commit 4441b5b2b823293da450160cbd2053fff64b4c66
author Sameer Agarwal <sameeragarwal@google.com> Tue Jun 12 18:01:11 2012 -0700
committer Sameer Agarwal <sameeragarwal@google.com> Tue Jun 12 23:32:34 2012 -0700
tree 7dc7a71d203c0d3b28d76867a62748557fad4f95
parent fa01519c474ace99017c444a73424f9fc7c83cc2

TrustRegionMinimier tests for Dogleg strategy.

Also a fix for a minor segfault in trust_region_minimizer.cc
which was discovered while writing this test.

Change-Id: I50353d0292fd37495bf73de3824c430912ef221d

internal/ceres/trust_region_minimizer.cc

diff --git a/internal/ceres/trust_region_minimizer.cc b/internal/ceres/trust_region_minimizer.cc
index dd4a8a7..4d0c91e 100644
--- a/internal/ceres/trust_region_minimizer.cc
+++ b/internal/ceres/trust_region_minimizer.cc
@@ -196,15 +196,18 @@
     scale.setOnes();
   }
 
-  const double absolute_gradient_tolerance =
-      options_.gradient_tolerance *
+  // The initial gradient max_norm is bounded from below so that we do
+  // not divide by zero.
+  const double gradient_max_norm_0 =
       max(iteration_summary.gradient_max_norm, kEpsilon);
+  const double absolute_gradient_tolerance =
+      options_.gradient_tolerance * gradient_max_norm_0;
+
   if (iteration_summary.gradient_max_norm <= absolute_gradient_tolerance) {
     summary->termination_type = GRADIENT_TOLERANCE;
     VLOG(1) << "Terminating: Gradient tolerance reached."
             << "Relative gradient max norm: "
-            << iteration_summary.gradient_max_norm /
-        summary->iterations[0].gradient_max_norm
+            << iteration_summary.gradient_max_norm / gradient_max_norm_0
             << " <= " << options_.gradient_tolerance;
     return;
   }
@@ -406,8 +409,7 @@
         summary->termination_type = GRADIENT_TOLERANCE;
         VLOG(1) << "Terminating: Gradient tolerance reached."
                 << "Relative gradient max norm: "
-                << iteration_summary.gradient_max_norm /
-            summary->iterations[0].gradient_max_norm
+                << iteration_summary.gradient_max_norm / gradient_max_norm_0
                 << " <= " << options_.gradient_tolerance;
         return;
       }