text: // Ceres Solver - A fast non-linear least squares minimizer
  // Copyright 2015 Google Inc. All rights reserved.
  // http://ceres-solver.org/
  //
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  // modification, are permitted provided that the following conditions are met:
  //
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  //   used to endorse or promote products derived from this software without
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  //
  // Author: sameeragarwal@google.com (Sameer Agarwal)
  //
  // Cost term that implements a prior on a parameter block using a
  // normal distribution.
  
  #ifndef CERES_PUBLIC_NORMAL_PRIOR_H_
  #define CERES_PUBLIC_NORMAL_PRIOR_H_
  
  #include "ceres/cost_function.h"
  #include "ceres/internal/eigen.h"
  #include "ceres/internal/disable_warnings.h"
  
  namespace ceres {
  
  // Implements a cost function of the form
  //
  //   cost(x) = ||A(x - b)||^2
  //
  // where, the matrix A and the vector b are fixed and x is the
  // variable. In case the user is interested in implementing a cost
  // function of the form
  //
  //   cost(x) = (x - mu)^T S^{-1} (x - mu)
  //
  // where, mu is a vector and S is a covariance matrix, then, A =
  // S^{-1/2}, i.e the matrix A is the square root of the inverse of the
  // covariance, also known as the stiffness matrix. There are however
  // no restrictions on the shape of A. It is free to be rectangular,
  // which would be the case if the covariance matrix S is rank
  // deficient.
  
  class CERES_EXPORT NormalPrior: public CostFunction {
   public:
    // Check that the number of rows in the vector b are the same as the
    // number of columns in the matrix A, crash otherwise.
    NormalPrior(const Matrix& A, const Vector& b);
  
    virtual bool Evaluate(double const* const* parameters,
                          double* residuals,
                          double** jacobians) const;
   private:
    Matrix A_;
    Vector b_;
  };
  
  }  // namespace ceres
  
  #include "ceres/internal/reenable_warnings.h"
  
  #endif  // CERES_PUBLIC_NORMAL_PRIOR_H_
  