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Clean up

release/4.3a0
Sungtae An 2014-12-08 00:44:36 -05:00
parent f6dd14126d
commit 0a1e844ae5
3 changed files with 8 additions and 73 deletions
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51
gtsam/linear/GaussianFactorGraph.cpp
View File

@ -355,14 +355,6 @@ namespace gtsam {
f->multiplyHessianAdd(alpha, x, y);
}
///* ************************************************************************* */
//void GaussianFactorGraph::multiplyHessianAdd(double alpha,
// const double* x, double* y) const {
//vector<size_t> FactorKeys = getkeydim();
//BOOST_FOREACH(const GaussianFactor::shared_ptr& f, *this)
// f->multiplyHessianAdd(alpha, x, y, FactorKeys);
//}
/* ************************************************************************* */
void GaussianFactorGraph::multiplyInPlace(const VectorValues& x, Errors& e) const {
multiplyInPlace(x, e.begin());
@ -392,42 +384,15 @@ namespace gtsam {
/* ************************************************************************* */
// x += alpha*A'*e
void GaussianFactorGraph::transposeMultiplyAdd(double alpha, const Errors& e,
VectorValues& x) const {
// For each factor add the gradient contribution
Errors::const_iterator ei = e.begin();
BOOST_FOREACH(const sharedFactor& Ai_G, *this) {
JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G);
Ai->transposeMultiplyAdd(alpha, *(ei++), x);
void GaussianFactorGraph::transposeMultiplyAdd(double alpha, const Errors& e,
VectorValues& x) const {
// For each factor add the gradient contribution
Errors::const_iterator ei = e.begin();
BOOST_FOREACH(const sharedFactor& Ai_G, *this) {
JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G);
Ai->transposeMultiplyAdd(alpha, *(ei++), x);
}
}
}
///* ************************************************************************* */
//void residual(const GaussianFactorGraph& fg, const VectorValues &x, VectorValues &r) {
// Key i = 0 ;
// BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) {
// JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G);
// r[i] = Ai->getb();
// i++;
// }
// VectorValues Ax = VectorValues::SameStructure(r);
// multiply(fg,x,Ax);
// axpy(-1.0,Ax,r);
//}
///* ************************************************************************* */
//void multiply(const GaussianFactorGraph& fg, const VectorValues &x, VectorValues &r) {
// r.setZero();
// Key i = 0;
// BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) {
// JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G);
// Vector &y = r[i];
// for(JacobianFactor::const_iterator j = Ai->begin(); j != Ai->end(); ++j) {
// y += Ai->getA(j) * x[*j];
// }
// ++i;
// }
//}
/* ************************************************************************* */
VectorValues GaussianFactorGraph::transposeMultiply(const Errors& e) const

4
gtsam/linear/GaussianFactorGraph.h
View File

@ -310,10 +310,6 @@ namespace gtsam {
void multiplyHessianAdd(double alpha, const VectorValues& x,
VectorValues& y) const;
///** y += alpha*A'A*x */
//void multiplyHessianAdd(double alpha, const double* x,
// double* y) const;
///** In-place version e <- A*x that overwrites e. */
void multiplyInPlace(const VectorValues& x, Errors& e) const;

26
gtsam/linear/tests/testGaussianFactorGraph.cpp
View File

@ -315,31 +315,6 @@ TEST( GaussianFactorGraph, multiplyHessianAdd2 )
EXPECT(assert_equal(2*expected, actual));
}
/* ************************************************************************* */
// Raw memory access
//TEST( GaussianFactorGraph, multiplyHessianAdd3 )
//{
// GaussianFactorGraph gfg = createGaussianFactorGraphWithHessianFactor();
// // brute force
// Matrix AtA; Vector eta; boost::tie(AtA,eta) = gfg.hessian();
// Vector X(6); X<<1,2,3,4,5,6;
// Vector Y(6); Y<<-450, -450, 300, 400, 2950, 3450;
// EXPECT(assert_equal(Y,AtA*X));
// double* x = &X[0];
// Vector fast_y = gtsam::zero(6);
// gfg.multiplyHessianAdd(1.0, x, fast_y.data());
// EXPECT(assert_equal(Y, fast_y));
// // now, do it with non-zero y
// gfg.multiplyHessianAdd(1.0, x, fast_y.data());
// EXPECT(assert_equal(2*Y, fast_y));
//}
/* ************************************************************************* */
TEST( GaussianFactorGraph, matricesMixed )
{
@ -352,7 +327,6 @@ TEST( GaussianFactorGraph, matricesMixed )
EXPECT(assert_equal(A.transpose()*b, eta));
}
/* ************************************************************************* */
TEST( GaussianFactorGraph, gradientAtZero )
{