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Diffstat (limited to 'extern/Eigen2/Eigen/src/Sparse/AmbiVector.h')
| -rw-r--r-- | extern/Eigen2/Eigen/src/Sparse/AmbiVector.h | 371 |
1 files changed, 371 insertions, 0 deletions
diff --git a/extern/Eigen2/Eigen/src/Sparse/AmbiVector.h b/extern/Eigen2/Eigen/src/Sparse/AmbiVector.h new file mode 100644 index 00000000000..75001a2fa25 --- /dev/null +++ b/extern/Eigen2/Eigen/src/Sparse/AmbiVector.h @@ -0,0 +1,371 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. Eigen itself is part of the KDE project. +// +// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr> +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see <http://www.gnu.org/licenses/>. + +#ifndef EIGEN_AMBIVECTOR_H +#define EIGEN_AMBIVECTOR_H + +/** \internal + * Hybrid sparse/dense vector class designed for intensive read-write operations. + * + * See BasicSparseLLT and SparseProduct for usage examples. + */ +template<typename _Scalar> class AmbiVector +{ + public: + typedef _Scalar Scalar; + typedef typename NumTraits<Scalar>::Real RealScalar; + AmbiVector(int size) + : m_buffer(0), m_size(0), m_allocatedSize(0), m_allocatedElements(0), m_mode(-1) + { + resize(size); + } + + void init(RealScalar estimatedDensity); + void init(int mode); + + void nonZeros() const; + + /** Specifies a sub-vector to work on */ + void setBounds(int start, int end) { m_start = start; m_end = end; } + + void setZero(); + + void restart(); + Scalar& coeffRef(int i); + Scalar coeff(int i); + + class Iterator; + + ~AmbiVector() { delete[] m_buffer; } + + void resize(int size) + { + if (m_allocatedSize < size) + reallocate(size); + m_size = size; + } + + int size() const { return m_size; } + + protected: + + void reallocate(int 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) + { + int 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() + { + int copyElements = m_allocatedElements; + m_allocatedElements = std::min(int(m_allocatedElements*1.5),m_size); + int 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)); + } + + protected: + // element type of the linked list + struct ListEl + { + int next; + int index; + Scalar value; + }; + + // used to store data in both mode + Scalar* m_buffer; + int m_size; + int m_start; + int m_end; + int m_allocatedSize; + int m_allocatedElements; + int m_mode; + + // linked list mode + int m_llStart; + int m_llCurrent; + int m_llSize; + + private: + AmbiVector(const AmbiVector&); + +}; + +/** \returns the number of non zeros in the current sub vector */ +template<typename Scalar> +void AmbiVector<Scalar>::nonZeros() const +{ + if (m_mode==IsSparse) + return m_llSize; + else + return m_end - m_start; +} + +template<typename Scalar> +void AmbiVector<Scalar>::init(RealScalar estimatedDensity) +{ + if (estimatedDensity>0.1) + init(IsDense); + else + init(IsSparse); +} + +template<typename Scalar> +void AmbiVector<Scalar>::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> +void AmbiVector<Scalar>::restart() +{ + m_llCurrent = m_llStart; +} + +/** Set all coefficients of current subvector to zero */ +template<typename Scalar> +void AmbiVector<Scalar>::setZero() +{ + if (m_mode==IsDense) + { + for (int i=m_start; i<m_end; ++i) + m_buffer[i] = Scalar(0); + } + else + { + ei_assert(m_mode==IsSparse); + m_llSize = 0; + m_llStart = -1; + } +} + +template<typename Scalar> +Scalar& AmbiVector<Scalar>::coeffRef(int 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 + ei_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 + { + int nextel = llElements[m_llCurrent].next; + ei_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(); + ei_internal_assert(m_llSize<m_size && "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> +Scalar AmbiVector<Scalar>::coeff(int i) +{ + if (m_mode==IsDense) + return m_buffer[i]; + else + { + ListEl* EIGEN_RESTRICT llElements = reinterpret_cast<ListEl*>(m_buffer); + ei_assert(m_mode==IsSparse); + if ((m_llSize==0) || (i<llElements[m_llStart].index)) + { + return Scalar(0); + } + else + { + int 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 Scalar(0); + } + } +} + +/** Iterator over the nonzero coefficients */ +template<typename _Scalar> +class AmbiVector<_Scalar>::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, RealScalar epsilon = RealScalar(0.1)*precision<RealScalar>()) + : m_vector(vec) + { + m_epsilon = epsilon; + m_isDense = m_vector.m_mode==IsDense; + if (m_isDense) + { + 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 && ei_abs(llElements[m_currentEl].value)<m_epsilon) + m_currentEl = llElements[m_currentEl].next; + if (m_currentEl<0) + { + m_cachedIndex = -1; + } + else + { + m_cachedIndex = llElements[m_currentEl].index; + m_cachedValue = llElements[m_currentEl].value; + } + } + } + + int index() const { return m_cachedIndex; } + Scalar value() const { return m_cachedValue; } + + operator bool() const { return m_cachedIndex>=0; } + + Iterator& operator++() + { + if (m_isDense) + { + do { + ++m_cachedIndex; + } while (m_cachedIndex<m_vector.m_end && ei_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 && ei_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 + int m_currentEl; // the current element in sparse/linked-list mode + RealScalar m_epsilon; // epsilon used to prune zero coefficients + int m_cachedIndex; // current coordinate + Scalar m_cachedValue; // current value + bool m_isDense; // mode of the vector +}; + + +#endif // EIGEN_AMBIVECTOR_H |