More pre-ordering support.
1. CX_SPARSE supports pre-ordering of the jacobian.
2. Add support for constrained approximate minimum degree ordering
for SuiteSparse versions >= 4.2.0
3. Using 2, support for pre-ordering for SPARSE_SCHUR when used
with SUITE_SPARSE.
4. Using 2, support for user orderings in SPARSE_NORMAL_CHOLESKY.
5. Minor cleanups in documentation and code all around.
6. Test update and refactoring.
Change-Id: Ibfe3ac95d59d54ab14d1d60a07f767688070f29f
diff --git a/internal/ceres/solver_impl_test.cc b/internal/ceres/solver_impl_test.cc
index a752eff..e99a3de 100644
--- a/internal/ceres/solver_impl_test.cc
+++ b/internal/ceres/solver_impl_test.cc
@@ -846,5 +846,83 @@
EXPECT_EQ(options.linear_solver_type, CGNR);
EXPECT_EQ(options.preconditioner_type, JACOBI);
}
+
+TEST(SolverImpl, CreateJacobianBlockSparsityTranspose) {
+ ProblemImpl problem;
+ double x[2];
+ double y[3];
+ double z;
+
+ problem.AddParameterBlock(x, 2);
+ problem.AddParameterBlock(y, 3);
+ problem.AddParameterBlock(&z, 1);
+
+ problem.AddResidualBlock(new MockCostFunctionBase<2, 2, 0, 0>(), NULL, x);
+ problem.AddResidualBlock(new MockCostFunctionBase<3, 1, 2, 0>(), NULL, &z, x);
+ problem.AddResidualBlock(new MockCostFunctionBase<4, 1, 3, 0>(), NULL, &z, y);
+ problem.AddResidualBlock(new MockCostFunctionBase<5, 1, 3, 0>(), NULL, &z, y);
+ problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 1, 0>(), NULL, x, &z);
+ problem.AddResidualBlock(new MockCostFunctionBase<2, 1, 3, 0>(), NULL, &z, y);
+ problem.AddResidualBlock(new MockCostFunctionBase<2, 2, 1, 0>(), NULL, x, &z);
+ problem.AddResidualBlock(new MockCostFunctionBase<1, 3, 0, 0>(), NULL, y);
+
+ TripletSparseMatrix expected_block_sparse_jacobian(3, 8, 14);
+ {
+ int* rows = expected_block_sparse_jacobian.mutable_rows();
+ int* cols = expected_block_sparse_jacobian.mutable_cols();
+ double* values = expected_block_sparse_jacobian.mutable_values();
+ rows[0] = 0;
+ cols[0] = 0;
+
+ rows[1] = 2;
+ cols[1] = 1;
+ rows[2] = 0;
+ cols[2] = 1;
+
+ rows[3] = 2;
+ cols[3] = 2;
+ rows[4] = 1;
+ cols[4] = 2;
+
+ rows[5] = 2;
+ cols[5] = 3;
+ rows[6] = 1;
+ cols[6] = 3;
+
+ rows[7] = 0;
+ cols[7] = 4;
+ rows[8] = 2;
+ cols[8] = 4;
+
+ rows[9] = 2;
+ cols[9] = 5;
+ rows[10] = 1;
+ cols[10] = 5;
+
+ rows[11] = 0;
+ cols[11] = 6;
+ rows[12] = 2;
+ cols[12] = 6;
+
+ rows[13] = 1;
+ cols[13] = 7;
+ fill(values, values + 14, 1.0);
+ expected_block_sparse_jacobian.set_num_nonzeros(14);
+ }
+
+ Program* program = problem.mutable_program();
+ program->SetParameterOffsetsAndIndex();
+
+ scoped_ptr<TripletSparseMatrix> actual_block_sparse_jacobian(
+ SolverImpl::CreateJacobianBlockSparsityTranspose(program));
+
+ Matrix expected_dense_jacobian;
+ expected_block_sparse_jacobian.ToDenseMatrix(&expected_dense_jacobian);
+
+ Matrix actual_dense_jacobian;
+ actual_block_sparse_jacobian->ToDenseMatrix(&actual_dense_jacobian);
+ EXPECT_EQ((expected_dense_jacobian - actual_dense_jacobian).norm(), 0.0);
+}
+
} // namespace internal
} // namespace ceres
