27 #include "tnt/tnt_array2d.h"
121 int sparseRows = 0,
int sparseCols = 0,
bool jigsaw =
false);
123 void AddKnown(
const std::vector<double> &input,
double expected,
124 double weight = 1.0);
126 std::vector<double>
GetInput(
int row)
const;
136 double Evaluate(
const std::vector<double> &input);
139 void Weight(
int index,
double weight);
148 return p_expected.size();
158 std::vector<double>
GetEpsilons ()
const {
return p_epsilonsSparse; }
167 void SolveCholesky () {}
171 void FillSparseA(
const std::vector<double> &data);
172 bool ApplyParameterWeights();
174 std::vector<double> p_xSparse;
175 std::vector<double> p_epsilonsSparse;
176 std::vector<double> p_parameterWeights;
178 gmm::row_matrix<gmm::rsvector<double> > p_sparseA;
180 gmm::row_matrix<gmm::rsvector<double> > p_normals;
182 gmm::dense_matrix<double> p_ATb;
183 gmm::SuperLU_factor<double> p_SLU_Factor;
189 int p_currentFillRow;
192 int p_constrainedParameters;
193 int p_degreesOfFreedom;
197 std::vector<std::vector<double> > p_input;
199 std::vector<double> p_expected;
201 std::vector<double> p_sqrtWeight;
204 std::vector<double> p_residuals;
void Weight(int index, double weight)
Reset the weight for the ith known.
Definition: LeastSquares.cpp:793
QR Decomposition.
Definition: LeastSquares.h:131
int GetDegreesOfFreedom()
Definition: LeastSquares.h:152
LeastSquares(Isis::BasisFunction &basis, bool sparse=false, int sparseRows=0, int sparseCols=0, bool jigsaw=false)
Creates a LeastSquares Object.
Definition: LeastSquares.cpp:41
Sparse.
Definition: LeastSquares.h:132
const gmm::row_matrix< gmm::rsvector< double > > & GetCovarianceMatrix() const
Definition: LeastSquares.h:161
std::vector< double > Residuals() const
Returns a vector of residuals (errors).
Definition: LeastSquares.cpp:749
~LeastSquares()
Destroys the LeastSquares object.
Definition: LeastSquares.cpp:83
SolveMethod
Definition: LeastSquares.h:130
bool SparseErrorPropagation()
Error propagation for sparse least-squares solution.
Definition: LeastSquares.cpp:649
Singular Value Decomposition.
Definition: LeastSquares.h:130
double Evaluate(const std::vector< double > &input)
Invokes the BasisFunction Evaluate method.
Definition: LeastSquares.cpp:732
void SetParameterWeights(const std::vector< double > weights)
Definition: LeastSquares.h:159
void Reset()
Definition: LeastSquares.cpp:701
Generic least square fitting class.
Definition: LeastSquares.h:117
void AddKnown(const std::vector< double > &input, double expected, double weight=1.0)
Invoke this method for each set of knowns.
Definition: LeastSquares.cpp:117
double Residual(int i) const
Returns the ith residual.
Definition: LeastSquares.cpp:769
std::vector< double > GetInput(int row) const
This method returns the data at the given row.
Definition: LeastSquares.cpp:184
Generic linear equation class.
Definition: BasisFunction.h:64
double GetExpected(int row) const
This method returns the expected value at the given row.
Definition: LeastSquares.cpp:199
void SetNumberOfConstrainedParameters(int n)
Definition: LeastSquares.h:160
void ResetSparse()
Definition: LeastSquares.h:156
int Knowns() const
The number of knowns (or times AddKnown was invoked) linear combination of the variables.
Definition: LeastSquares.h:147
std::vector< double > GetEpsilons() const
Definition: LeastSquares.h:158
int Solve(Isis::LeastSquares::SolveMethod method=SVD)
After all the data has been registered through AddKnown, invoke this method to solve the system of eq...
Definition: LeastSquares.cpp:231
double GetSigma0()
Definition: LeastSquares.h:151
int Rows() const
This methods returns the number of rows in the matrix.
Definition: LeastSquares.cpp:213