340 lines
9.2 KiB
C++
340 lines
9.2 KiB
C++
/**
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* @file Matrix.h
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* @brief typedef and functions to augment Boost's ublas::matrix<double>
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* @author Christian Potthast
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* @author Kai Ni
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* @author Frank Dellaert
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*/
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// \callgraph
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#pragma once
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#include <list>
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#include <boost/format.hpp>
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#include <boost/numeric/ublas/matrix.hpp>
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#include <boost/tuple/tuple.hpp>
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#include "Vector.h"
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/**
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* Vector is a *global* typedef
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* wrap-matlab does this typedef as well
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* we use the default < double,row_major,unbounded_array<double> >
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*/
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#if ! defined (MEX_H)
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typedef boost::numeric::ublas::matrix<double> Matrix;
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#endif
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namespace gtsam {
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/**
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* constructor with size and initial data, row order !
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*/
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Matrix Matrix_(size_t m, size_t n, const double* const data);
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/**
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* constructor with size and vector data, column order !!!
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*/
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Matrix Matrix_(size_t m, size_t n, const Vector& v);
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/**
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* constructor from Vector yielding v.size()*1 vector
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*/
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inline Matrix Matrix_(const Vector& v) { return Matrix_(v.size(),1,v);}
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/**
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* nice constructor, dangerous as number of arguments must be exactly right
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* and you have to pass doubles !!! always use 0.0 never 0
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*/
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Matrix Matrix_(size_t m, size_t n, ...);
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/**
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* MATLAB like constructors
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*/
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Matrix zeros(size_t m, size_t n);
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Matrix eye(size_t m, size_t n);
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inline Matrix eye( size_t m ) { return eye(m,m); }
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Matrix diag(const Vector& v);
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/**
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* equals with an tolerance
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*/
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bool equal_with_abs_tol(const Matrix& A, const Matrix& B, double tol = 1e-9);
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/**
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* equality is just equal_with_abs_tol 1e-9
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*/
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inline bool operator==(const Matrix& A, const Matrix& B) {
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return equal_with_abs_tol(A,B,1e-9);
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}
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/**
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* inequality
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*/
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inline bool operator!=(const Matrix& A, const Matrix& B) {
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return !(A==B);
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}
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/**
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* equals with an tolerance, prints out message if unequal
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*/
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bool assert_equal(const Matrix& A, const Matrix& B, double tol = 1e-9);
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/**
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* overload * for matrix-vector multiplication (as BOOST does not)
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*/
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inline Vector operator*(const Matrix& A, const Vector & v) { return prod(A,v);}
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/**
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* BLAS Level-2 style e <- e + alpha*A*x
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*/
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void multiplyAdd(double alpha, const Matrix& A, const Vector& x, Vector& e);
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/**
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* overload ^ for trans(A)*v
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* We transpose the vectors for speed.
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*/
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Vector operator^(const Matrix& A, const Vector & v);
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/**
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* BLAS Level-2 style x <- x + alpha*A'*e
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*/
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void transposeMultiplyAdd(double alpha, const Matrix& A, const Vector& e, Vector& x);
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/**
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* overload * for vector*matrix multiplication (as BOOST does not)
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*/
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inline Vector operator*(const Vector & v, const Matrix& A) { return prod(v,A);}
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/**
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* overload * for matrix multiplication (as BOOST does not)
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*/
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inline Matrix operator*(const Matrix& A, const Matrix& B) { return prod(A,B);}
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/**
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* convert to column vector, column order !!!
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*/
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Vector Vector_(const Matrix& A);
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/**
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* print a matrix
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*/
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void print(const Matrix& A, const std::string& s = "");
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/**
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* extract submatrix, slice semantics, i.e. range = [i1,i2[ excluding i2
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* @param A matrix
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* @param i1 first row index
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* @param i2 last row index + 1
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* @param j1 first col index
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* @param j2 last col index + 1
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* @return submatrix A(i1:i2-1,j1:j2-1)
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*/
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Matrix sub(const Matrix& A, size_t i1, size_t i2, size_t j1, size_t j2);
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/**
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* insert a submatrix IN PLACE at a specified location in a larger matrix
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* NOTE: there is no size checking
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* @param large matrix to be updated
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* @param small matrix to be inserted
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* @param i is the row of the upper left corner insert location
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* @param j is the column of the upper left corner insert location
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*/
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void insertSub(Matrix& big, const Matrix& small, size_t i, size_t j);
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/**
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* extracts a column from a matrix
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* NOTE: using this without the underscore is the ublas version!
