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864 lines
43 KiB
864 lines
43 KiB
#include <boost/functional/hash.hpp>
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// To detect whether the usage of TBB is possible, this include is neccessary
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#include "storm-config.h"
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#ifdef STORM_HAVE_INTELTBB
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#include "tbb/tbb.h"
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#endif
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#include "src/storage/SparseMatrix.h"
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#include "src/exceptions/InvalidStateException.h"
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#include "log4cplus/logger.h"
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#include "log4cplus/loggingmacros.h"
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extern log4cplus::Logger logger;
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namespace storm {
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namespace storage {
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template<typename T>
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SparseMatrixBuilder<T>::SparseMatrixBuilder(uint_fast64_t rows, uint_fast64_t columns, uint_fast64_t entries) : rowCountSet(rows != 0), rowCount(rows), columnCountSet(columns != 0), columnCount(columns), entryCount(entries), storagePreallocated(rows != 0 && columns != 0 && entries != 0), columnsAndValues(), rowIndications(), currentEntryCount(0), lastRow(0), lastColumn(0) {
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this->prepareInternalStorage();
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}
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template<typename T>
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void SparseMatrixBuilder<T>::addNextValue(uint_fast64_t row, uint_fast64_t column, T const& value) {
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// Depending on whether the internal data storage was preallocated or not, adding the value is done somewhat
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// differently.
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if (storagePreallocated) {
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// Check whether the given row and column positions are valid and throw error otherwise.
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if (row >= rowCount || column >= columnCount) {
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throw storm::exceptions::OutOfRangeException() << "Illegal call to SparseMatrixBuilder::addNextValue: adding entry at out-of-bounds position (" << row << ", " << column << ") in matrix of size (" << rowCount << ", " << columnCount << ").";
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}
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} else {
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if (rowCountSet) {
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if (row >= rowCount) {
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throw storm::exceptions::OutOfRangeException() << "Illegal call to SparseMatrixBuilder::addNextValue: adding entry at out-of-bounds row " << row << " in matrix with " << rowCount << " rows.";
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}
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}
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if (columnCountSet) {
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if (column >= columnCount) {
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throw storm::exceptions::OutOfRangeException() << "Illegal call to SparseMatrixBuilder::addNextValue: adding entry at out-of-bounds column " << column << " in matrix with " << columnCount << " columns.";
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}
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}
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}
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// Check that we did not move backwards wrt. the row.
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if (row < lastRow) {
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throw storm::exceptions::InvalidArgumentException() << "Illegal call to SparseMatrixBuilder::addNextValue: adding an element in row " << row << ", but an element in row " << lastRow << " has already been added.";
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}
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// Check that we did not move backwards wrt. to column.
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if (row == lastRow && column < lastColumn) {
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throw storm::exceptions::InvalidArgumentException() << "Illegal call to SparseMatrixBuilder::addNextValue: adding an element in column " << column << " in row " << row << ", but an element in column " << lastColumn << " has already been added in that row.";
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}
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// If we switched to another row, we have to adjust the missing entries in the row indices vector.
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if (row != lastRow) {
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if (storagePreallocated) {
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// If the storage was preallocated, we can access the elements in the vectors with the subscript
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// operator.
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for (uint_fast64_t i = lastRow + 1; i <= row; ++i) {
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rowIndications[i] = currentEntryCount;
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}
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} else {
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// Otherwise, we need to push the correct values to the vectors, which might trigger reallocations.
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for (uint_fast64_t i = lastRow + 1; i <= row; ++i) {
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rowIndications.push_back(currentEntryCount);
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}
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}
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lastRow = row;
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}
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lastColumn = column;
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// Finally, set the element and increase the current size.
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if (storagePreallocated) {
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columnsAndValues[currentEntryCount] = std::make_pair(column, value);
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} else {
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columnsAndValues.emplace_back(column, value);
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if (!columnCountSet) {
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columnCount = std::max(columnCount, column + 1);
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}
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if (!rowCountSet) {
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rowCount = row + 1;
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}
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}
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++currentEntryCount;
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}
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template<typename T>
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SparseMatrix<T> SparseMatrixBuilder<T>::build(uint_fast64_t overriddenRowCount, uint_fast64_t overriddenColumnCount) {
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// Check whether it's safe to finalize the matrix and throw error otherwise.
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if (storagePreallocated && currentEntryCount != entryCount) {
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throw storm::exceptions::InvalidStateException() << "Illegal call to SparseMatrix::finalize: expected " << entryCount << " entries, but got " << currentEntryCount << " instead.";
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} else {
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// Fill in the missing entries in the row indices array, as there may be empty rows at the end.
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if (storagePreallocated) {
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for (uint_fast64_t i = lastRow + 1; i < rowCount; ++i) {
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rowIndications[i] = currentEntryCount;
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}
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} else {
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if (!rowCountSet) {
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rowCount = std::max(overriddenRowCount, rowCount);
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}
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for (uint_fast64_t i = lastRow + 1; i < rowCount; ++i) {
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rowIndications.push_back(currentEntryCount);
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}
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}
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// We put a sentinel element at the last position of the row indices array. This eases iteration work,
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// as now the indices of row i are always between rowIndications[i] and rowIndications[i + 1], also for
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// the first and last row.
