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Fix machine precision bug in DogLeg compute blend
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This commit fixes a bug that could cause the incorrect solution to be
returned from ComputeBlend that is documented in Issue #1861.
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DanMcGann committed Oct 8, 2024
1 parent 498d0b3 commit 021b0c3
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Showing 2 changed files with 21 additions and 3 deletions.
8 changes: 5 additions & 3 deletions gtsam/nonlinear/DoglegOptimizerImpl.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -67,12 +67,14 @@ VectorValues DoglegOptimizerImpl::ComputeBlend(double delta, const VectorValues&
double tau1 = (-b + sqrt_b_m4ac) / (2.*a);
double tau2 = (-b - sqrt_b_m4ac) / (2.*a);

// Determine correct solution accounting for machine precision
double tau;
if(0.0 <= tau1 && tau1 <= 1.0) {
assert(!(0.0 <= tau2 && tau2 <= 1.0));
const double eps = std::numeric_limits<double>::epsilon();
if(-eps <= tau1 && tau1 <= 1.0 + eps) {
assert(!(-eps <= tau2 && tau2 <= 1.0 + eps));
tau = tau1;
} else {
assert(0.0 <= tau2 && tau2 <= 1.0);
assert(-eps <= tau2 && tau2 <= 1.0 + eps);
tau = tau2;
}

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16 changes: 16 additions & 0 deletions tests/testDoglegOptimizer.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -72,6 +72,22 @@ TEST(DoglegOptimizer, ComputeBlend) {
DOUBLES_EQUAL(Delta, xb.vector().norm(), 1e-10);
}

/* ************************************************************************* */
TEST(DoglegOptimizer, ComputeBlendEdgeCases) {
// Test Derived from Issue #1861
// Evaluate ComputeBlend Behavior for edge cases where the trust region
// is equal in size to that of the newton step or the gradient step.

// Simulated Newton (n) and Gradient Descent (u) step vectors w/ ||n|| > ||u||
VectorValues n(Vector3(0.3233546123, -0.2133456123, 0.3664345632), {{0, 3}});
VectorValues u(Vector3(0.0023456342, -0.04535687, 0.087345661212), {{0, 3}});

// Test upper edge case where trust region is equal to magnitude of newton step
DOUBLES_EQUAL(1.0, ComputeBlend(n.norm(), u, n, false), 1e-10);
// Test lower edge case where trust region is equal to magnitude of gradient step
DOUBLES_EQUAL(0.0, ComputeBlend(u.norm(), u, n, false), 1e-10);
}

/* ************************************************************************* */
TEST(DoglegOptimizer, ComputeDoglegPoint) {
// Create an arbitrary Bayes Net
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