diff --git a/internal/ceres/cxsparse.h b/internal/ceres/cxsparse.h
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2015 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// * Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+//   used to endorse or promote products derived from this software without
+//   specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Author: strandmark@google.com (Petter Strandmark)
+
+#ifndef CERES_INTERNAL_CXSPARSE_H_
+#define CERES_INTERNAL_CXSPARSE_H_
+
+// This include must come before any #ifndef check on Ceres compile options.
+#include "ceres/internal/port.h"
+
+#ifndef CERES_NO_CXSPARSE
+
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "ceres/linear_solver.h"
+#include "ceres/sparse_cholesky.h"
+#include "cs.h"
+
+namespace ceres {
+namespace internal {
+
+class CompressedRowSparseMatrix;
+class TripletSparseMatrix;
+
+// This object provides access to solving linear systems using Cholesky
+// factorization with a known symbolic factorization. This features does not
+// explicitly exist in CXSparse. The methods in the class are nonstatic because
+// the class manages internal scratch space.
+class CXSparse {
+ public:
+  CXSparse();
+  ~CXSparse();
+
+  // Solve the system lhs * solution = rhs in place by using an
+  // approximate minimum degree fill reducing ordering.
+  bool SolveCholesky(cs_di* lhs, double* rhs_and_solution);
+
+  // Solves a linear system given its symbolic and numeric factorization.
+  void Solve(cs_dis* symbolic_factor,
+             csn* numeric_factor,
+             double* rhs_and_solution);
+
+  // Compute the numeric Cholesky factorization of A, given its
+  // symbolic factorization.
+  //
+  // Caller owns the result.
+  csn* Cholesky(cs_di* A, cs_dis* symbolic_factor);
+
+  // Creates a sparse matrix from a compressed-column form. No memory is
+  // allocated or copied; the structure A is filled out with info from the
+  // argument.
+  cs_di CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A);
+
+  // Creates a new matrix from a triplet form. Deallocate the returned matrix
+  // with Free. May return NULL if the compression or allocation fails.
+  cs_di* CreateSparseMatrix(TripletSparseMatrix* A);
+
+  // B = A'
+  //
+  // The returned matrix should be deallocated with Free when not used
+  // anymore.
+  cs_di* TransposeMatrix(cs_di* A);
+
+  // C = A * B
+  //
+  // The returned matrix should be deallocated with Free when not used
+  // anymore.
+  cs_di* MatrixMatrixMultiply(cs_di* A, cs_di* B);
+
+  // Computes a symbolic factorization of A that can be used in SolveCholesky.
+  //
+  // The returned matrix should be deallocated with Free when not used anymore.
+  cs_dis* AnalyzeCholesky(cs_di* A);
+
+  // Computes a symbolic factorization of A that can be used in
+  // SolveCholesky, but does not compute a fill-reducing ordering.
+  //
+  // The returned matrix should be deallocated with Free when not used anymore.
+  cs_dis* AnalyzeCholeskyWithNaturalOrdering(cs_di* A);
+
+  // Computes a symbolic factorization of A that can be used in
+  // SolveCholesky. The difference from AnalyzeCholesky is that this
+  // function first detects the block sparsity of the matrix using
+  // information about the row and column blocks and uses this block
+  // sparse matrix to find a fill-reducing ordering. This ordering is
+  // then used to find a symbolic factorization. This can result in a
+  // significant performance improvement AnalyzeCholesky on block
+  // sparse matrices.
+  //
+  // The returned matrix should be deallocated with Free when not used
+  // anymore.
+  cs_dis* BlockAnalyzeCholesky(cs_di* A,
+                               const std::vector<int>& row_blocks,
+                               const std::vector<int>& col_blocks);
+
+  // Compute an fill-reducing approximate minimum degree ordering of
+  // the matrix A. ordering should be non-NULL and should point to
+  // enough memory to hold the ordering for the rows of A.
+  void ApproximateMinimumDegreeOrdering(cs_di* A, int* ordering);
+
+  void Free(cs_di* sparse_matrix);
+  void Free(cs_dis* symbolic_factorization);
+  void Free(csn* numeric_factorization);
+
+ private:
+  // Cached scratch space
+  CS_ENTRY* scratch_;
+  int scratch_size_;
+};
+
+// An implementation of SparseCholesky interface using the CXSparse
+// library.
+class CXSparseCholesky : public SparseCholesky {
+ public:
+  // Factory
+  static std::unique_ptr<SparseCholesky> Create(OrderingType ordering_type);
+
+  // SparseCholesky interface.
+  virtual ~CXSparseCholesky();
+  virtual CompressedRowSparseMatrix::StorageType StorageType() const;
+  virtual LinearSolverTerminationType Factorize(CompressedRowSparseMatrix* lhs,
+                                                std::string* message);
+  virtual LinearSolverTerminationType Solve(const double* rhs,
+                                            double* solution,
+                                            std::string* message);
+
+ private:
+  CXSparseCholesky(const OrderingType ordering_type);
+  void FreeSymbolicFactorization();
+  void FreeNumericFactorization();
+
+  const OrderingType ordering_type_;
+  CXSparse cs_;
+  cs_dis* symbolic_factor_;
+  csn* numeric_factor_;
+};
+
+}  // namespace internal
+}  // namespace ceres
+
+#else   // CERES_NO_CXSPARSE
+
+typedef void cs_dis;
+
+class CXSparse {
+ public:
+  void Free(void* arg) {}
+};
+#endif  // CERES_NO_CXSPARSE
+
+#endif  // CERES_INTERNAL_CXSPARSE_H_