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if (storagePreallocated) {
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rowIndications[rowCount] = currentEntryCount;
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} else {
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rowIndications.push_back(currentEntryCount);
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if (!columnCountSet) {
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columnCount = std::max(columnCount, overriddenColumnCount);
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}
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}
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entryCount = currentEntryCount;
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}
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return SparseMatrix<T>(columnCount, std::move(rowIndications), std::move(columnsAndValues));
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}
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template<typename T>
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void SparseMatrixBuilder<T>::prepareInternalStorage() {
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// Only allocate the memory if the dimensions of the matrix are already known.
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if (storagePreallocated) {
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columnsAndValues = std::vector<std::pair<uint_fast64_t, T>>(entryCount, std::make_pair(0, storm::utility::constantZero<T>()));
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rowIndications = std::vector<uint_fast64_t>(rowCount + 1, 0);
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} else {
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rowIndications.push_back(0);
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}
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}
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template<typename T>
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SparseMatrix<T>::rows::rows(iterator begin, uint_fast64_t entryCount) : beginIterator(begin), entryCount(entryCount) {
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// Intentionally left empty.
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}
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template<typename T>
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typename SparseMatrix<T>::iterator SparseMatrix<T>::rows::begin() {
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return beginIterator;
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}
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template<typename T>
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typename SparseMatrix<T>::iterator SparseMatrix<T>::rows::end() {
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return beginIterator + entryCount;
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}
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template<typename T>
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SparseMatrix<T>::const_rows::const_rows(const_iterator begin, uint_fast64_t entryCount) : beginIterator(begin), entryCount(entryCount) {
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// Intentionally left empty.
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}
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template<typename T>
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typename SparseMatrix<T>::const_iterator SparseMatrix<T>::const_rows::begin() const {
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return beginIterator;
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}
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template<typename T>
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typename SparseMatrix<T>::const_iterator SparseMatrix<T>::const_rows::end() const {
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return beginIterator + entryCount;
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}
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template<typename T>
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SparseMatrix<T>::SparseMatrix() : rowCount(0), columnCount(0), entryCount(0), columnsAndValues(), rowIndications() {
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// Intentionally left empty.
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}
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template<typename T>
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SparseMatrix<T>::SparseMatrix(SparseMatrix<T> const& other) : rowCount(other.rowCount), columnCount(other.columnCount), entryCount(other.entryCount), columnsAndValues(other.columnsAndValues), rowIndications(other.rowIndications) {
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// Intentionally left empty.
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}
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template<typename T>
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SparseMatrix<T>::SparseMatrix(SparseMatrix<T>&& other) : rowCount(other.rowCount), columnCount(other.columnCount), entryCount(other.entryCount), columnsAndValues(std::move(other.columnsAndValues)), rowIndications(std::move(other.rowIndications)) {
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// Now update the source matrix
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other.rowCount = 0;
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other.columnCount = 0;
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other.entryCount = 0;
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}
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template<typename T>
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SparseMatrix<T>::SparseMatrix(uint_fast64_t columnCount, std::vector<uint_fast64_t> const& rowIndications, std::vector<std::pair<uint_fast64_t, T>> const& columnsAndValues) : rowCount(rowIndications.size() - 1), columnCount(columnCount), entryCount(columnsAndValues.size()), columnsAndValues(columnsAndValues), rowIndications(rowIndications) {
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// Intentionally left empty.
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}
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template<typename T>
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SparseMatrix<T>::SparseMatrix(uint_fast64_t columnCount, std::vector<uint_fast64_t>&& rowIndications, std::vector<std::pair<uint_fast64_t, T>>&& columnsAndValues) : rowCount(rowIndications.size() - 1), columnCount(columnCount), entryCount(columnsAndValues.size()), columnsAndValues(std::move(columnsAndValues)), rowIndications(std::move(rowIndications)) {
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// Intentionally left empty.
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}
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template<typename T>
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SparseMatrix<T>& SparseMatrix<T>::operator=(SparseMatrix<T> const& other) {
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// Only perform assignment if source and target are not the same.
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if (this != &other) {
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rowCount = other.rowCount;
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columnCount = other.columnCount;
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entryCount = other.entryCount;
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columnsAndValues = other.columnsAndValues;
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rowIndications = other.rowIndications;
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}
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return *this;
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}
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template<typename T>
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SparseMatrix<T>& SparseMatrix<T>::operator=(SparseMatrix<T>&& other) {
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// Only perform assignment if source and target are not the same.
