commit 05292bf8fc5208b86b4a13544615b584f6efa936
author Sameer Agarwal <sameeragarwal@google.com> Mon Aug 20 07:40:45 2012 -0700
committer ceres-solver code review <noreply-gerritcodereview@google.com> Mon Aug 20 08:48:09 2012 -0700
tree 529f980a8548a1008c315c043efc9a2a52b96837
parent b12b906c4d21c3949f0dce62c4c0d083c8edecf1

Add a TrustRegionStrategy::Summary object.

Change-Id: I7caee35a3408ee4a0ec16ba407410d822929340d

internal/ceres/dogleg_strategy.cc

diff --git a/internal/ceres/dogleg_strategy.cc b/internal/ceres/dogleg_strategy.cc
index 44d484f..4b1f074 100644
--- a/internal/ceres/dogleg_strategy.cc
+++ b/internal/ceres/dogleg_strategy.cc
@@ -71,7 +71,7 @@
 // gradient) and the new Gauss-Newton step are computed from
 // scratch. The Dogleg step is then computed as interpolation of these
 // two vectors.
-LinearSolver::Summary DoglegStrategy::ComputeStep(
+TrustRegionStrategy::Summary DoglegStrategy::ComputeStep(
     const TrustRegionStrategy::PerSolveOptions& per_solve_options,
     SparseMatrix* jacobian,
     const double* residuals,
@@ -85,10 +85,10 @@
     // Gauss-Newton and gradient vectors are always available, only a
     // new interpolant need to be computed.
     ComputeDoglegStep(step);
-    LinearSolver::Summary linear_solver_summary;
-    linear_solver_summary.num_iterations = 0;
-    linear_solver_summary.termination_type = TOLERANCE;
-    return linear_solver_summary;
+    TrustRegionStrategy::Summary summary;
+    summary.num_iterations = 0;
+    summary.termination_type = TOLERANCE;
+    return summary;
   }
 
   reuse_ = true;
@@ -123,7 +123,11 @@
     ComputeDoglegStep(step);
   }
 
-  return linear_solver_summary;
+  TrustRegionStrategy::Summary summary;
+  summary.residual_norm = linear_solver_summary.residual_norm;
+  summary.num_iterations = linear_solver_summary.num_iterations;
+  summary.termination_type = linear_solver_summary.termination_type;
+  return summary;
 }
 
 // The trust region is assumed to be elliptical with the