commit 5a974716e111e4aa87a4840902b957060bd644fc
author Sameer Agarwal <sameeragarwal@google.com> Fri Jun 07 22:38:30 2013 -0700
committer Sameer Agarwal <sameeragarwal@google.com> Wed Jul 17 22:56:01 2013 -0700
tree 52626572b123ceae3f326e659034f5e286a88eb6
parent 719889b8b7a3ef6712516d169a4ce3a33d272fda

Covariance estimation using SuiteSparseQR.

Change-Id: I70d1686e3288fdde5f9723e832e15ffb857d6d85

internal/ceres/covariance_test.cc

diff --git a/internal/ceres/covariance_test.cc b/internal/ceres/covariance_test.cc
index f9c5cd4..e7d25a1 100644
--- a/internal/ceres/covariance_test.cc
+++ b/internal/ceres/covariance_test.cc
@@ -400,11 +400,14 @@
   Covariance::Options options;
 
 #ifndef CERES_NO_SUITESPARSE
-  options.use_dense_linear_algebra = false;
+  options.algorithm_type = SPARSE_CHOLESKY;
+  ComputeAndCompareCovarianceBlocks(options, expected_covariance);
+
+  options.algorithm_type = SPARSE_QR;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 #endif
 
-  options.use_dense_linear_algebra = true;
+  options.algorithm_type = DENSE_SVD;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 }
 
@@ -445,11 +448,14 @@
   options.num_threads = 4;
 
 #ifndef CERES_NO_SUITESPARSE
-  options.use_dense_linear_algebra = false;
+  options.algorithm_type = SPARSE_CHOLESKY;
+  ComputeAndCompareCovarianceBlocks(options, expected_covariance);
+
+  options.algorithm_type = SPARSE_QR;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 #endif
 
-  options.use_dense_linear_algebra = true;
+  options.algorithm_type = DENSE_SVD;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 }
 
@@ -491,11 +497,11 @@
   Covariance::Options options;
 
 #ifndef CERES_NO_SUITESPARSE
-  options.use_dense_linear_algebra = false;
+  options.algorithm_type = SPARSE_CHOLESKY;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 #endif
 
-  options.use_dense_linear_algebra = true;
+  options.algorithm_type = DENSE_SVD;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 }
 
@@ -544,11 +550,11 @@
   Covariance::Options options;
 
 #ifndef CERES_NO_SUITESPARSE
-  options.use_dense_linear_algebra = false;
+  options.algorithm_type = SPARSE_CHOLESKY;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 #endif
 
-  options.use_dense_linear_algebra = true;
+  options.algorithm_type = DENSE_SVD;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 }
 
@@ -589,7 +595,7 @@
 
   {
     Covariance::Options options;
-    options.use_dense_linear_algebra = true;
+    options.algorithm_type = DENSE_SVD;
     // Force dropping of the smallest eigenvector.
     options.null_space_rank = 1;
     ComputeAndCompareCovarianceBlocks(options, expected_covariance);
@@ -597,7 +603,7 @@
 
   {
     Covariance::Options options;
-    options.use_dense_linear_algebra = true;
+    options.algorithm_type = DENSE_SVD;
     // Force dropping of the smallest eigenvector via the ratio but
     // automatic truncation.
     options.min_reciprocal_condition_number = 0.044494;
@@ -693,7 +699,7 @@
   };
 
   Covariance::Options options;
-  options.use_dense_linear_algebra = true;
+  options.algorithm_type = DENSE_SVD;
   options.null_space_rank = -1;
   ComputeAndCompareCovarianceBlocks(options, expected_covariance);
 }
@@ -723,9 +729,10 @@
     }
   }
 
-  void ComputeAndCompare(int num_threads) {
+  void ComputeAndCompare(CovarianceAlgorithmType algorithm_type,
+                         int num_threads) {
     Covariance::Options options;
-    options.use_dense_linear_algebra = false;
+    options.algorithm_type = algorithm_type;
     options.num_threads = num_threads;
     Covariance covariance(options);
     EXPECT_TRUE(covariance.Compute(all_covariance_blocks_, &problem_));
@@ -768,7 +775,7 @@
 #if !defined(CERES_NO_SUITESPARSE) && defined(CERES_USE_OPENMP)
 
 TEST_F(LargeScaleCovarianceTest, Parallel) {
-  ComputeAndCompare(4);
+  ComputeAndCompare(SPARSE_CHOLESKY, 4);
 }
 
 #endif  // !defined(CERES_NO_SUITESPARSE) && defined(CERES_USE_OPENMP)