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if (this != &other) {
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rowCount = other.rowCount;
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columnCount = other.columnCount;
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entryCount = other.entryCount;
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columnsAndValues = std::move(other.columnsAndValues);
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rowIndications = std::move(other.rowIndications);
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}
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return *this;
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}
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template<typename T>
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bool SparseMatrix<T>::operator==(SparseMatrix<T> const& other) const {
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if (this == &other) {
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return true;
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}
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bool equalityResult = true;
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equalityResult &= rowCount == other.rowCount;
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equalityResult &= columnCount == other.columnCount;
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// For the actual contents, we need to do a little bit more work, because we want to ignore elements that
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// are set to zero, please they may be represented implicitly in the other matrix.
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for (uint_fast64_t row = 0; row < this->getRowCount(); ++row) {
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for (const_iterator it1 = this->begin(row), ite1 = this->end(row), it2 = other.begin(row), ite2 = other.end(row); it1 != ite1 && it2 != ite2; ++it1, ++it2) {
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// Skip over all zero entries in both matrices.
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while (it1 != ite1 && it1->second == storm::utility::constantZero<T>()) {
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++it1;
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}
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while (it2 != ite2 && it2->second == storm::utility::constantZero<T>()) {
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++it2;
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}
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if ((it1 == ite1) || (it2 == ite2)) {
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equalityResult = (it1 == ite1) ^ (it2 == ite2);
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break;
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} else {
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if (it1->first != it2->first || it1->second != it2->second) {
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equalityResult = false;
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break;
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}
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}
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}
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}
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return equalityResult;
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}
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template<typename T>
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uint_fast64_t SparseMatrix<T>::getRowCount() const {
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return rowCount;
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}
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template<typename T>
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uint_fast64_t SparseMatrix<T>::getColumnCount() const {
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return columnCount;
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}
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template<typename T>
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uint_fast64_t SparseMatrix<T>::getEntryCount() const {
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return entryCount;
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}
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template<typename T>
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void SparseMatrix<T>::makeRowsAbsorbing(storm::storage::BitVector const& rows) {
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for (auto row : rows) {
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makeRowAbsorbing(row, row);
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}
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}
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template<typename T>
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void SparseMatrix<T>::makeRowsAbsorbing(storm::storage::BitVector const& rowGroupConstraint, std::vector<uint_fast64_t> const& rowGroupIndices) {
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for (auto rowGroup : rowGroupConstraint) {
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for (uint_fast64_t row = rowGroupIndices[rowGroup]; row < rowGroupIndices[rowGroup + 1]; ++row) {
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makeRowAbsorbing(row, rowGroup);
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}
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}
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}
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template<typename T>
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void SparseMatrix<T>::makeRowAbsorbing(uint_fast64_t row, uint_fast64_t column) {
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if (row > rowCount) {
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throw storm::exceptions::OutOfRangeException() << "Illegal call to SparseMatrix::makeRowAbsorbing: access to row " << row << " is out of bounds.";
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}
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iterator columnValuePtr = this->begin(row);
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iterator columnValuePtrEnd = this->end(row);
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// If the row has no elements in it, we cannot make it absorbing, because we would need to move all elements
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// in the vector of nonzeros otherwise.
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if (columnValuePtr >= columnValuePtrEnd) {
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throw storm::exceptions::InvalidStateException() << "Illegal call to SparseMatrix::makeRowAbsorbing: cannot make row " << row << " absorbing, but there is no entry in this row.";
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}
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// If there is at least one entry in this row, we can just set it to one, modify its column value to the
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// one given by the parameter and set all subsequent elements of this row to zero.
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columnValuePtr->first = column;
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columnValuePtr->second = storm::utility::constantOne<T>();
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++columnValuePtr;
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for (; columnValuePtr != columnValuePtrEnd; ++columnValuePtr) {
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columnValuePtr->first = 0;
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columnValuePtr->second = storm::utility::constantZero<T>();
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}
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}
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template<typename T>
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T SparseMatrix<T>::getConstrainedRowSum(uint_fast64_t row, storm::storage::BitVector const& constraint) const {
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T result(0);
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for (const_iterator it = this->begin(row), ite = this->end(row); it != ite; ++it) {
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if (constraint.get(it->first)) {
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result += it->second;
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}
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}
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return result;
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}
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template<typename T>
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std::vector<T> SparseMatrix<T>::getConstrainedRowSumVector(storm::storage::BitVector const& rowConstraint, storm::storage::BitVector const& columnConstraint) const {
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std::vector<T> result(rowConstraint.getNumberOfSetBits());
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uint_fast64_t currentRowCount = 0;
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for (auto row : rowConstraint) {
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result[currentRowCount++] = getConstrainedRowSum(row, columnConstraint);
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}
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return result;
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}
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template<typename T>
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std::vector<T> SparseMatrix<T>::getConstrainedRowSumVector(storm::storage::BitVector const& rowGroupConstraint, std::vector<uint_fast64_t> const& rowGroupIndices, storm::storage::BitVector const& columnConstraint) const {
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std::vector<T> result;
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result.reserve(rowGroupConstraint.getNumberOfSetBits());
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for (auto rowGroup : rowGroupConstraint) {
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for (uint_fast64_t row = rowGroupIndices[rowGroup]; row < rowGroupIndices[rowGroup + 1]; ++row) {
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result.push_back(getConstrainedRowSum(row, columnConstraint));
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}
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}
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return result;
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}
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template<typename T>
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SparseMatrix<T> SparseMatrix<T>::getSubmatrix(storm::storage::BitVector const& constraint) const {
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// Create a fake row grouping to reduce this to a call to a more general method.
