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release/4.3a0
Frank Dellaert 2010-02-20 23:43:41 +00:00
parent 75b35949c9
commit ac316f2d56
1 changed files with 13 additions and 9 deletions
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22
cpp/iterative-inl.h
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@ -25,7 +25,8 @@ namespace gtsam {
V g, d; V g, d;
E Ad; E Ad;
/** constructor */ /* ************************************************************************* */
// Constructor
CGState(const S& Ab, const V& x, bool verb, double epsilon, CGState(const S& Ab, const V& x, bool verb, double epsilon,
double epsilon_abs, size_t maxIt, bool steep) { double epsilon_abs, size_t maxIt, bool steep) {
k = 0; k = 0;
@ -47,7 +48,8 @@ namespace gtsam {
if (gamma > epsilon) Ad = Ab * d; if (gamma > epsilon) Ad = Ab * d;
} }
/** print */ /* ************************************************************************* */
// print
void print(const V& x) { void print(const V& x) {
cout << "iteration = " << k << endl; cout << "iteration = " << k << endl;
gtsam::print(x,"x"); gtsam::print(x,"x");
@ -57,7 +59,8 @@ namespace gtsam {
gtsam::print(Ad, "Ad"); gtsam::print(Ad, "Ad");
} }
/** step the solution */ /* ************************************************************************* */
// step the solution
double takeOptimalStep(V& x) { double takeOptimalStep(V& x) {
// TODO: can we use gamma instead of dot(d,g) ????? Answer not trivial // TODO: can we use gamma instead of dot(d,g) ????? Answer not trivial
double alpha = -dot(d, g) / dot(Ad, Ad); // calculate optimal step-size double alpha = -dot(d, g) / dot(Ad, Ad); // calculate optimal step-size
@ -65,7 +68,8 @@ namespace gtsam {
return alpha; return alpha;
} }
/** take a step, return true if converged */ /* ************************************************************************* */
// take a step, return true if converged
bool step(const S& Ab, V& x) { bool step(const S& Ab, V& x) {
k += 1; // increase iteration number k += 1; // increase iteration number
@ -101,12 +105,12 @@ namespace gtsam {
Ab.multiplyInPlace(d, Ad); Ab.multiplyInPlace(d, Ad);
return false; return false;
} }
};
/** }; // CGState Class
* conjugate gradient method.
* S: linear system, V: step vector, E: errors /* ************************************************************************* */
*/ // conjugate gradient method.
// S: linear system, V: step vector, E: errors
template<class S, class V, class E> template<class S, class V, class E>
V conjugateGradients(const S& Ab, V x, bool verbose, double epsilon, V conjugateGradients(const S& Ab, V x, bool verbose, double epsilon,
double epsilon_abs, size_t maxIterations, bool steepest = false) { double epsilon_abs, size_t maxIterations, bool steepest = false) {