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Diffstat (limited to 'third_party/eigen3/Eigen/src/SparseCore')
25 files changed, 6949 insertions, 0 deletions
diff --git a/third_party/eigen3/Eigen/src/SparseCore/AmbiVector.h b/third_party/eigen3/Eigen/src/SparseCore/AmbiVector.h new file mode 100644 index 0000000000..17fff96a78 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/AmbiVector.h @@ -0,0 +1,373 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_AMBIVECTOR_H +#define EIGEN_AMBIVECTOR_H + +namespace Eigen { + +namespace internal { + +/** \internal + * Hybrid sparse/dense vector class designed for intensive read-write operations. + * + * See BasicSparseLLT and SparseProduct for usage examples. + */ +template<typename _Scalar, typename _Index> +class AmbiVector +{ + public: + typedef _Scalar Scalar; + typedef _Index Index; + typedef typename NumTraits<Scalar>::Real RealScalar; + + AmbiVector(Index size) + : m_buffer(0), m_zero(0), m_size(0), m_allocatedSize(0), m_allocatedElements(0), m_mode(-1) + { + resize(size); + } + + void init(double estimatedDensity); + void init(int mode); + + Index nonZeros() const; + + /** Specifies a sub-vector to work on */ + void setBounds(Index start, Index end) { m_start = start; m_end = end; } + + void setZero(); + + void restart(); + Scalar& coeffRef(Index i); + Scalar& coeff(Index i); + + class Iterator; + + ~AmbiVector() { delete[] m_buffer; } + + void resize(Index size) + { + if (m_allocatedSize < size) + reallocate(size); + m_size = size; + } + + Index size() const { return m_size; } + + protected: + + void reallocate(Index size) + { + // if the size of the matrix is not too large, let's allocate a bit more than needed such + // that we can handle dense vector even in sparse mode. + delete[] m_buffer; + if (size<1000) + { + Index allocSize = (size * sizeof(ListEl))/sizeof(Scalar); + m_allocatedElements = (allocSize*sizeof(Scalar))/sizeof(ListEl); + m_buffer = new Scalar[allocSize]; + } + else + { + m_allocatedElements = (size*sizeof(Scalar))/sizeof(ListEl); + m_buffer = new Scalar[size]; + } + m_size = size; + m_start = 0; + m_end = m_size; + } + + void reallocateSparse() + { + Index copyElements = m_allocatedElements; + m_allocatedElements = (std::min)(Index(m_allocatedElements*1.5),m_size); + Index allocSize = m_allocatedElements * sizeof(ListEl); + allocSize = allocSize/sizeof(Scalar) + (allocSize%sizeof(Scalar)>0?1:0); + Scalar* newBuffer = new Scalar[allocSize]; + memcpy(newBuffer, m_buffer, copyElements * sizeof(ListEl)); + delete[] m_buffer; + m_buffer = newBuffer; + } + + protected: + // element type of the linked list + struct ListEl + { + Index next; + Index index; + Scalar value; + }; + + // used to store data in both mode + Scalar* m_buffer; + Scalar m_zero; + Index m_size; + Index m_start; + Index m_end; + Index m_allocatedSize; + Index m_allocatedElements; + Index m_mode; + + // linked list mode + Index m_llStart; + Index m_llCurrent; + Index m_llSize; +}; + +/** \returns the number of non zeros in the current sub vector */ +template<typename _Scalar,typename _Index> +_Index AmbiVector<_Scalar,_Index>::nonZeros() const +{ + if (m_mode==IsSparse) + return m_llSize; + else + return m_end - m_start; +} + +template<typename _Scalar,typename _Index> +void AmbiVector<_Scalar,_Index>::init(double estimatedDensity) +{ + if (estimatedDensity>0.1) + init(IsDense); + else + init(IsSparse); +} + +template<typename _Scalar,typename _Index> +void AmbiVector<_Scalar,_Index>::init(int mode) +{ + m_mode = mode; + if (m_mode==IsSparse) + { + m_llSize = 0; + m_llStart = -1; + } +} + +/** Must be called whenever we might perform a write access + * with an index smaller than the previous one. + * + * Don't worry, this function is extremely cheap. + */ +template<typename _Scalar,typename _Index> +void AmbiVector<_Scalar,_Index>::restart() +{ + m_llCurrent = m_llStart; +} + +/** Set all coefficients of current subvector to zero */ +template<typename _Scalar,typename _Index> +void AmbiVector<_Scalar,_Index>::setZero() +{ + if (m_mode==IsDense) + { + for (Index i=m_start; i<m_end; ++i) + m_buffer[i] = Scalar(0); + } + else + { + eigen_assert(m_mode==IsSparse); + m_llSize = 0; + m_llStart = -1; + } +} + +template<typename _Scalar,typename _Index> +_Scalar& AmbiVector<_Scalar,_Index>::coeffRef(_Index i) +{ + if (m_mode==IsDense) + return m_buffer[i]; + else + { + ListEl* EIGEN_RESTRICT llElements = reinterpret_cast<ListEl*>(m_buffer); + // TODO factorize the following code to reduce code generation + eigen_assert(m_mode==IsSparse); + if (m_llSize==0) + { + // this is the first element + m_llStart = 0; + m_llCurrent = 0; + ++m_llSize; + llElements[0].value = Scalar(0); + llElements[0].index = i; + llElements[0].next = -1; + return llElements[0].value; + } + else if (i<llElements[m_llStart].index) + { + // this is going to be the new first element of the list + ListEl& el = llElements[m_llSize]; + el.value = Scalar(0); + el.index = i; + el.next = m_llStart; + m_llStart = m_llSize; + ++m_llSize; + m_llCurrent = m_llStart; + return el.value; + } + else + { + Index nextel = llElements[m_llCurrent].next; + eigen_assert(i>=llElements[m_llCurrent].index && "you must call restart() before inserting an element with lower or equal index"); + while (nextel >= 0 && llElements[nextel].index<=i) + { + m_llCurrent = nextel; + nextel = llElements[nextel].next; + } + + if (llElements[m_llCurrent].index==i) + { + // the coefficient already exists and we found it ! + return llElements[m_llCurrent].value; + } + else + { + if (m_llSize>=m_allocatedElements) + { + reallocateSparse(); + llElements = reinterpret_cast<ListEl*>(m_buffer); + } + eigen_internal_assert(m_llSize<m_allocatedElements && "internal error: overflow in sparse mode"); + // let's insert a new coefficient + ListEl& el = llElements[m_llSize]; + el.value = Scalar(0); + el.index = i; + el.next = llElements[m_llCurrent].next; + llElements[m_llCurrent].next = m_llSize; + ++m_llSize; + return el.value; + } + } + } +} + +template<typename _Scalar,typename _Index> +_Scalar& AmbiVector<_Scalar,_Index>::coeff(_Index i) +{ + if (m_mode==IsDense) + return m_buffer[i]; + else + { + ListEl* EIGEN_RESTRICT llElements = reinterpret_cast<ListEl*>(m_buffer); + eigen_assert(m_mode==IsSparse); + if ((m_llSize==0) || (i<llElements[m_llStart].index)) + { + return m_zero; + } + else + { + Index elid = m_llStart; + while (elid >= 0 && llElements[elid].index<i) + elid = llElements[elid].next; + + if (llElements[elid].index==i) + return llElements[m_llCurrent].value; + else + return m_zero; + } + } +} + +/** Iterator over the nonzero coefficients */ +template<typename _Scalar,typename _Index> +class AmbiVector<_Scalar,_Index>::Iterator +{ + public: + typedef _Scalar Scalar; + typedef typename NumTraits<Scalar>::Real RealScalar; + + /** Default constructor + * \param vec the vector on which we iterate + * \param epsilon the minimal value used to prune zero coefficients. + * In practice, all coefficients having a magnitude smaller than \a epsilon + * are skipped. + */ + Iterator(const AmbiVector& vec, const RealScalar& epsilon = 0) + : m_vector(vec) + { + using std::abs; + m_epsilon = epsilon; + m_isDense = m_vector.m_mode==IsDense; + if (m_isDense) + { + m_currentEl = 0; // this is to avoid a compilation warning + m_cachedValue = 0; // this is to avoid a compilation warning + m_cachedIndex = m_vector.m_start-1; + ++(*this); + } + else + { + ListEl* EIGEN_RESTRICT llElements = reinterpret_cast<ListEl*>(m_vector.m_buffer); + m_currentEl = m_vector.m_llStart; + while (m_currentEl>=0 && abs(llElements[m_currentEl].value)<=m_epsilon) + m_currentEl = llElements[m_currentEl].next; + if (m_currentEl<0) + { + m_cachedValue = 0; // this is to avoid a compilation warning + m_cachedIndex = -1; + } + else + { + m_cachedIndex = llElements[m_currentEl].index; + m_cachedValue = llElements[m_currentEl].value; + } + } + } + + Index index() const { return m_cachedIndex; } + Scalar value() const { return m_cachedValue; } + + operator bool() const { return m_cachedIndex>=0; } + + Iterator& operator++() + { + using std::abs; + if (m_isDense) + { + do { + ++m_cachedIndex; + } while (m_cachedIndex<m_vector.m_end && abs(m_vector.m_buffer[m_cachedIndex])<m_epsilon); + if (m_cachedIndex<m_vector.m_end) + m_cachedValue = m_vector.m_buffer[m_cachedIndex]; + else + m_cachedIndex=-1; + } + else + { + ListEl* EIGEN_RESTRICT llElements = reinterpret_cast<ListEl*>(m_vector.m_buffer); + do { + m_currentEl = llElements[m_currentEl].next; + } while (m_currentEl>=0 && abs(llElements[m_currentEl].value)<m_epsilon); + if (m_currentEl<0) + { + m_cachedIndex = -1; + } + else + { + m_cachedIndex = llElements[m_currentEl].index; + m_cachedValue = llElements[m_currentEl].value; + } + } + return *this; + } + + protected: + const AmbiVector& m_vector; // the target vector + Index m_currentEl; // the current element in sparse/linked-list mode + RealScalar m_epsilon; // epsilon used to prune zero coefficients + Index m_cachedIndex; // current coordinate + Scalar m_cachedValue; // current value + bool m_isDense; // mode of the vector +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_AMBIVECTOR_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/CompressedStorage.h b/third_party/eigen3/Eigen/src/SparseCore/CompressedStorage.h new file mode 100644 index 0000000000..ab3989ce28 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/CompressedStorage.h @@ -0,0 +1,235 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_COMPRESSED_STORAGE_H +#define EIGEN_COMPRESSED_STORAGE_H + +namespace Eigen { + +namespace internal { + +/** \internal + * Stores a sparse set of values as a list of values and a list of indices. + * + */ +template<typename _Scalar,typename _Index> +class CompressedStorage +{ + public: + + typedef _Scalar Scalar; + typedef _Index Index; + + protected: + + typedef typename NumTraits<Scalar>::Real RealScalar; + + public: + + CompressedStorage() + : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0) + {} + + CompressedStorage(size_t size) + : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0) + { + resize(size); + } + + CompressedStorage(const CompressedStorage& other) + : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0) + { + *this = other; + } + + CompressedStorage& operator=(const CompressedStorage& other) + { + resize(other.size()); + internal::smart_copy(other.m_values, other.m_values + m_size, m_values); + internal::smart_copy(other.m_indices, other.m_indices + m_size, m_indices); + return *this; + } + + void swap(CompressedStorage& other) + { + std::swap(m_values, other.m_values); + std::swap(m_indices, other.m_indices); + std::swap(m_size, other.m_size); + std::swap(m_allocatedSize, other.m_allocatedSize); + } + + ~CompressedStorage() + { + delete[] m_values; + delete[] m_indices; + } + + void reserve(size_t size) + { + size_t newAllocatedSize = m_size + size; + if (newAllocatedSize > m_allocatedSize) + reallocate(newAllocatedSize); + } + + void squeeze() + { + if (m_allocatedSize>m_size) + reallocate(m_size); + } + + void resize(size_t size, float reserveSizeFactor = 0) + { + if (m_allocatedSize<size) + reallocate(size + size_t(reserveSizeFactor*size)); + m_size = size; + } + + void append(const Scalar& v, Index i) + { + Index id = static_cast<Index>(m_size); + resize(m_size+1, 1); + m_values[id] = v; + m_indices[id] = i; + } + + inline size_t size() const { return m_size; } + inline size_t allocatedSize() const { return m_allocatedSize; } + inline void clear() { m_size = 0; } + + inline Scalar& value(size_t i) { return m_values[i]; } + inline const Scalar& value(size_t i) const { return m_values[i]; } + + inline Index& index(size_t i) { return m_indices[i]; } + inline const Index& index(size_t i) const { return m_indices[i]; } + + static CompressedStorage Map(Index* indices, Scalar* values, size_t size) + { + CompressedStorage res; + res.m_indices = indices; + res.m_values = values; + res.m_allocatedSize = res.m_size = size; + return res; + } + + /** \returns the largest \c k such that for all \c j in [0,k) index[\c j]\<\a key */ + inline Index searchLowerIndex(Index key) const + { + return searchLowerIndex(0, m_size, key); + } + + /** \returns the largest \c k in [start,end) such that for all \c j in [start,k) index[\c j]\<\a key */ + inline Index searchLowerIndex(size_t start, size_t end, Index key) const + { + while(end>start) + { + size_t mid = (end+start)>>1; + if (m_indices[mid]<key) + start = mid+1; + else + end = mid; + } + return static_cast<Index>(start); + } + + /** \returns the stored value at index \a key + * If the value does not exist, then the value \a defaultValue is returned without any insertion. */ + inline Scalar at(Index key, const Scalar& defaultValue = Scalar(0)) const + { + if (m_size==0) + return defaultValue; + else if (key==m_indices[m_size-1]) + return m_values[m_size-1]; + // ^^ optimization: let's first check if it is the last coefficient + // (very common in high level algorithms) + const size_t id = searchLowerIndex(0,m_size-1,key); + return ((id<m_size) && (m_indices[id]==key)) ? m_values[id] : defaultValue; + } + + /** Like at(), but the search is performed in the range [start,end) */ + inline Scalar atInRange(size_t start, size_t end, Index key, const Scalar& defaultValue = Scalar(0)) const + { + if (start>=end) + return Scalar(0); + else if (end>start && key==m_indices[end-1]) + return m_values[end-1]; + // ^^ optimization: let's first check if it is the last coefficient + // (very common in high level algorithms) + const size_t id = searchLowerIndex(start,end-1,key); + return ((id<end) && (m_indices[id]==key)) ? m_values[id] : defaultValue; + } + + /** \returns a reference to the value at index \a key + * If the value does not exist, then the value \a defaultValue is inserted + * such that the keys are sorted. */ + inline Scalar& atWithInsertion(Index key, const Scalar& defaultValue = Scalar(0)) + { + size_t id = searchLowerIndex(0,m_size,key); + if (id>=m_size || m_indices[id]!=key) + { + resize(m_size+1,1); + for (size_t j=m_size-1; j>id; --j) + { + m_indices[j] = m_indices[j-1]; + m_values[j] = m_values[j-1]; + } + m_indices[id] = key; + m_values[id] = defaultValue; + } + return m_values[id]; + } + + void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) + { + size_t k = 0; + size_t n = size(); + for (size_t i=0; i<n; ++i) + { + if (!internal::isMuchSmallerThan(value(i), reference, epsilon)) + { + value(k) = value(i); + index(k) = index(i); + ++k; + } + } + resize(k,0); + } + + protected: + + inline void reallocate(size_t size) + { + Scalar* newValues = new Scalar[size]; + Index* newIndices = new Index[size]; + size_t copySize = (std::min)(size, m_size); + // copy + if (copySize>0) { + internal::smart_copy(m_values, m_values+copySize, newValues); + internal::smart_copy(m_indices, m_indices+copySize, newIndices); + } + // delete old stuff + delete[] m_values; + delete[] m_indices; + m_values = newValues; + m_indices = newIndices; + m_allocatedSize = size; + } + + protected: + Scalar* m_values; + Index* m_indices; + size_t m_size; + size_t m_allocatedSize; + +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_COMPRESSED_STORAGE_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h b/third_party/eigen3/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h new file mode 100644 index 0000000000..5c320e2d2d --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h @@ -0,0 +1,245 @@ +// 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 diff --git a/third_party/eigen3/Eigen/src/SparseCore/MappedSparseMatrix.h b/third_party/eigen3/Eigen/src/SparseCore/MappedSparseMatrix.h new file mode 100644 index 0000000000..ab1a266a90 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/MappedSparseMatrix.h @@ -0,0 +1,181 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_MAPPED_SPARSEMATRIX_H +#define EIGEN_MAPPED_SPARSEMATRIX_H + +namespace Eigen { + +/** \class MappedSparseMatrix + * + * \brief Sparse matrix + * + * \param _Scalar the scalar type, i.e. the type of the coefficients + * + * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme. + * + */ +namespace internal { +template<typename _Scalar, int _Flags, typename _Index> +struct traits<MappedSparseMatrix<_Scalar, _Flags, _Index> > : traits<SparseMatrix<_Scalar, _Flags, _Index> > +{}; +} + +template<typename _Scalar, int _Flags, typename _Index> +class MappedSparseMatrix + : public SparseMatrixBase<MappedSparseMatrix<_Scalar, _Flags, _Index> > +{ + public: + EIGEN_SPARSE_PUBLIC_INTERFACE(MappedSparseMatrix) + enum { IsRowMajor = Base::IsRowMajor }; + + protected: + + Index m_outerSize; + Index m_innerSize; + Index m_nnz; + Index* m_outerIndex; + Index* m_innerIndices; + Scalar* m_values; + + public: + + inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; } + inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; } + inline Index innerSize() const { return m_innerSize; } + inline Index outerSize() const { return m_outerSize; } + + bool isCompressed() const { return true; } + + //---------------------------------------- + // direct access interface + inline const Scalar* valuePtr() const { return m_values; } + inline Scalar* valuePtr() { return m_values; } + + inline const Index* innerIndexPtr() const { return m_innerIndices; } + inline Index* innerIndexPtr() { return m_innerIndices; } + + inline const Index* outerIndexPtr() const { return m_outerIndex; } + inline Index* outerIndexPtr() { return m_outerIndex; } + //---------------------------------------- + + inline Scalar coeff(Index row, Index col) const + { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + Index start = m_outerIndex[outer]; + Index end = m_outerIndex[outer+1]; + if (start==end) + return Scalar(0); + else if (end>0 && inner==m_innerIndices[end-1]) + return m_values[end-1]; + // ^^ optimization: let's first check if it is the last coefficient + // (very common in high level algorithms) + + const Index* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end-1],inner); + const Index id = r-&m_innerIndices[0]; + return ((*r==inner) && (id<end)) ? m_values[id] : Scalar(0); + } + + inline Scalar& coeffRef(Index row, Index col) + { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + Index start = m_outerIndex[outer]; + Index end = m_outerIndex[outer+1]; + eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix"); + eigen_assert(end>start && "coeffRef cannot be called on a zero coefficient"); + Index* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end],inner); + const Index id = r-&m_innerIndices[0]; + eigen_assert((*r==inner) && (id<end) && "coeffRef cannot be called on a zero coefficient"); + return m_values[id]; + } + + class InnerIterator; + class ReverseInnerIterator; + + /** \returns the number of non zero coefficients */ + inline Index nonZeros() const { return m_nnz; } + + inline MappedSparseMatrix(Index rows, Index cols, Index nnz, Index* outerIndexPtr, Index* innerIndexPtr, Scalar* valuePtr) + : m_outerSize(IsRowMajor?rows:cols), m_innerSize(IsRowMajor?cols:rows), m_nnz(nnz), m_outerIndex(outerIndexPtr), + m_innerIndices(innerIndexPtr), m_values(valuePtr) + {} + + /** Empty destructor */ + inline ~MappedSparseMatrix() {} +}; + +template<typename Scalar, int _Flags, typename _Index> +class MappedSparseMatrix<Scalar,_Flags,_Index>::InnerIterator +{ + public: + InnerIterator(const MappedSparseMatrix& mat, Index outer) + : m_matrix(mat), + m_outer(outer), + m_id(mat.outerIndexPtr()[outer]), + m_start(m_id), + m_end(mat.outerIndexPtr()[outer+1]) + {} + + inline InnerIterator& operator++() { m_id++; return *this; } + + inline Scalar value() const { return m_matrix.valuePtr()[m_id]; } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.valuePtr()[m_id]); } + + inline Index index() const { return m_matrix.innerIndexPtr()[m_id]; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id < m_end) && (m_id>=m_start); } + + protected: + const MappedSparseMatrix& m_matrix; + const Index m_outer; + Index m_id; + const Index m_start; + const Index m_end; +}; + +template<typename Scalar, int _Flags, typename _Index> +class MappedSparseMatrix<Scalar,_Flags,_Index>::ReverseInnerIterator +{ + public: + ReverseInnerIterator(const MappedSparseMatrix& mat, Index outer) + : m_matrix(mat), + m_outer(outer), + m_id(mat.outerIndexPtr()[outer+1]), + m_start(mat.outerIndexPtr()[outer]), + m_end(m_id) + {} + + inline ReverseInnerIterator& operator--() { m_id--; return *this; } + + inline Scalar value() const { return m_matrix.valuePtr()[m_id-1]; } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.valuePtr()[m_id-1]); } + + inline Index index() const { return m_matrix.innerIndexPtr()[m_id-1]; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id <= m_end) && (m_id>m_start); } + + protected: + const MappedSparseMatrix& m_matrix; + const Index m_outer; + Index m_id; + const Index m_start; + const Index m_end; +}; + +} // end namespace Eigen + +#endif // EIGEN_MAPPED_SPARSEMATRIX_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseBlock.h b/third_party/eigen3/Eigen/src/SparseCore/SparseBlock.h new file mode 100644 index 0000000000..3a6d8a275c --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseBlock.h @@ -0,0 +1,547 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2009 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_SPARSE_BLOCK_H +#define EIGEN_SPARSE_BLOCK_H + +namespace Eigen { + +template<typename XprType, int BlockRows, int BlockCols> +class BlockImpl<XprType,BlockRows,BlockCols,true,Sparse> + : public SparseMatrixBase<Block<XprType,BlockRows,BlockCols,true> > +{ + typedef typename internal::remove_all<typename XprType::Nested>::type _MatrixTypeNested; + typedef Block<XprType, BlockRows, BlockCols, true> BlockType; +public: + enum { IsRowMajor = internal::traits<BlockType>::IsRowMajor }; +protected: + enum { OuterSize = IsRowMajor ? BlockRows : BlockCols }; +public: + EIGEN_SPARSE_PUBLIC_INTERFACE(BlockType) + + class InnerIterator: public XprType::InnerIterator + { + typedef typename BlockImpl::Index Index; + public: + inline InnerIterator(const BlockType& xpr, Index outer) + : XprType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer) + {} + inline Index row() const { return IsRowMajor ? m_outer : this->index(); } + inline Index col() const { return IsRowMajor ? this->index() : m_outer; } + protected: + Index m_outer; + }; + class ReverseInnerIterator: public XprType::ReverseInnerIterator + { + typedef typename BlockImpl::Index Index; + public: + inline ReverseInnerIterator(const BlockType& xpr, Index outer) + : XprType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer) + {} + inline Index row() const { return IsRowMajor ? m_outer : this->index(); } + inline Index col() const { return IsRowMajor ? this->index() : m_outer; } + protected: + Index m_outer; + }; + + inline BlockImpl(const XprType& xpr, int i) + : m_matrix(xpr), m_outerStart(i), m_outerSize(OuterSize) + {} + + inline BlockImpl(const XprType& xpr, int startRow, int startCol, int blockRows, int blockCols) + : m_matrix(xpr), m_outerStart(IsRowMajor ? startRow : startCol), m_outerSize(IsRowMajor ? blockRows : blockCols) + {} + + EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); } + EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); } + + Index nonZeros() const + { + Index nnz = 0; + Index end = m_outerStart + m_outerSize.value(); + for(int j=m_outerStart; j<end; ++j) + for(typename XprType::InnerIterator it(m_matrix, j); it; ++it) + ++nnz; + return nnz; + } + + protected: + + typename XprType::Nested m_matrix; + Index m_outerStart; + const internal::variable_if_dynamic<Index, OuterSize> m_outerSize; + + public: + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl) +}; + + +/*************************************************************************** +* specialization for SparseMatrix +***************************************************************************/ + +namespace internal { + +template<typename SparseMatrixType, int BlockRows, int BlockCols> +class sparse_matrix_block_impl + : public SparseMatrixBase<Block<SparseMatrixType,BlockRows,BlockCols,true> > +{ + typedef typename internal::remove_all<typename SparseMatrixType::Nested>::type _MatrixTypeNested; + typedef Block<SparseMatrixType, BlockRows, BlockCols, true> BlockType; +public: + enum { IsRowMajor = internal::traits<BlockType>::IsRowMajor }; + EIGEN_SPARSE_PUBLIC_INTERFACE(BlockType) +protected: + enum { OuterSize = IsRowMajor ? BlockRows : BlockCols }; +public: + + class InnerIterator: public SparseMatrixType::InnerIterator + { + public: + inline InnerIterator(const BlockType& xpr, Index outer) + : SparseMatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer) + {} + inline Index row() const { return IsRowMajor ? m_outer : this->index(); } + inline Index col() const { return IsRowMajor ? this->index() : m_outer; } + protected: + Index m_outer; + }; + class ReverseInnerIterator: public SparseMatrixType::ReverseInnerIterator + { + public: + inline ReverseInnerIterator(const BlockType& xpr, Index outer) + : SparseMatrixType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer) + {} + inline Index row() const { return IsRowMajor ? m_outer : this->index(); } + inline Index col() const { return IsRowMajor ? this->index() : m_outer; } + protected: + Index m_outer; + }; + + inline sparse_matrix_block_impl(const SparseMatrixType& xpr, int i) + : m_matrix(xpr), m_outerStart(i), m_outerSize(OuterSize) + {} + + inline sparse_matrix_block_impl(const SparseMatrixType& xpr, int startRow, int startCol, int blockRows, int blockCols) + : m_matrix(xpr), m_outerStart(IsRowMajor ? startRow : startCol), m_outerSize(IsRowMajor ? blockRows : blockCols) + {} + + template<typename OtherDerived> + inline BlockType& operator=(const SparseMatrixBase<OtherDerived>& other) + { + typedef typename internal::remove_all<typename SparseMatrixType::Nested>::type _NestedMatrixType; + _NestedMatrixType& matrix = const_cast<_NestedMatrixType&>(m_matrix);; + // This assignment is slow if this vector set is not empty + // and/or it is not at the end of the nonzeros of the underlying matrix. + + // 1 - eval to a temporary to avoid transposition and/or aliasing issues + SparseMatrix<Scalar, IsRowMajor ? RowMajor : ColMajor, Index> tmp(other); + + // 2 - let's check whether there is enough allocated memory + Index nnz = tmp.nonZeros(); + Index start = m_outerStart==0 ? 