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std::vector<uint_fast64_t> rowGroupIndices(rowCount + 1);
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uint_fast64_t i = 0;
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for (std::vector<uint_fast64_t>::iterator it = rowGroupIndices.begin(); it != rowGroupIndices.end(); ++it, ++i) {
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*it = i;
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}
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return getSubmatrix(constraint, constraint, rowGroupIndices);
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}
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template<typename T>
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SparseMatrix<T> SparseMatrix<T>::getSubmatrix(storm::storage::BitVector const& rowGroupConstraint, std::vector<uint_fast64_t> const& rowGroupIndices, bool insertDiagonalEntries) const {
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return getSubmatrix(rowGroupConstraint, rowGroupConstraint, rowGroupIndices, insertDiagonalEntries);
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}
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template<typename T>
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SparseMatrix<T> SparseMatrix<T>::getSubmatrix(storm::storage::BitVector const& rowGroupConstraint, storm::storage::BitVector const& columnConstraint, std::vector<uint_fast64_t> const& rowGroupIndices, bool insertDiagonalEntries) const {
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// First, we need to determine the number of entries and the number of rows of the submatrix.
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uint_fast64_t subEntries = 0;
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uint_fast64_t subRows = 0;
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for (auto index : rowGroupConstraint) {
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subRows += rowGroupIndices[index + 1] - rowGroupIndices[index];
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for (uint_fast64_t i = rowGroupIndices[index]; i < rowGroupIndices[index + 1]; ++i) {
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bool foundDiagonalElement = false;
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for (const_iterator it = this->begin(i), ite = this->end(i); it != ite; ++it) {
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if (columnConstraint.get(it->first)) {
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++subEntries;
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if (index == it->first) {
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foundDiagonalElement = true;
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}
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}
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}
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// If requested, we need to reserve one entry more for inserting the diagonal zero entry.
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if (insertDiagonalEntries && !foundDiagonalElement) {
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++subEntries;
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}
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}
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}
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// Create and initialize resulting matrix.
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SparseMatrixBuilder<T> matrixBuilder(subRows, columnConstraint.getNumberOfSetBits(), subEntries);
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// Create a temporary vector that stores for each index whose bit is set to true the number of bits that
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// were set before that particular index.
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std::vector<uint_fast64_t> bitsSetBeforeIndex;
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bitsSetBeforeIndex.reserve(columnCount);
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// Compute the information to fill this vector.
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uint_fast64_t lastIndex = 0;
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uint_fast64_t currentNumberOfSetBits = 0;
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// If we are requested to add missing diagonal entries, we need to make sure the corresponding rows are also
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// taken.
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storm::storage::BitVector columnBitCountConstraint = columnConstraint;
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if (insertDiagonalEntries) {
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columnBitCountConstraint |= rowGroupConstraint;
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}
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for (auto index : columnBitCountConstraint) {
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while (lastIndex <= index) {
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bitsSetBeforeIndex.push_back(currentNumberOfSetBits);
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++lastIndex;
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}
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++currentNumberOfSetBits;
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}
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// Copy over selected entries.
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uint_fast64_t rowCount = 0;
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for (auto index : rowGroupConstraint) {
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for (uint_fast64_t i = rowGroupIndices[index]; i < rowGroupIndices[index + 1]; ++i) {
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bool insertedDiagonalElement = false;
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for (const_iterator it = this->begin(i), ite = this->end(i); it != ite; ++it) {
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if (columnConstraint.get(it->first)) {
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if (index == it->first) {
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insertedDiagonalElement = true;
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} else if (insertDiagonalEntries && !insertedDiagonalElement && it->first > index) {
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matrixBuilder.addNextValue(rowCount, bitsSetBeforeIndex[index], storm::utility::constantZero<T>());
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insertedDiagonalElement = true;
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}
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matrixBuilder.addNextValue(rowCount, bitsSetBeforeIndex[it->first], it->second);
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}
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}
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if (insertDiagonalEntries && !insertedDiagonalElement) {
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matrixBuilder.addNextValue(rowCount, bitsSetBeforeIndex[index], storm::utility::constantZero<T>());
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}
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++rowCount;
|
|
}
|
|
}
|
|
|
|
return matrixBuilder.build();
|
|
}
|
|
|
|
template<typename T>
|
|
SparseMatrix<T> SparseMatrix<T>::getSubmatrix(std::vector<uint_fast64_t> const& rowGroupToRowIndexMapping, std::vector<uint_fast64_t> const& rowGroupIndices, bool insertDiagonalEntries) const {
|
|
// First, we need to count how many non-zero entries the resulting matrix will have and reserve space for
|
|
// diagonal entries if requested.
