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Plot thickens: delta computed from damped system points downhill but non-linear error does not decrease

release/4.3a0
Frank Dellaert 2014-02-20 09:02:24 -05:00
parent 33ae83fcb2
commit 541dbd5199
1 changed files with 26 additions and 5 deletions
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31
tests/testNonlinearOptimizer.cpp
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@ -264,8 +264,8 @@ TEST(NonlinearOptimizer, MoreOptimization) {
// params.setVerbosityLM("TRYDELTA");
// params.setVerbosity("TERMINATION");
params.setlambdaUpperBound(1e9);
params.setRelativeErrorTol(0);
params.setAbsoluteErrorTol(0);
// params.setRelativeErrorTol(0);
// params.setAbsoluteErrorTol(0);
//params.setlambdaInitial(10);
{
@ -281,7 +281,7 @@ TEST(NonlinearOptimizer, MoreOptimization) {
}
EXPECT(assert_equal(expected, DoglegOptimizer(fg, init).optimize()));
cout << "===================================================================================" << endl;
// cout << "===================================================================================" << endl;
// Try LM with diagonal damping
Values initBetter = init;
@ -300,13 +300,34 @@ TEST(NonlinearOptimizer, MoreOptimization) {
expectedDiagonal = d + params.lambdaInitial * d;
EXPECT(assert_equal(expectedDiagonal, damped.hessianDiagonal()));
// test convergence
// test convergence (does not!)
Values actual = optimizer.optimize();
EXPECT(assert_equal(expected, actual));
// Check that the gradient is zero
// Check that the gradient is zero (it is not!)
linear = optimizer.linearize();
EXPECT(assert_equal(expectedGradient,linear->gradientAtZero()));
// Check that the gradient is zero for damped system (it is not!)
damped = optimizer.buildDampedSystem(*linear);
VectorValues actualGradient = damped.gradientAtZero();
EXPECT(assert_equal(expectedGradient,actualGradient));
// Check errors at convergence and errors in direction of gradient (decreases!)
EXPECT_DOUBLES_EQUAL(46.0254859,fg.error(actual),1e-5);
EXPECT_DOUBLES_EQUAL(44.7490532,fg.error(actual.retract(-0.01*actualGradient)),1e-5);
// Check that solve yields gradient (it's not equal to gradient, as predicted)
VectorValues delta = damped.optimize();
// cout << damped.augmentedHessian() << endl;
double factor = actualGradient[0][0]/delta[0][0];
EXPECT(assert_equal(actualGradient,factor*delta));
// Still pointing downhill !
EXPECT_DOUBLES_EQUAL( 0.0105584,dot(-1*actualGradient,delta),1e-5);
// Check errors at convergence and errors in direction of solution (does not decreaase!)
EXPECT_DOUBLES_EQUAL(46.0254859,fg.error(actual.retract(delta)),1e-5);
}
}