0 : matrix.outerIndexPtr()[m_outerStart]; // starting position of the current block + Index end = m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()]; // ending position of the current block + Index block_size = end - start; // available room in the current block + Index tail_size = m_matrix.outerIndexPtr()[m_matrix.outerSize()] - end; + + Index free_size = m_matrix.isCompressed() + ? Index(matrix.data().allocatedSize()) + block_size + : block_size; + + if(nnz>free_size) + { + // realloc manually to reduce copies + typename SparseMatrixType::Storage newdata(m_matrix.data().allocatedSize() - block_size + nnz); + + internal::smart_copy(&m_matrix.data().value(0), &m_matrix.data().value(0) + start, &newdata.value(0)); + internal::smart_copy(&m_matrix.data().index(0), &m_matrix.data().index(0) + start, &newdata.index(0)); + + internal::smart_copy(&tmp.data().value(0), &tmp.data().value(0) + nnz, &newdata.value(start)); + internal::smart_copy(&tmp.data().index(0), &tmp.data().index(0) + nnz, &newdata.index(start)); + + internal::smart_copy(&matrix.data().value(end), &matrix.data().value(end) + tail_size, &newdata.value(start+nnz)); + internal::smart_copy(&matrix.data().index(end), &matrix.data().index(end) + tail_size, &newdata.index(start+nnz)); + + newdata.resize(m_matrix.outerIndexPtr()[m_matrix.outerSize()] - block_size + nnz); + + matrix.data().swap(newdata); + } + else + { + // no need to realloc, simply copy the tail at its respective position and insert tmp + matrix.data().resize(start + nnz + tail_size); + + internal::smart_memmove(&matrix.data().value(end), &matrix.data().value(end) + tail_size, &matrix.data().value(start + nnz)); + internal::smart_memmove(&matrix.data().index(end), &matrix.data().index(end) + tail_size, &matrix.data().index(start + nnz)); + + internal::smart_copy(&tmp.data().value(0), &tmp.data().value(0) + nnz, &matrix.data().value(start)); + internal::smart_copy(&tmp.data().index(0), &tmp.data().index(0) + nnz, &matrix.data().index(start)); + } + + // update innerNonZeros + if(!m_matrix.isCompressed()) + for(Index j=0; j<m_outerSize.value(); ++j) + matrix.innerNonZeroPtr()[m_outerStart+j] = tmp.innerVector(j).nonZeros(); + + // update outer index pointers + Index p = start; + for(Index k=0; k<m_outerSize.value(); ++k) + { + matrix.outerIndexPtr()[m_outerStart+k] = p; + p += tmp.innerVector(k).nonZeros(); + } + std::ptrdiff_t offset = nnz - block_size; + for(Index k = m_outerStart + m_outerSize.value(); k<=matrix.outerSize(); ++k) + { + matrix.outerIndexPtr()[k] += offset; + } + + return derived(); + } + + inline BlockType& operator=(const BlockType& other) + { + return operator=<BlockType>(other); + } + + inline const Scalar* valuePtr() const + { return m_matrix.valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; } + inline Scalar* valuePtr() + { return m_matrix.const_cast_derived().valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; } + + inline const Index* innerIndexPtr() const + { return m_matrix.innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; } + inline Index* innerIndexPtr() + { return m_matrix.const_cast_derived().innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; } + + inline const Index* outerIndexPtr() const + { return m_matrix.outerIndexPtr() + m_outerStart; } + inline Index* outerIndexPtr() + { return m_matrix.const_cast_derived().outerIndexPtr() + m_outerStart; } + + Index nonZeros() const + { + if(m_matrix.isCompressed()) + return std::size_t(m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()]) + - std::size_t(m_matrix.outerIndexPtr()[m_outerStart]); + else if(m_outerSize.value()==0) + return 0; + else + return Map<const Matrix<Index,OuterSize,1> >(m_matrix.innerNonZeroPtr()+m_outerStart, m_outerSize.value()).sum(); + } + + const Scalar& lastCoeff() const + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(sparse_matrix_block_impl); + eigen_assert(nonZeros()>0); + if(m_matrix.isCompressed()) + return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart+1]-1]; + else + return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart]+m_matrix.innerNonZeroPtr()[m_outerStart]-1]; + } + + EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); } + EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); } + + protected: + + typename SparseMatrixType::Nested m_matrix; + Index m_outerStart; + const internal::variable_if_dynamic<Index, OuterSize> m_outerSize; + +}; + +} // namespace internal + +template<typename _Scalar, int _Options, typename _Index, int BlockRows, int BlockCols> +class BlockImpl<SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols,true,Sparse> + : public internal::sparse_matrix_block_impl<SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols> +{ +public: + typedef SparseMatrix<_Scalar, _Options, _Index> SparseMatrixType; + typedef internal::sparse_matrix_block_impl<SparseMatrixType,BlockRows,BlockCols> Base; + inline BlockImpl(SparseMatrixType& xpr, int i) + : Base(xpr, i) + {} + + inline BlockImpl(SparseMatrixType& xpr, int startRow, int startCol, int blockRows, int blockCols) + : Base(xpr, startRow, startCol, blockRows, blockCols) + {} + + using Base::operator=; +}; + +template<typename _Scalar, int _Options, typename _Index, int BlockRows, int BlockCols> +class BlockImpl<const SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols,true,Sparse> + : public internal::sparse_matrix_block_impl<const SparseMatrix<_Scalar, _Options, _Index>,BlockRows,BlockCols> +{ +public: + typedef const SparseMatrix<_Scalar, _Options, _Index> SparseMatrixType; + typedef internal::sparse_matrix_block_impl<SparseMatrixType,BlockRows,BlockCols> Base; + inline BlockImpl(SparseMatrixType& xpr, int i) + : Base(xpr, i) + {} + + inline BlockImpl(SparseMatrixType& xpr, int startRow, int startCol, int blockRows, int blockCols) + : Base(xpr, startRow, startCol, blockRows, blockCols) + {} + + using Base::operator=; +}; + +//---------- + +/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this + * is col-major (resp. row-major). + */ +template<typename Derived> +typename SparseMatrixBase<Derived>::InnerVectorReturnType SparseMatrixBase<Derived>::innerVector(Index outer) +{ return InnerVectorReturnType(derived(), outer); } + +/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this + * is col-major (resp. row-major). Read-only. + */ +template<typename Derived> +const typename SparseMatrixBase<Derived>::ConstInnerVectorReturnType SparseMatrixBase<Derived>::innerVector(Index outer) const +{ return ConstInnerVectorReturnType(derived(), outer); } + +/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this + * is col-major (resp. row-major). + */ +template<typename Derived> +Block<Derived,Dynamic,Dynamic,true> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize) +{ + return Block<Derived,Dynamic,Dynamic,true>(derived(), + IsRowMajor ? outerStart : 0, IsRowMajor ? 0 : outerStart, + IsRowMajor ? outerSize : rows(), IsRowMajor ? cols() : outerSize); + +} + +/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this + * is col-major (resp. row-major). Read-only. + */ +template<typename Derived> +const Block<const Derived,Dynamic,Dynamic,true> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize) const +{ + return Block<const Derived,Dynamic,Dynamic,true>(derived(), + IsRowMajor ? outerStart : 0, IsRowMajor ? 0 : outerStart, + IsRowMajor ? outerSize : rows(), IsRowMajor ? cols() : outerSize); + +} + +namespace internal { + +template< typename XprType, int BlockRows, int BlockCols, bool InnerPanel, + bool OuterVector = (BlockCols==1 && XprType::IsRowMajor) + | // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&". + // revert to || as soon as not needed anymore. + (BlockRows==1 && !XprType::IsRowMajor)> +class GenericSparseBlockInnerIteratorImpl; + +} + +/** Generic implementation of sparse Block expression. + * Real-only. + */ +template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> +class BlockImpl<XprType,BlockRows,BlockCols,InnerPanel,Sparse> + : public SparseMatrixBase<Block<XprType,BlockRows,BlockCols,InnerPanel> >, internal::no_assignment_operator +{ + typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType; +public: + enum { IsRowMajor = internal::traits<BlockType>::IsRowMajor }; + EIGEN_SPARSE_PUBLIC_INTERFACE(BlockType) + + typedef typename internal::remove_all<typename XprType::Nested>::type _MatrixTypeNested; + + /** Column or Row constructor + */ + inline BlockImpl(const XprType& xpr, int i) + : m_matrix(xpr), + m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0), + m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0), + m_blockRows(BlockRows==1 ? 1 : xpr.rows()), + m_blockCols(BlockCols==1 ? 1 : xpr.cols()) + {} + + /** Dynamic-size constructor + */ + inline BlockImpl(const XprType& xpr, int startRow, int startCol, int blockRows, int blockCols) + : m_matrix(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(blockRows), m_blockCols(blockCols) + {} + + inline int rows() const { return m_blockRows.value(); } + inline int cols() const { return m_blockCols.value(); } + + inline Scalar& coeffRef(int row, int col) + { + return m_matrix.const_cast_derived() + .coeffRef(row + m_startRow.value(), col + m_startCol.value()); + } + + inline const Scalar coeff(int row, int col) const + { + return m_matrix.coeff(row + m_startRow.value(), col + m_startCol.value()); + } + + inline Scalar& coeffRef(int index) + { + return m_matrix.const_cast_derived() + .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), + m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); + } + + inline const Scalar coeff(int index) const + { + return m_matrix + .coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), + m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); + } + + inline const _MatrixTypeNested& nestedExpression() const { return m_matrix; } + + typedef internal::GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel> InnerIterator; + + class ReverseInnerIterator : public _MatrixTypeNested::ReverseInnerIterator + { + typedef typename _MatrixTypeNested::ReverseInnerIterator Base; + const BlockType& m_block; + Index m_begin; + public: + + EIGEN_STRONG_INLINE ReverseInnerIterator(const BlockType& block, Index outer) + : Base(block.derived().nestedExpression(), outer + (IsRowMajor ? block.m_startRow.value() : block.m_startCol.value())), + m_block(block), + m_begin(IsRowMajor ? block.m_startCol.value() : block.m_startRow.value()) + { + while( (Base::operator bool()) && (Base::index() >= (IsRowMajor ? m_block.m_startCol.value()+block.m_blockCols.value() : m_block.m_startRow.value()+block.m_blockRows.value())) ) + Base::operator--(); + } + + inline Index index() const { return Base::index() - (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value()); } + inline Index outer() const { return Base::outer() - (IsRowMajor ? m_block.m_startRow.value() : m_block.m_startCol.value()); } + inline Index row() const { return Base::row() - m_block.m_startRow.value(); } + inline Index col() const { return Base::col() - m_block.m_startCol.value(); } + + inline operator bool() const { return Base::operator bool() && Base::index() >= m_begin; } + }; + protected: + friend class internal::GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel>; + friend class ReverseInnerIterator; + + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl) + + typename XprType::Nested m_matrix; + const internal::variable_if_dynamic<Index, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow; + const internal::variable_if_dynamic<Index, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol; + const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_blockRows; + const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_blockCols; + +}; + +namespace internal { + template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> + class GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel,false> : public Block<XprType, BlockRows, BlockCols, InnerPanel>::_MatrixTypeNested::InnerIterator + { + typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType; + enum { + IsRowMajor = BlockType::IsRowMajor + }; + typedef typename BlockType::_MatrixTypeNested _MatrixTypeNested; + typedef typename BlockType::Index Index; + typedef typename _MatrixTypeNested::InnerIterator Base; + const BlockType& m_block; + Index m_end; + public: + + EIGEN_STRONG_INLINE GenericSparseBlockInnerIteratorImpl(const BlockType& block, Index outer) + : Base(block.derived().nestedExpression(), outer + (IsRowMajor ? block.m_startRow.value() : block.m_startCol.value())), + m_block(block), + m_end(IsRowMajor ? block.m_startCol.value()+block.m_blockCols.value() : block.m_startRow.value()+block.m_blockRows.value()) + { + while( (Base::operator bool()) && (Base::index() < (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value())) ) + Base::operator++(); + } + + inline Index index() const { return Base::index() - (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value()); } + inline Index outer() const { return Base::outer() - (IsRowMajor ? m_block.m_startRow.value() : m_block.m_startCol.value()); } + inline Index row() const { return Base::row() - m_block.m_startRow.value(); } + inline Index col() const { return Base::col() - m_block.m_startCol.value(); } + + inline operator bool() const { return Base::operator bool() && Base::index() < m_end; } + }; + + // Row vector of a column-major sparse matrix or column of a row-major one. + template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> + class GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel,true> + { + typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType; + enum { + IsRowMajor = BlockType::IsRowMajor + }; + typedef typename BlockType::_MatrixTypeNested _MatrixTypeNested; + typedef typename BlockType::Index Index; + typedef typename BlockType::Scalar Scalar; + const BlockType& m_block; + Index m_outerPos; + Index m_innerIndex; + Scalar m_value; + Index m_end; + public: + + EIGEN_STRONG_INLINE GenericSparseBlockInnerIteratorImpl(const BlockType& block, Index outer = 0) + : + m_block(block), + m_outerPos( (IsRowMajor ? block.m_startCol.value() : block.m_startRow.value()) - 1), // -1 so that operator++ finds the first non-zero entry + m_innerIndex(IsRowMajor ? block.m_startRow.value() : block.m_startCol.value()), + m_end(IsRowMajor ? block.m_startCol.value()+block.m_blockCols.value() : block.m_startRow.value()+block.m_blockRows.value()) + { + EIGEN_UNUSED_VARIABLE(outer); + eigen_assert(outer==0); + + ++(*this); + } + + inline Index index() const { return m_outerPos - (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value()); } + inline Index outer() const { return 0; } + inline Index row() const { return IsRowMajor ? 0 : index(); } + inline Index col() const { return IsRowMajor ? index() : 0; } + + inline Scalar value() const { return m_value; } + + inline GenericSparseBlockInnerIteratorImpl& operator++() + { + // At end already? + if (m_outerPos >= m_end) + return *this; + + // search next non-zero entry. + while(++m_outerPos<m_end) + { + typename XprType::InnerIterator it(m_block.m_matrix, m_outerPos); + // search for the key m_innerIndex in the current outer-vector + while(it && it.index() < m_innerIndex) ++it; + if(it && it.index()==m_innerIndex) + { + m_value = it.value(); + break; + } + } + return *this; + } + + inline operator bool() const { return m_outerPos < m_end; } + }; + +} // end namespace internal + + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_BLOCK_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseColEtree.h b/third_party/eigen3/Eigen/src/SparseCore/SparseColEtree.h new file mode 100644 index 0000000000..f8745f4610 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseColEtree.h @@ -0,0 +1,206 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/. + + +/* + + * NOTE: This file is the modified version of sp_coletree.c file in SuperLU + + * -- SuperLU routine (version 3.1) -- + * Univ. of California Berkeley, Xerox Palo Alto Research Center, + * and Lawrence Berkeley National Lab. + * August 1, 2008 + * + * Copyright (c) 1994 by Xerox Corporation. All rights reserved. + * + * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY + * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK. + * + * Permission is hereby granted to use or copy this program for any + * purpose, provided the above notices are retained on all copies. + * Permission to modify the code and to distribute modified code is + * granted, provided the above notices are retained, and a notice that + * the code was modified is included with the above copyright notice. + */ +#ifndef SPARSE_COLETREE_H +#define SPARSE_COLETREE_H + +namespace Eigen { + +namespace internal { + +/** Find the root of the tree/set containing the vertex i : Use Path halving */ +template<typename Index, typename IndexVector> +Index etree_find (Index i, IndexVector& pp) +{ + Index p = pp(i); // Parent + Index gp = pp(p); // Grand parent + while (gp != p) + { + pp(i) = gp; // Parent pointer on find path is changed to former grand parent + i = gp; + p = pp(i); + gp = pp(p); + } + return p; +} + +/** Compute the column elimination tree of a sparse matrix + * \param mat The matrix in column-major format. + * \param parent The elimination tree + * \param firstRowElt The column index of the first element in each row + * \param perm The permutation to apply to the column of \b mat + */ +template <typename MatrixType, typename IndexVector> +int coletree(const MatrixType& mat, IndexVector& parent, IndexVector& firstRowElt, typename MatrixType::Index *perm=0) +{ + typedef typename MatrixType::Index Index; + Index nc = mat.cols(); // Number of columns + Index m = mat.rows(); + Index diagSize = (std::min)(nc,m); + IndexVector root(nc); // root of subtree of etree + root.setZero(); + IndexVector pp(nc); // disjoint sets + pp.setZero(); // Initialize disjoint sets + parent.resize(mat.cols()); + //Compute first nonzero column in each row + Index row,col; + firstRowElt.resize(m); + firstRowElt.setConstant(nc); + firstRowElt.segment(0, diagSize).setLinSpaced(diagSize, 0, diagSize-1); + bool found_diag; + for (col = 0; col < nc; col++) + { + Index pcol = col; + if(perm) pcol = perm[col]; + for (typename MatrixType::InnerIterator it(mat, pcol); it; ++it) + { + row = it.row(); + firstRowElt(row) = (std::min)(firstRowElt(row), col); + } + } + /* Compute etree by Liu's algorithm for symmetric matrices, + except use (firstRowElt[r],c) in place of an edge (r,c) of A. + Thus each row clique in A'*A is replaced by a star + centered at its first vertex, which has the same fill. */ + Index rset, cset, rroot; + for (col = 0; col < nc; col++) + { + found_diag = col>=m; + pp(col) = col; + cset = col; + root(cset) = col; + parent(col) = nc; + /* The diagonal element is treated here even if it does not exist in the matrix + * hence the loop is executed once more */ + Index pcol = col; + if(perm) pcol = perm[col]; + for (typename MatrixType::InnerIterator it(mat, pcol); it||!found_diag; ++it) + { // A sequence of interleaved find and union is performed + Index i = col; + if(it) i = it.index(); + if (i == col) found_diag = true; + + row = firstRowElt(i); + if (row >= col) continue; + rset = internal::etree_find(row, pp); // Find the name of the set containing row + rroot = root(rset); + if (rroot != col) + { + parent(rroot) = col; + pp(cset) = rset; + cset = rset; + root(cset) = col; + } + } + } + return 0; +} + +/** + * Depth-first search from vertex n. No recursion. + * This routine was contributed by Cédric Doucet, CEDRAT Group, Meylan, France. +*/ +template <typename Index, typename IndexVector> +void nr_etdfs (Index n, IndexVector& parent, IndexVector& first_kid, IndexVector& next_kid, IndexVector& post, Index postnum) +{ + Index current = n, first, next; + while (postnum != n) + { + // No kid for the current node + first = first_kid(current); + + // no kid for the current node + if (first == -1) + { + // Numbering this node because it has no kid + post(current) = postnum++; + + // looking for the next kid + next = next_kid(current); + while (next == -1) + { + // No more kids : back to the parent node + current = parent(current); + // numbering the parent node + post(current) = postnum++; + + // Get the next kid + next = next_kid(current); + } + // stopping criterion + if (postnum == n+1) return; + + // Updating current node + current = next; + } + else + { + current = first; + } + } +} + + +/** + * \brief Post order a tree + * \param n the number of nodes + * \param parent Input tree + * \param post postordered tree + */ +template <typename Index, typename IndexVector> +void treePostorder(Index n, IndexVector& parent, IndexVector& post) +{ + IndexVector first_kid, next_kid; // Linked list of children + Index postnum; + // Allocate storage for working arrays and results + first_kid.resize(n+1); + next_kid.setZero(n+1); + post.setZero(n+1); + + // Set up structure describing children + Index v, dad; + first_kid.setConstant(-1); + for (v = n-1; v >= 0; v--) + { + dad = parent(v); + next_kid(v) = first_kid(dad); + first_kid(dad) = v; + } + + // Depth-first search from dummy root vertex #n + postnum = 0; + internal::nr_etdfs(n, parent, first_kid, next_kid, post, postnum); +} + +} // end namespace internal + +} // end namespace Eigen + +#endif // SPARSE_COLETREE_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseCwiseBinaryOp.h b/third_party/eigen3/Eigen/src/SparseCore/SparseCwiseBinaryOp.h new file mode 100644 index 0000000000..ec86ca933c --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseCwiseBinaryOp.h @@ -0,0 +1,324 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_SPARSE_CWISE_BINARY_OP_H +#define EIGEN_SPARSE_CWISE_BINARY_OP_H + +namespace Eigen { + +// Here we have to handle 3 cases: +// 1 - sparse op dense +// 2 - dense op sparse +// 3 - sparse op sparse +// We also need to implement a 4th iterator for: +// 4 - dense op dense +// Finally, we also need to distinguish between the product and other operations : +// configuration returned mode +// 1 - sparse op dense product sparse +// generic dense +// 2 - dense op sparse product sparse +// generic dense +// 3 - sparse op sparse product sparse +// generic sparse +// 4 - dense op dense product dense +// generic dense + +namespace internal { + +template<> struct promote_storage_type<Dense,Sparse> +{ typedef Sparse ret; }; + +template<> struct promote_storage_type<Sparse,Dense> +{ typedef Sparse ret; }; + +template<typename BinaryOp, typename Lhs, typename Rhs, typename Derived, + typename _LhsStorageMode = typename traits<Lhs>::StorageKind, + typename _RhsStorageMode = typename traits<Rhs>::StorageKind> +class sparse_cwise_binary_op_inner_iterator_selector; + +} // end namespace internal + +template<typename BinaryOp, typename Lhs, typename Rhs> +class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Sparse> + : public SparseMatrixBase<CwiseBinaryOp<BinaryOp, Lhs, Rhs> > +{ + public: + class InnerIterator; + class ReverseInnerIterator; + typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived; + EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) + CwiseBinaryOpImpl() + { + typedef typename internal::traits<Lhs>::StorageKind LhsStorageKind; + typedef typename internal::traits<Rhs>::StorageKind RhsStorageKind; + EIGEN_STATIC_ASSERT(( + (!internal::is_same<LhsStorageKind,RhsStorageKind>::value) + || ((Lhs::Flags&RowMajorBit) == (Rhs::Flags&RowMajorBit))), + THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH); + } +}; + +template<typename BinaryOp, typename Lhs, typename Rhs> +class CwiseBinaryOpImpl<BinaryOp,Lhs,Rhs,Sparse>::InnerIterator + : public internal::sparse_cwise_binary_op_inner_iterator_selector<BinaryOp,Lhs,Rhs,typename CwiseBinaryOpImpl<BinaryOp,Lhs,Rhs,Sparse>::InnerIterator> +{ + public: + typedef typename Lhs::Index Index; + typedef internal::sparse_cwise_binary_op_inner_iterator_selector< + BinaryOp,Lhs,Rhs, InnerIterator> Base; + + EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOpImpl& binOp, Index outer) + : Base(binOp.derived(),outer) + {} +}; + +/*************************************************************************** +* Implementation of inner-iterators +***************************************************************************/ + +// template<typename T> struct internal::func_is_conjunction { enum { ret = false }; }; +// template<typename T> struct internal::func_is_conjunction<internal::scalar_product_op<T> > { enum { ret = true }; }; + +// TODO generalize the internal::scalar_product_op specialization to all conjunctions if any ! + +namespace internal { + +// sparse - sparse (generic) +template<typename BinaryOp, typename Lhs, typename Rhs, typename Derived> +class sparse_cwise_binary_op_inner_iterator_selector<BinaryOp, Lhs, Rhs, Derived, Sparse, Sparse> +{ + typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> CwiseBinaryXpr; + typedef typename traits<CwiseBinaryXpr>::Scalar Scalar; + typedef typename traits<CwiseBinaryXpr>::_LhsNested _LhsNested; + typedef typename traits<CwiseBinaryXpr>::_RhsNested _RhsNested; + typedef typename _LhsNested::InnerIterator LhsIterator; + typedef typename _RhsNested::InnerIterator RhsIterator; + typedef typename Lhs::Index Index; + + public: + + EIGEN_STRONG_INLINE sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer) + : m_lhsIter(xpr.lhs(),outer), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor()) + { + this->operator++(); + } + + EIGEN_STRONG_INLINE Derived& operator++() + { + if (m_lhsIter && m_rhsIter && (m_lhsIter.index() == m_rhsIter.index())) + { + m_id = m_lhsIter.index(); + m_value = m_functor(m_lhsIter.value(), m_rhsIter.value()); + ++m_lhsIter; + ++m_rhsIter; + } + else if (m_lhsIter && (!m_rhsIter || (m_lhsIter.index() < m_rhsIter.index()))) + { + m_id = m_lhsIter.index(); + m_value = m_functor(m_lhsIter.value(), Scalar(0)); + ++m_lhsIter; + } + else if (m_rhsIter && (!m_lhsIter || (m_lhsIter.index() > m_rhsIter.index()))) + { + m_id = m_rhsIter.index(); + m_value = m_functor(Scalar(0), m_rhsIter.value()); + ++m_rhsIter; + } + else + { + m_value = 0; // this is to avoid a compilation warning + m_id = -1; + } + return *static_cast<Derived*>(this); + } + + EIGEN_STRONG_INLINE Scalar value() const { return m_value; } + + EIGEN_STRONG_INLINE Index index() const { return m_id; } + EIGEN_STRONG_INLINE Index row() const { return Lhs::IsRowMajor ? m_lhsIter.row() : index(); } + EIGEN_STRONG_INLINE Index col() const { return Lhs::IsRowMajor ? index() : m_lhsIter.col(); } + + EIGEN_STRONG_INLINE operator bool() const { return m_id>=0; } + + protected: + LhsIterator m_lhsIter; + RhsIterator m_rhsIter; + const BinaryOp& m_functor; + Scalar m_value; + Index m_id; +}; + +// sparse - sparse (product) +template<typename T, typename Lhs, typename Rhs, typename Derived> +class sparse_cwise_binary_op_inner_iterator_selector<scalar_product_op<T>, Lhs, Rhs, Derived, Sparse, Sparse> +{ + typedef scalar_product_op<T> BinaryFunc; + typedef CwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr; + typedef typename CwiseBinaryXpr::Scalar Scalar; + typedef typename traits<CwiseBinaryXpr>::_LhsNested _LhsNested; + typedef typename _LhsNested::InnerIterator LhsIterator; + typedef