|
|
uint_fast64_t subEntries = 0;
|
|
for (uint_fast64_t rowGroupIndex = 0, rowGroupIndexEnd = rowGroupToRowIndexMapping.size(); rowGroupIndex < rowGroupIndexEnd; ++rowGroupIndex) {
|
|
// Determine which row we need to select from the current row group.
|
|
uint_fast64_t rowToCopy = rowGroupIndices[rowGroupIndex] + rowGroupToRowIndexMapping[rowGroupIndex];
|
|
|
|
// Iterate through that row and count the number of slots we have to reserve for copying.
|
|
bool foundDiagonalElement = false;
|
|
for (const_iterator it = this->begin(rowToCopy), ite = this->end(rowToCopy); it != ite; ++it) {
|
|
if (it->first == rowGroupIndex) {
|
|
foundDiagonalElement = true;
|
|
}
|
|
++subEntries;
|
|
}
|
|
if (insertDiagonalEntries && !foundDiagonalElement) {
|
|
++subEntries;
|
|
}
|
|
}
|
|
|
|
// Now create the matrix to be returned with the appropriate size.
|
|
SparseMatrixBuilder<T> matrixBuilder(rowGroupIndices.size() - 1, columnCount, subEntries);
|
|
|
|
// Copy over the selected lines from the source matrix.
|
|
for (uint_fast64_t rowGroupIndex = 0, rowGroupIndexEnd = rowGroupToRowIndexMapping.size(); rowGroupIndex < rowGroupIndexEnd; ++rowGroupIndex) {
|
|
// Determine which row we need to select from the current row group.
|
|
uint_fast64_t rowToCopy = rowGroupIndices[rowGroupIndex] + rowGroupToRowIndexMapping[rowGroupIndex];
|
|
|
|
// Iterate through that row and copy the entries. This also inserts a zero element on the diagonal if
|
|
// there is no entry yet.
|
|
bool insertedDiagonalElement = false;
|
|
for (const_iterator it = this->begin(rowToCopy), ite = this->end(rowToCopy); it != ite; ++it) {
|
|
if (it->first == rowGroupIndex) {
|
|
insertedDiagonalElement = true;
|
|
} else if (insertDiagonalEntries && !insertedDiagonalElement && it->first > rowGroupIndex) {
|
|
matrixBuilder.addNextValue(rowGroupIndex, rowGroupIndex, storm::utility::constantZero<T>());
|
|
insertedDiagonalElement = true;
|
|
}
|
|
matrixBuilder.addNextValue(rowGroupIndex, it->first, it->second);
|
|
}
|
|
if (insertDiagonalEntries && !insertedDiagonalElement) {
|
|
matrixBuilder.addNextValue(rowGroupIndex, rowGroupIndex, storm::utility::constantZero<T>());
|
|
}
|
|
}
|
|
|
|
// Finalize created matrix and return result.
|
|
return matrixBuilder.build();
|
|
}
|
|
|
|
template <typename T>
|
|
SparseMatrix<T> SparseMatrix<T>::transpose() const {
|
|
uint_fast64_t rowCount = this->columnCount;
|
|
uint_fast64_t columnCount = this->rowCount;
|
|
uint_fast64_t entryCount = this->entryCount;
|
|
|
|
std::vector<uint_fast64_t> rowIndications(rowCount + 1);
|
|
std::vector<std::pair<uint_fast64_t, T>> columnsAndValues(entryCount);
|
|
|
|
// First, we need to count how many entries each column has.
|
|
for (uint_fast64_t row = 0; row < this->rowCount; ++row) {
|
|
for (const_iterator it = this->begin(row), ite = this->end(row); it != ite; ++it) {
|
|
if (it->second > 0) {
|
|
++rowIndications[it->first + 1];
|
|
}
|
|
}
|
|
}
|
|
|
|
// Now compute the accumulated offsets.
|
|
for (uint_fast64_t i = 1; i < rowCount + 1; ++i) {
|
|
rowIndications[i] = rowIndications[i - 1] + rowIndications[i];
|
|
}
|
|
|
|
// Create an array that stores the index for the next value to be added for
|
|
// each row in the transposed matrix. Initially this corresponds to the previously
|
|
// computed accumulated offsets.
|
|
std::vector<uint_fast64_t> nextIndices = rowIndications;
|
|
|
|
// Now we are ready to actually fill in the values of the transposed matrix.
