  // namespace ceres