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diff --git a/third_party/eigen3/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h b/third_party/eigen3/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h
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-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H
-#define EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H
-
-namespace Eigen {
-
-namespace internal {
-
-template<typename Lhs, typename Rhs, typename ResultType>
-static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-{
- typedef typename remove_all<Lhs>::type::Scalar Scalar;
- typedef typename remove_all<Lhs>::type::Index Index;
-
- // make sure to call innerSize/outerSize since we fake the storage order.
- Index rows = lhs.innerSize();
- Index cols = rhs.outerSize();
- eigen_assert(lhs.outerSize() == rhs.innerSize());
-
- std::vector<bool> mask(rows,false);
- Matrix<Scalar,Dynamic,1> values(rows);
- Matrix<Index,Dynamic,1> indices(rows);
-
- // estimate the number of non zero entries
- // given a rhs column containing Y non zeros, we assume that the respective Y columns
- // of the lhs differs in average of one non zeros, thus the number of non zeros for
- // the product of a rhs column with the lhs is X+Y where X is the average number of non zero
- // per column of the lhs.
- // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs)
- Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros();
-
- res.setZero();
- res.reserve(Index(estimated_nnz_prod));
- // we compute each column of the result, one after the other
- for (Index j=0; j<cols; ++j)
- {
-
- res.startVec(j);
- Index nnz = 0;
- for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
- {
- Scalar y = rhsIt.value();
- Index k = rhsIt.index();
- for (typename Lhs::InnerIterator lhsIt(lhs, k); lhsIt; ++lhsIt)
- {
- Index i = lhsIt.index();
- Scalar x = lhsIt.value();
- if(!mask[i])
- {
- mask[i] = true;
- values[i] = x * y;
- indices[nnz] = i;
- ++nnz;
- }
- else
- values[i] += x * y;
- }
- }
-
- // unordered insertion
- for(Index k=0; k<nnz; ++k)
- {
- Index i = indices[k];
- res.insertBackByOuterInnerUnordered(j,i) = values[i];
- mask[i] = false;
- }
-
-#if 0
- // alternative ordered insertion code:
-
- Index t200 = rows/(log2(200)*1.39);
- Index t = (rows*100)/139;
-
- // FIXME reserve nnz non zeros
- // FIXME implement fast sort algorithms for very small nnz
- // if the result is sparse enough => use a quick sort
- // otherwise => loop through the entire vector
- // In order to avoid to perform an expensive log2 when the
- // result is clearly very sparse we use a linear bound up to 200.
- //if((nnz<200 && nnz<t200) || nnz * log2(nnz) < t)
- //res.startVec(j);
- if(true)
- {
- if(nnz>1) std::sort(indices.data(),indices.data()+nnz);
- for(Index k=0; k<nnz; ++k)
- {
- Index i = indices[k];
- res.insertBackByOuterInner(j,i) = values[i];
- mask[i] = false;
- }
- }
- else
- {
- // dense path
- for(Index i=0; i<rows; ++i)
- {
- if(mask[i])
- {
- mask[i] = false;
- res.insertBackByOuterInner(j,i) = values[i];
- }
- }
- }
-#endif
-
- }
- res.finalize();
-}
-
-
-} // end namespace internal
-
-namespace internal {
-
-template<typename Lhs, typename Rhs, typename ResultType,
- int LhsStorageOrder = (traits<Lhs>::Flags&RowMajorBit) ? RowMajor : ColMajor,
- int RhsStorageOrder = (traits<Rhs>::Flags&RowMajorBit) ? RowMajor : ColMajor,
- int ResStorageOrder = (traits<ResultType>::Flags&RowMajorBit) ? RowMajor : ColMajor>
-struct conservative_sparse_sparse_product_selector;
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,ColMajor>
-{
- typedef typename remove_all<Lhs>::type LhsCleaned;
- typedef typename LhsCleaned::Scalar Scalar;
-
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
- {
- typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
- typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
- ColMajorMatrix resCol(lhs.rows(),rhs.cols());
- internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol);
- // sort the non zeros:
- RowMajorMatrix resRow(resCol);
- res = resRow;
- }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor,ColMajor>
-{
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
- {
- typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
- RowMajorMatrix rhsRow = rhs;
- RowMajorMatrix resRow(lhs.rows(), rhs.cols());
- internal::conservative_sparse_sparse_product_impl<RowMajorMatrix,Lhs,RowMajorMatrix>(rhsRow, lhs, resRow);
- res = resRow;
- }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor,ColMajor>
-{
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
- {
- typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
- RowMajorMatrix lhsRow = lhs;
- RowMajorMatrix resRow(lhs.rows(), rhs.cols());
- internal::conservative_sparse_sparse_product_impl<Rhs,RowMajorMatrix,RowMajorMatrix>(rhs, lhsRow, resRow);
- res = resRow;
- }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor>
-{
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
- {
- typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
- RowMajorMatrix resRow(lhs.rows(), rhs.cols());
- internal::conservative_sparse_sparse_product_impl<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow);
- res = resRow;
- }
-};
-
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,RowMajor>
-{
- typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
-
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
- {
- typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
- ColMajorMatrix resCol(lhs.rows(), rhs.cols());
- internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol);
- res = resCol;
- }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor,RowMajor>
-{
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
- {
- typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
- ColMajorMatrix lhsCol = lhs;
- ColMajorMatrix resCol(lhs.rows(), rhs.cols());
- internal::conservative_sparse_sparse_product_impl<ColMajorMatrix,Rhs,ColMajorMatrix>(lhsCol, rhs, resCol);
- res = resCol;
- }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor,RowMajor>
-{
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
- {
- typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
- ColMajorMatrix rhsCol = rhs;
- ColMajorMatrix resCol(lhs.rows(), rhs.cols());
- internal::conservative_sparse_sparse_product_impl<Lhs,ColMajorMatrix,ColMajorMatrix>(lhs, rhsCol, resCol);
- res = resCol;
- }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,RowMajor>
-{
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
- {
- typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix;
- typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix;
- RowMajorMatrix resRow(lhs.rows(),rhs.cols());
- internal::conservative_sparse_sparse_product_impl<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow);
- // sort the non zeros:
- ColMajorMatrix resCol(resRow);
- res = resCol;
- }
-};
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H
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