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test optimization with Rosenbrock function

release/4.3a0
Varun Agrawal 2024-10-17 13:28:06 -04:00
parent 83e3fdaa24
commit 8a0bbe9666
1 changed files with 11 additions and 6 deletions
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17
gtsam/nonlinear/tests/testNonlinearConjugateGradientOptimizer.cpp
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@ -207,7 +207,7 @@ TEST(NonlinearConjugateGradientOptimizer, Rosenbrock) {
TEST(NonlinearConjugateGradientOptimizer, Optimization) {
using namespace rosenbrock;
double a = 7;
double a = 12;
auto graph = GetRosenbrockGraph(a);
// Assert that error at global minimum is 0.
@ -215,7 +215,7 @@ TEST(NonlinearConjugateGradientOptimizer, Optimization) {
EXPECT_DOUBLES_EQUAL(0.0, error, 1e-12);
NonlinearOptimizerParams param;
param.maxIterations = 50;
param.maxIterations = 350;
// param.verbosity = NonlinearOptimizerParams::LINEAR;
param.verbosity = NonlinearOptimizerParams::SILENT;
@ -224,15 +224,20 @@ TEST(NonlinearConjugateGradientOptimizer, Optimization) {
initialEstimate.insert<double>(X(0), x);
initialEstimate.insert<double>(Y(0), y);
std::cout << f(graph, x, y) << std::endl;
GaussianFactorGraph::shared_ptr linear = graph.linearize(initialEstimate);
// std::cout << "error: " << f(graph, x, y) << std::endl;
// linear->print();
linear->gradientAtZero().print("Gradient: ");
// linear->gradientAtZero().print("Gradient: ");
NonlinearConjugateGradientOptimizer optimizer(graph, initialEstimate, param);
Values result = optimizer.optimize();
result.print();
cout << "cg final error = " << graph.error(result) << endl;
// result.print();
// cout << "cg final error = " << graph.error(result) << endl;
Values expected;
expected.insert<double>(X(0), a);
expected.insert<double>(Y(0), a * a);
EXPECT(assert_equal(expected, result, 1e-1));
}
/* ************************************************************************* */