|
|
for (uint_fast64_t row = 0; row < this->rowCount; ++row) {
|
|
for (const_iterator it = this->begin(row), ite = this->end(row); it != ite; ++it) {
|
|
if (it->second > 0) {
|
|
columnsAndValues[nextIndices[it->first]] = std::make_pair(row, it->second);
|
|
nextIndices[it->first]++;
|
|
}
|
|
}
|
|
}
|
|
|
|
storm::storage::SparseMatrix<T> transposedMatrix(columnCount, std::move(rowIndications), std::move(columnsAndValues));
|
|
|
|
return transposedMatrix;
|
|
}
|
|
|
|
template<typename T>
|
|
void SparseMatrix<T>::convertToEquationSystem() {
|
|
invertDiagonal();
|
|
negateAllNonDiagonalEntries();
|
|
}
|
|
|
|
template<typename T>
|
|
void SparseMatrix<T>::invertDiagonal() {
|
|
// Check if the matrix is square, because only then it makes sense to perform this
|
|
// transformation.
|
|
if (this->getRowCount() != this->getColumnCount()) {
|
|
throw storm::exceptions::InvalidArgumentException() << "SparseMatrix::invertDiagonal requires the Matrix to be square!";
|
|
}
|
|
|
|
// Now iterate over all rows and set the diagonal elements to the inverted value.
|
|
// If there is a row without the diagonal element, an exception is thrown.
|
|
T one = storm::utility::constantOne<T>();
|
|
bool foundDiagonalElement = false;
|
|
for (uint_fast64_t row = 0; row < rowCount; ++row) {
|
|
for (iterator it = this->begin(row), ite = this->end(row); it != ite; ++it) {
|
|
if (it->first == row) {
|
|
it->second = one - it->second;
|
|
foundDiagonalElement = true;
|
|
}
|
|
}
|
|
|
|
// Throw an exception if a row did not have an element on the diagonal.
|
|
if (!foundDiagonalElement) {
|
|
throw storm::exceptions::InvalidArgumentException() << "Illegal call to SparseMatrix::invertDiagonal: matrix is missing diagonal entries.";
|
|
}
|
|
}
|
|
}
|
|
|
|
template<typename T>
|
|
void SparseMatrix<T>::negateAllNonDiagonalEntries() {
|
|
// Check if the matrix is square, because only then it makes sense to perform this transformation.
|
|
if (this->getRowCount() != this->getColumnCount()) {
|
|
throw storm::exceptions::InvalidArgumentException() << "Illegal call to SparseMatrix::invertDiagonal: matrix is non-square.";
|
|
}
|
|
|
|
// Iterate over all rows and negate all the elements that are not on the diagonal.
|
|
for (uint_fast64_t row = 0; row < rowCount; ++row) {
|
|
for (iterator it = this->begin(row), ite = this->end(row); it != ite; ++it) {
|
|
if (it->first != row) {
|
|
it->second = -it->second;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template<typename T>
|
|
void SparseMatrix<T>::deleteDiagonalEntries() {
|
|
// Check if the matrix is square, because only then it makes sense to perform this transformation.
|
|
if (this->getRowCount() != this->getColumnCount()) {
|
|
throw storm::exceptions::InvalidArgumentException() << "Illegal call to SparseMatrix::deleteDiagonalEntries: matrix is non-square.";
|
|
}
|
|
|
|
// Iterate over all rows and negate all the elements that are not on the diagonal.
|
|
for (uint_fast64_t row = 0; row < rowCount; ++row) {
|
|
for (iterator it = this->begin(row), ite = this->end(row); it != ite; ++it) {
|
|
if (it->first == row) {
|
|
it->second = storm::utility::constantZero<T>();
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template<typename T>
|
|
typename std::pair<storm::storage::SparseMatrix<T>, storm::storage::SparseMatrix<T>> SparseMatrix<T>::getJacobiDecomposition() const {
|
|
if (rowCount != columnCount) {
|
|
throw storm::exceptions::InvalidArgumentException() << "Illegal call to SparseMatrix::invertDiagonal: matrix is non-square.";
|
|
}
|
|
storm::storage::SparseMatrix<T> resultLU(*this);
|
|
resultLU.deleteDiagonalEntries();
|
|
|
|
SparseMatrixBuilder<T> dInvBuilder(rowCount, columnCount, rowCount);
|
|
|
|
// Copy entries to the appropriate matrices.
|
|
for (uint_fast64_t rowNumber = 0; rowNumber < rowCount; ++rowNumber) {
|
|
|
|
// Because the matrix may have several entries on the diagonal, we need to sum them before we are able
|
|
// to invert the entry.
|
|
T diagonalValue = storm::utility::constantZero<T>();
|
|
for (const_iterator it = this->begin(rowNumber), ite = this->end(rowNumber); it != ite; ++it) {
|
|
if (it->first == rowNumber) {
|
|
diagonalValue += it->second;
|
|
} else if (it->first > rowNumber) {
|
|
break;
|
|
}
|
|
}
|
|
dInvBuilder.addNextValue(rowNumber, rowNumber, storm::utility::constantOne<T>() / diagonalValue);
|
|
}
|
|
|
|
return std::make_pair(std::move(resultLU), dInvBuilder.build());
|
|
}
|
|
|
|
template<typename T>
|
|
std::vector<T> SparseMatrix<T>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<T> const& otherMatrix) const {
|
|
std::vector<T> result(rowCount, storm::utility::constantZero<T>());
|
|
|
|
// Iterate over all elements of the current matrix and either continue with the next element in case the
|
|
// given matrix does not have a non-zero element at this column position, or multiply the two entries and
|
|
// add the result to the corresponding position in the vector.