typename traits<CwiseBinaryXpr>::_RhsNested _RhsNested; + typedef typename _RhsNested::InnerIterator RhsIterator; + typedef typename Lhs::Index Index; + public: + + EIGEN_STRONG_INLINE sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer) + : m_lhsIter(xpr.lhs(),outer), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor()) + { + while (m_lhsIter && m_rhsIter && (m_lhsIter.index() != m_rhsIter.index())) + { + if (m_lhsIter.index() < m_rhsIter.index()) + ++m_lhsIter; + else + ++m_rhsIter; + } + } + + EIGEN_STRONG_INLINE Derived& operator++() + { + ++m_lhsIter; + ++m_rhsIter; + while (m_lhsIter && m_rhsIter && (m_lhsIter.index() != m_rhsIter.index())) + { + if (m_lhsIter.index() < m_rhsIter.index()) + ++m_lhsIter; + else + ++m_rhsIter; + } + return *static_cast<Derived*>(this); + } + + EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_lhsIter.value(), m_rhsIter.value()); } + + EIGEN_STRONG_INLINE Index index() const { return m_lhsIter.index(); } + EIGEN_STRONG_INLINE Index row() const { return m_lhsIter.row(); } + EIGEN_STRONG_INLINE Index col() const { return m_lhsIter.col(); } + + EIGEN_STRONG_INLINE operator bool() const { return (m_lhsIter && m_rhsIter); } + + protected: + LhsIterator m_lhsIter; + RhsIterator m_rhsIter; + const BinaryFunc& m_functor; +}; + +// sparse - dense (product) +template<typename T, typename Lhs, typename Rhs, typename Derived> +class sparse_cwise_binary_op_inner_iterator_selector<scalar_product_op<T>, Lhs, Rhs, Derived, Sparse, Dense> +{ + typedef scalar_product_op<T> BinaryFunc; + typedef CwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr; + typedef typename CwiseBinaryXpr::Scalar Scalar; + typedef typename traits<CwiseBinaryXpr>::_LhsNested _LhsNested; + typedef typename traits<CwiseBinaryXpr>::RhsNested RhsNested; + typedef typename _LhsNested::InnerIterator LhsIterator; + typedef typename Lhs::Index Index; + enum { IsRowMajor = (int(Lhs::Flags)&RowMajorBit)==RowMajorBit }; + public: + + EIGEN_STRONG_INLINE sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer) + : m_rhs(xpr.rhs()), m_lhsIter(xpr.lhs(),outer), m_functor(xpr.functor()), m_outer(outer) + {} + + EIGEN_STRONG_INLINE Derived& operator++() + { + ++m_lhsIter; + return *static_cast<Derived*>(this); + } + + EIGEN_STRONG_INLINE Scalar value() const + { return m_functor(m_lhsIter.value(), + m_rhs.coeff(IsRowMajor?m_outer:m_lhsIter.index(),IsRowMajor?m_lhsIter.index():m_outer)); } + + EIGEN_STRONG_INLINE Index index() const { return m_lhsIter.index(); } + EIGEN_STRONG_INLINE Index row() const { return m_lhsIter.row(); } + EIGEN_STRONG_INLINE Index col() const { return m_lhsIter.col(); } + + EIGEN_STRONG_INLINE operator bool() const { return m_lhsIter; } + + protected: + RhsNested m_rhs; + LhsIterator m_lhsIter; + const BinaryFunc m_functor; + const Index m_outer; +}; + +// sparse - dense (product) +template<typename T, typename Lhs, typename Rhs, typename Derived> +class sparse_cwise_binary_op_inner_iterator_selector<scalar_product_op<T>, Lhs, Rhs, Derived, Dense, Sparse> +{ + typedef scalar_product_op<T> BinaryFunc; + typedef CwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr; + typedef typename CwiseBinaryXpr::Scalar Scalar; + typedef typename traits<CwiseBinaryXpr>::_RhsNested _RhsNested; + typedef typename _RhsNested::InnerIterator RhsIterator; + typedef typename Lhs::Index Index; + + enum { IsRowMajor = (int(Rhs::Flags)&RowMajorBit)==RowMajorBit }; + public: + + EIGEN_STRONG_INLINE sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer) + : m_xpr(xpr), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor()), m_outer(outer) + {} + + EIGEN_STRONG_INLINE Derived& operator++() + { + ++m_rhsIter; + return *static_cast<Derived*>(this); + } + + EIGEN_STRONG_INLINE Scalar value() const + { return m_functor(m_xpr.lhs().coeff(IsRowMajor?m_outer:m_rhsIter.index(),IsRowMajor?m_rhsIter.index():m_outer), m_rhsIter.value()); } + + EIGEN_STRONG_INLINE Index index() const { return m_rhsIter.index(); } + EIGEN_STRONG_INLINE Index row() const { return m_rhsIter.row(); } + EIGEN_STRONG_INLINE Index col() const { return m_rhsIter.col(); } + + EIGEN_STRONG_INLINE operator bool() const { return m_rhsIter; } + + protected: + const CwiseBinaryXpr& m_xpr; + RhsIterator m_rhsIter; + const BinaryFunc& m_functor; + const Index m_outer; +}; + +} // end namespace internal + +/*************************************************************************** +* Implementation of SparseMatrixBase and SparseCwise functions/operators +***************************************************************************/ + +template<typename Derived> +template<typename OtherDerived> +EIGEN_STRONG_INLINE Derived & +SparseMatrixBase<Derived>::operator-=(const SparseMatrixBase<OtherDerived> &other) +{ + return derived() = derived() - other.derived(); +} + +template<typename Derived> +template<typename OtherDerived> +EIGEN_STRONG_INLINE Derived & +SparseMatrixBase<Derived>::operator+=(const SparseMatrixBase<OtherDerived>& other) +{ + return derived() = derived() + other.derived(); +} + +template<typename Derived> +template<typename OtherDerived> +EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE +SparseMatrixBase<Derived>::cwiseProduct(const MatrixBase<OtherDerived> &other) const +{ + return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(derived(), other.derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_CWISE_BINARY_OP_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseCwiseUnaryOp.h b/third_party/eigen3/Eigen/src/SparseCore/SparseCwiseUnaryOp.h new file mode 100644 index 0000000000..5a50c78030 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseCwiseUnaryOp.h @@ -0,0 +1,163 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2010 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_SPARSE_CWISE_UNARY_OP_H +#define EIGEN_SPARSE_CWISE_UNARY_OP_H + +namespace Eigen { + +template<typename UnaryOp, typename MatrixType> +class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse> + : public SparseMatrixBase<CwiseUnaryOp<UnaryOp, MatrixType> > +{ + public: + + class InnerIterator; + class ReverseInnerIterator; + + typedef CwiseUnaryOp<UnaryOp, MatrixType> Derived; + EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) + + protected: + typedef typename internal::traits<Derived>::_XprTypeNested _MatrixTypeNested; + typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator; + typedef typename _MatrixTypeNested::ReverseInnerIterator MatrixTypeReverseIterator; +}; + +template<typename UnaryOp, typename MatrixType> +class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::InnerIterator + : public CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeIterator +{ + typedef typename CwiseUnaryOpImpl::Scalar Scalar; + typedef typename CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeIterator Base; + public: + + EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOpImpl& unaryOp, typename CwiseUnaryOpImpl::Index outer) + : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) + {} + + EIGEN_STRONG_INLINE InnerIterator& operator++() + { Base::operator++(); return *this; } + + EIGEN_STRONG_INLINE typename CwiseUnaryOpImpl::Scalar value() const { return m_functor(Base::value()); } + + protected: + const UnaryOp m_functor; + private: + typename CwiseUnaryOpImpl::Scalar& valueRef(); +}; + +template<typename UnaryOp, typename MatrixType> +class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::ReverseInnerIterator + : public CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeReverseIterator +{ + typedef typename CwiseUnaryOpImpl::Scalar Scalar; + typedef typename CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeReverseIterator Base; + public: + + EIGEN_STRONG_INLINE ReverseInnerIterator(const CwiseUnaryOpImpl& unaryOp, typename CwiseUnaryOpImpl::Index outer) + : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) + {} + + EIGEN_STRONG_INLINE ReverseInnerIterator& operator--() + { Base::operator--(); return *this; } + + EIGEN_STRONG_INLINE typename CwiseUnaryOpImpl::Scalar value() const { return m_functor(Base::value()); } + + protected: + const UnaryOp m_functor; + private: + typename CwiseUnaryOpImpl::Scalar& valueRef(); +}; + +template<typename ViewOp, typename MatrixType> +class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse> + : public SparseMatrixBase<CwiseUnaryView<ViewOp, MatrixType> > +{ + public: + + class InnerIterator; + class ReverseInnerIterator; + + typedef CwiseUnaryView<ViewOp, MatrixType> Derived; + EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) + + protected: + typedef typename internal::traits<Derived>::_MatrixTypeNested _MatrixTypeNested; + typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator; + typedef typename _MatrixTypeNested::ReverseInnerIterator MatrixTypeReverseIterator; +}; + +template<typename ViewOp, typename MatrixType> +class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::InnerIterator + : public CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeIterator +{ + typedef typename CwiseUnaryViewImpl::Scalar Scalar; + typedef typename CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeIterator Base; + public: + + EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryViewImpl& unaryOp, typename CwiseUnaryViewImpl::Index outer) + : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) + {} + + EIGEN_STRONG_INLINE InnerIterator& operator++() + { Base::operator++(); return *this; } + + EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar value() const { return m_functor(Base::value()); } + EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar& valueRef() { return m_functor(Base::valueRef()); } + + protected: + const ViewOp m_functor; +}; + +template<typename ViewOp, typename MatrixType> +class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::ReverseInnerIterator + : public CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeReverseIterator +{ + typedef typename CwiseUnaryViewImpl::Scalar Scalar; + typedef typename CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeReverseIterator Base; + public: + + EIGEN_STRONG_INLINE ReverseInnerIterator(const CwiseUnaryViewImpl& unaryOp, typename CwiseUnaryViewImpl::Index outer) + : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) + {} + + EIGEN_STRONG_INLINE ReverseInnerIterator& operator--() + { Base::operator--(); return *this; } + + EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar value() const { return m_functor(Base::value()); } + EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar& valueRef() { return m_functor(Base::valueRef()); } + + protected: + const ViewOp m_functor; +}; + +template<typename Derived> +EIGEN_STRONG_INLINE Derived& +SparseMatrixBase<Derived>::operator*=(const Scalar& other) +{ + for (Index j=0; j<outerSize(); ++j) + for (typename Derived::InnerIterator i(derived(),j); i; ++i) + i.valueRef() *= other; + return derived(); +} + +template<typename Derived> +EIGEN_STRONG_INLINE Derived& +SparseMatrixBase<Derived>::operator/=(const Scalar& other) +{ + for (Index j=0; j<outerSize(); ++j) + for (typename Derived::InnerIterator i(derived(),j); i; ++i) + i.valueRef() /= other; + return derived(); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_CWISE_UNARY_OP_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseDenseProduct.h b/third_party/eigen3/Eigen/src/SparseCore/SparseDenseProduct.h new file mode 100644 index 0000000000..610833f3b0 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseDenseProduct.h @@ -0,0 +1,311 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2010 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_SPARSEDENSEPRODUCT_H +#define EIGEN_SPARSEDENSEPRODUCT_H + +namespace Eigen { + +template<typename Lhs, typename Rhs, int InnerSize> struct SparseDenseProductReturnType +{ + typedef SparseTimeDenseProduct<Lhs,Rhs> Type; +}; + +template<typename Lhs, typename Rhs> struct SparseDenseProductReturnType<Lhs,Rhs,1> +{ + typedef SparseDenseOuterProduct<Lhs,Rhs,false> Type; +}; + +template<typename Lhs, typename Rhs, int InnerSize> struct DenseSparseProductReturnType +{ + typedef DenseTimeSparseProduct<Lhs,Rhs> Type; +}; + +template<typename Lhs, typename Rhs> struct DenseSparseProductReturnType<Lhs,Rhs,1> +{ + typedef SparseDenseOuterProduct<Rhs,Lhs,true> Type; +}; + +namespace internal { + +template<typename Lhs, typename Rhs, bool Tr> +struct traits<SparseDenseOuterProduct<Lhs,Rhs,Tr> > +{ + typedef Sparse StorageKind; + typedef typename scalar_product_traits<typename traits<Lhs>::Scalar, + typename traits<Rhs>::Scalar>::ReturnType Scalar; + typedef typename Lhs::Index Index; + typedef typename Lhs::Nested LhsNested; + typedef typename Rhs::Nested RhsNested; + typedef typename remove_all<LhsNested>::type _LhsNested; + typedef typename remove_all<RhsNested>::type _RhsNested; + + enum { + LhsCoeffReadCost = traits<_LhsNested>::CoeffReadCost, + RhsCoeffReadCost = traits<_RhsNested>::CoeffReadCost, + + RowsAtCompileTime = Tr ? int(traits<Rhs>::RowsAtCompileTime) : int(traits<Lhs>::RowsAtCompileTime), + ColsAtCompileTime = Tr ? int(traits<Lhs>::ColsAtCompileTime) : int(traits<Rhs>::ColsAtCompileTime), + MaxRowsAtCompileTime = Tr ? int(traits<Rhs>::MaxRowsAtCompileTime) : int(traits<Lhs>::MaxRowsAtCompileTime), + MaxColsAtCompileTime = Tr ? int(traits<Lhs>::MaxColsAtCompileTime) : int(traits<Rhs>::MaxColsAtCompileTime), + + Flags = Tr ? RowMajorBit : 0, + + CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + NumTraits<Scalar>::MulCost + }; +}; + +} // end namespace internal + +template<typename Lhs, typename Rhs, bool Tr> +class SparseDenseOuterProduct + : public SparseMatrixBase<SparseDenseOuterProduct<Lhs,Rhs,Tr> > +{ + public: + + typedef SparseMatrixBase<SparseDenseOuterProduct> Base; + EIGEN_DENSE_PUBLIC_INTERFACE(SparseDenseOuterProduct) + typedef internal::traits<SparseDenseOuterProduct> Traits; + + private: + + typedef typename Traits::LhsNested LhsNested; + typedef typename Traits::RhsNested RhsNested; + typedef typename Traits::_LhsNested _LhsNested; + typedef typename Traits::_RhsNested _RhsNested; + + public: + + class InnerIterator; + + EIGEN_STRONG_INLINE SparseDenseOuterProduct(const Lhs& lhs, const Rhs& rhs) + : m_lhs(lhs), m_rhs(rhs) + { + EIGEN_STATIC_ASSERT(!Tr,YOU_MADE_A_PROGRAMMING_MISTAKE); + } + + EIGEN_STRONG_INLINE SparseDenseOuterProduct(const Rhs& rhs, const Lhs& lhs) + : m_lhs(lhs), m_rhs(rhs) + { + EIGEN_STATIC_ASSERT(Tr,YOU_MADE_A_PROGRAMMING_MISTAKE); + } + + EIGEN_STRONG_INLINE Index rows() const { return Tr ? m_rhs.rows() : m_lhs.rows(); } + EIGEN_STRONG_INLINE Index cols() const { return Tr ? m_lhs.cols() : m_rhs.cols(); } + + EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; } + EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; } + + protected: + LhsNested m_lhs; + RhsNested m_rhs; +}; + +template<typename Lhs, typename Rhs, bool Transpose> +class SparseDenseOuterProduct<Lhs,Rhs,Transpose>::InnerIterator : public _LhsNested::InnerIterator +{ + typedef typename _LhsNested::InnerIterator Base; + typedef typename SparseDenseOuterProduct::Index Index; + public: + EIGEN_STRONG_INLINE InnerIterator(const SparseDenseOuterProduct& prod, Index outer) + : Base(prod.lhs(), 0), m_outer(outer), m_factor(prod.rhs().coeff(outer)) + { + } + + inline Index outer() const { return m_outer; } + inline Index row() const { return Transpose ? Base::row() : m_outer; } + inline Index col() const { return Transpose ? m_outer : Base::row(); } + + inline Scalar value() const { return Base::value() * m_factor; } + + protected: + Index m_outer; + Scalar m_factor; +}; + +namespace internal { +template<typename Lhs, typename Rhs> +struct traits<SparseTimeDenseProduct<Lhs,Rhs> > + : traits<ProductBase<SparseTimeDenseProduct<Lhs,Rhs>, Lhs, Rhs> > +{ + typedef Dense StorageKind; + typedef MatrixXpr XprKind; +}; + +template<typename SparseLhsType, typename DenseRhsType, typename DenseResType, + typename AlphaType, + int LhsStorageOrder = ((SparseLhsType::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor, + bool ColPerCol = ((DenseRhsType::Flags&RowMajorBit)==0) || DenseRhsType::ColsAtCompileTime==1> +struct sparse_time_dense_product_impl; + +template<typename SparseLhsType, typename DenseRhsType, typename DenseResType> +struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, typename DenseResType::Scalar, RowMajor, true> +{ + typedef typename internal::remove_all<SparseLhsType>::type Lhs; + typedef typename internal::remove_all<DenseRhsType>::type Rhs; + typedef typename internal::remove_all<DenseResType>::type Res; + typedef typename Lhs::Index Index; + typedef typename Lhs::InnerIterator LhsInnerIterator; + static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha) + { + for(Index c=0; c<rhs.cols(); ++c) + { + Index n = lhs.outerSize(); + for(Index j=0; j<n; ++j) + { + typename Res::Scalar tmp(0); + for(LhsInnerIterator it(lhs,j); it ;++it) + tmp += it.value() * rhs.coeff(it.index(),c); + res.coeffRef(j,c) = alpha * tmp; + } + } + } +}; + +template<typename T1, typename T2/*, int _Options, typename _StrideType*/> +struct scalar_product_traits<T1, Ref<T2/*, _Options, _StrideType*/> > +{ + enum { + Defined = 1 + }; + typedef typename CwiseUnaryOp<scalar_multiple2_op<T1, typename T2::Scalar>, T2>::PlainObject ReturnType; +}; +template<typename SparseLhsType, typename DenseRhsType, typename DenseResType, typename AlphaType> +struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, AlphaType, ColMajor, true> +{ + typedef typename internal::remove_all<SparseLhsType>::type Lhs; + typedef typename internal::remove_all<DenseRhsType>::type Rhs; + typedef typename internal::remove_all<DenseResType>::type Res; + typedef typename Lhs::InnerIterator LhsInnerIterator; + typedef typename Lhs::Index Index; + static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha) + { + for(Index c=0; c<rhs.cols(); ++c) + { + for(Index j=0; j<lhs.outerSize(); ++j) + { +// typename Res::Scalar rhs_j = alpha * rhs.coeff(j,c); + typename internal::scalar_product_traits<AlphaType, typename Rhs::Scalar>::ReturnType rhs_j(alpha * rhs.coeff(j,c)); + for(LhsInnerIterator it(lhs,j); it ;++it) + res.coeffRef(it.index(),c) += it.value() * rhs_j; + } + } + } +}; + +template<typename SparseLhsType, typename DenseRhsType, typename DenseResType> +struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, typename DenseResType::Scalar, RowMajor, false> +{ + typedef typename internal::remove_all<SparseLhsType>::type Lhs; + typedef typename internal::remove_all<DenseRhsType>::type Rhs; + typedef typename internal::remove_all<DenseResType>::type Res; + typedef typename Lhs::InnerIterator LhsInnerIterator; + typedef typename Lhs::Index Index; + static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha) + { + for(Index j=0; j<lhs.outerSize(); ++j) + { + typename Res::RowXpr res_j(res.row(j)); + for(LhsInnerIterator it(lhs,j); it ;++it) + res_j += (alpha*it.value()) * rhs.row(it.index()); + } + } +}; + +template<typename SparseLhsType, typename DenseRhsType, typename DenseResType> +struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, typename DenseResType::Scalar, ColMajor, false> +{ + typedef typename internal::remove_all<SparseLhsType>::type Lhs; + typedef typename internal::remove_all<DenseRhsType>::type Rhs; + typedef typename internal::remove_all<DenseResType>::type Res; + typedef typename Lhs::InnerIterator LhsInnerIterator; + typedef typename Lhs::Index Index; + static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha) + { + for(Index j=0; j<lhs.outerSize(); ++j) + { + typename Rhs::ConstRowXpr rhs_j(rhs.row(j)); + for(LhsInnerIterator it(lhs,j); it ;++it) + res.row(it.index()) += (alpha*it.value()) * rhs_j; + } + } +}; + +template<typename SparseLhsType, typename DenseRhsType, typename DenseResType,typename AlphaType> +inline void sparse_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha) +{ + sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, AlphaType>::run(lhs, rhs, res, alpha); +} + +} // end namespace internal + +template<typename Lhs, typename Rhs> +class SparseTimeDenseProduct + : public ProductBase<SparseTimeDenseProduct<Lhs,Rhs>, Lhs, Rhs> +{ + public: + EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseTimeDenseProduct) + + SparseTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) + {} + + template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const + { + internal::sparse_time_dense_product(m_lhs, m_rhs, dest, alpha); + } + + private: + SparseTimeDenseProduct& operator=(const SparseTimeDenseProduct&); +}; + + +// dense = dense * sparse +namespace internal { +template<typename Lhs, typename Rhs> +struct traits<DenseTimeSparseProduct<Lhs,Rhs> > + : traits<ProductBase<DenseTimeSparseProduct<Lhs,Rhs>, Lhs, Rhs> > +{ + typedef Dense StorageKind; +}; +} // end namespace internal + +template<typename Lhs, typename Rhs> +class DenseTimeSparseProduct + : public ProductBase<DenseTimeSparseProduct<Lhs,Rhs>, Lhs, Rhs> +{ + public: + EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseProduct) + + DenseTimeSparseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) + {} + + template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const + { + Transpose<const _LhsNested> lhs_t(m_lhs); + Transpose<const _RhsNested> rhs_t(m_rhs); + Transpose<Dest> dest_t(dest); + internal::sparse_time_dense_product(rhs_t, lhs_t, dest_t, alpha); + } + + private: + DenseTimeSparseProduct& operator=(const DenseTimeSparseProduct&); +}; + +// sparse * dense +template<typename Derived> +template<typename OtherDerived> +inline const typename SparseDenseProductReturnType<Derived,OtherDerived>::Type +SparseMatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const +{ + return typename SparseDenseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSEDENSEPRODUCT_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseDiagonalProduct.h b/third_party/eigen3/Eigen/src/SparseCore/SparseDiagonalProduct.h new file mode 100644 index 0000000000..1bb590e64d --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseDiagonalProduct.h @@ -0,0 +1,196 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 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_SPARSE_DIAGONAL_PRODUCT_H +#define EIGEN_SPARSE_DIAGONAL_PRODUCT_H + +namespace Eigen { + +// The product of a diagonal matrix with a sparse matrix can be easily +// implemented using expression template. +// We have two consider very different cases: +// 1 - diag * row-major sparse +// => each inner vector <=> scalar * sparse vector product +// => so we can reuse CwiseUnaryOp::InnerIterator +// 2 - diag * col-major sparse +// => each inner vector <=> densevector * sparse vector cwise product +// => again, we can reuse specialization of CwiseBinaryOp::InnerIterator +// for that particular case +// The two other cases are symmetric. + +namespace internal { + +template<typename Lhs, typename Rhs> +struct traits<SparseDiagonalProduct<Lhs, Rhs> > +{ + typedef typename remove_all<Lhs>::type _Lhs; + typedef typename remove_all<Rhs>::type _Rhs; + typedef typename _Lhs::Scalar Scalar; + typedef typename promote_index_type<typename traits<Lhs>::Index, + typename traits<Rhs>::Index>::type Index; + typedef Sparse StorageKind; + typedef MatrixXpr XprKind; + enum { + RowsAtCompileTime = _Lhs::RowsAtCompileTime, + ColsAtCompileTime = _Rhs::ColsAtCompileTime, + + MaxRowsAtCompileTime = _Lhs::MaxRowsAtCompileTime, + MaxColsAtCompileTime = _Rhs::MaxColsAtCompileTime, + + SparseFlags = is_diagonal<_Lhs>::ret ? int(_Rhs::Flags) : int(_Lhs::Flags), + Flags = (SparseFlags&RowMajorBit), + CoeffReadCost = Dynamic + }; +}; + +enum {SDP_IsDiagonal, SDP_IsSparseRowMajor, SDP_IsSparseColMajor}; +template<typename Lhs, typename Rhs, typename SparseDiagonalProductType, int RhsMode, int LhsMode> +class sparse_diagonal_product_inner_iterator_selector; + +} // end namespace internal + +template<typename Lhs, typename Rhs> +class SparseDiagonalProduct + : public SparseMatrixBase<SparseDiagonalProduct<Lhs,Rhs> >, + internal::no_assignment_operator +{ + typedef typename Lhs::Nested LhsNested; + typedef typename Rhs::Nested RhsNested; + + typedef typename internal::remove_all<LhsNested>::type _LhsNested; + typedef typename internal::remove_all<RhsNested>::type _RhsNested; + + enum { + LhsMode = internal::is_diagonal<_LhsNested>::ret ? internal::SDP_IsDiagonal + : (_LhsNested::Flags&RowMajorBit) ? internal::SDP_IsSparseRowMajor : internal::SDP_IsSparseColMajor, + RhsMode = internal::is_diagonal<_RhsNested>::ret ? internal::SDP_IsDiagonal + : (_RhsNested::Flags&RowMajorBit) ? internal::SDP_IsSparseRowMajor : internal::SDP_IsSparseColMajor + }; + + public: + + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseDiagonalProduct) + + typedef internal::sparse_diagonal_product_inner_iterator_selector + <_LhsNested,_RhsNested,SparseDiagonalProduct,LhsMode,RhsMode> InnerIterator; + + // We do not want ReverseInnerIterator for diagonal-sparse products, + // but this dummy declaration is needed to make diag * sparse * diag compile. + class ReverseInnerIterator; + + EIGEN_STRONG_INLINE SparseDiagonalProduct(const Lhs& lhs, const Rhs& rhs) + : m_lhs(lhs), m_rhs(rhs) + { + eigen_assert(lhs.cols() == rhs.rows() && "invalid sparse matrix * diagonal matrix product"); + } + + EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); } + EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); } + + EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; } + EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; } + + protected: + LhsNested m_lhs; + RhsNested m_rhs; +}; + +namespace internal { + +template<typename Lhs, typename Rhs, typename SparseDiagonalProductType> +class sparse_diagonal_product_inner_iterator_selector +<Lhs,Rhs,SparseDiagonalProductType,SDP_IsDiagonal,SDP_IsSparseRowMajor> + : public CwiseUnaryOp<scalar_multiple_op<typename Lhs::Scalar>,const Rhs>::InnerIterator +{ + typedef typename CwiseUnaryOp<scalar_multiple_op<typename Lhs::Scalar>,const Rhs>::InnerIterator Base; + typedef typename Lhs::Index Index; + public: + inline sparse_diagonal_product_inner_iterator_selector( + const SparseDiagonalProductType& expr, Index outer) + : Base(expr.rhs()*(expr.lhs().diagonal().coeff(outer)), outer) + {} +}; + +template<typename Lhs, typename Rhs, typename SparseDiagonalProductType> +class sparse_diagonal_product_inner_iterator_selector +<Lhs,Rhs,SparseDiagonalProductType,SDP_IsDiagonal,SDP_IsSparseColMajor> + : public CwiseBinaryOp< + scalar_product_op<typename Lhs::Scalar>, + const typename Rhs::ConstInnerVectorReturnType, + const typename Lhs::DiagonalVectorType>::InnerIterator +{ + typedef typename CwiseBinaryOp< + scalar_product_op<typename Lhs::Scalar>, + const typename Rhs::ConstInnerVectorReturnType, + const typename Lhs::DiagonalVectorType>::InnerIterator Base; + typedef typename Lhs::Index Index; + Index