surface_skd_tree.cpp

/*---------------------------------------------------------------------------*\
 *
 *  bitpit
 *
 *  Copyright (C) 2015-2021 OPTIMAD engineering Srl
 *
 *  -------------------------------------------------------------------------
 *  License
 *  This file is part of bitpit.
 *
 *  bitpit is free software: you can redistribute it and/or modify it
 *  under the terms of the GNU Lesser General Public License v3 (LGPL)
 *  as published by the Free Software Foundation.
 *
 *  bitpit 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 for more details.
 *
 *  You should have received a copy of the GNU Lesser General Public License
 *  along with bitpit. If not, see <http://www.gnu.org/licenses/>.
 *
\*---------------------------------------------------------------------------*/
 
#include "bitpit_common.hpp"
 
#include "surface_skd_tree.hpp"
 
namespace bitpit {
 
SurfaceSkdTree::SurfaceSkdTree(const SurfaceKernel *patch, bool interiorCellsOnly)
    : PatchSkdTree(patch, interiorCellsOnly)
{
}
 
void SurfaceSkdTree::clear(bool release)
{
    if (release) {
        m_closestCellCandidates = ClosestCellCandidates();
    }
 
    PatchSkdTree::clear(release);
}
 
double SurfaceSkdTree::evalPointDistance(const std::array<double, 3> &point) const
{
    return evalPointDistance(point, std::numeric_limits<double>::max(), false);
}
 
double SurfaceSkdTree::evalPointDistance(const std::array<double, 3> &point, double maxDistance) const
{
    return evalPointDistance(point, maxDistance, false);
}
 
double SurfaceSkdTree::evalPointDistance(const std::array<double, 3> &point, double maxDistance, bool interiorCellsOnly) const
{
    long id;
    double distance = maxDistance;
 
    findPointClosestCell(point, interiorCellsOnly, &id, &distance);
 
    return distance;
}
 
void SurfaceSkdTree::evalPointDistance(int nPoints, const std::array<double, 3> *points, double *distances) const
{
    std::vector<double> maxDistances(nPoints, std::numeric_limits<double>::max());
 
    evalPointDistance(nPoints, points, maxDistances.data(), false, distances);
}
 
void SurfaceSkdTree::evalPointDistance(int nPoints, const std::array<double, 3> *points, double maxDistance, double *distances) const
{
    std::vector<double> maxDistances(nPoints, maxDistance);
 
    evalPointDistance(nPoints, points, maxDistances.data(), false, distances);
}
 
void SurfaceSkdTree::evalPointDistance(int nPoints, const std::array<double, 3> *points, const double *maxDistances, double *distances) const
{
    evalPointDistance(nPoints, points, maxDistances, false, distances);
}
 
 
void SurfaceSkdTree::evalPointDistance(int nPoints, const std::array<double, 3> *points, const double *maxDistances, bool interiorCellsOnly, double *distances) const
{
    std::vector<long> ids(nPoints, Cell::NULL_ID);
 
    findPointClosestCell(nPoints, points, maxDistances, interiorCellsOnly, ids.data(), distances);
}
 
#if BITPIT_ENABLE_MPI
void SurfaceSkdTree::evalPointGlobalDistance(int nPoints, const std::array<double, 3> *points, double *distances) const
{
    std::vector<double> maxDistances(nPoints, std::numeric_limits<double>::max());
 
    evalPointGlobalDistance(nPoints, points, maxDistances.data(), distances);
}
 
void SurfaceSkdTree::evalPointGlobalDistance(int nPoints, const std::array<double, 3> *points, double maxDistance, double *distances) const
{
    std::vector<double> maxDistances(nPoints, maxDistance);
 
    evalPointGlobalDistance(nPoints, points, maxDistances.data(), distances);
}
 
void SurfaceSkdTree::evalPointGlobalDistance(int nPoints, const std::array<double, 3> *points, const double *maxDistances, double *distances) const
{
    std::vector<long> ids(nPoints, Cell::NULL_ID);
    std::vector<int> ranks(nPoints, -1);
 