|
|
for (uint_fast64_t row = 0; row < rowCount && row < otherMatrix.rowCount; ++row) {
|
|
for (const_iterator it1 = this->begin(row), ite1 = this->end(row), it2 = otherMatrix.begin(row), ite2 = otherMatrix.end(row); it1 != ite1 && it2 != ite2; ++it1) {
|
|
if (it1->first < it2->first) {
|
|
continue;
|
|
} else {
|
|
// If the precondition of this method (i.e. that the given matrix is a submatrix
|
|
// of the current one) was fulfilled, we know now that the two elements are in
|
|
// the same column, so we can multiply and add them to the row sum vector.
|
|
result[row] += it2->second * it1->second;
|
|
++it2;
|
|
}
|
|
}
|
|
}
|
|
|
|
return result;
|
|
}
|
|
|
|
|
|
template<typename T>
|
|
void SparseMatrix<T>::multiplyWithVector(std::vector<T> const& vector, std::vector<T>& result) const {
|
|
#ifdef STORM_HAVE_INTELTBB
|
|
tbb::parallel_for(tbb::blocked_range<uint_fast64_t>(0, result.size(), 10),
|
|
[&] (tbb::blocked_range<uint_fast64_t> const& range) {
|
|
uint_fast64_t startRow = range.begin();
|
|
uint_fast64_t endRow = range.end();
|
|
const_iterator it = this->begin(startRow);
|
|
const_iterator ite;
|
|
typename std::vector<uint_fast64_t>::const_iterator rowIterator = this->rowIndications.begin() + startRow;
|
|
typename std::vector<uint_fast64_t>::const_iterator rowIteratorEnd = this->rowIndications.begin() + endRow;
|
|
typename std::vector<T>::iterator resultIterator = result.begin() + startRow;
|
|
typename std::vector<T>::iterator resultIteratorEnd = result.begin() + endRow;
|
|
|
|
for (; resultIterator != resultIteratorEnd; ++rowIterator, ++resultIterator) {
|
|
*resultIterator = storm::utility::constantZero<T>();
|
|
|
|
for (ite = this->begin() + *(rowIterator + 1); it != ite; ++it) {
|
|
*resultIterator += it->second * vector[it->first];
|
|
}
|
|
}
|
|
});
|
|
#else
|
|
const_iterator it = this->begin();
|
|
const_iterator ite;
|
|
typename std::vector<uint_fast64_t>::const_iterator rowIterator = rowIndications.begin();
|
|
typename std::vector<uint_fast64_t>::const_iterator rowIteratorEnd = rowIndications.end();
|
|
typename std::vector<T>::iterator resultIterator = result.begin();
|
|
typename std::vector<T>::iterator resultIteratorEnd = result.end();
|
|
|
|
for (; resultIterator != resultIteratorEnd; ++rowIterator, ++resultIterator) {
|
|
*resultIterator = storm::utility::constantZero<T>();
|
|
|
|
for (ite = this->begin() + *(rowIterator + 1); it != ite; ++it) {
|
|
*resultIterator += it->second * vector[it->first];
|
|
}
|
|
}
|
|
#endif
|
|
}
|
|
|
|
template<typename T>
|
|
uint_fast64_t SparseMatrix<T>::getSizeInMemory() const {
|
|
uint_fast64_t size = sizeof(*this);
|
|
|
|
// Add size of columns and values.
|
|
size += sizeof(std::pair<uint_fast64_t, T>) * columnsAndValues.capacity();
|
|
|
|
// Add row_indications size.