m_outer; + public: + inline sparse_diagonal_product_inner_iterator_selector( + const SparseDiagonalProductType& expr, Index outer) + : Base(expr.rhs().innerVector(outer) .cwiseProduct(expr.lhs().diagonal()), 0), m_outer(outer) + {} + + inline Index outer() const { return m_outer; } + inline Index col() const { return m_outer; } +}; + +template<typename Lhs, typename Rhs, typename SparseDiagonalProductType> +class sparse_diagonal_product_inner_iterator_selector +<Lhs,Rhs,SparseDiagonalProductType,SDP_IsSparseColMajor,SDP_IsDiagonal> + : public CwiseUnaryOp<scalar_multiple_op<typename Rhs::Scalar>,const Lhs>::InnerIterator +{ + typedef typename CwiseUnaryOp<scalar_multiple_op<typename Rhs::Scalar>,const Lhs>::InnerIterator Base; + typedef typename Lhs::Index Index; + public: + inline sparse_diagonal_product_inner_iterator_selector( + const SparseDiagonalProductType& expr, Index outer) + : Base(expr.lhs()*expr.rhs().diagonal().coeff(outer), outer) + {} +}; + +template<typename Lhs, typename Rhs, typename SparseDiagonalProductType> +class sparse_diagonal_product_inner_iterator_selector +<Lhs,Rhs,SparseDiagonalProductType,SDP_IsSparseRowMajor,SDP_IsDiagonal> + : public CwiseBinaryOp< + scalar_product_op<typename Rhs::Scalar>, + const typename Lhs::ConstInnerVectorReturnType, + const Transpose<const typename Rhs::DiagonalVectorType> >::InnerIterator +{ + typedef typename CwiseBinaryOp< + scalar_product_op<typename Rhs::Scalar>, + const typename Lhs::ConstInnerVectorReturnType, + const Transpose<const typename Rhs::DiagonalVectorType> >::InnerIterator Base; + typedef typename Lhs::Index Index; + Index m_outer; + public: + inline sparse_diagonal_product_inner_iterator_selector( + const SparseDiagonalProductType& expr, Index outer) + : Base(expr.lhs().innerVector(outer) .cwiseProduct(expr.rhs().diagonal().transpose()), 0), m_outer(outer) + {} + + inline Index outer() const { return m_outer; } + inline Index row() const { return m_outer; } +}; + +} // end namespace internal + +// SparseMatrixBase functions + +template<typename Derived> +template<typename OtherDerived> +const SparseDiagonalProduct<Derived,OtherDerived> +SparseMatrixBase<Derived>::operator*(const DiagonalBase<OtherDerived> &other) const +{ + return SparseDiagonalProduct<Derived,OtherDerived>(this->derived(), other.derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_DIAGONAL_PRODUCT_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseDot.h b/third_party/eigen3/Eigen/src/SparseCore/SparseDot.h new file mode 100644 index 0000000000..db39c9aecc --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseDot.h @@ -0,0 +1,101 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_SPARSE_DOT_H +#define EIGEN_SPARSE_DOT_H + +namespace Eigen { + +template<typename Derived> +template<typename OtherDerived> +typename internal::traits<Derived>::Scalar +SparseMatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const +{ + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived) + EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + + eigen_assert(size() == other.size()); + eigen_assert(other.size()>0 && "you are using a non initialized vector"); + + typename Derived::InnerIterator i(derived(),0); + Scalar res(0); + while (i) + { + res += numext::conj(i.value()) * other.coeff(i.index()); + ++i; + } + return res; +} + +template<typename Derived> +template<typename OtherDerived> +typename internal::traits<Derived>::Scalar +SparseMatrixBase<Derived>::dot(const SparseMatrixBase<OtherDerived>& other) const +{ + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived) + EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + + eigen_assert(size() == other.size()); + + typedef typename Derived::Nested Nested; + typedef typename OtherDerived::Nested OtherNested; + typedef typename internal::remove_all<Nested>::type NestedCleaned; + typedef typename internal::remove_all<OtherNested>::type OtherNestedCleaned; + + Nested nthis(derived()); + OtherNested nother(other.derived()); + + typename NestedCleaned::InnerIterator i(nthis,0); + typename OtherNestedCleaned::InnerIterator j(nother,0); + Scalar res(0); + while (i && j) + { + if (i.index()==j.index()) + { + res += numext::conj(i.value()) * j.value(); + ++i; ++j; + } + else if (i.index()<j.index()) + ++i; + else + ++j; + } + return res; +} + +template<typename Derived> +inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real +SparseMatrixBase<Derived>::squaredNorm() const +{ + return numext::real((*this).cwiseAbs2().sum()); +} + +template<typename Derived> +inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real +SparseMatrixBase<Derived>::norm() const +{ + using std::sqrt; + return sqrt(squaredNorm()); +} + +template<typename Derived> +inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real +SparseMatrixBase<Derived>::blueNorm() const +{ + return internal::blueNorm_impl(*this); +} +} // end namespace Eigen + +#endif // EIGEN_SPARSE_DOT_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseFuzzy.h b/third_party/eigen3/Eigen/src/SparseCore/SparseFuzzy.h new file mode 100644 index 0000000000..45f36e9eb9 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseFuzzy.h @@ -0,0 +1,26 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_SPARSE_FUZZY_H +#define EIGEN_SPARSE_FUZZY_H + +// template<typename Derived> +// template<typename OtherDerived> +// bool SparseMatrixBase<Derived>::isApprox( +// const OtherDerived& other, +// typename NumTraits<Scalar>::Real prec +// ) const +// { +// const typename internal::nested<Derived,2>::type nested(derived()); +// const typename internal::nested<OtherDerived,2>::type otherNested(other.derived()); +// return (nested - otherNested).cwise().abs2().sum() +// <= prec * prec * (std::min)(nested.cwise().abs2().sum(), otherNested.cwise().abs2().sum()); +// } + +#endif // EIGEN_SPARSE_FUZZY_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseMatrix.h b/third_party/eigen3/Eigen/src/SparseCore/SparseMatrix.h new file mode 100644 index 0000000000..5070c81d9f --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseMatrix.h @@ -0,0 +1,1259 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2010 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_SPARSEMATRIX_H +#define EIGEN_SPARSEMATRIX_H + +namespace Eigen { + +/** \ingroup SparseCore_Module + * + * \class SparseMatrix + * + * \brief A versatible sparse matrix representation + * + * This class implements a more versatile variants of the common \em compressed row/column storage format. + * Each colmun's (resp. row) non zeros are stored as a pair of value with associated row (resp. colmiun) index. + * All the non zeros are stored in a single large buffer. Unlike the \em compressed format, there might be extra + * space inbetween the nonzeros of two successive colmuns (resp. rows) such that insertion of new non-zero + * can be done with limited memory reallocation and copies. + * + * A call to the function makeCompressed() turns the matrix into the standard \em compressed format + * compatible with many library. + * + * More details on this storage sceheme are given in the \ref TutorialSparse "manual pages". + * + * \tparam _Scalar the scalar type, i.e. the type of the coefficients + * \tparam _Options Union of bit flags controlling the storage scheme. Currently the only possibility + * is ColMajor or RowMajor. The default is 0 which means column-major. + * \tparam _Index the type of the indices. It has to be a \b signed type (e.g., short, int, std::ptrdiff_t). Default is \c int. + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIX_PLUGIN. + */ + +namespace internal { +template<typename _Scalar, int _Options, typename _Index> +struct traits<SparseMatrix<_Scalar, _Options, _Index> > +{ + typedef _Scalar Scalar; + typedef _Index Index; + typedef Sparse StorageKind; + typedef MatrixXpr XprKind; + enum { + RowsAtCompileTime = Dynamic, + ColsAtCompileTime = Dynamic, + MaxRowsAtCompileTime = Dynamic, + MaxColsAtCompileTime = Dynamic, + Flags = _Options | NestByRefBit | LvalueBit, + CoeffReadCost = NumTraits<Scalar>::ReadCost, + SupportedAccessPatterns = InnerRandomAccessPattern + }; +}; + +template<typename _Scalar, int _Options, typename _Index, int DiagIndex> +struct traits<Diagonal<const SparseMatrix<_Scalar, _Options, _Index>, DiagIndex> > +{ + typedef SparseMatrix<_Scalar, _Options, _Index> MatrixType; + typedef typename nested<MatrixType>::type MatrixTypeNested; + typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested; + + typedef _Scalar Scalar; + typedef Dense StorageKind; + typedef _Index Index; + typedef MatrixXpr XprKind; + + enum { + RowsAtCompileTime = Dynamic, + ColsAtCompileTime = 1, + MaxRowsAtCompileTime = Dynamic, + MaxColsAtCompileTime = 1, + Flags = 0, + CoeffReadCost = _MatrixTypeNested::CoeffReadCost*10 + }; +}; + +} // end namespace internal + +template<typename _Scalar, int _Options, typename _Index> +class SparseMatrix + : public SparseMatrixBase<SparseMatrix<_Scalar, _Options, _Index> > +{ + public: + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=) + + typedef MappedSparseMatrix<Scalar,Flags> Map; + using Base::IsRowMajor; + typedef internal::CompressedStorage<Scalar,Index> Storage; + enum { + Options = _Options + }; + + protected: + + typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix; + + Index m_outerSize; + Index m_innerSize; + Index* m_outerIndex; + Index* m_innerNonZeros; // optional, if null then the data is compressed + Storage m_data; + + Eigen::Map<Matrix<Index,Dynamic,1> > innerNonZeros() { return Eigen::Map<Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); } + const Eigen::Map<const Matrix<Index,Dynamic,1> > innerNonZeros() const { return Eigen::Map<const Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); } + + public: + + /** \returns whether \c *this is in compressed form. */ + inline bool isCompressed() const { return m_innerNonZeros==0; } + + /** \returns the number of rows of the matrix */ + inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; } + /** \returns the number of columns of the matrix */ + inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; } + + /** \returns the number of rows (resp. columns) of the matrix if the storage order column major (resp. row major) */ + inline Index innerSize() const { return m_innerSize; } + /** \returns the number of columns (resp. rows) of the matrix if the storage order column major (resp. row major) */ + inline Index outerSize() const { return m_outerSize; } + + /** \returns a const pointer to the array of values. + * This function is aimed at interoperability with other libraries. + * \sa innerIndexPtr(), outerIndexPtr() */ + inline const Scalar* valuePtr() const { return &m_data.value(0); } + /** \returns a non-const pointer to the array of values. + * This function is aimed at interoperability with other libraries. + * \sa innerIndexPtr(), outerIndexPtr() */ + inline Scalar* valuePtr() { return &m_data.value(0); } + + /** \returns a const pointer to the array of inner indices. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), outerIndexPtr() */ + inline const Index* innerIndexPtr() const { return &m_data.index(0); } + /** \returns a non-const pointer to the array of inner indices. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), outerIndexPtr() */ + inline Index* innerIndexPtr() { return &m_data.index(0); } + + /** \returns a const pointer to the array of the starting positions of the inner vectors. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), innerIndexPtr() */ + inline const Index* outerIndexPtr() const { return m_outerIndex; } + /** \returns a non-const pointer to the array of the starting positions of the inner vectors. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), innerIndexPtr() */ + inline Index* outerIndexPtr() { return m_outerIndex; } + + /** \returns a const pointer to the array of the number of non zeros of the inner vectors. + * This function is aimed at interoperability with other libraries. + * \warning it returns the null pointer 0 in compressed mode */ + inline const Index* innerNonZeroPtr() const { return m_innerNonZeros; } + /** \returns a non-const pointer to the array of the number of non zeros of the inner vectors. + * This function is aimed at interoperability with other libraries. + * \warning it returns the null pointer 0 in compressed mode */ + inline Index* innerNonZeroPtr() { return m_innerNonZeros; } + + /** \internal */ + inline Storage& data() { return m_data; } + /** \internal */ + inline const Storage& data() const { return m_data; } + + /** \returns the value of the matrix at position \a i, \a j + * This function returns Scalar(0) if the element is an explicit \em zero */ + inline Scalar coeff(Index row, Index col) const + { + eigen_assert(row>=0 && row<rows() && col>=0 && col<cols()); + + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1]; + return m_data.atInRange(m_outerIndex[outer], end, inner); + } + + /** \returns a non-const reference to the value of the matrix at position \a i, \a j + * + * If the element does not exist then it is inserted via the insert(Index,Index) function + * which itself turns the matrix into a non compressed form if that was not the case. + * + * This is a O(log(nnz_j)) operation (binary search) plus the cost of insert(Index,Index) + * function if the element does not already exist. + */ + inline Scalar& coeffRef(Index row, Index col) + { + eigen_assert(row>=0 && row<rows() && col>=0 && col<cols()); + + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + Index start = m_outerIndex[outer]; + Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1]; + eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix"); + if(end<=start) + return insert(row,col); + const Index p = m_data.searchLowerIndex(start,end-1,inner); + if((p<end) && (m_data.index(p)==inner)) + return m_data.value(p); + else + return insert(row,col); + } + + /** \returns a reference to a novel non zero coefficient with coordinates \a row x \a col. + * The non zero coefficient must \b not already exist. + * + * If the matrix \c *this is in compressed mode, then \c *this is turned into uncompressed + * mode while reserving room for 2 non zeros per inner vector. It is strongly recommended to first + * call reserve(const SizesType &) to reserve a more appropriate number of elements per + * inner vector that better match your scenario. + * + * This function performs a sorted insertion in O(1) if the elements of each inner vector are + * inserted in increasing inner index order, and in O(nnz_j) for a random insertion. + * + */ + Scalar& insert(Index row, Index col) + { + eigen_assert(row>=0 && row<rows() && col>=0 && col<cols()); + + if(isCompressed()) + { + reserve(Matrix<Index,Dynamic,1>::Constant(outerSize(), 2)); + } + return insertUncompressed(row,col); + } + + public: + + class InnerIterator; + class ReverseInnerIterator; + + /** Removes all non zeros but keep allocated memory */ + inline void setZero() + { + m_data.clear(); + memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index)); + if(m_innerNonZeros) + memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(Index)); + } + + /** \returns the number of non zero coefficients */ + inline Index nonZeros() const + { + if(m_innerNonZeros) + return innerNonZeros().sum(); + return static_cast<Index>(m_data.size()); + } + + /** Preallocates \a reserveSize non zeros. + * + * Precondition: the matrix must be in compressed mode. */ + inline void reserve(Index reserveSize) + { + eigen_assert(isCompressed() && "This function does not make sense in non compressed mode."); + m_data.reserve(reserveSize); + } + + #ifdef EIGEN_PARSED_BY_DOXYGEN + /** Preallocates \a reserveSize[\c j] non zeros for each column (resp. row) \c j. + * + * This function turns the matrix in non-compressed mode */ + template<class SizesType> + inline void reserve(const SizesType& reserveSizes); + #else + template<class SizesType> + inline void reserve(const SizesType& reserveSizes, const typename SizesType::value_type& enableif = typename SizesType::value_type()) + { + EIGEN_UNUSED_VARIABLE(enableif); + reserveInnerVectors(reserveSizes); + } + template<class SizesType> + inline void reserve(const SizesType& reserveSizes, const typename SizesType::Scalar& enableif = + #if (!EIGEN_COMP_MSVC) || (EIGEN_COMP_MSVC>=1500) // MSVC 2005 fails to compile with this typename + typename + #endif + SizesType::Scalar()) + { + EIGEN_UNUSED_VARIABLE(enableif); + reserveInnerVectors(reserveSizes); + } + #endif // EIGEN_PARSED_BY_DOXYGEN + protected: + template<class SizesType> + inline void reserveInnerVectors(const SizesType& reserveSizes) + { + if(isCompressed()) + { + std::size_t totalReserveSize = 0; + // turn the matrix into non-compressed mode + m_innerNonZeros = static_cast<Index*>(std::malloc(m_outerSize * sizeof(Index))); + if (!m_innerNonZeros) internal::throw_std_bad_alloc(); + + // temporarily use m_innerSizes to hold the new starting points. + Index* newOuterIndex = m_innerNonZeros; + + Index count = 0; + for(Index j=0; j<m_outerSize; ++j) + { + newOuterIndex[j] = count; + count += reserveSizes[j] + (m_outerIndex[j+1]-m_outerIndex[j]); + totalReserveSize += reserveSizes[j]; + } + m_data.reserve(totalReserveSize); + Index previousOuterIndex = m_outerIndex[m_outerSize]; + for(Index j=m_outerSize-1; j>=0; --j) + { + Index innerNNZ = previousOuterIndex - m_outerIndex[j]; + for(Index i=innerNNZ-1; i>=0; --i) + { + m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i); + m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i); + } + previousOuterIndex = m_outerIndex[j]; + m_outerIndex[j] = newOuterIndex[j]; + m_innerNonZeros[j] = innerNNZ; + } + m_outerIndex[m_outerSize] = m_outerIndex[m_outerSize-1] + m_innerNonZeros[m_outerSize-1] + reserveSizes[m_outerSize-1]; + + m_data.resize(m_outerIndex[m_outerSize]); + } + else + { + Index* newOuterIndex = static_cast<Index*>(std::malloc((m_outerSize+1)*sizeof(Index))); + if (!newOuterIndex) internal::throw_std_bad_alloc(); + + Index count = 0; + for(Index j=0; j<m_outerSize; ++j) + { + newOuterIndex[j] = count; + Index alreadyReserved = (m_outerIndex[j+1]-m_outerIndex[j]) - m_innerNonZeros[j]; + Index toReserve = std::max<Index>(reserveSizes[j], alreadyReserved); + count += toReserve + m_innerNonZeros[j]; + } + newOuterIndex[m_outerSize] = count; + + m_data.resize(count); + for(Index j=m_outerSize-1; j>=0; --j) + { + Index offset = newOuterIndex[j] - m_outerIndex[j]; + if(offset>0) + { + Index innerNNZ = m_innerNonZeros[j]; + for(Index i=innerNNZ-1; i>=0; --i) + { + m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i); + m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i); + } + } + } + + std::swap(m_outerIndex, newOuterIndex); + std::free(newOuterIndex); + } + + } + public: + + //--- low level purely coherent filling --- + + /** \internal + * \returns a reference to the non zero coefficient at position \a row, \a col assuming that: + * - the nonzero does not already exist + * - the new coefficient is the last one according to the storage order + * + * Before filling a given inner vector you must call the statVec(Index) function. + * + * After an insertion session, you should call the finalize() function. + * + * \sa insert, insertBackByOuterInner, startVec */ + inline Scalar& insertBack(Index row, Index col) + { + return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row); + } + + /** \internal + * \sa insertBack, startVec */ + inline Scalar& insertBackByOuterInner(Index outer, Index inner) + { + eigen_assert(size_t(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)"); + eigen_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)<inner) && "Invalid ordered insertion (invalid inner index)"); + Index p = m_outerIndex[outer+1]; + ++m_outerIndex[outer+1]; + m_data.append(Scalar(0), inner); + return m_data.value(p); + } + + /** \internal + * \warning use it only if you know what you are doing */ + inline Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner) + { + Index p = m_outerIndex[outer+1]; + ++m_outerIndex[outer+1]; + m_data.append(Scalar(0), inner); + return m_data.value(p); + } + + /** \internal + * \sa insertBack, insertBackByOuterInner */ + inline void startVec(Index outer) + { + eigen_assert(m_outerIndex[outer]==Index(m_data.size()) && "You must call startVec for each inner vector sequentially"); + eigen_assert(m_outerIndex[outer+1]==0 && "You must call startVec for each inner vector sequentially"); + m_outerIndex[outer+1] = m_outerIndex[outer]; + } + + /** \internal + * Must be called after inserting a set of non zero entries using the low level compressed API. + */ + inline void finalize() + { + if(isCompressed()) + { + Index size = static_cast<Index>(m_data.size()); + Index i = m_outerSize; + // find the last filled column + while (i>=0 && m_outerIndex[i]==0) + --i; + ++i; + while (i<=m_outerSize) + { + m_outerIndex[i] = size; + ++i; + } + } + } + + //--- + + template<typename InputIterators> + void setFromTriplets(const InputIterators& begin, const InputIterators& end); + + void sumupDuplicates(); + + //--- + + /** \internal + * same as insert(Index,Index) except that the indices are given relative to the storage order */ + Scalar& insertByOuterInner(Index j, Index i) + { + return insert(IsRowMajor ? j : i, IsRowMajor ? i : j); + } + + /** Turns the matrix into the \em compressed format. + */ + void makeCompressed() + { + if(isCompressed()) + return; + + Index oldStart = m_outerIndex[1]; + m_outerIndex[1] = m_innerNonZeros[0]; + for(Index j=1; j<m_outerSize; ++j) + { + Index nextOldStart = m_outerIndex[j+1]; + Index offset = oldStart - m_outerIndex[j]; + if(offset>0) + { + for(Index k=0; k<m_innerNonZeros[j]; ++k) + { + m_data.index(m_outerIndex[j]+k) = m_data.index(oldStart+k); + m_data.value(m_outerIndex[j]+k) = m_data.value(oldStart+k); + } + } + m_outerIndex[j+1] = m_outerIndex[j] + m_innerNonZeros[j]; + oldStart = nextOldStart; + } + std::free(m_innerNonZeros); + m_innerNonZeros = 0; + m_data.resize(m_outerIndex[m_outerSize]); + m_data.squeeze(); + } + + /** Turns the matrix into the uncompressed mode */ + void uncompress() + { + if(m_innerNonZeros != 0) + return; + m_innerNonZeros = static_cast<Index*>(std::malloc(m_outerSize * sizeof(Index))); + for (Index i = 0; i < m_outerSize; i++) + { + m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i]; + } + } + + /** Suppresses all nonzeros which are \b much \b smaller \b than \a reference under the tolerence \a epsilon */ + void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) + { + prune(default_prunning_func(reference,epsilon)); + } + + /** Turns the matrix into compressed format, and suppresses all nonzeros which do not satisfy the predicate \a keep. + * The functor type \a KeepFunc must implement the following function: + * \code + * bool operator() (const Index& row, const Index& col, const Scalar& value) const; + * \endcode + * \sa prune(Scalar,RealScalar) + */ + template<typename KeepFunc> + void prune(const KeepFunc& keep = KeepFunc()) + { + // TODO optimize the uncompressed mode to avoid moving and allocating the data twice + // TODO also implement a unit test + makeCompressed(); + + Index k = 0; + for(Index j=0; j<m_outerSize; ++j) + { + Index previousStart = m_outerIndex[j]; + m_outerIndex[j] = k; + Index end = m_outerIndex[j+1]; + for(Index i=previousStart; i<end; ++i) + { + if(keep(IsRowMajor?j:m_data.index(i), IsRowMajor?m_data.index(i):j, m_data.value(i))) + { + m_data.value(k) = m_data.value(i); + m_data.index(k) = m_data.index(i); + ++k; + } + } + } + m_outerIndex[m_outerSize] = k; + m_data.resize(k,0); + } + + /** Resizes the matrix to a \a rows x \a cols matrix leaving old values untouched. + * \sa resizeNonZeros(Index), reserve(), setZero() + */ + void conservativeResize(Index rows, Index cols) + { + // No change + if (this->rows() == rows && this->cols() == cols) return; + + // If one dimension is null, then there is nothing to be preserved + if(rows==0 || cols==0) return resize(rows,cols); + + Index innerChange = IsRowMajor ? cols - this->cols() : rows - this->rows(); + Index outerChange = IsRowMajor ? rows - this->rows() : cols - this->cols(); + Index newInnerSize = IsRowMajor ? cols : rows; + + // Deals with inner non zeros + if (m_innerNonZeros) + { + // Resize m_innerNonZeros + Index *newInnerNonZeros = static_cast<Index*>(std::realloc(m_innerNonZeros, (m_outerSize + outerChange) * sizeof(Index))); + if (!newInnerNonZeros) internal::throw_std_bad_alloc(); + m_innerNonZeros = newInnerNonZeros; + + for(Index i=m_outerSize; i<m_outerSize+outerChange; i++) + m_innerNonZeros[i] = 0; + } + else if (innerChange < 0) + { + // Inner size decreased: allocate a new m_innerNonZeros + m_innerNonZeros = static_cast<Index*>(std::malloc((m_outerSize+outerChange+1) * sizeof(Index))); + if (!m_innerNonZeros) internal::throw_std_bad_alloc(); + for(Index i = 0; i < m_outerSize; i++) + m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i]; + } + + // Change the m_innerNonZeros in case of a decrease of inner size + if (m_innerNonZeros && innerChange < 0) + { + for(Index i = 0; i < m_outerSize + (std::min)(outerChange, Index(0)); i++) + { + Index &n = m_innerNonZeros[i]; + Index start = m_outerIndex[i]; + while (n > 0 && m_data.index(start+n-1) >= newInnerSize) --n; + } + } + + m_innerSize = newInnerSize; + + // Re-allocate outer index structure if necessary + if (outerChange == 0) + return; + + Index *newOuterIndex = static_cast<Index*>(std::realloc(m_outerIndex, (m_outerSize + outerChange + 1) * sizeof(Index))); + if (!newOuterIndex) internal::throw_std_bad_alloc(); + m_outerIndex = newOuterIndex; + if (outerChange > 0) + { + Index last = m_outerSize == 0 ? 