1 // Ceres Solver - A fast non-linear least squares minimizer
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29 // Author: sameeragarwal@google.com (Sameer Agarwal)
30 //
31 // Cost term that implements a prior on a parameter block using a
32 // normal distribution.
33 
34 #ifndef CERES_PUBLIC_NORMAL_PRIOR_H_
35 #define CERES_PUBLIC_NORMAL_PRIOR_H_
36 
37 #include "ceres/cost_function.h"
38 #include "ceres/internal/eigen.h"
39 #include "ceres/internal/disable_warnings.h"
40 
41 namespace ceres {
42 
43 // Implements a cost function of the form
44 //
45 //   cost(x) = ||A(x - b)||^2
46 //
47 // where, the matrix A and the vector b are fixed and x is the
48 // variable. In case the user is interested in implementing a cost
49 // function of the form
50 //
51 //   cost(x) = (x - mu)^T S^{-1} (x - mu)
52 //
53 // where, mu is a vector and S is a covariance matrix, then, A =
54 // S^{-1/2}, i.e the matrix A is the square root of the inverse of the
55 // covariance, also known as the stiffness matrix. There are however
56 // no restrictions on the shape of A. It is free to be rectangular,
57 // which would be the case if the covariance matrix S is rank
58 // deficient.
59 
60 class CERES_EXPORT NormalPrior: public CostFunction {
61  public:
62   // Check that the number of rows in the vector b are the same as the
63   // number of columns in the matrix A, crash otherwise.
64   NormalPrior(const Matrix& A, const Vector& b);
65 
66   virtual bool Evaluate(double const* const* parameters,
67                         double* residuals,
68                         double** jacobians) const;
69  private:
70   Matrix A_;
71   Vector b_;
72 };
73 
74 }  // namespace ceres
75 
76 #include "ceres/internal/reenable_warnings.h"
77 
78 #endif  // CERES_PUBLIC_NORMAL_PRIOR_H_
79