|
|
size += sizeof(uint_fast64_t) * rowIndications.capacity();
|
|
|
|
return size;
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::const_rows SparseMatrix<T>::getRows(uint_fast64_t startRow, uint_fast64_t endRow) const {
|
|
return const_rows(this->columnsAndValues.begin() + this->rowIndications[startRow], this->rowIndications[endRow + 1] - this->rowIndications[startRow]);
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::rows SparseMatrix<T>::getRows(uint_fast64_t startRow, uint_fast64_t endRow) {
|
|
return rows(this->columnsAndValues.begin() + this->rowIndications[startRow], this->rowIndications[endRow + 1] - this->rowIndications[startRow]);
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::const_rows SparseMatrix<T>::getRow(uint_fast64_t row) const {
|
|
return getRows(row, row);
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::rows SparseMatrix<T>::getRow(uint_fast64_t row) {
|
|
return getRows(row, row);
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::const_iterator SparseMatrix<T>::begin(uint_fast64_t row) const {
|
|
return this->columnsAndValues.begin() + this->rowIndications[row];
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::iterator SparseMatrix<T>::begin(uint_fast64_t row) {
|
|
return this->columnsAndValues.begin() + this->rowIndications[row];
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::const_iterator SparseMatrix<T>::end(uint_fast64_t row) const {
|
|
return this->columnsAndValues.begin() + this->rowIndications[row + 1];
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::iterator SparseMatrix<T>::end(uint_fast64_t row) {
|
|
return this->columnsAndValues.begin() + this->rowIndications[row + 1];
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::const_iterator SparseMatrix<T>::end() const {
|
|
return this->columnsAndValues.begin() + this->rowIndications[rowCount];
|
|
}
|
|
|
|
template<typename T>
|
|
typename SparseMatrix<T>::iterator SparseMatrix<T>::end() {
|
|
return this->columnsAndValues.begin() + this->rowIndications[rowCount];
|
|
}
|
|
|
|
template<typename T>
|
|
T SparseMatrix<T>::getRowSum(uint_fast64_t row) const {
|
|
T sum = storm::utility::constantZero<T>();
|
|
for (const_iterator it = this->begin(row), ite = this->end(row); it != ite; ++it) {
|
|
sum += it->second;
|
|
}
|
|
return sum;
|
|
}
|
|
|
|
template<typename T>
|
|
bool SparseMatrix<T>::isSubmatrixOf(SparseMatrix<T> const& matrix) const {
|
|
// Check for matching sizes.
|
|
if (this->getRowCount() != matrix.getRowCount()) return false;
|
|
if (this->getColumnCount() != matrix.getColumnCount()) return false;
|
|
|
|
// Check the subset property for all rows individually.
|
|
for (uint_fast64_t row = 0; row < this->getRowCount(); ++row) {
|
|
for (const_iterator it1 = this->begin(row), ite1 = this->end(row), it2 = matrix.begin(row), ite2 = matrix.end(row); it1 != ite1; ++it1) {
|
|
// Skip over all entries of the other matrix that are before the current entry in the current matrix.
|
|
while (it2 != ite2 && it2->first < it1->first) {
|
|
++it2;
|
|
}
|
|
if (it2 == ite2 || it1->first != it2->first) {
|
|
return false;
|
|
}
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
template<typename T>
|
|
std::ostream& operator<<(std::ostream& out, SparseMatrix<T> const& matrix) {
|
|
// Print column numbers in header.
|
|
out << "\t\t";
|
|
for (uint_fast64_t i = 0; i < matrix.columnCount; ++i) {
|
|
out << i << "\t";
|
|
}
|
|
out << std::endl;
|
|
|
|
// Iterate over all rows.
|
|
for (uint_fast64_t i = 0; i < matrix.rowCount; ++i) {
|
|
uint_fast64_t nextIndex = matrix.rowIndications[i];
|
|
|
|
// Print the actual row.
|
|
out << i << "\t(\t";
|
|
uint_fast64_t currentRealIndex = 0;
|
|
while (currentRealIndex < matrix.columnCount) {
|
|
if (nextIndex < matrix.rowIndications[i + 1] && currentRealIndex == matrix.columnsAndValues[nextIndex].first) {
|
|
out << matrix.columnsAndValues[nextIndex].second << "\t";
|
|
++nextIndex;
|
|
} else {
|
|
out << "0\t";
|
|
}
|
|
++currentRealIndex;
|
|
}
|
|
out << "\t)\t" << i << std::endl;
|
|
}
|
|
|
|
// Print column numbers in footer.
|
|
out << "\t\t";
|
|
for (uint_fast64_t i = 0; i < matrix.columnCount; ++i) {
|
|
out << i << "\t";
|
|
}
|
|
out << std::endl;
|
|
|
|
return out;
|
|
}
|
|
|
|
template<typename T>
|
|
std::size_t SparseMatrix<T>::hash() const {
|
|
std::size_t result = 0;
|
|
|
|
boost::hash_combine(result, rowCount);
|
|
boost::hash_combine(result, columnCount);
|
|
boost::hash_combine(result, entryCount);
|
|
boost::hash_combine(result, boost::hash_range(columnsAndValues.begin(), columnsAndValues.end()));
|
|
boost::hash_combine(result, boost::hash_range(rowIndications.begin(), rowIndications.end()));
|
|
|
|
return result;
|
|
}
|
|
|
|
// Explicitly instantiate the builder and the matrix.
|
|
template class SparseMatrixBuilder<double>;
|
|
template class SparseMatrix<double>;
|
|
template std::ostream& operator<<(std::ostream& out, SparseMatrix<double> const& matrix);
|
|
template class SparseMatrixBuilder<int>;
|
|
template class SparseMatrix<int>;
|
|
template std::ostream& operator<<(std::ostream& out, SparseMatrix<int> const& matrix);
|
|
|
|
} // namespace storage
|
|
} // namespace storm
|
|
|
|
|
|
|