0 : m_outerIndex[m_outerSize]; + for(Index i=m_outerSize; i<m_outerSize+outerChange+1; i++) + m_outerIndex[i] = last; + } + m_outerSize += outerChange; + } + + /** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero. + * \sa resizeNonZeros(Index), reserve(), setZero() + */ + void resize(Index rows, Index cols) + { + const Index outerSize = IsRowMajor ? rows : cols; + m_innerSize = IsRowMajor ? cols : rows; + m_data.clear(); + if (m_outerSize != outerSize || m_outerSize==0) + { + std::free(m_outerIndex); + m_outerIndex = static_cast<Index*>(std::malloc((outerSize + 1) * sizeof(Index))); + if (!m_outerIndex) internal::throw_std_bad_alloc(); + + m_outerSize = outerSize; + } + if(m_innerNonZeros) + { + std::free(m_innerNonZeros); + m_innerNonZeros = 0; + } + memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index)); + } + + /** \internal + * Resize the nonzero vector to \a size */ + void resizeNonZeros(Index size) + { + // TODO remove this function + m_data.resize(size); + } + + /** \returns a const expression of the diagonal coefficients */ + const Diagonal<const SparseMatrix> diagonal() const { return *this; } + + /** Default constructor yielding an empty \c 0 \c x \c 0 matrix */ + inline SparseMatrix() + : m_outerSize(-1), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + resize(0, 0); + } + + /** Constructs a \a rows \c x \a cols empty matrix */ + inline SparseMatrix(Index rows, Index cols) + : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + resize(rows, cols); + } + + /** Constructs a sparse matrix from the sparse expression \a other */ + template<typename OtherDerived> + inline SparseMatrix(const SparseMatrixBase<OtherDerived>& other) + : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + check_template_parameters(); + *this = other.derived(); + } + + /** Constructs a sparse matrix from the sparse selfadjoint view \a other */ + template<typename OtherDerived, unsigned int UpLo> + inline SparseMatrix(const SparseSelfAdjointView<OtherDerived, UpLo>& other) + : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + *this = other; + } + + /** Copy constructor (it performs a deep copy) */ + inline SparseMatrix(const SparseMatrix& other) + : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + *this = other.derived(); + } + + /** \brief Copy constructor with in-place evaluation */ + template<typename OtherDerived> + SparseMatrix(const ReturnByValue<OtherDerived>& other) + : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + initAssignment(other); + other.evalTo(*this); + } + + /** Swaps the content of two sparse matrices of the same type. + * This is a fast operation that simply swaps the underlying pointers and parameters. */ + inline void swap(SparseMatrix& other) + { + //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n"); + std::swap(m_outerIndex, other.m_outerIndex); + std::swap(m_innerSize, other.m_innerSize); + std::swap(m_outerSize, other.m_outerSize); + std::swap(m_innerNonZeros, other.m_innerNonZeros); + m_data.swap(other.m_data); + } + + /** Sets *this to the identity matrix */ + inline void setIdentity() + { + eigen_assert(rows() == cols() && "ONLY FOR SQUARED MATRICES"); + this->m_data.resize(rows()); + Eigen::Map<Matrix<Index, Dynamic, 1> >(&this->m_data.index(0), rows()).setLinSpaced(0, rows()-1); + Eigen::Map<Matrix<Scalar, Dynamic, 1> >(&this->m_data.value(0), rows()).setOnes(); + Eigen::Map<Matrix<Index, Dynamic, 1> >(this->m_outerIndex, rows()+1).setLinSpaced(0, rows()); + } + inline SparseMatrix& operator=(const SparseMatrix& other) + { + if (other.isRValue()) + { + swap(other.const_cast_derived()); + } + else if(this!=&other) + { + initAssignment(other); + if(other.isCompressed()) + { + internal::smart_copy(other.m_outerIndex, other.m_outerIndex + m_outerSize + 1, m_outerIndex); + m_data = other.m_data; + } + else + { + Base::operator=(other); + } + } + return *this; + } + + #ifndef EIGEN_PARSED_BY_DOXYGEN + template<typename Lhs, typename Rhs> + inline SparseMatrix& operator=(const SparseSparseProduct<Lhs,Rhs>& product) + { return Base::operator=(product); } + + template<typename OtherDerived> + inline SparseMatrix& operator=(const ReturnByValue<OtherDerived>& other) + { + initAssignment(other); + return Base::operator=(other.derived()); + } + + template<typename OtherDerived> + inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other) + { return Base::operator=(other.derived()); } + #endif + + template<typename OtherDerived> + EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other); + + friend std::ostream & operator << (std::ostream & s, const SparseMatrix& m) + { + EIGEN_DBG_SPARSE( + s << "Nonzero entries:\n"; + if(m.isCompressed()) + for (Index i=0; i<m.nonZeros(); ++i) + s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") "; + else + for (Index i=0; i<m.outerSize(); ++i) + { + Index p = m.m_outerIndex[i]; + Index pe = m.m_outerIndex[i]+m.m_innerNonZeros[i]; + Index k=p; + for (; k<pe; ++k) + s << "(" << m.m_data.value(k) << "," << m.m_data.index(k) << ") "; + for (; k<m.m_outerIndex[i+1]; ++k) + s << "(_,_) "; + } + s << std::endl; + s << std::endl; + s << "Outer pointers:\n"; + for (Index i=0; i<m.outerSize(); ++i) + s << m.m_outerIndex[i] << " "; + s << " $" << std::endl; + if(!m.isCompressed()) + { + s << "Inner non zeros:\n"; + for (Index i=0; i<m.outerSize(); ++i) + s << m.m_innerNonZeros[i] << " "; + s << " $" << std::endl; + } + s << std::endl; + ); + s << static_cast<const SparseMatrixBase<SparseMatrix>&>(m); + return s; + } + + /** Destructor */ + inline ~SparseMatrix() + { + std::free(m_outerIndex); + std::free(m_innerNonZeros); + } + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** Overloaded for performance */ + Scalar sum() const; +#endif + +# ifdef EIGEN_SPARSEMATRIX_PLUGIN +# include EIGEN_SPARSEMATRIX_PLUGIN +# endif + +protected: + + template<typename Other> + void initAssignment(const Other& other) + { + resize(other.rows(), other.cols()); + if(m_innerNonZeros) + { + std::free(m_innerNonZeros); + m_innerNonZeros = 0; + } + } + + /** \internal + * \sa insert(Index,Index) */ + EIGEN_DONT_INLINE Scalar& insertCompressed(Index row, Index col); + + /** \internal + * A vector object that is equal to 0 everywhere but v at the position i */ + class SingletonVector + { + Index m_index; + Index m_value; + public: + typedef Index value_type; + SingletonVector(Index i, Index v) + : m_index(i), m_value(v) + {} + + Index operator[](Index i) const { return i==m_index ? m_value : 0; } + }; + + /** \internal + * \sa insert(Index,Index) */ + EIGEN_DONT_INLINE Scalar& insertUncompressed(Index row, Index col); + +public: + /** \internal + * \sa insert(Index,Index) */ + EIGEN_STRONG_INLINE Scalar& insertBackUncompressed(Index row, Index col) + { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(!isCompressed()); + eigen_assert(m_innerNonZeros[outer]<=(m_outerIndex[outer+1] - m_outerIndex[outer])); + + Index p = m_outerIndex[outer] + m_innerNonZeros[outer]++; + m_data.index(p) = inner; + return (m_data.value(p) = 0); + } + +private: + static void check_template_parameters() + { + EIGEN_STATIC_ASSERT(NumTraits<Index>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE); + EIGEN_STATIC_ASSERT((Options&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS); + } + + struct default_prunning_func { + default_prunning_func(const Scalar& ref, const RealScalar& eps) : reference(ref), epsilon(eps) {} + inline bool operator() (const Index&, const Index&, const Scalar& value) const + { + return !internal::isMuchSmallerThan(value, reference, epsilon); + } + Scalar reference; + RealScalar epsilon; + }; +}; + +template<typename Scalar, int _Options, typename _Index> +class SparseMatrix<Scalar,_Options,_Index>::InnerIterator +{ + public: + InnerIterator(const SparseMatrix& mat, Index outer) + : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_id(mat.m_outerIndex[outer]) + { + if(mat.isCompressed()) + m_end = mat.m_outerIndex[outer+1]; + else + m_end = m_id + mat.m_innerNonZeros[outer]; + } + + inline InnerIterator& operator++() { m_id++; return *this; } + + inline const Scalar& value() const { return m_values[m_id]; } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id]); } + + inline Index index() const { return m_indices[m_id]; } + inline Index outer() const { return m_outer; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id < m_end); } + + protected: + const Scalar* m_values; + const Index* m_indices; + const Index m_outer; + Index m_id; + Index m_end; +}; + +template<typename Scalar, int _Options, typename _Index> +class SparseMatrix<Scalar,_Options,_Index>::ReverseInnerIterator +{ + public: + ReverseInnerIterator(const SparseMatrix& mat, Index outer) + : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_start(mat.m_outerIndex[outer]) + { + if(mat.isCompressed()) + m_id = mat.m_outerIndex[outer+1]; + else + m_id = m_start + mat.m_innerNonZeros[outer]; + } + + inline ReverseInnerIterator& operator--() { --m_id; return *this; } + + inline const Scalar& value() const { return m_values[m_id-1]; } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id-1]); } + + inline Index index() const { return m_indices[m_id-1]; } + inline Index outer() const { return m_outer; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id > m_start); } + + protected: + const Scalar* m_values; + const Index* m_indices; + const Index m_outer; + Index m_id; + const Index m_start; +}; + +namespace internal { + +template<typename InputIterator, typename SparseMatrixType> +void set_from_triplets(const InputIterator& begin, const InputIterator& end, SparseMatrixType& mat, int Options = 0) +{ + EIGEN_UNUSED_VARIABLE(Options); + enum { IsRowMajor = SparseMatrixType::IsRowMajor }; + typedef typename SparseMatrixType::Scalar Scalar; + typedef typename SparseMatrixType::Index Index; + SparseMatrix<Scalar,IsRowMajor?ColMajor:RowMajor> trMat(mat.rows(),mat.cols()); + + if(begin!=end) + { + // pass 1: count the nnz per inner-vector + Matrix<Index,Dynamic,1> wi(trMat.outerSize()); + wi.setZero(); + for(InputIterator it(begin); it!=end; ++it) + { + eigen_assert(it->row()>=0 && it->row()<mat.rows() && it->col()>=0 && it->col()<mat.cols()); + wi(IsRowMajor ? it->col() : it->row())++; + } + + // pass 2: insert all the elements into trMat + trMat.reserve(wi); + for(InputIterator it(begin); it!=end; ++it) + trMat.insertBackUncompressed(it->row(),it->col()) = it->value(); + + // pass 3: + trMat.sumupDuplicates(); + } + + // pass 4: transposed copy -> implicit sorting + mat = trMat; +} + +} + + +/** Fill the matrix \c *this with the list of \em triplets defined by the iterator range \a begin - \a end. + * + * A \em triplet is a tuple (i,j,value) defining a non-zero element. + * The input list of triplets does not have to be sorted, and can contains duplicated elements. + * In any case, the result is a \b sorted and \b compressed sparse matrix where the duplicates have been summed up. + * This is a \em O(n) operation, with \em n the number of triplet elements. + * The initial contents of \c *this is destroyed. + * The matrix \c *this must be properly resized beforehand using the SparseMatrix(Index,Index) constructor, + * or the resize(Index,Index) method. The sizes are not extracted from the triplet list. + * + * The \a InputIterators value_type must provide the following interface: + * \code + * Scalar value() const; // the value + * Scalar row() const; // the row index i + * Scalar col() const; // the column index j + * \endcode + * See for instance the Eigen::Triplet template class. + * + * Here is a typical usage example: + * \code + typedef Triplet<double> T; + std::vector<T> tripletList; + triplets.reserve(estimation_of_entries); + for(...) + { + // ... + tripletList.push_back(T(i,j,v_ij)); + } + SparseMatrixType m(rows,cols); + m.setFromTriplets(tripletList.begin(), tripletList.end()); + // m is ready to go! + * \endcode + * + * \warning The list of triplets is read multiple times (at least twice). Therefore, it is not recommended to define + * an abstract iterator over a complex data-structure that would be expensive to evaluate. The triplets should rather + * be explicitely stored into a std::vector for instance. + */ +template<typename Scalar, int _Options, typename _Index> +template<typename InputIterators> +void SparseMatrix<Scalar,_Options,_Index>::setFromTriplets(const InputIterators& begin, const InputIterators& end) +{ + internal::set_from_triplets(begin, end, *this); +} + +/** \internal */ +template<typename Scalar, int _Options, typename _Index> +void SparseMatrix<Scalar,_Options,_Index>::sumupDuplicates() +{ + eigen_assert(!isCompressed()); + // TODO, in practice we should be able to use m_innerNonZeros for that task + Matrix<Index,Dynamic,1> wi(innerSize()); + wi.fill(-1); + Index count = 0; + // for each inner-vector, wi[inner_index] will hold the position of first element into the index/value buffers + for(Index j=0; j<outerSize(); ++j) + { + Index start = count; + Index oldEnd = m_outerIndex[j]+m_innerNonZeros[j]; + for(Index k=m_outerIndex[j]; k<oldEnd; ++k) + { + Index i = m_data.index(k); + if(wi(i)>=start) + { + // we already meet this entry => accumulate it + m_data.value(wi(i)) += m_data.value(k); + } + else + { + m_data.value(count) = m_data.value(k); + m_data.index(count) = m_data.index(k); + wi(i) = count; + ++count; + } + } + m_outerIndex[j] = start; + } + m_outerIndex[m_outerSize] = count; + + // turn the matrix into compressed form + std::free(m_innerNonZeros); + m_innerNonZeros = 0; + m_data.resize(m_outerIndex[m_outerSize]); +} + +template<typename Scalar, int _Options, typename _Index> +template<typename OtherDerived> +EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_Index>& SparseMatrix<Scalar,_Options,_Index>::operator=(const SparseMatrixBase<OtherDerived>& other) +{ + EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + + const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + if (needToTranspose) + { + // two passes algorithm: + // 1 - compute the number of coeffs per dest inner vector + // 2 - do the actual copy/eval + // Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed + typedef typename internal::nested<OtherDerived,2>::type OtherCopy; + typedef typename internal::remove_all<OtherCopy>::type _OtherCopy; + OtherCopy otherCopy(other.derived()); + + SparseMatrix dest(other.rows(),other.cols()); + Eigen::Map<Matrix<Index, Dynamic, 1> > (dest.m_outerIndex,dest.outerSize()).setZero(); + + // pass 1 + // FIXME the above copy could be merged with that pass + for (Index j=0; j<otherCopy.outerSize(); ++j) + for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it) + ++dest.m_outerIndex[it.index()]; + + // prefix sum + Index count = 0; + Matrix<Index,Dynamic,1> positions(dest.outerSize()); + for (Index j=0; j<dest.outerSize(); ++j) + { + Index tmp = dest.m_outerIndex[j]; + dest.m_outerIndex[j] = count; + positions[j] = count; + count += tmp; + } + dest.m_outerIndex[dest.outerSize()] = count; + // alloc + dest.m_data.resize(count); + // pass 2 + for (Index j=0; j<otherCopy.outerSize(); ++j) + { + for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it) + { + Index pos = positions[it.index()]++; + dest.m_data.index(pos) = j; + dest.m_data.value(pos) = it.value(); + } + } + this->swap(dest); + return *this; + } + else + { + if(other.isRValue()) + initAssignment(other.derived()); + // there is no special optimization + return Base::operator=(other.derived()); + } +} + +template<typename _Scalar, int _Options, typename _Index> +EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& SparseMatrix<_Scalar,_Options,_Index>::insertUncompressed(Index row, Index col) +{ + eigen_assert(!isCompressed()); + + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + Index room = m_outerIndex[outer+1] - m_outerIndex[outer]; + Index innerNNZ = m_innerNonZeros[outer]; + if(innerNNZ>=room) + { + // this inner vector is full, we need to reallocate the whole buffer :( + reserve(SingletonVector(outer,std::max<Index>(2,innerNNZ))); + } + + Index startId = m_outerIndex[outer]; + Index p = startId + m_innerNonZeros[outer]; + while ( (p > startId) && (m_data.index(p-1) > inner) ) + { + m_data.index(p) = m_data.index(p-1); + m_data.value(p) = m_data.value(p-1); + --p; + } + eigen_assert((p<=startId || m_data.index(p-1)!=inner) && "you cannot insert an element that already exists, you must call coeffRef to this end"); + + m_innerNonZeros[outer]++; + + m_data.index(p) = inner; + return (m_data.value(p) = 0); +} + +template<typename _Scalar, int _Options, typename _Index> +EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_Index>::Scalar& SparseMatrix<_Scalar,_Options,_Index>::insertCompressed(Index row, Index col) +{ + eigen_assert(isCompressed()); + + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + Index previousOuter = outer; + if (m_outerIndex[outer+1]==0) + { + // we start a new inner vector + while (previousOuter>=0 && m_outerIndex[previousOuter]==0) + { + m_outerIndex[previousOuter] = static_cast<Index>(m_data.size()); + --previousOuter; + } + m_outerIndex[outer+1] = m_outerIndex[outer]; + } + + // here we have to handle the tricky case where the outerIndex array + // starts with: [ 0 0 0 0 0 1 ...] and we are inserted in, e.g., + // the 2nd inner vector... + bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0)) + && (size_t(m_outerIndex[outer+1]) == m_data.size()); + + size_t startId = m_outerIndex[outer]; + // FIXME let's make sure sizeof(long int) == sizeof(size_t) + size_t p = m_outerIndex[outer+1]; + ++m_outerIndex[outer+1]; + + float reallocRatio = 1; + if (m_data.allocatedSize()<=m_data.size()) + { + // if there is no preallocated memory, let's reserve a minimum of 32 elements + if (m_data.size()==0) + { + m_data.reserve(32); + } + else + { + // we need to reallocate the data, to reduce multiple reallocations + // we use a smart resize algorithm based on the current filling ratio + // in addition, we use float to avoid integers overflows + float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1); + reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size()); + // furthermore we bound the realloc ratio to: + // 1) reduce multiple minor realloc when the matrix is almost filled + // 2) avoid to allocate too much memory when the matrix is almost empty + reallocRatio = (std::min)((std::max)(reallocRatio,1.5f),8.f); + } + } + m_data.resize(m_data.size()+1,reallocRatio); + + if (!isLastVec) + { + if (previousOuter==-1) + { + // oops wrong guess. + // let's correct the outer offsets + for (Index k=0; k<=(outer+1); ++k) + m_outerIndex[k] = 0; + Index k=outer+1; + while(m_outerIndex[k]==0) + m_outerIndex[k++] = 1; + while (k<=m_outerSize && m_outerIndex[k]!=0) + m_outerIndex[k++]++; + p = 0; + --k; + k = m_outerIndex[k]-1; + while (k>0) + { + m_data.index(k) = m_data.index(k-1); + m_data.value(k) = m_data.value(k-1); + k--; + } + } + else + { + // we are not inserting into the last inner vec + // update outer indices: + Index j = outer+2; + while (j<=m_outerSize && m_outerIndex[j]!=0) + m_outerIndex[j++]++; + --j; + // shift data of last vecs: + Index k = m_outerIndex[j]-1; + while (k>=Index(p)) + { + m_data.index(k) = m_data.index(k-1); + m_data.value(k) = m_data.value(k-1); + k--; + } + } + } + + while ( (p > startId) && (m_data.index(p-1) > inner) ) + { + m_data.index(p) = m_data.index(p-1); + m_data.value(p) = m_data.value(p-1); + --p; + } + + m_data.index(p) = inner; + return (m_data.value(p) = 0); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSEMATRIX_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseMatrixBase.h b/third_party/eigen3/Eigen/src/SparseCore/SparseMatrixBase.h new file mode 100644 index 0000000000..bbcf7fb1c6 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseMatrixBase.h @@ -0,0 +1,451 @@ +// 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_SPARSEMATRIXBASE_H +#define EIGEN_SPARSEMATRIXBASE_H + +namespace Eigen { + +/** \ingroup SparseCore_Module + * + * \class SparseMatrixBase + * + * \brief Base class of any sparse matrices or sparse expressions + * + * \tparam Derived + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIXBASE_PLUGIN. + */ +template<typename Derived> class SparseMatrixBase : public EigenBase<Derived> +{ + public: + + typedef typename internal::traits<Derived>::Scalar Scalar; + typedef typename internal::packet_traits<Scalar>::type PacketScalar; + typedef typename internal::traits<Derived>::StorageKind StorageKind; + typedef typename internal::traits<Derived>::Index Index; + typedef typename internal::add_const_on_value_type_if_arithmetic< + typename internal::packet_traits<Scalar>::type + >::type PacketReturnType; + + typedef SparseMatrixBase StorageBaseType; + typedef EigenBase<Derived> Base; + + template<typename OtherDerived> + Derived& operator=(const EigenBase<OtherDerived> &other) + { + other.derived().evalTo(derived()); + return derived(); + } + + enum { + + RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime, + /**< The number of rows at compile-time. This is just a copy of the value provided + * by the \a Derived type. If a value is not known at compile-time, + * it is set to the \a Dynamic constant. + * \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */ + + ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime, + /**< The number of columns at compile-time. This is just a copy of the value provided + * by the \a Derived type. If a value is not known at compile-time, + * it is set to the \a Dynamic constant. + * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */ + + + SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime, + internal::traits<Derived>::ColsAtCompileTime>::ret), + /**< This is equal to the number of coefficients, i.e. the number of + * rows times the number of columns, or to \a Dynamic if this is not + * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */ + + MaxRowsAtCompileTime = RowsAtCompileTime, + MaxColsAtCompileTime = ColsAtCompileTime, + + MaxSizeAtCompileTime = (internal::size_at_compile_time<MaxRowsAtCompileTime, + MaxColsAtCompileTime>::ret), + + IsVectorAtCompileTime = RowsAtCompileTime == 1 || ColsAtCompileTime == 1, + /**< This is set to true if either the number of rows or the number of + * columns is known at compile-time to be equal to 1. Indeed, in that case, + * we are dealing with a column-vector (if there is only one column) or with + * a row-vector (if there is only one row). */ + + Flags = internal::traits<Derived>::Flags, + /**< This stores expression \ref flags flags which may or may not be inherited by new expressions + * constructed from this one. See the \ref flags "list of flags". + */ + + CoeffReadCost = internal::traits<Derived>::CoeffReadCost, + /**< This is a rough measure of how expensive it is to read one coefficient from + * this expression. + */ + + IsRowMajor = Flags&RowMajorBit ? 1 : 0, + + InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime) + : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime), + + #ifndef EIGEN_PARSED_BY_DOXYGEN + _HasDirectAccess = (int(Flags)&DirectAccessBit) ? 1 : 0 // workaround sunCC + #endif + }; + + /** \internal the return type of MatrixBase::adjoint() */ + typedef typename internal::conditional<NumTraits<Scalar>::IsComplex, + CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, Eigen::Transpose<const Derived> >, + Transpose<const Derived> + >::type AdjointReturnType; + + + typedef SparseMatrix<Scalar, Flags&RowMajorBit ? RowMajor : ColMajor, Index> PlainObject; + + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** This is the "real scalar" type; if the \a Scalar type is already real numbers + * (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If + * \a Scalar is \a std::complex<T> then RealScalar is \a T. + * + * \sa class NumTraits + */ + typedef typename NumTraits<Scalar>::Real RealScalar; + + /** \internal the return type of coeff() + */ + typedef typename internal::conditional<_HasDirectAccess, const Scalar&, Scalar>::type CoeffReturnType; + + /** \internal Represents a matrix with all coefficients equal to one another*/ + typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Matrix<Scalar,Dynamic,Dynamic> > ConstantReturnType; + + /** type of the equivalent square matrix */ + typedef Matrix<Scalar,EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime), + EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime)> SquareMatrixType; + + inline const Derived& derived() const { return *static_cast<const Derived*>(this); } + inline Derived& derived() { return *static_cast<Derived*>(this); } + inline Derived& const_cast_derived() const + { return *static_cast<Derived*>(const_cast<SparseMatrixBase*>(this)); } +#endif // not EIGEN_PARSED_BY_DOXYGEN + +#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase +# include "../plugins/CommonCwiseUnaryOps.h" +# include "../plugins/CommonCwiseBinaryOps.h" +# include "../plugins/MatrixCwiseUnaryOps.h" +# include "../plugins/MatrixCwiseBinaryOps.h" +# include "../plugins/BlockMethods.h" +# ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN +# include EIGEN_SPARSEMATRIXBASE_PLUGIN +# endif +# undef EIGEN_CURRENT_STORAGE_BASE_CLASS +#undef EIGEN_CURRENT_STORAGE_BASE_CLASS + + /** \returns the number of rows. \sa cols() */ + inline Index rows() const { return derived().rows(); } + /** \returns the number of columns. \sa rows() */ + inline Index cols() const { return derived().cols(); } + /** \returns the number of coefficients, which is \a rows()*cols(). + * \sa rows(), cols(). */ + inline Index size() const { return rows() * cols(); } + /** \returns the number of nonzero coefficients which is in practice the number + * of stored coefficients. */ + inline Index nonZeros() const { return derived().nonZeros(); } + /** \returns true if either the number of rows or the number of columns is equal to 1. + * In other words, this function returns + * \code rows()==1 || cols()==1 \endcode + * \sa rows(), cols(), IsVectorAtCompileTime. */ + inline bool isVector() const { return rows()==1 || cols()==1; } + /** \returns the size of the storage major dimension, + * i.e., the number of columns for a columns major matrix, and the number of rows otherwise */ + Index outerSize() const { return (int(Flags)&RowMajorBit) ? this->rows() : this->cols(); } + /** \returns the size of the inner dimension according to the storage order, + * i.e., the number of rows for a columns major matrix, and the number of cols otherwise */ + Index innerSize() const { return (int(Flags)&RowMajorBit) ? this->cols() : this->rows(); } + + bool isRValue() const { return m_isRValue; } + Derived& markAsRValue() { m_isRValue = true; return derived(); } + + SparseMatrixBase() : m_isRValue(false) { /* TODO check flags */ } + + + template<typename OtherDerived> + Derived& operator=(const ReturnByValue<OtherDerived>& other) + { + other.evalTo(derived()); + return derived(); + } + + + template<typename OtherDerived> + inline Derived& operator=(const SparseMatrixBase<OtherDerived>& other) + { + return assign(other.derived()); + } + + inline Derived& operator=(const Derived& other) + { +// if (other.isRValue()) +// derived().swap(other.const_cast_derived()); +// else + return assign(other.derived()); + } + + protected: + + template<typename OtherDerived> + inline Derived& assign(const OtherDerived& other) + { + const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + const Index outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols(); + if ((!transpose) && other.isRValue()) + { + // eval without temporary + derived().resize(other.rows(), other.cols()); + derived().setZero(); + derived().reserve((std::max)(this->rows(),this->cols())*2); + for (Index j=0; j<outerSize; ++j) + { + derived().startVec(j); + for (typename OtherDerived::InnerIterator it(other, j); it; ++it) + { + Scalar v = it.value(); + derived().insertBackByOuterInner(j,it.index()) = v; + } + } + derived().finalize(); + } + else + { + assignGeneric(other); + } + return derived(); + } + + template<typename OtherDerived> + inline void assignGeneric(const OtherDerived& other) + { + //const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + eigen_assert(( ((internal::traits<Derived>::SupportedAccessPatterns&OuterRandomAccessPattern)==OuterRandomAccessPattern) || + (!((Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit)))) && + "the transpose operation is supposed to be handled in SparseMatrix::operator="); + + enum { Flip = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit) }; + + const Index outerSize = other.outerSize(); + //typedef typename internal::conditional<transpose, LinkedVectorMatrix<Scalar,Flags&RowMajorBit>, Derived>::type TempType; + // thanks to shallow copies, we always eval to a tempary + Derived temp(other.rows(), other.cols()); + + temp.reserve((std::max)(this->rows(),this->cols())*2); + for (Index j=0; j<outerSize; ++j) + { + temp.startVec(j); + for (typename OtherDerived::InnerIterator it(other.derived(), j); it; ++it) + { + Scalar v = it.value(); + temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v; + } + } + temp.finalize(); + + derived() = temp.markAsRValue(); + } + + public: + + template<typename Lhs, typename Rhs> + inline Derived& operator=(const SparseSparseProduct<Lhs,Rhs>& product); + + friend std::ostream & operator << (std::ostream & s, const SparseMatrixBase& m) + { + typedef typename Derived::Nested Nested; + typedef typename internal::remove_all<Nested>::type NestedCleaned; + + if (Flags&RowMajorBit) + { + const Nested nm(m.derived()); + for (Index row=0; row<nm.outerSize(); ++row) + { + Index col = 0; + for (typename NestedCleaned::InnerIterator it(nm.derived(), row); it; ++it) + { + for ( ; col<it.index(); ++col) + s << "0 "; + s << it.value() << " "; + ++col; + } + for ( ; col<m.cols(); ++col) + s << "0 "; + s << std::endl; + } + } + else + { + const Nested nm(m.derived()); + if (m.cols() == 1) { + Index row = 0; + for (typename NestedCleaned::InnerIterator it(nm.derived(), 0); it; ++it) + { + for ( ; row<it.index(); ++row) + s << "0" << std::endl; + s << it.value() << std::endl; + ++row; + } + for ( ; row<m.rows(); ++row) + s << "0" << std::endl; + } + else + { + SparseMatrix<Scalar, RowMajorBit, Index> trans = m; + s << static_cast<const SparseMatrixBase<SparseMatrix<Scalar, RowMajorBit, Index> >&>(trans); + } + } + return s; + } + + template<typename OtherDerived> + Derived& operator+=(const SparseMatrixBase<OtherDerived>& other); + template<typename OtherDerived> + Derived& operator-=(const SparseMatrixBase<OtherDerived>& other); + + Derived& operator*=(const Scalar& other); + Derived& operator/=(const Scalar& other); + + #define EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE \ + CwiseBinaryOp< \ + internal::scalar_product_op< \ + typename internal::scalar_product_traits< \ + typename internal::traits<Derived>::Scalar, \ + typename internal::traits<OtherDerived>::Scalar \ + >::ReturnType \ + >, \ + const Derived, \ + const OtherDerived \ + > + + template<typename OtherDerived> + EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE + cwiseProduct(const MatrixBase<OtherDerived> &other) const; + + // sparse * sparse + template<typename OtherDerived> + const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type + operator*(const SparseMatrixBase<OtherDerived> &other) const; + + // sparse * diagonal + template<typename OtherDerived> + const SparseDiagonalProduct<Derived,OtherDerived> + operator*(const DiagonalBase<OtherDerived> &other) const; + + // diagonal * sparse + template<typename OtherDerived> friend + const SparseDiagonalProduct<OtherDerived,Derived> + operator*(const DiagonalBase<OtherDerived> &lhs, const SparseMatrixBase& rhs) + { return SparseDiagonalProduct<OtherDerived,Derived>(lhs.derived(), rhs.derived()); } + + /** dense * sparse (return a dense object unless it is an outer product) */ + template<typename OtherDerived> friend + const typename DenseSparseProductReturnType<OtherDerived,Derived>::Type + operator*(const MatrixBase<OtherDerived>& lhs, const Derived& rhs) + { return typename DenseSparseProductReturnType<OtherDerived,Derived>::Type(lhs.derived(),rhs); } + + /** sparse * dense (returns a dense object unless it is an outer product) */ + template<typename OtherDerived> + const typename SparseDenseProductReturnType<Derived,OtherDerived>::Type + operator*(const MatrixBase<OtherDerived> &other) const; + + /** \returns an expression of P H P^-1 where H is the matrix represented by \c *this */ + SparseSymmetricPermutationProduct<Derived,Upper|Lower> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& perm) const + { + return SparseSymmetricPermutationProduct<Derived,Upper|Lower>(derived(), perm); + } + + template<typename OtherDerived> + Derived& operator*=(const SparseMatrixBase<OtherDerived>& other); + + #ifdef EIGEN2_SUPPORT + // deprecated + template<typename OtherDerived> + typename internal::plain_matrix_type_column_major<OtherDerived>::type + solveTriangular(const MatrixBase<OtherDerived>& other) const; + + // deprecated + template<typename OtherDerived> + void solveTriangularInPlace(MatrixBase<OtherDerived>& other) const; + #endif // EIGEN2_SUPPORT + + template<int Mode> + inline const SparseTriangularView<Derived, Mode> triangularView() const; + + template<unsigned int UpLo> inline const SparseSelfAdjointView<Derived, UpLo> selfadjointView() const; + template<unsigned int UpLo> inline SparseSelfAdjointView<Derived, UpLo> selfadjointView(); + + template<typename OtherDerived> Scalar dot(const MatrixBase<OtherDerived>& other) const; + template<typename OtherDerived> Scalar dot(const SparseMatrixBase<OtherDerived>& other) const; + RealScalar squaredNorm() const; + RealScalar norm() const; + RealScalar blueNorm() const; + + Transpose<Derived> transpose() { return derived(); } + const Transpose<const Derived> transpose() const { return derived(); } + const AdjointReturnType adjoint() const { return transpose(); } + + // inner-vector + typedef Block<Derived,IsRowMajor?1:Dynamic,IsRowMajor?Dynamic:1,true> InnerVectorReturnType; + typedef Block<const Derived,IsRowMajor?1:Dynamic,IsRowMajor?Dynamic:1,true> ConstInnerVectorReturnType; + InnerVectorReturnType innerVector(Index outer); + const ConstInnerVectorReturnType innerVector(Index outer) const; + + // set of inner-vectors + Block<Derived,Dynamic,Dynamic,true> innerVectors(Index outerStart, Index outerSize); + const Block<const Derived,Dynamic,Dynamic,true> innerVectors(Index outerStart, Index outerSize) const; + + /** \internal use operator= */ + template<typename DenseDerived> + void evalTo(MatrixBase<DenseDerived>& dst) const + { + dst.setZero(); + for (Index j=0; j<outerSize(); ++j) + for (typename Derived::InnerIterator i(derived(),j); i; ++i) + dst.coeffRef(i.row(),i.col()) = i.value(); + } + + Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> toDense() const + { + return derived(); + } + + template<typename OtherDerived> + bool isApprox(const SparseMatrixBase<OtherDerived>& other, + const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const + { return toDense().isApprox(other.toDense(),prec); } + + template<typename OtherDerived> + bool isApprox(const MatrixBase<OtherDerived>& other, + const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const + { return toDense().isApprox(other,prec); } + + /** \returns the matrix or vector obtained by evaluating this expression. + * + * Notice that in the case of a plain matrix or vector (not an expression) this function just returns + * a const reference, in order to avoid a useless copy. + */ + inline const typename internal::eval<Derived>::type eval() const + { return typename internal::eval<Derived>::type(derived()); } + + Scalar sum() const; + + protected: + + bool m_isRValue; +}; + +} // end namespace Eigen + +#endif // EIGEN_SPARSEMATRIXBASE_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparsePermutation.h b/third_party/eigen3/Eigen/src/SparseCore/SparsePermutation.h new file mode 100644 index 0000000000..b85be93f6f --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparsePermutation.h @@ -0,0 +1,148 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2012 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_SPARSE_PERMUTATION_H +#define EIGEN_SPARSE_PERMUTATION_H + +// This file implements sparse * permutation products + +namespace Eigen { + +namespace internal { + +template<typename PermutationType, typename MatrixType, int Side, bool Transposed> +struct traits<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> > +{ + typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned; + typedef typename MatrixTypeNestedCleaned::Scalar Scalar; + typedef typename MatrixTypeNestedCleaned::Index Index; + enum { + SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor, + MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight + }; + + typedef typename internal::conditional<MoveOuter, + SparseMatrix<Scalar,SrcStorageOrder,Index>, + SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> >::type ReturnType; +}; + +template<typename PermutationType, typename MatrixType, int Side, bool Transposed> +struct permut_sparsematrix_product_retval + : public ReturnByValue<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> > +{ + typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned; + typedef typename MatrixTypeNestedCleaned::Scalar Scalar; + typedef typename MatrixTypeNestedCleaned::Index Index; + + enum { + SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor, + MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight + }; + + permut_sparsematrix_product_retval(const PermutationType& perm, const MatrixType& matrix) + : m_permutation(perm), m_matrix(matrix) + {} + + inline int rows() const { return m_matrix.rows(); } + inline int cols() const { return m_matrix.cols(); } + + template<typename Dest> inline void evalTo(Dest& dst) const + { + if(MoveOuter) + { + SparseMatrix<Scalar,SrcStorageOrder,Index> tmp(m_matrix.rows(), m_matrix.cols()); + Matrix<Index,Dynamic,1> sizes(m_matrix.outerSize()); + for(Index j=0; j<m_matrix.outerSize(); ++j) + { + Index jp = m_permutation.indices().coeff(j); + sizes[((Side==OnTheLeft) ^ Transposed) ? jp : j] = m_matrix.innerVector(((Side==OnTheRight) ^ Transposed) ? jp : j).size(); + } + tmp.reserve(sizes); + for(Index j=0; j<m_matrix.outerSize(); ++j) + { + Index jp = m_permutation.indices().coeff(j); + Index jsrc = ((Side==OnTheRight) ^ Transposed) ? jp : j; + Index jdst = ((Side==OnTheLeft) ^ Transposed) ? jp : j; + for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,jsrc); it; ++it) + tmp.insertByOuterInner(jdst,it.index()) = it.value(); + } + dst = tmp; + } + else + { + SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> tmp(m_matrix.rows(), m_matrix.cols()); + Matrix<Index,Dynamic,1> sizes(tmp.outerSize()); + sizes.setZero(); + PermutationMatrix<Dynamic,Dynamic,Index> perm; + if((Side==OnTheLeft) ^ Transposed) + perm = m_permutation; + else + perm = m_permutation.transpose(); + + for(Index j=0; j<m_matrix.outerSize(); ++j) + for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it) + sizes[perm.indices().coeff(it.index())]++; + tmp.reserve(sizes); + for(Index j=0; j<m_matrix.outerSize(); ++j) + for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it) + tmp.insertByOuterInner(perm.indices().coeff(it.index()),j) = it.value(); + dst = tmp; + } + } + + protected: + const PermutationType& m_permutation; + typename MatrixType::Nested m_matrix; +}; + +} + + + +/** \returns the matrix with the permutation applied to the columns + */ +template<typename SparseDerived, typename PermDerived> +inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false> +operator*(const SparseMatrixBase<SparseDerived>& matrix, const PermutationBase<PermDerived>& perm) +{ + return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>(perm, matrix.derived()); +} + +/** \returns the matrix with the permutation applied to the rows + */ +template<typename SparseDerived, typename PermDerived> +inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false> +operator*( const PermutationBase<PermDerived>& perm, const SparseMatrixBase<SparseDerived>& matrix) +{ + return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>(perm, matrix.derived()); +} + + + +/** \returns the matrix with the inverse permutation applied to the columns. + */ +template<typename SparseDerived, typename PermDerived> +inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true> +operator*(const SparseMatrixBase<SparseDerived>& matrix, const Transpose<PermutationBase<PermDerived> >& tperm) +{ + return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>(tperm.nestedPermutation(), matrix.derived()); +} + +/** \returns the matrix with the inverse permutation applied to the rows. + */ +template<typename SparseDerived, typename PermDerived> +inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true> +operator*(const Transpose<PermutationBase<PermDerived> >& tperm, const SparseMatrixBase<SparseDerived>& matrix) +{ + return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>(tperm.nestedPermutation(), matrix.derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseProduct.h b/third_party/eigen3/Eigen/src/SparseCore/SparseProduct.h new file mode 100644 index 0000000000..cf76630700 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseProduct.h @@ -0,0 +1,188 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2010 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_SPARSEPRODUCT_H +#define EIGEN_SPARSEPRODUCT_H + +namespace Eigen { + +template<typename Lhs, typename Rhs> +struct SparseSparseProductReturnType +{ + typedef typename internal::traits<Lhs>::Scalar Scalar; + typedef typename internal::traits<Lhs>::Index Index; + enum { + LhsRowMajor = internal::traits<Lhs>::Flags & RowMajorBit, + RhsRowMajor = internal::traits<Rhs>::Flags & RowMajorBit, + TransposeRhs = (!LhsRowMajor) && RhsRowMajor, + TransposeLhs = LhsRowMajor && (!RhsRowMajor) + }; + + typedef typename internal::conditional<TransposeLhs, + SparseMatrix<Scalar,0,Index>, + typename internal::nested<Lhs,Rhs::RowsAtCompileTime>::type>::type LhsNested; + + typedef typename internal::conditional<TransposeRhs, + SparseMatrix<Scalar,0,Index>, + typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type>::type RhsNested; + + typedef SparseSparseProduct<LhsNested, RhsNested> Type; +}; + +namespace internal { +template<typename LhsNested, typename RhsNested> +struct traits<SparseSparseProduct<LhsNested, RhsNested> > +{ + typedef MatrixXpr XprKind; + // clean the nested types: + typedef typename remove_all<LhsNested>::type _LhsNested; + typedef typename remove_all<RhsNested>::type _RhsNested; + typedef typename _LhsNested::Scalar Scalar; + typedef typename promote_index_type<typename traits<_LhsNested>::Index, + typename traits<_RhsNested>::Index>::type Index; + + enum { + LhsCoeffReadCost = _LhsNested::CoeffReadCost, + RhsCoeffReadCost = _RhsNested::CoeffReadCost, + LhsFlags = _LhsNested::Flags, + RhsFlags = _RhsNested::Flags, + + RowsAtCompileTime = _LhsNested::RowsAtCompileTime, + ColsAtCompileTime = _RhsNested::ColsAtCompileTime, + MaxRowsAtCompileTime = _LhsNested::MaxRowsAtCompileTime, + MaxColsAtCompileTime = _RhsNested::MaxColsAtCompileTime, + + InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(_LhsNested::ColsAtCompileTime, _RhsNested::RowsAtCompileTime), + + EvalToRowMajor = (RhsFlags & LhsFlags & RowMajorBit), + + RemovedBits = ~(EvalToRowMajor ? 0 : RowMajorBit), + + Flags = (int(LhsFlags | RhsFlags) & HereditaryBits & RemovedBits) + | EvalBeforeAssigningBit + | EvalBeforeNestingBit, + + CoeffReadCost = Dynamic + }; + + typedef Sparse StorageKind; +}; + +} // end namespace internal + +template<typename LhsNested, typename RhsNested> +class SparseSparseProduct : internal::no_assignment_operator, + public SparseMatrixBase<SparseSparseProduct<LhsNested, RhsNested> > +{ + public: + + typedef SparseMatrixBase<SparseSparseProduct> Base; + EIGEN_DENSE_PUBLIC_INTERFACE(SparseSparseProduct) + + private: + + typedef typename internal::traits<SparseSparseProduct>::_LhsNested _LhsNested; + typedef typename internal::traits<SparseSparseProduct>::_RhsNested _RhsNested; + + public: + + template<typename Lhs, typename Rhs> + EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs) + : m_lhs(lhs), m_rhs(rhs), m_tolerance(0), m_conservative(true) + { + init(); + } + + template<typename Lhs, typename Rhs> + EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs, const RealScalar& tolerance) + : m_lhs(lhs), m_rhs(rhs), m_tolerance(tolerance), m_conservative(false) + { + init(); + } + + SparseSparseProduct pruned(const Scalar& reference = 0, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) const + { + using std::abs; + return SparseSparseProduct(m_lhs,m_rhs,abs(reference)*epsilon); + } + + template<typename Dest> + void evalTo(Dest& result) const + { + if(m_conservative) + internal::conservative_sparse_sparse_product_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result); + else + internal::sparse_sparse_product_with_pruning_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result,m_tolerance); + } + + EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); } + EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); } + + EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; } + EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; } + + protected: + void init() + { + eigen_assert(m_lhs.cols() == m_rhs.rows()); + + enum { + ProductIsValid = _LhsNested::ColsAtCompileTime==Dynamic + || _RhsNested::RowsAtCompileTime==Dynamic + || int(_LhsNested::ColsAtCompileTime)==int(_RhsNested::RowsAtCompileTime), + AreVectors = _LhsNested::IsVectorAtCompileTime && _RhsNested::IsVectorAtCompileTime, + SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(_LhsNested,_RhsNested) + }; + // note to the lost user: + // * for a dot product use: v1.dot(v2) + // * for a coeff-wise product use: v1.cwise()*v2 + EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), + INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) + EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), + INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) + EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) + } + + LhsNested m_lhs; + RhsNested m_rhs; + RealScalar m_tolerance; + bool m_conservative; +}; + +// sparse = sparse * sparse +template<typename Derived> +template<typename Lhs, typename Rhs> +inline Derived& SparseMatrixBase<Derived>::operator=(const SparseSparseProduct<Lhs,Rhs>& product) +{ + product.evalTo(derived()); + return derived(); +} + +/** \returns an expression of the product of two sparse matrices. + * By default a conservative product preserving the symbolic non zeros is performed. + * The automatic pruning of the small values can be achieved by calling the pruned() function + * in which case a totally different product algorithm is employed: + * \code + * C = (A*B).pruned(); // supress numerical zeros (exact) + * C = (A*B).pruned(ref); + * C = (A*B).pruned(ref,epsilon); + * \endcode + * where \c ref is a meaningful non zero reference value. + * */ +template<typename Derived> +template<typename OtherDerived> +inline const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type +SparseMatrixBase<Derived>::operator*(const SparseMatrixBase<OtherDerived> &other) const +{ + return typename SparseSparseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSEPRODUCT_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseRedux.h b/third_party/eigen3/Eigen/src/SparseCore/SparseRedux.h new file mode 100644 index 0000000000..f3da93a71d --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseRedux.h @@ -0,0 +1,45 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_SPARSEREDUX_H +#define EIGEN_SPARSEREDUX_H + +namespace Eigen { + +template<typename Derived> +typename internal::traits<Derived>::Scalar +SparseMatrixBase<Derived>::sum() const +{ + eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix"); + Scalar res(0); + for (Index j=0; j<outerSize(); ++j) + for (typename Derived::InnerIterator iter(derived(),j); iter; ++iter) + res += iter.value(); + return res; +} + +template<typename _Scalar, int _Options, typename _Index> +typename internal::traits<SparseMatrix<_Scalar,_Options,_Index> >::Scalar +SparseMatrix<_Scalar,_Options,_Index>::sum() const +{ + eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix"); + return Matrix<Scalar,1,Dynamic>::Map(&m_data.value(0), m_data.size()).sum(); +} + +template<typename _Scalar, int _Options, typename _Index> +typename internal::traits<SparseVector<_Scalar,_Options, _Index> >::Scalar +SparseVector<_Scalar,_Options,_Index>::sum() const +{ + eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix"); + return Matrix<Scalar,1,Dynamic>::Map(&m_data.value(0), m_data.size()).sum(); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSEREDUX_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseSelfAdjointView.h b/third_party/eigen3/Eigen/src/SparseCore/SparseSelfAdjointView.h new file mode 100644 index 0000000000..0eda96bc47 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseSelfAdjointView.h @@ -0,0 +1,507 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 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_SPARSE_SELFADJOINTVIEW_H +#define EIGEN_SPARSE_SELFADJOINTVIEW_H + +namespace Eigen { + +/** \ingroup SparseCore_Module + * \class SparseSelfAdjointView + * + * \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix. + * + * \param MatrixType the type of the dense matrix storing the coefficients + * \param UpLo can be either \c #Lower or \c #Upper + * + * This class is an expression of a sefladjoint matrix from a triangular part of a matrix + * with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView() + * and most of the time this is the only way that it is used. + * + * \sa SparseMatrixBase::selfadjointView() + */ +template<typename Lhs, typename Rhs, int UpLo> +class SparseSelfAdjointTimeDenseProduct; + +template<typename Lhs, typename Rhs, int UpLo> +class DenseTimeSparseSelfAdjointProduct; + +namespace internal { + +template<typename MatrixType, unsigned int UpLo> +struct traits<SparseSelfAdjointView<MatrixType,UpLo> > : traits<MatrixType> { +}; + +template<int SrcUpLo,int DstUpLo,typename MatrixType,int DestOrder> +void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0); + +template<int UpLo,typename MatrixType,int DestOrder> +void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0); + +} + +template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView + : public EigenBase<SparseSelfAdjointView<MatrixType,UpLo> > +{ + public: + + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef Matrix<Index,Dynamic,1> VectorI; + typedef typename MatrixType::Nested MatrixTypeNested; + typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested; + + inline SparseSelfAdjointView(const MatrixType& matrix) : m_matrix(matrix) + { + eigen_assert(rows()==cols() && "SelfAdjointView is only for squared matrices"); + } + + inline Index rows() const { return m_matrix.rows(); } + inline Index cols() const { return m_matrix.cols(); } + + /** \internal \returns a reference to the nested matrix */ + const _MatrixTypeNested& matrix() const { return m_matrix; } + _MatrixTypeNested& matrix() { return m_matrix.const_cast_derived(); } + + /** \returns an expression of the matrix product between a sparse self-adjoint matrix \c *this and a sparse matrix \a rhs. + * + * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product. + * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product. + */ + template<typename OtherDerived> + SparseSparseProduct<typename OtherDerived::PlainObject, OtherDerived> + operator*(const SparseMatrixBase<OtherDerived>& rhs) const + { + return SparseSparseProduct<typename OtherDerived::PlainObject, OtherDerived>(*this, rhs.derived()); + } + + /** \returns an expression of the matrix product between a sparse matrix \a lhs and a sparse self-adjoint matrix \a rhs. + * + * Note that there is no algorithmic advantage of performing such a product compared to a general sparse-sparse matrix product. + * Indeed, the SparseSelfadjointView operand is first copied into a temporary SparseMatrix before computing the product. + */ + template<typename OtherDerived> friend + SparseSparseProduct<OtherDerived, typename OtherDerived::PlainObject > + operator*(const SparseMatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs) + { + return SparseSparseProduct<OtherDerived, typename OtherDerived::PlainObject>(lhs.derived(), rhs); + } + + /** Efficient sparse self-adjoint matrix times dense vector/matrix product */ + template<typename OtherDerived> + SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo> + operator*(const MatrixBase<OtherDerived>& rhs) const + { + return SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>(m_matrix, rhs.derived()); + } + + /** Efficient dense vector/matrix times sparse self-adjoint matrix product */ + template<typename OtherDerived> friend + DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo> + operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs) + { + return DenseTimeSparseSelfAdjointProduct<OtherDerived,_MatrixTypeNested,UpLo>(lhs.derived(), rhs.m_matrix); + } + + /** Perform a symmetric rank K update of the selfadjoint matrix \c *this: + * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix. + * + * \returns a reference to \c *this + * + * To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply + * call this function with u.adjoint(). + */ + template<typename DerivedU> + SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha = Scalar(1)); + + /** \internal triggered by sparse_matrix = SparseSelfadjointView; */ + template<typename DestScalar,int StorageOrder> void evalTo(SparseMatrix<DestScalar,StorageOrder,Index>& _dest) const + { + internal::permute_symm_to_fullsymm<UpLo>(m_matrix, _dest); + } + + template<typename DestScalar> void evalTo(DynamicSparseMatrix<DestScalar,ColMajor,Index>& _dest) const + { + // TODO directly evaluate into _dest; + SparseMatrix<DestScalar,ColMajor,Index> tmp(_dest.rows(),_dest.cols()); + internal::permute_symm_to_fullsymm<UpLo>(m_matrix, tmp); + _dest = tmp; + } + + /** \returns an expression of P H P^-1 */ + SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& perm) const + { + return SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo>(m_matrix, perm); + } + + template<typename SrcMatrixType,int SrcUpLo> + SparseSelfAdjointView& operator=(const SparseSymmetricPermutationProduct<SrcMatrixType,SrcUpLo>& permutedMatrix) + { + permutedMatrix.evalTo(*this); + return *this; + } + + + SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src) + { + PermutationMatrix<Dynamic> pnull; + return *this = src.twistedBy(pnull); + } + + template<typename