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* @param matrix to extract column from
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* @param index of the column
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* @return the column in vector form
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*/
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Vector column_(const Matrix& A, size_t j);
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/**
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* inserts a column into a matrix IN PLACE
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* NOTE: there is no size checking
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* Alternate form allows for vectors smaller than the whole column to be inserted
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* @param A matrix to be modified in place
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* @param col is the vector to be inserted
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* @param j is the index to insert the column
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*/
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void insertColumn(Matrix& A, const Vector& col, size_t j);
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void insertColumn(Matrix& A, const Vector& col, size_t i, size_t j);
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/**
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* extracts a row from a matrix
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* @param matrix to extract row from
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* @param index of the row
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* @return the row in vector form
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*/
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Vector row_(const Matrix& A, size_t j);
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// left multiply with scalar
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//inline Matrix operator*(double s, const Matrix& A) { return A*s;}
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/**
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* solve AX=B via in-place Lu factorization and backsubstitution
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* After calling, A contains LU, B the solved RHS vectors
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*/
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void solve(Matrix& A, Matrix& B);
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/**
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* invert A
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*/
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Matrix inverse(const Matrix& A);
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/**
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* Perform updates of system matrices
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*/
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static void updateAb(Matrix& A, Vector& b, int j, const Vector& a,
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const Vector& r, double d);
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/**
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* QR factorization, inefficient, best use imperative householder below
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* m*n matrix -> m*m Q, m*n R
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* @param A a matrix
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* @return <Q,R> rotation matrix Q, upper triangular R
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*/
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std::pair<Matrix,Matrix> qr(const Matrix& A);
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/**
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* Imperative version of Householder rank 1 update
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*/
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void householder_update(Matrix &A, int j, double beta, const Vector& vjm);
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/**
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* Imperative algorithm for in-place full elimination with
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* weights and constraint handling
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* @param A is a matrix to eliminate
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* @param b is the rhs
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* @param sigmas is a vector of the measurement standard deviation
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* @return list of r vectors, d and sigma
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*/
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std::list<boost::tuple<Vector, double, double> >
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weighted_eliminate(Matrix& A, Vector& b, const Vector& sigmas);
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/**
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* Householder tranformation, Householder vectors below diagonal
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* @param k number of columns to zero out below diagonal
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* @param A matrix
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* @return nothing: in place !!!
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*/
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void householder_(Matrix& A, size_t k);
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/**
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* Householder tranformation, zeros below diagonal
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* @param k number of columns to zero out below diagonal
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* @param A matrix
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* @return nothing: in place !!!
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*/
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void householder(Matrix& A, size_t k);
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/**
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* backSubstitute U*x=b
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* @param U an upper triangular matrix
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* @param b an RHS vector
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* @param unit, set true if unit triangular
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* @return the solution x of U*x=b
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* TODO: use boost
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*/
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Vector backSubstituteUpper(const Matrix& U, const Vector& b, bool unit=false);
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/**
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* backSubstitute x'*U=b'
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* @param U an upper triangular matrix
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* @param b an RHS vector
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* @param unit, set true if unit triangular
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* @return the solution x of x'*U=b'
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* TODO: use boost
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*/
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Vector backSubstituteUpper(const Vector& b, const Matrix& U, bool unit=false);
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/**
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* backSubstitute L*x=b
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* @param L an lower triangular matrix
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* @param b an RHS vector
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* @param unit, set true if unit triangular
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* @return the solution x of L*x=b
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* TODO: use boost
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*/
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Vector backSubstituteLower(const Matrix& L, const Vector& d, bool unit=false);
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/**
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* create a matrix by stacking other matrices
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* Given a set of matrices: A1, A2, A3...
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* @return combined matrix [A1; A2; A3]
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*/
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Matrix stack(size_t nrMatrices, ...);
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/**
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* create a matrix by concatenating
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* Given a set of matrices: A1, A2, A3...
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* If all matrices have the same size, specifying single matrix dimensions
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* will avoid the lookup of dimensions
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* @param matrices is a vector of matrices in the order to be collected
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* @param m is the number of rows of a single matrix
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* @param n is the number of columns of a single matrix
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* @return combined matrix [A1 A2 A3]
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*/
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Matrix collect(const std::vector<const Matrix *>& matrices, size_t m = 0, size_t n = 0);
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Matrix collect(size_t nrMatrices, ...);
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/**
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* scales a matrix row or column by the values in a vector
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* Arguments (Matrix, Vector) scales the columns,
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* (Vector, Matrix) scales the rows
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*/
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Matrix vector_scale(const Vector& v, const Matrix& A); // row
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Matrix vector_scale(const Matrix& A, const Vector& v); // column
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/**
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* skew symmetric matrix returns this:
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* 0 -wz wy
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* wz 0 -wx
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* -wy wx 0
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* @param wx 3 dimensional vector
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* @param wy
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* @param wz
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* @return a 3*3 skew symmetric matrix
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*/
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Matrix skewSymmetric(double wx, double wy, double wz);
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inline Matrix skewSymmetric(const Vector& w) { return skewSymmetric(w(0),w(1),w(2));}
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/**
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* SVD computes economy SVD A=U*S*V'
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* @param A an m*n matrix
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* @param U output argument: m*n matrix
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* @param S output argument: n-dim vector of singular values, *not* sorted !!!
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* @param V output argument: n*n matrix
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*/
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void svd(const Matrix& A, Matrix& U, Vector& S, Matrix& V);
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// in-place version
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void svd(Matrix& A, Vector& S, Matrix& V);
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/** Use SVD to calculate inverse square root of a matrix */
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Matrix inverse_square_root(const Matrix& A);
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/** Use SVD to calculate the positive square root of a matrix */
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Matrix square_root_positive(const Matrix& A);
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/** Calculate the LL^t decomposition of a S.P.D matrix */
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Matrix LLt(const Matrix& A);
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/** Calculate the R^tR decomposition of a S.P.D matrix */
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Matrix RtR(const Matrix& A);
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/** Return the inverse of a S.P.D. matrix. Inversion is done via Cholesky decomposition. */
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Matrix cholesky_inverse(const Matrix &A);
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// macro for unit tests
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#define EQUALITY(expected,actual)\
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{ if (!assert_equal(expected,actual)) \
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result_.addFailure(Failure(name_, __FILE__, __LINE__, #expected, #actual)); }
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} // namespace gtsam
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