106 lines
3.4 KiB
C++
106 lines
3.4 KiB
C++
/***************************************************************************
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* Copyright (c) 2023 Ondsel, Inc. *
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* *
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* This file is part of OndselSolver. *
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* *
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* See LICENSE file for details about copyright. *
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***************************************************************************/
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#include <cassert>
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#include <memory>
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#include "GESpMatParPvMarkoFast.h"
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#include "SingularMatrixError.h"
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using namespace MbD;
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void GESpMatParPvMarkoFast::preSolvewithsaveOriginal(SpMatDsptr spMat, FColDsptr fullCol, bool saveOriginal)
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{
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//throw SimulationStoppingError("To be implemented.");
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//"Optimized for speed."
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if (m != spMat->nrow() || n != spMat->ncol()) {
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m = spMat->nrow();
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n = spMat->ncol();
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matrixA = std::make_shared<SparseMatrix<double>>(m);
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rowPositionsOfNonZerosInPivotColumn = std::make_shared<std::vector<size_t>>();
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}
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if (saveOriginal) {
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rightHandSideB = fullCol->copy();
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}
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else {
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rightHandSideB = fullCol;
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}
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for (size_t i = 0; i < m; i++)
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{
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auto& spRowi = spMat->at(i);
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double maxRowMagnitude = spRowi->maxMagnitude();
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if (maxRowMagnitude == 0) throwSingularMatrixError("");
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auto scaling = 1.0 / maxRowMagnitude;
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matrixA->at(i) = spRowi->timesconditionedWithTol(scaling, singularPivotTolerance);
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rightHandSideB->atitimes(i, scaling);
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}
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}
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void GESpMatParPvMarkoFast::doPivoting(size_t p)
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{
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//"Search from bottom to top."
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//"Optimized for speed. No check for singular pivot."
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//"Do partial pivoting."
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//"criterion := mag / (2.0d raisedTo: rowiCount)."
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//"Rows are explicitly scaled in preSolve:."
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//"Pivot size are nieither checked nor stored."
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//| lookForFirstNonZeroInPivotCol i rowi aip criterionMax rowPivoti criterion max |
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ssize_t i; //Use ssize_t because of decrement
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size_t rowPivoti;
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double aip, max, criterion, criterionMax;
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SpRowDsptr spRowi;
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rowPositionsOfNonZerosInPivotColumn->clear();
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auto lookForFirstNonZeroInPivotCol = true;
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i = (ssize_t)m - 1;
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while (lookForFirstNonZeroInPivotCol) {
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spRowi = matrixA->at(i);
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if (spRowi->find(p) == spRowi->end()) {
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if (i <= (ssize_t)p) throwSingularMatrixError(""); //Use ssize_t because i can be negative
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}
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else {
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markowitzPivotColCount = 0;
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aip = spRowi->at(p);
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if (aip < 0) aip = -aip;
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max = aip;
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criterionMax = aip / std::pow(2.0, spRowi->size());
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rowPivoti = (size_t)i;
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lookForFirstNonZeroInPivotCol = false;
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}
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i--;
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}
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while (i >= (ssize_t)p) { //Use ssize_t because i can be negative
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spRowi = matrixA->at(i);
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if (spRowi->find(p) == spRowi->end()) {
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aip = std::numeric_limits<double>::min();
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}
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else {
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aip = spRowi->at(p);
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markowitzPivotColCount++;
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if (aip < 0) aip = -aip;
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criterion = aip / std::pow(2.0, spRowi->size());
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if (criterion > criterionMax) {
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max = aip;
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criterionMax = criterion;
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rowPositionsOfNonZerosInPivotColumn->push_back(rowPivoti);
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rowPivoti = (size_t)i;
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}
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else {
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rowPositionsOfNonZerosInPivotColumn->push_back(i);
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}
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}
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i--;
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}
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if (p != rowPivoti) {
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matrixA->swapElems(p, rowPivoti);
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rightHandSideB->swapElems(p, rowPivoti);
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if (aip != std::numeric_limits<double>::min()) rowPositionsOfNonZerosInPivotColumn->at(markowitzPivotColCount - 1) = rowPivoti;
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}
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if (max < singularPivotTolerance) throwSingularMatrixError("");
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}
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