SrcMatrixType,unsigned int SrcUpLo> + SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcUpLo>& src) + { + PermutationMatrix<Dynamic> pnull; + return *this = src.twistedBy(pnull); + } + + + // const SparseLLT<PlainObject, UpLo> llt() const; + // const SparseLDLT<PlainObject, UpLo> ldlt() const; + + protected: + + typename MatrixType::Nested m_matrix; + mutable VectorI m_countPerRow; + mutable VectorI m_countPerCol; +}; + +/*************************************************************************** +* Implementation of SparseMatrixBase methods +***************************************************************************/ + +template<typename Derived> +template<unsigned int UpLo> +const SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() const +{ + return derived(); +} + +template<typename Derived> +template<unsigned int UpLo> +SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() +{ + return derived(); +} + +/*************************************************************************** +* Implementation of SparseSelfAdjointView methods +***************************************************************************/ + +template<typename MatrixType, unsigned int UpLo> +template<typename DerivedU> +SparseSelfAdjointView<MatrixType,UpLo>& +SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha) +{ + SparseMatrix<Scalar,MatrixType::Flags&RowMajorBit?RowMajor:ColMajor> tmp = u * u.adjoint(); + if(alpha==Scalar(0)) + m_matrix.const_cast_derived() = tmp.template triangularView<UpLo>(); + else + m_matrix.const_cast_derived() += alpha * tmp.template triangularView<UpLo>(); + + return *this; +} + +/*************************************************************************** +* Implementation of sparse self-adjoint time dense matrix +***************************************************************************/ + +namespace internal { +template<typename Lhs, typename Rhs, int UpLo> +struct traits<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo> > + : traits<ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> > +{ + typedef Dense StorageKind; +}; +} + +template<typename Lhs, typename Rhs, int UpLo> +class SparseSelfAdjointTimeDenseProduct + : public ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> +{ + public: + EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseSelfAdjointTimeDenseProduct) + + SparseSelfAdjointTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) + {} + + template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const + { + EIGEN_ONLY_USED_FOR_DEBUG(alpha); + // TODO use alpha + eigen_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry"); + typedef typename internal::remove_all<Lhs>::type _Lhs; + typedef typename _Lhs::InnerIterator LhsInnerIterator; + enum { + LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit, + ProcessFirstHalf = + ((UpLo&(Upper|Lower))==(Upper|Lower)) + || ( (UpLo&Upper) && !LhsIsRowMajor) + || ( (UpLo&Lower) && LhsIsRowMajor), + ProcessSecondHalf = !ProcessFirstHalf + }; + for (Index j=0; j<m_lhs.outerSize(); ++j) + { + LhsInnerIterator i(m_lhs,j); + if (ProcessSecondHalf) + { + while (i && i.index()<j) ++i; + if(i && i.index()==j) + { + dest.row(j) += i.value() * m_rhs.row(j); + ++i; + } + } + for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i) + { + Index a = LhsIsRowMajor ? j : i.index(); + Index b = LhsIsRowMajor ? i.index() : j; + typename Lhs::Scalar v = i.value(); + dest.row(a) += (v) * m_rhs.row(b); + dest.row(b) += numext::conj(v) * m_rhs.row(a); + } + if (ProcessFirstHalf && i && (i.index()==j)) + dest.row(j) += i.value() * m_rhs.row(j); + } + } + + private: + SparseSelfAdjointTimeDenseProduct& operator=(const SparseSelfAdjointTimeDenseProduct&); +}; + +namespace internal { +template<typename Lhs, typename Rhs, int UpLo> +struct traits<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo> > + : traits<ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> > +{}; +} + +template<typename Lhs, typename Rhs, int UpLo> +class DenseTimeSparseSelfAdjointProduct + : public ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> +{ + public: + EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseSelfAdjointProduct) + + DenseTimeSparseSelfAdjointProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) + {} + + template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, const Scalar& /*alpha*/) const + { + // TODO + } + + private: + DenseTimeSparseSelfAdjointProduct& operator=(const DenseTimeSparseSelfAdjointProduct&); +}; + +/*************************************************************************** +* Implementation of symmetric copies and permutations +***************************************************************************/ +namespace internal { + +template<typename MatrixType, int UpLo> +struct traits<SparseSymmetricPermutationProduct<MatrixType,UpLo> > : traits<MatrixType> { +}; + +template<int UpLo,typename MatrixType,int DestOrder> +void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm) +{ + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + typedef SparseMatrix<Scalar,DestOrder,Index> Dest; + typedef Matrix<Index,Dynamic,1> VectorI; + + Dest& dest(_dest.derived()); + enum { + StorageOrderMatch = int(Dest::IsRowMajor) == int(MatrixType::IsRowMajor) + }; + + Index size = mat.rows(); + VectorI count; + count.resize(size); + count.setZero(); + dest.resize(size,size); + for(Index j = 0; j<size; ++j) + { + Index jp = perm ? perm[j] : j; + for(typename MatrixType::InnerIterator it(mat,j); it; ++it) + { + Index i = it.index(); + Index r = it.row(); + Index c = it.col(); + Index ip = perm ? perm[i] : i; + if(UpLo==(Upper|Lower)) + count[StorageOrderMatch ? jp : ip]++; + else if(r==c) + count[ip]++; + else if(( UpLo==Lower && r>c) || ( UpLo==Upper && r<c)) + { + count[ip]++; + count[jp]++; + } + } + } + Index nnz = count.sum(); + + // reserve space + dest.resizeNonZeros(nnz); + dest.outerIndexPtr()[0] = 0; + for(Index j=0; j<size; ++j) + dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j]; + for(Index j=0; j<size; ++j) + count[j] = dest.outerIndexPtr()[j]; + + // copy data + for(Index j = 0; j<size; ++j) + { + for(typename MatrixType::InnerIterator it(mat,j); it; ++it) + { + Index i = it.index(); + Index r = it.row(); + Index c = it.col(); + + Index jp = perm ? perm[j] : j; + Index ip = perm ? perm[i] : i; + + if(UpLo==(Upper|Lower)) + { + Index k = count[StorageOrderMatch ? jp : ip]++; + dest.innerIndexPtr()[k] = StorageOrderMatch ? ip : jp; + dest.valuePtr()[k] = it.value(); + } + else if(r==c) + { + Index k = count[ip]++; + dest.innerIndexPtr()[k] = ip; + dest.valuePtr()[k] = it.value(); + } + else if(( (UpLo&Lower)==Lower && r>c) || ( (UpLo&Upper)==Upper && r<c)) + { + if(!StorageOrderMatch) + std::swap(ip,jp); + Index k = count[jp]++; + dest.innerIndexPtr()[k] = ip; + dest.valuePtr()[k] = it.value(); + k = count[ip]++; + dest.innerIndexPtr()[k] = jp; + dest.valuePtr()[k] = numext::conj(it.value()); + } + } + } +} + +template<int _SrcUpLo,int _DstUpLo,typename MatrixType,int DstOrder> +void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm) +{ + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + SparseMatrix<Scalar,DstOrder,Index>& dest(_dest.derived()); + typedef Matrix<Index,Dynamic,1> VectorI; + enum { + SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor, + StorageOrderMatch = int(SrcOrder) == int(DstOrder), + DstUpLo = DstOrder==RowMajor ? (_DstUpLo==Upper ? Lower : Upper) : _DstUpLo, + SrcUpLo = SrcOrder==RowMajor ? (_SrcUpLo==Upper ? Lower : Upper) : _SrcUpLo + }; + + Index size = mat.rows(); + VectorI count(size); + count.setZero(); + dest.resize(size,size); + for(Index j = 0; j<size; ++j) + { + Index jp = perm ? perm[j] : j; + for(typename MatrixType::InnerIterator it(mat,j); it; ++it) + { + Index i = it.index(); + if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j)) + continue; + + Index ip = perm ? perm[i] : i; + count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; + } + } + dest.outerIndexPtr()[0] = 0; + for(Index j=0; j<size; ++j) + dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j]; + dest.resizeNonZeros(dest.outerIndexPtr()[size]); + for(Index j=0; j<size; ++j) + count[j] = dest.outerIndexPtr()[j]; + + for(Index j = 0; j<size; ++j) + { + + for(typename MatrixType::InnerIterator it(mat,j); it; ++it) + { + Index i = it.index(); + if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j)) + continue; + + Index jp = perm ? perm[j] : j; + Index ip = perm? perm[i] : i; + + Index k = count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; + dest.innerIndexPtr()[k] = int(DstUpLo)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp); + + if(!StorageOrderMatch) std::swap(ip,jp); + if( ((int(DstUpLo)==int(Lower) && ip<jp) || (int(DstUpLo)==int(Upper) && ip>jp))) + dest.valuePtr()[k] = numext::conj(it.value()); + else + dest.valuePtr()[k] = it.value(); + } + } +} + +} + +template<typename MatrixType,int UpLo> +class SparseSymmetricPermutationProduct + : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,UpLo> > +{ + public: + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + protected: + typedef PermutationMatrix<Dynamic,Dynamic,Index> Perm; + public: + typedef Matrix<Index,Dynamic,1> VectorI; + typedef typename MatrixType::Nested MatrixTypeNested; + typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested; + + SparseSymmetricPermutationProduct(const MatrixType& mat, const Perm& perm) + : m_matrix(mat), m_perm(perm) + {} + + inline Index rows() const { return m_matrix.rows(); } + inline Index cols() const { return m_matrix.cols(); } + + template<typename DestScalar, int Options, typename DstIndex> + void evalTo(SparseMatrix<DestScalar,Options,DstIndex>& _dest) const + { +// internal::permute_symm_to_fullsymm<UpLo>(m_matrix,_dest,m_perm.indices().data()); + SparseMatrix<DestScalar,(Options&RowMajor)==RowMajor ? ColMajor : RowMajor, DstIndex> tmp; + internal::permute_symm_to_fullsymm<UpLo>(m_matrix,tmp,m_perm.indices().data()); + _dest = tmp; + } + + template<typename DestType,unsigned int DestUpLo> void evalTo(SparseSelfAdjointView<DestType,DestUpLo>& dest) const + { + internal::permute_symm_to_symm<UpLo,DestUpLo>(m_matrix,dest.matrix(),m_perm.indices().data()); + } + + protected: + MatrixTypeNested m_matrix; + const Perm& m_perm; + +}; + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseSparseProductWithPruning.h b/third_party/eigen3/Eigen/src/SparseCore/SparseSparseProductWithPruning.h new file mode 100644 index 0000000000..fcc18f5c9c --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseSparseProductWithPruning.h @@ -0,0 +1,150 @@ +// 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_SPARSESPARSEPRODUCTWITHPRUNING_H +#define EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H + +namespace Eigen { + +namespace internal { + + +// perform a pseudo in-place sparse * sparse product assuming all matrices are col major +template<typename Lhs, typename Rhs, typename ResultType> +static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, const typename ResultType::RealScalar& tolerance) +{ + // return sparse_sparse_product_with_pruning_impl2(lhs,rhs,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(); + //Index size = lhs.outerSize(); + eigen_assert(lhs.outerSize() == rhs.innerSize()); + + // allocate a temporary buffer + AmbiVector<Scalar,Index> tempVector(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(); + + // mimics a resizeByInnerOuter: + if(ResultType::IsRowMajor) + res.resize(cols, rows); + else + res.resize(rows, cols); + + res.reserve(estimated_nnz_prod); + double ratioColRes = double(estimated_nnz_prod)/double(lhs.rows()*rhs.cols()); + for (Index j=0; j<cols; ++j) + { + // FIXME: + //double ratioColRes = (double(rhs.innerVector(j).nonZeros()) + double(lhs.nonZeros())/double(lhs.cols()))/double(lhs.rows()); + // let's do a more accurate determination of the nnz ratio for the current column j of res + tempVector.init(ratioColRes); + tempVector.setZero(); + for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt) + { + // FIXME should be written like this: tmp += rhsIt.value() * lhs.col(rhsIt.index()) + tempVector.restart(); + Scalar x = rhsIt.value(); + for (typename Lhs::InnerIterator lhsIt(lhs, rhsIt.index()); lhsIt; ++lhsIt) + { + tempVector.coeffRef(lhsIt.index()) += lhsIt.value() * x; + } + } + res.startVec(j); + for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector,tolerance); it; ++it) + res.insertBackByOuterInner(j,it.index()) = it.value(); + } + res.finalize(); +} + +template<typename Lhs, typename Rhs, typename ResultType, + int LhsStorageOrder = traits<Lhs>::Flags&RowMajorBit, + int RhsStorageOrder = traits<Rhs>::Flags&RowMajorBit, + int ResStorageOrder = traits<ResultType>::Flags&RowMajorBit> +struct sparse_sparse_product_with_pruning_selector; + +template<typename Lhs, typename Rhs, typename ResultType> +struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,ColMajor> +{ + typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar; + typedef typename ResultType::RealScalar RealScalar; + + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) + { + typename remove_all<ResultType>::type _res(res.rows(), res.cols()); + internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,ResultType>(lhs, rhs, _res, tolerance); + res.swap(_res); + } +}; + +template<typename Lhs, typename Rhs, typename ResultType> +struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,RowMajor> +{ + typedef typename ResultType::RealScalar RealScalar; + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) + { + // we need a col-major matrix to hold the result + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> SparseTemporaryType; + SparseTemporaryType _res(res.rows(), res.cols()); + internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,SparseTemporaryType>(lhs, rhs, _res, tolerance); + res = _res; + } +}; + +template<typename Lhs, typename Rhs, typename ResultType> +struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,RowMajor> +{ + typedef typename ResultType::RealScalar RealScalar; + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) + { + // let's transpose the product to get a column x column product + typename remove_all<ResultType>::type _res(res.rows(), res.cols()); + internal::sparse_sparse_product_with_pruning_impl<Rhs,Lhs,ResultType>(rhs, lhs, _res, tolerance); + res.swap(_res); + } +}; + +template<typename Lhs, typename Rhs, typename ResultType> +struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor> +{ + typedef typename ResultType::RealScalar RealScalar; + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) + { + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::Index> ColMajorMatrixLhs; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::Index> ColMajorMatrixRhs; + ColMajorMatrixLhs colLhs(lhs); + ColMajorMatrixRhs colRhs(rhs); + internal::sparse_sparse_product_with_pruning_impl<ColMajorMatrixLhs,ColMajorMatrixRhs,ResultType>(colLhs, colRhs, res, tolerance); + + // let's transpose the product to get a column x column product +// typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType; +// SparseTemporaryType _res(res.cols(), res.rows()); +// sparse_sparse_product_with_pruning_impl<Rhs,Lhs,SparseTemporaryType>(rhs, lhs, _res); +// res = _res.transpose(); + } +}; + +// NOTE the 2 others cases (col row *) must never occur since they are caught +// by ProductReturnType which transforms it to (col col *) by evaluating rhs. + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseTranspose.h b/third_party/eigen3/Eigen/src/SparseCore/SparseTranspose.h new file mode 100644 index 0000000000..7c300ee8db --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseTranspose.h @@ -0,0 +1,63 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2009 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_SPARSETRANSPOSE_H +#define EIGEN_SPARSETRANSPOSE_H + +namespace Eigen { + +template<typename MatrixType> class TransposeImpl<MatrixType,Sparse> + : public SparseMatrixBase<Transpose<MatrixType> > +{ + typedef typename internal::remove_all<typename MatrixType::Nested>::type _MatrixTypeNested; + public: + + EIGEN_SPARSE_PUBLIC_INTERFACE(Transpose<MatrixType> ) + + class InnerIterator; + class ReverseInnerIterator; + + inline Index nonZeros() const { return derived().nestedExpression().nonZeros(); } +}; + +// NOTE: VC10 trigger an ICE if don't put typename TransposeImpl<MatrixType,Sparse>:: in front of Index, +// a typedef typename TransposeImpl<MatrixType,Sparse>::Index Index; +// does not fix the issue. +// An alternative is to define the nested class in the parent class itself. +template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>::InnerIterator + : public _MatrixTypeNested::InnerIterator +{ + typedef typename _MatrixTypeNested::InnerIterator Base; + typedef typename TransposeImpl::Index Index; + public: + + EIGEN_STRONG_INLINE InnerIterator(const TransposeImpl& trans, typename TransposeImpl<MatrixType,Sparse>::Index outer) + : Base(trans.derived().nestedExpression(), outer) + {} + Index row() const { return Base::col(); } + Index col() const { return Base::row(); } +}; + +template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>::ReverseInnerIterator + : public _MatrixTypeNested::ReverseInnerIterator +{ + typedef typename _MatrixTypeNested::ReverseInnerIterator Base; + typedef typename TransposeImpl::Index Index; + public: + + EIGEN_STRONG_INLINE ReverseInnerIterator(const TransposeImpl& xpr, typename TransposeImpl<MatrixType,Sparse>::Index outer) + : Base(xpr.derived().nestedExpression(), outer) + {} + Index row() const { return Base::col(); } + Index col() const { return Base::row(); } +}; + +} // end namespace Eigen + +#endif // EIGEN_SPARSETRANSPOSE_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseTriangularView.h b/third_party/eigen3/Eigen/src/SparseCore/SparseTriangularView.h new file mode 100644 index 0000000000..333127b78e --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseTriangularView.h @@ -0,0 +1,179 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> +// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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_SPARSE_TRIANGULARVIEW_H +#define EIGEN_SPARSE_TRIANGULARVIEW_H + +namespace Eigen { + +namespace internal { + +template<typename MatrixType, int Mode> +struct traits<SparseTriangularView<MatrixType,Mode> > +: public traits<MatrixType> +{}; + +} // namespace internal + +template<typename MatrixType, int Mode> class SparseTriangularView + : public SparseMatrixBase<SparseTriangularView<MatrixType,Mode> > +{ + enum { SkipFirst = ((Mode&Lower) && !(MatrixType::Flags&RowMajorBit)) + || ((Mode&Upper) && (MatrixType::Flags&RowMajorBit)), + SkipLast = !SkipFirst, + SkipDiag = (Mode&ZeroDiag) ? 1 : 0, + HasUnitDiag = (Mode&UnitDiag) ? 1 : 0 + }; + + public: + + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseTriangularView) + + class InnerIterator; + class ReverseInnerIterator; + + inline Index rows() const { return m_matrix.rows(); } + inline Index cols() const { return m_matrix.cols(); } + + typedef typename MatrixType::Nested MatrixTypeNested; + typedef typename internal::remove_reference<MatrixTypeNested>::type MatrixTypeNestedNonRef; + typedef typename internal::remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned; + + inline SparseTriangularView(const MatrixType& matrix) : m_matrix(matrix) {} + + /** \internal */ + inline const MatrixTypeNestedCleaned& nestedExpression() const { return m_matrix; } + + template<typename OtherDerived> + typename internal::plain_matrix_type_column_major<OtherDerived>::type + solve(const MatrixBase<OtherDerived>& other) const; + + template<typename OtherDerived> void solveInPlace(MatrixBase<OtherDerived>& other) const; + template<typename OtherDerived> void solveInPlace(SparseMatrixBase<OtherDerived>& other) const; + + protected: + MatrixTypeNested m_matrix; +}; + +template<typename MatrixType, int Mode> +class SparseTriangularView<MatrixType,Mode>::InnerIterator : public MatrixTypeNestedCleaned::InnerIterator +{ + typedef typename MatrixTypeNestedCleaned::InnerIterator Base; + typedef typename SparseTriangularView::Index Index; + public: + + EIGEN_STRONG_INLINE InnerIterator(const SparseTriangularView& view, Index outer) + : Base(view.nestedExpression(), outer), m_returnOne(false) + { + if(SkipFirst) + { + while((*this) && ((HasUnitDiag||SkipDiag) ? this->index()<=outer : this->index()<outer)) + Base::operator++(); + if(HasUnitDiag) + m_returnOne = true; + } + else if(HasUnitDiag && ((!Base::operator bool()) || Base::index()>=Base::outer())) + { + if((!SkipFirst) && Base::operator bool()) + Base::operator++(); + m_returnOne = true; + } + } + + EIGEN_STRONG_INLINE InnerIterator& operator++() + { + if(HasUnitDiag && m_returnOne) + m_returnOne = false; + else + { + Base::operator++(); + if(HasUnitDiag && (!SkipFirst) && ((!Base::operator bool()) || Base::index()>=Base::outer())) + { + if((!SkipFirst) && Base::operator bool()) + Base::operator++(); + m_returnOne = true; + } + } + return *this; + } + + inline Index row() const { return (MatrixType::Flags&RowMajorBit ? Base::outer() : this->index()); } + inline Index col() const { return (MatrixType::Flags&RowMajorBit ? this->index() : Base::outer()); } + inline Index index() const + { + if(HasUnitDiag && m_returnOne) return Base::outer(); + else return Base::index(); + } + inline Scalar value() const + { + if(HasUnitDiag && m_returnOne) return Scalar(1); + else return Base::value(); + } + + EIGEN_STRONG_INLINE operator bool() const + { + if(HasUnitDiag && m_returnOne) + return true; + if(SkipFirst) return Base::operator bool(); + else + { + if (SkipDiag) return (Base::operator bool() && this->index() < this->outer()); + else return (Base::operator bool() && this->index() <= this->outer()); + } + } + protected: + bool m_returnOne; +}; + +template<typename MatrixType, int Mode> +class SparseTriangularView<MatrixType,Mode>::ReverseInnerIterator : public MatrixTypeNestedCleaned::ReverseInnerIterator +{ + typedef typename MatrixTypeNestedCleaned::ReverseInnerIterator Base; + typedef typename SparseTriangularView::Index Index; + public: + + EIGEN_STRONG_INLINE ReverseInnerIterator(const SparseTriangularView& view, Index outer) + : Base(view.nestedExpression(), outer) + { + eigen_assert((!HasUnitDiag) && "ReverseInnerIterator does not support yet triangular views with a unit diagonal"); + if(SkipLast) { + while((*this) && (SkipDiag ? this->index()>=outer : this->index()>outer)) + --(*this); + } + } + + EIGEN_STRONG_INLINE ReverseInnerIterator& operator--() + { Base::operator--(); return *this; } + + inline Index row() const { return Base::row(); } + inline Index col() const { return Base::col(); } + + EIGEN_STRONG_INLINE operator bool() const + { + if (SkipLast) return Base::operator bool() ; + else + { + if(SkipDiag) return (Base::operator bool() && this->index() > this->outer()); + else return (Base::operator bool() && this->index() >= this->outer()); + } + } +}; + +template<typename Derived> +template<int Mode> +inline const SparseTriangularView<Derived, Mode> +SparseMatrixBase<Derived>::triangularView() const +{ + return derived(); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_TRIANGULARVIEW_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseUtil.h b/third_party/eigen3/Eigen/src/SparseCore/SparseUtil.h new file mode 100644 index 0000000000..05023858b1 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseUtil.h @@ -0,0 +1,171 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_SPARSEUTIL_H +#define EIGEN_SPARSEUTIL_H + +namespace Eigen { + +#ifdef NDEBUG +#define EIGEN_DBG_SPARSE(X) +#else +#define EIGEN_DBG_SPARSE(X) X +#endif + +#define EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, Op) \ +template<typename OtherDerived> \ +EIGEN_STRONG_INLINE Derived& operator Op(const Eigen::SparseMatrixBase<OtherDerived>& other) \ +{ \ + return Base::operator Op(other.derived()); \ +} \ +EIGEN_STRONG_INLINE Derived& operator Op(const Derived& other) \ +{ \ + return Base::operator Op(other); \ +} + +#define EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, Op) \ +template<typename Other> \ +EIGEN_STRONG_INLINE Derived& operator Op(const Other& scalar) \ +{ \ + return Base::operator Op(scalar); \ +} + +#define EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATORS(Derived) \ +EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, =) \ +EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, +=) \ +EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(Derived, -=) \ +EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, *=) \ +EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, /=) + +#define _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, BaseClass) \ + typedef BaseClass Base; \ + typedef typename Eigen::internal::traits<Derived >::Scalar Scalar; \ + typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; \ + typedef typename Eigen::internal::nested<Derived >::type Nested; \ + typedef typename Eigen::internal::traits<Derived >::StorageKind StorageKind; \ + typedef typename Eigen::internal::traits<Derived >::Index Index; \ + enum { RowsAtCompileTime = Eigen::internal::traits<Derived >::RowsAtCompileTime, \ + ColsAtCompileTime = Eigen::internal::traits<Derived >::ColsAtCompileTime, \ + Flags = Eigen::internal::traits<Derived >::Flags, \ + CoeffReadCost = Eigen::internal::traits<Derived >::CoeffReadCost, \ + SizeAtCompileTime = Base::SizeAtCompileTime, \ + IsVectorAtCompileTime = Base::IsVectorAtCompileTime }; \ + using Base::derived; \ + using Base::const_cast_derived; + +#define EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) \ + _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, Eigen::SparseMatrixBase<Derived >) + +const int CoherentAccessPattern = 0x1; +const int InnerRandomAccessPattern = 0x2 | CoherentAccessPattern; +const int OuterRandomAccessPattern = 0x4 | CoherentAccessPattern; +const int RandomAccessPattern = 0x8 | OuterRandomAccessPattern | InnerRandomAccessPattern; + +template<typename Derived> class SparseMatrixBase; +template<typename _Scalar, int _Flags = 0, typename _Index = int> class SparseMatrix; +template<typename _Scalar, int _Flags = 0, typename _Index = int> class DynamicSparseMatrix; +template<typename _Scalar, int _Flags = 0, typename _Index = int> class SparseVector; +template<typename _Scalar, int _Flags = 0, typename _Index = int> class MappedSparseMatrix; + +template<typename MatrixType, int Mode> class SparseTriangularView; +template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView; +template<typename Lhs, typename Rhs> class SparseDiagonalProduct; +template<typename MatrixType> class SparseView; + +template<typename Lhs, typename Rhs> class SparseSparseProduct; +template<typename Lhs, typename Rhs> class SparseTimeDenseProduct; +template<typename Lhs, typename Rhs> class DenseTimeSparseProduct; +template<typename Lhs, typename Rhs, bool Transpose> class SparseDenseOuterProduct; + +template<typename Lhs, typename Rhs> struct SparseSparseProductReturnType; +template<typename Lhs, typename Rhs, int InnerSize = internal::traits<Lhs>::ColsAtCompileTime> struct DenseSparseProductReturnType; +template<typename Lhs, typename Rhs, int InnerSize = internal::traits<Lhs>::ColsAtCompileTime> struct SparseDenseProductReturnType; +template<typename MatrixType,int UpLo> class SparseSymmetricPermutationProduct; + +namespace internal { + +template<typename T,int Rows,int Cols> struct sparse_eval; + +template<typename T> struct eval<T,Sparse> + : public sparse_eval<T, traits<T>::RowsAtCompileTime,traits<T>::ColsAtCompileTime> +{}; + +template<typename T,int Cols> struct sparse_eval<T,1,Cols> { + typedef typename traits<T>::Scalar _Scalar; + typedef typename traits<T>::Index _Index; + public: + typedef SparseVector<_Scalar, RowMajor, _Index> type; +}; + +template<typename T,int Rows> struct sparse_eval<T,Rows,1> { + typedef typename traits<T>::Scalar _Scalar; + typedef typename traits<T>::Index _Index; + public: + typedef SparseVector<_Scalar, ColMajor, _Index> type; +}; + +template<typename T,int Rows,int Cols> struct sparse_eval { + typedef typename traits<T>::Scalar _Scalar; + typedef typename traits<T>::Index _Index; + enum { _Options = ((traits<T>::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor }; + public: + typedef SparseMatrix<_Scalar, _Options, _Index> type; +}; + +template<typename T> struct sparse_eval<T,1,1> { + typedef typename traits<T>::Scalar _Scalar; + public: + typedef Matrix<_Scalar, 1, 1> type; +}; + +template<typename T> struct plain_matrix_type<T,Sparse> +{ + typedef typename traits<T>::Scalar _Scalar; + typedef typename traits<T>::Index _Index; + enum { _Options = ((traits<T>::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor }; + public: + typedef SparseMatrix<_Scalar, _Options, _Index> type; +}; + +} // end namespace internal + +/** \ingroup SparseCore_Module + * + * \class Triplet + * + * \brief A small structure to hold a non zero as a triplet (i,j,value). + * + * \sa SparseMatrix::setFromTriplets() + */ +template<typename Scalar, typename Index=typename SparseMatrix<Scalar>::Index > +class Triplet +{ +public: + Triplet() : m_row(0), m_col(0), m_value(0) {} + + Triplet(const Index& i, const Index& j, const Scalar& v = Scalar(0)) + : m_row(i), m_col(j), m_value(v) + {} + + /** \returns the row index of the element */ + const Index& row() const { return m_row; } + + /** \returns the column index of the element */ + const Index& col() const { return m_col; } + + /** \returns the value of the element */ + const Scalar& value() const { return m_value; } +protected: + Index m_row, m_col; + Scalar m_value; +}; + +} // end namespace Eigen + +#endif // EIGEN_SPARSEUTIL_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseVector.h b/third_party/eigen3/Eigen/src/SparseCore/SparseVector.h new file mode 100644 index 0000000000..7e15c814b6 --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseVector.h @@ -0,0 +1,447 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2009 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_SPARSEVECTOR_H +#define EIGEN_SPARSEVECTOR_H + +namespace Eigen { + +/** \ingroup SparseCore_Module + * \class SparseVector + * + * \brief a sparse vector class + * + * \tparam _Scalar the scalar type, i.e. the type of the coefficients + * + * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme. + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN. + */ + +namespace internal { +template<typename _Scalar, int _Options, typename _Index> +struct traits<SparseVector<_Scalar, _Options, _Index> > +{ + typedef _Scalar Scalar; + typedef _Index Index; + typedef Sparse StorageKind; + typedef MatrixXpr XprKind; + enum { + IsColVector = (_Options & RowMajorBit) ? 