141 lines
3.8 KiB
C++
141 lines
3.8 KiB
C++
/**
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* @file testNonlinearOptimizer.cpp
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* @brief Unit tests for NonlinearOptimizer class
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* @author Frank Dellaert
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*/
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#include <iostream>
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using namespace std;
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#include <boost/assign/std/list.hpp> // for operator +=
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using namespace boost::assign;
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#include <CppUnitLite/TestHarness.h>
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#include "Matrix.h"
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#include "Ordering.h"
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#include "smallExample.h"
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// template definitions
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#include "NonlinearFactorGraph-inl.h"
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#include "NonlinearOptimizer-inl.h"
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using namespace gtsam;
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typedef NonlinearOptimizer<ExampleNonlinearFactorGraph,VectorConfig> Optimizer;
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/* ************************************************************************* */
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TEST( NonlinearOptimizer, delta )
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{
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ExampleNonlinearFactorGraph fg = createNonlinearFactorGraph();
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Optimizer::shared_config initial = sharedNoisyConfig();
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// Expected configuration is the difference between the noisy config
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// and the ground-truth config. One step only because it's linear !
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VectorConfig expected;
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Vector dl1(2);
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dl1(0) = -0.1;
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dl1(1) = 0.1;
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expected.insert("l1", dl1);
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Vector dx1(2);
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dx1(0) = -0.1;
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dx1(1) = -0.1;
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expected.insert("x1", dx1);
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Vector dx2(2);
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dx2(0) = 0.1;
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dx2(1) = -0.2;
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expected.insert("x2", dx2);
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// Check one ordering
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Ordering ord1;
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ord1 += "x2","l1","x1";
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Optimizer optimizer1(fg, ord1, initial);
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VectorConfig actual1 = optimizer1.linearizeAndOptimizeForDelta();
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CHECK(assert_equal(actual1,expected));
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// Check another
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Ordering ord2;
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ord2 += "x1","x2","l1";
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Optimizer optimizer2(fg, ord2, initial);
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VectorConfig actual2 = optimizer2.linearizeAndOptimizeForDelta();
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CHECK(assert_equal(actual2,expected));
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// And yet another...
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Ordering ord3;
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ord3 += "l1","x1","x2";
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Optimizer optimizer3(fg, ord3, initial);
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VectorConfig actual3 = optimizer3.linearizeAndOptimizeForDelta();
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CHECK(assert_equal(actual3,expected));
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}
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/* ************************************************************************* */
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TEST( NonlinearOptimizer, iterateLM )
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{
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// really non-linear factor graph
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ExampleNonlinearFactorGraph fg = createReallyNonlinearFactorGraph();
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// config far from minimum
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Vector x0 = Vector_(1, 3.0);
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boost::shared_ptr<VectorConfig> config(new VectorConfig);
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config->insert("x", x0);
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// ordering
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Ordering ord;
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ord.push_back("x");
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// create initial optimization state, with lambda=0
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Optimizer optimizer(fg, ord, config, 0);
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// normal iterate
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Optimizer iterated1 = optimizer.iterate();
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// LM iterate with lambda 0 should be the same
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Optimizer iterated2 = optimizer.iterateLM();
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CHECK(assert_equal(*iterated1.config(), *iterated2.config(), 1e-9));
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}
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/* ************************************************************************* */
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TEST( NonlinearOptimizer, optimize )
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{
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ExampleNonlinearFactorGraph fg = createReallyNonlinearFactorGraph();
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// test error at minimum
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Vector xstar = Vector_(1, 0.0);
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VectorConfig cstar;
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cstar.insert("x", xstar);
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DOUBLES_EQUAL(0.0,fg.error(cstar),0.0);
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// test error at initial = [(1-cos(3))^2 + (sin(3))^2]*50 =
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Vector x0 = Vector_(1, 3.0);
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boost::shared_ptr<VectorConfig> c0(new VectorConfig);
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c0->insert("x", x0);
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DOUBLES_EQUAL(199.0,fg.error(*c0),1e-3);
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// optimize parameters
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Ordering ord;
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ord.push_back("x");
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double relativeThreshold = 1e-5;
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double absoluteThreshold = 1e-5;
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// initial optimization state is the same in both cases tested
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Optimizer optimizer(fg, ord, c0);
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// Gauss-Newton
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Optimizer actual1 = optimizer.gaussNewton(relativeThreshold,
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absoluteThreshold);
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CHECK(assert_equal(*(actual1.config()),cstar));
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// Levenberg-Marquardt
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Optimizer actual2 = optimizer.levenbergMarquardt(relativeThreshold,
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absoluteThreshold, Optimizer::SILENT);
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CHECK(assert_equal(*(actual2.config()),cstar));
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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/* ************************************************************************* */
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