0 : 1, + + RowsAtCompileTime = IsColVector ? Dynamic : 1, + ColsAtCompileTime = IsColVector ? 1 : Dynamic, + MaxRowsAtCompileTime = RowsAtCompileTime, + MaxColsAtCompileTime = ColsAtCompileTime, + Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit), + CoeffReadCost = NumTraits<Scalar>::ReadCost, + SupportedAccessPatterns = InnerRandomAccessPattern + }; +}; + +// Sparse-Vector-Assignment kinds: +enum { + SVA_RuntimeSwitch, + SVA_Inner, + SVA_Outer +}; + +template< typename Dest, typename Src, + int AssignmentKind = !bool(Src::IsVectorAtCompileTime) ? SVA_RuntimeSwitch + : Src::InnerSizeAtCompileTime==1 ? SVA_Outer + : SVA_Inner> +struct sparse_vector_assign_selector; + +} + +template<typename _Scalar, int _Options, typename _Index> +class SparseVector + : public SparseMatrixBase<SparseVector<_Scalar, _Options, _Index> > +{ + typedef SparseMatrixBase<SparseVector> SparseBase; + + public: + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=) + + typedef internal::CompressedStorage<Scalar,Index> Storage; + enum { IsColVector = internal::traits<SparseVector>::IsColVector }; + + enum { + Options = _Options + }; + + EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; } + EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; } + EIGEN_STRONG_INLINE Index innerSize() const { return m_size; } + EIGEN_STRONG_INLINE Index outerSize() const { return 1; } + + EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return &m_data.value(0); } + EIGEN_STRONG_INLINE Scalar* valuePtr() { return &m_data.value(0); } + + EIGEN_STRONG_INLINE const Index* innerIndexPtr() const { return &m_data.index(0); } + EIGEN_STRONG_INLINE Index* innerIndexPtr() { return &m_data.index(0); } + + /** \internal */ + inline Storage& data() { return m_data; } + /** \internal */ + inline const Storage& data() const { return m_data; } + + inline Scalar coeff(Index row, Index col) const + { + eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); + return coeff(IsColVector ? row : col); + } + inline Scalar coeff(Index i) const + { + eigen_assert(i>=0 && i<m_size); + return m_data.at(i); + } + + inline Scalar& coeffRef(Index row, Index col) + { + eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); + return coeff(IsColVector ? row : col); + } + + /** \returns a reference to the coefficient value at given index \a i + * This operation involes a log(rho*size) binary search. If the coefficient does not + * exist yet, then a sorted insertion into a sequential buffer is performed. + * + * This insertion might be very costly if the number of nonzeros above \a i is large. + */ + inline Scalar& coeffRef(Index i) + { + eigen_assert(i>=0 && i<m_size); + return m_data.atWithInsertion(i); + } + + public: + + class InnerIterator; + class ReverseInnerIterator; + + inline void setZero() { m_data.clear(); } + + /** \returns the number of non zero coefficients */ + inline Index nonZeros() const { return static_cast<Index>(m_data.size()); } + + inline void startVec(Index outer) + { + EIGEN_UNUSED_VARIABLE(outer); + eigen_assert(outer==0); + } + + inline Scalar& insertBackByOuterInner(Index outer, Index inner) + { + EIGEN_UNUSED_VARIABLE(outer); + eigen_assert(outer==0); + return insertBack(inner); + } + inline Scalar& insertBack(Index i) + { + m_data.append(0, i); + return m_data.value(m_data.size()-1); + } + + inline Scalar& insert(Index row, Index col) + { + eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); + + Index inner = IsColVector ? row : col; + Index outer = IsColVector ? col : row; + eigen_assert(outer==0); + return insert(inner); + } + Scalar& insert(Index i) + { + eigen_assert(i>=0 && i<m_size); + + Index startId = 0; + Index p = Index(m_data.size()) - 1; + // TODO smart realloc + m_data.resize(p+2,1); + + while ( (p >= startId) && (m_data.index(p) > i) ) + { + m_data.index(p+1) = m_data.index(p); + m_data.value(p+1) = m_data.value(p); + --p; + } + m_data.index(p+1) = i; + m_data.value(p+1) = 0; + return m_data.value(p+1); + } + + /** + */ + inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); } + + + inline void finalize() {} + + void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) + { + m_data.prune(reference,epsilon); + } + + void resize(Index rows, Index cols) + { + eigen_assert(rows==1 || cols==1); + resize(IsColVector ? rows : cols); + } + + void resize(Index newSize) + { + m_size = newSize; + m_data.clear(); + } + + void resizeNonZeros(Index size) { m_data.resize(size); } + + inline SparseVector() : m_size(0) { check_template_parameters(); resize(0); } + + inline SparseVector(Index size) : m_size(0) { check_template_parameters(); resize(size); } + + inline SparseVector(Index rows, Index cols) : m_size(0) { check_template_parameters(); resize(rows,cols); } + + template<typename OtherDerived> + inline SparseVector(const SparseMatrixBase<OtherDerived>& other) + : m_size(0) + { + check_template_parameters(); + *this = other.derived(); + } + + inline SparseVector(const SparseVector& other) + : SparseBase(other), m_size(0) + { + check_template_parameters(); + *this = other.derived(); + } + + /** Swaps the values of \c *this and \a other. + * Overloaded for performance: this version performs a \em shallow swap by swaping pointers and attributes only. + * \sa SparseMatrixBase::swap() + */ + inline void swap(SparseVector& other) + { + std::swap(m_size, other.m_size); + m_data.swap(other.m_data); + } + + inline SparseVector& operator=(const SparseVector& other) + { + if (other.isRValue()) + { + swap(other.const_cast_derived()); + } + else + { + resize(other.size()); + m_data = other.m_data; + } + return *this; + } + + template<typename OtherDerived> + inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other) + { + SparseVector tmp(other.size()); + internal::sparse_vector_assign_selector<SparseVector,OtherDerived>::run(tmp,other.derived()); + this->swap(tmp); + return *this; + } + + #ifndef EIGEN_PARSED_BY_DOXYGEN + template<typename Lhs, typename Rhs> + inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product) + { + return Base::operator=(product); + } + #endif + + friend std::ostream & operator << (std::ostream & s, const SparseVector& m) + { + for (Index i=0; i<m.nonZeros(); ++i) + s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") "; + s << std::endl; + return s; + } + + /** Destructor */ + inline ~SparseVector() {} + + /** Overloaded for performance */ + Scalar sum() const; + + public: + + /** \internal \deprecated use setZero() and reserve() */ + EIGEN_DEPRECATED void startFill(Index reserve) + { + setZero(); + m_data.reserve(reserve); + } + + /** \internal \deprecated use insertBack(Index,Index) */ + EIGEN_DEPRECATED Scalar& fill(Index r, Index c) + { + eigen_assert(r==0 || c==0); + return fill(IsColVector ? r : c); + } + + /** \internal \deprecated use insertBack(Index) */ + EIGEN_DEPRECATED Scalar& fill(Index i) + { + m_data.append(0, i); + return m_data.value(m_data.size()-1); + } + + /** \internal \deprecated use insert(Index,Index) */ + EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c) + { + eigen_assert(r==0 || c==0); + return fillrand(IsColVector ? r : c); + } + + /** \internal \deprecated use insert(Index) */ + EIGEN_DEPRECATED Scalar& fillrand(Index i) + { + return insert(i); + } + + /** \internal \deprecated use finalize() */ + EIGEN_DEPRECATED void endFill() {} + + // These two functions were here in the 3.1 release, so let's keep them in case some code rely on them. + /** \internal \deprecated use data() */ + EIGEN_DEPRECATED Storage& _data() { return m_data; } + /** \internal \deprecated use data() */ + EIGEN_DEPRECATED const Storage& _data() const { return m_data; } + +# ifdef EIGEN_SPARSEVECTOR_PLUGIN +# include EIGEN_SPARSEVECTOR_PLUGIN +# endif + +protected: + + static void check_template_parameters() + { + EIGEN_STATIC_ASSERT(NumTraits<Index>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE); + EIGEN_STATIC_ASSERT((_Options&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS); + } + + Storage m_data; + Index m_size; +}; + +template<typename Scalar, int _Options, typename _Index> +class SparseVector<Scalar,_Options,_Index>::InnerIterator +{ + public: + InnerIterator(const SparseVector& vec, Index outer=0) + : m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size())) + { + EIGEN_UNUSED_VARIABLE(outer); + eigen_assert(outer==0); + } + + InnerIterator(const internal::CompressedStorage<Scalar,Index>& data) + : m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size())) + {} + + inline InnerIterator& operator++() { m_id++; return *this; } + + inline Scalar value() const { return m_data.value(m_id); } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id)); } + + inline Index index() const { return m_data.index(m_id); } + inline Index row() const { return IsColVector ? index() : 0; } + inline Index col() const { return IsColVector ? 0 : index(); } + + inline operator bool() const { return (m_id < m_end); } + + protected: + const internal::CompressedStorage<Scalar,Index>& m_data; + Index m_id; + const Index m_end; +}; + +template<typename Scalar, int _Options, typename _Index> +class SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator +{ + public: + ReverseInnerIterator(const SparseVector& vec, Index outer=0) + : m_data(vec.m_data), m_id(static_cast<Index>(m_data.size())), m_start(0) + { + EIGEN_UNUSED_VARIABLE(outer); + eigen_assert(outer==0); + } + + ReverseInnerIterator(const internal::CompressedStorage<Scalar,Index>& data) + : m_data(data), m_id(static_cast<Index>(m_data.size())), m_start(0) + {} + + inline ReverseInnerIterator& operator--() { m_id--; return *this; } + + inline Scalar value() const { return m_data.value(m_id-1); } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id-1)); } + + inline Index index() const { return m_data.index(m_id-1); } + inline Index row() const { return IsColVector ? index() : 0; } + inline Index col() const { return IsColVector ? 0 : index(); } + + inline operator bool() const { return (m_id > m_start); } + + protected: + const internal::CompressedStorage<Scalar,Index>& m_data; + Index m_id; + const Index m_start; +}; + +namespace internal { + +template< typename Dest, typename Src> +struct sparse_vector_assign_selector<Dest,Src,SVA_Inner> { + static void run(Dest& dst, const Src& src) { + eigen_internal_assert(src.innerSize()==src.size()); + for(typename Src::InnerIterator it(src, 0); it; ++it) + dst.insert(it.index()) = it.value(); + } +}; + +template< typename Dest, typename Src> +struct sparse_vector_assign_selector<Dest,Src,SVA_Outer> { + static void run(Dest& dst, const Src& src) { + eigen_internal_assert(src.outerSize()==src.size()); + for(typename Dest::Index i=0; i<src.size(); ++i) + { + typename Src::InnerIterator it(src, i); + if(it) + dst.insert(i) = it.value(); + } + } +}; + +template< typename Dest, typename Src> +struct sparse_vector_assign_selector<Dest,Src,SVA_RuntimeSwitch> { + static void run(Dest& dst, const Src& src) { + if(src.outerSize()==1) sparse_vector_assign_selector<Dest,Src,SVA_Inner>::run(dst, src); + else sparse_vector_assign_selector<Dest,Src,SVA_Outer>::run(dst, src); + } +}; + +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSEVECTOR_H diff --git a/third_party/eigen3/Eigen/src/SparseCore/SparseView.h b/third_party/eigen3/Eigen/src/SparseCore/SparseView.h new file mode 100644 index 0000000000..fd8450463f --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/SparseView.h @@ -0,0 +1,99 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr> +// Copyright (C) 2010 Daniel Lowengrub <lowdanie@gmail.com> +// +// 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_SPARSEVIEW_H +#define EIGEN_SPARSEVIEW_H + +namespace Eigen { + +namespace internal { + +template<typename MatrixType> +struct traits<SparseView<MatrixType> > : traits<MatrixType> +{ + typedef typename MatrixType::Index Index; + typedef Sparse StorageKind; + enum { + Flags = int(traits<MatrixType>::Flags) & (RowMajorBit) + }; +}; + +} // end namespace internal + +template<typename MatrixType> +class SparseView : public SparseMatrixBase<SparseView<MatrixType> > +{ + typedef typename MatrixType::Nested MatrixTypeNested; + typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested; +public: + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseView) + + SparseView(const MatrixType& mat, const Scalar& m_reference = Scalar(0), + typename NumTraits<Scalar>::Real m_epsilon = NumTraits<Scalar>::dummy_precision()) : + m_matrix(mat), m_reference(m_reference), m_epsilon(m_epsilon) {} + + class InnerIterator; + + inline Index rows() const { return m_matrix.rows(); } + inline Index cols() const { return m_matrix.cols(); } + + inline Index innerSize() const { return m_matrix.innerSize(); } + inline Index outerSize() const { return m_matrix.outerSize(); } + +protected: + MatrixTypeNested m_matrix; + Scalar m_reference; + typename NumTraits<Scalar>::Real m_epsilon; +}; + +template<typename MatrixType> +class SparseView<MatrixType>::InnerIterator : public _MatrixTypeNested::InnerIterator +{ + typedef typename SparseView::Index Index; +public: + typedef typename _MatrixTypeNested::InnerIterator IterBase; + InnerIterator(const SparseView& view, Index outer) : + IterBase(view.m_matrix, outer), m_view(view) + { + incrementToNonZero(); + } + + EIGEN_STRONG_INLINE InnerIterator& operator++() + { + IterBase::operator++(); + incrementToNonZero(); + return *this; + } + + using IterBase::value; + +protected: + const SparseView& m_view; + +private: + void incrementToNonZero() + { + while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.m_reference, m_view.m_epsilon)) + { + IterBase::operator++(); + } + } +}; + +template<typename Derived> +const SparseView<Derived> MatrixBase<Derived>::sparseView(const Scalar& m_reference, + const typename NumTraits<Scalar>::Real& m_epsilon) const +{ + return SparseView<Derived>(derived(), m_reference, m_epsilon); +} + +} // end namespace Eigen + +#endif diff --git a/third_party/eigen3/Eigen/src/SparseCore/TriangularSolver.h b/third_party/eigen3/Eigen/src/SparseCore/TriangularSolver.h new file mode 100644 index 0000000000..cb8ad82b4f --- /dev/null +++ b/third_party/eigen3/Eigen/src/SparseCore/TriangularSolver.h @@ -0,0 +1,334 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008 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_SPARSETRIANGULARSOLVER_H +#define EIGEN_SPARSETRIANGULARSOLVER_H + +namespace Eigen { + +namespace internal { + +template<typename Lhs, typename Rhs, int Mode, + int UpLo = (Mode & Lower) + ? Lower + : (Mode & Upper) + ? Upper + : -1, + int StorageOrder = int(traits<Lhs>::Flags) & RowMajorBit> +struct sparse_solve_triangular_selector; + +// forward substitution, row-major +template<typename Lhs, typename Rhs, int Mode> +struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,RowMajor> +{ + typedef typename Rhs::Scalar Scalar; + static void run(const Lhs& lhs, Rhs& other) + { + for(int col=0 ; col<other.cols() ; ++col) + { + for(int i=0; i<lhs.rows(); ++i) + { + Scalar tmp = other.coeff(i,col); + Scalar lastVal(0); + int lastIndex = 0; + for(typename Lhs::InnerIterator it(lhs, i); it; ++it) + { + lastVal = it.value(); + lastIndex = it.index(); + if(lastIndex==i) + break; + tmp -= lastVal * other.coeff(lastIndex,col); + } + if (Mode & UnitDiag) + other.coeffRef(i,col) = tmp; + else + { + eigen_assert(lastIndex==i); + other.coeffRef(i,col) = tmp/lastVal; + } + } + } + } +}; + +// backward substitution, row-major +template<typename Lhs, typename Rhs, int Mode> +struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,RowMajor> +{ + typedef typename Rhs::Scalar Scalar; + static void run(const Lhs& lhs, Rhs& other) + { + for(int col=0 ; col<other.cols() ; ++col) + { + for(int i=lhs.rows()-1 ; i>=0 ; --i) + { + Scalar tmp = other.coeff(i,col); + Scalar l_ii = 0; + typename Lhs::InnerIterator it(lhs, i); + while(it && it.index()<i) + ++it; + if(!(Mode & UnitDiag)) + { + eigen_assert(it && it.index()==i); + l_ii = it.value(); + ++it; + } + else if (it && it.index() == i) + ++it; + for(; it; ++it) + { + tmp -= it.value() * other.coeff(it.index(),col); + } + + if (Mode & UnitDiag) + other.coeffRef(i,col) = tmp; + else + other.coeffRef(i,col) = tmp/l_ii; + } + } + } +}; + +// forward substitution, col-major +template<typename Lhs, typename Rhs, int Mode> +struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,ColMajor> +{ + typedef typename Rhs::Scalar Scalar; + static void run(const Lhs& lhs, Rhs& other) + { + for(int col=0 ; col<other.cols() ; ++col) + { + for(int i=0; i<lhs.cols(); ++i) + { + Scalar& tmp = other.coeffRef(i,col); + if (tmp!=Scalar(0)) // optimization when other is actually sparse + { + typename Lhs::InnerIterator it(lhs, i); + while(it && it.index()<i) + ++it; + if(!(Mode & UnitDiag)) + { + eigen_assert(it && it.index()==i); + tmp /= it.value(); + } + if (it && it.index()==i) + ++it; + for(; it; ++it) + other.coeffRef(it.index(), col) -= tmp * it.value(); + } + } + } + } +}; + +// backward substitution, col-major +template<typename Lhs, typename Rhs, int Mode> +struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,ColMajor> +{ + typedef typename Rhs::Scalar Scalar; + static void run(const Lhs& lhs, Rhs& other) + { + for(int col=0 ; col<other.cols() ; ++col) + { + for(int i=lhs.cols()-1; i>=0; --i) + { + Scalar& tmp = other.coeffRef(i,col); + if (tmp!=Scalar(0)) // optimization when other is actually sparse + { + if(!(Mode & UnitDiag)) + { + // TODO replace this by a binary search. make sure the binary search is safe for partially sorted elements + typename Lhs::ReverseInnerIterator it(lhs, i); + while(it && it.index()!=i) + --it; + eigen_assert(it && it.index()==i); + other.coeffRef(i,col) /= it.value(); + } + typename Lhs::InnerIterator it(lhs, i); + for(; it && it.index()<i; ++it) + other.coeffRef(it.index(), col) -= tmp * it.value(); + } + } + } + } +}; + +} // end namespace internal + +template<typename ExpressionType,int Mode> +template<typename OtherDerived> +void SparseTriangularView<ExpressionType,Mode>::solveInPlace(MatrixBase<OtherDerived>& other) const +{ + eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows()); + eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower))); + + enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit }; + + typedef typename internal::conditional<copy, + typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::type OtherCopy; + OtherCopy otherCopy(other.derived()); + + internal::sparse_solve_triangular_selector<ExpressionType, typename internal::remove_reference<OtherCopy>::type, Mode>::run(m_matrix, otherCopy); + + if (copy) + other = otherCopy; +} + +template<typename ExpressionType,int Mode> +template<typename OtherDerived> +typename internal::plain_matrix_type_column_major<OtherDerived>::type +SparseTriangularView<ExpressionType,Mode>::solve(const MatrixBase<OtherDerived>& other) const +{ + typename internal::plain_matrix_type_column_major<OtherDerived>::type res(other); + solveInPlace(res); + return res; +} + +// pure sparse path + +namespace internal { + +template<typename Lhs, typename Rhs, int Mode, + int UpLo = (Mode & Lower) + ? Lower + : (Mode & Upper) + ? Upper + : -1, + int StorageOrder = int(Lhs::Flags) & (RowMajorBit)> +struct sparse_solve_triangular_sparse_selector; + +// forward substitution, col-major +template<typename Lhs, typename Rhs, int Mode, int UpLo> +struct sparse_solve_triangular_sparse_selector<Lhs,Rhs,Mode,UpLo,ColMajor> +{ + typedef typename Rhs::Scalar Scalar; + typedef typename promote_index_type<typename traits<Lhs>::Index, + typename traits<Rhs>::Index>::type Index; + static void run(const Lhs& lhs, Rhs& other) + { + const bool IsLower = (UpLo==Lower); + AmbiVector<Scalar,Index> tempVector(other.rows()*2); + tempVector.setBounds(0,other.rows()); + + Rhs res(other.rows(), other.cols()); + res.reserve(other.nonZeros()); + + for(int col=0 ; col<other.cols() ; ++col) + { + // FIXME estimate number of non zeros + tempVector.init(.99/*float(other.col(col).nonZeros())/float(other.rows())*/); + tempVector.setZero(); + tempVector.restart(); + for (typename Rhs::InnerIterator rhsIt(other, col); rhsIt; ++rhsIt) + { + tempVector.coeffRef(rhsIt.index()) = rhsIt.value(); + } + + for(int i=IsLower?0:lhs.cols()-1; + IsLower?i<lhs.cols():i>=0; + i+=IsLower?1:-1) + { + tempVector.restart(); + Scalar& ci = tempVector.coeffRef(i); + if (ci!=Scalar(0)) + { + // find + typename Lhs::InnerIterator it(lhs, i); + if(!(Mode & UnitDiag)) + { + if (IsLower) + { + eigen_assert(it.index()==i); + ci /= it.value(); + } + else + ci /= lhs.coeff(i,i); + } + tempVector.restart(); + if (IsLower) + { + if (it.index()==i) + ++it; + for(; it; ++it) + tempVector.coeffRef(it.index()) -= ci * it.value(); + } + else + { + for(; it && it.index()<i; ++it) + tempVector.coeffRef(it.index()) -= ci * it.value(); + } + } + } + + + int count = 0; + // FIXME compute a reference value to filter zeros + for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector/*,1e-12*/); it; ++it) + { + ++ count; +// std::cerr << "fill " << it.index() << ", " << col << "\n"; +// std::cout << it.value() << " "; + // FIXME use insertBack + res.insert(it.index(), col) = it.value(); + } +// std::cout << "tempVector.nonZeros() == " << int(count) << " / " << (other.rows()) << "\n"; + } + res.finalize(); + other = res.markAsRValue(); + } +}; + +} // end namespace internal + +template<typename ExpressionType,int Mode> +template<typename OtherDerived> +void SparseTriangularView<ExpressionType,Mode>::solveInPlace(SparseMatrixBase<OtherDerived>& other) const +{ + eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows()); + eigen_assert( (!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower))); + +// enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit }; + +// typedef typename internal::conditional<copy, +// typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::type OtherCopy; +// OtherCopy otherCopy(other.derived()); + + internal::sparse_solve_triangular_sparse_selector<ExpressionType, OtherDerived, Mode>::run(m_matrix, other.derived()); + +// if (copy) +// other = otherCopy; +} + +#ifdef EIGEN2_SUPPORT + +// deprecated stuff: + +/** \deprecated */ +template<typename Derived> +template<typename OtherDerived> +void SparseMatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other) const +{ + this->template triangular<Flags&(Upper|Lower)>().solveInPlace(other); +} + +/** \deprecated */ +template<typename Derived> +template<typename OtherDerived> +typename internal::plain_matrix_type_column_major<OtherDerived>::type +SparseMatrixBase<Derived>::solveTriangular(const MatrixBase<OtherDerived>& other) const +{ + typename internal::plain_matrix_type_column_major<OtherDerived>::type res(other); + derived().solveTriangularInPlace(res); + return res; +} +#endif // EIGEN2_SUPPORT + +} // end namespace Eigen + +#endif // EIGEN_SPARSETRIANGULARSOLVER_H |