    findPointClosestGlobalCell(nPoints, points, maxDistances, ids.data(), ranks.data(), distances);
}
#endif
 
long SurfaceSkdTree::findPointClosestCell(const std::array<double, 3> &point, long *id, double *distance) const
{
    return findPointClosestCell(point, std::numeric_limits<double>::max(), false, id, distance);
}
 
long SurfaceSkdTree::findPointClosestCell(const std::array<double, 3> &point, double maxDistance,
                                          long *id, double *distance) const
{
    return findPointClosestCell(point, maxDistance, false, id, distance);
}
 
long SurfaceSkdTree::findPointClosestCell(const std::array<double, 3> &point, double maxDistance,
                                          bool interiorCellsOnly, long *id, double *distance) const
{
    // Tolerance for distance evaluations
    const PatchKernel &patch = getPatch();
    double tolerance = patch.getTol();
 
    // Initialize the cell id
    *id = Cell::NULL_ID;
 
    // Get the root of the tree
    std::size_t rootId = 0;
    const SkdNode &root = m_nodes[rootId];
    if (root.isEmpty()) {
        *distance = std::numeric_limits<double>::max();
 
        return 0;
    }
 
    ClosestCellCandidates *closestCellCandidates = nullptr;
    std::unique_ptr<ClosestCellCandidates> privateStorage = nullptr;
    if (areLookupsThreadSafe()) {
        privateStorage = std::unique_ptr<ClosestCellCandidates>(new ClosestCellCandidates());
        closestCellCandidates = privateStorage.get();
    } else {
        closestCellCandidates = &m_closestCellCandidates;
    }
    closestCellCandidates->maxDistance = *distance;
    findPointClosestCandidates(point, maxDistance, closestCellCandidates);
 
    // Process the candidates and find the closest cell
    long nDistanceEvaluations = 0;
    for (std::size_t k = 0; k < closestCellCandidates->ids.size(); ++k) {
        // Do not consider nodes with a minimum distance greater than the
        // distance estimate
        if (utils::DoubleFloatingGreater()(closestCellCandidates->minDistances.at(k), closestCellCandidates->maxDistance, tolerance, tolerance)) {
            continue;
        }
 
        // Evaluate the distance
        std::size_t nodeId = closestCellCandidates->ids.at(k);
        const SkdNode &node = m_nodes[nodeId];
 
        node.updatePointClosestCell(point, interiorCellsOnly, id, &(closestCellCandidates->maxDistance));
        ++nDistanceEvaluations;
    }
    *distance = closestCellCandidates->maxDistance;
 
    return nDistanceEvaluations;
}
 
long SurfaceSkdTree::findPointClosestCell(int nPoints, const std::array<double, 3> *points, long *ids, double *distances) const
{
    long nDistanceEvaluations = 0;
    for (int i = 0; i < nPoints; ++i) {
        nDistanceEvaluations += findPointClosestCell(points[i], std::numeric_limits<double>::max(), false, ids + i, distances + i);
    }
 
    return nDistanceEvaluations;
}
 
long SurfaceSkdTree::findPointClosestCell(int nPoints, const std::array<double, 3> *points, double maxDistance, long *ids, double *distances) const
{
    long nDistanceEvaluations = 0;
    for (int i = 0; i < nPoints; ++i) {
        nDistanceEvaluations += findPointClosestCell(points[i], maxDistance, false, ids + i, distances + i);
    }
 
    return nDistanceEvaluations;
}
 
long SurfaceSkdTree::findPointClosestCell(int nPoints, const std::array<double, 3> *points, const double *maxDistances, long *ids, double *distances) const
{
    return findPointClosestCell(nPoints, points, maxDistances, false, ids, distances);
}
 
long SurfaceSkdTree::findPointClosestCell(int nPoints, const std::array<double, 3> *points, const double *maxDistances, bool interiorCellsOnly, long *ids, double *distances) const
{
    long nDistanceEvaluations = 0;
    for (int i = 0; i < nPoints; ++i) {
        nDistanceEvaluations += findPointClosestCell(points[i], maxDistances[i], interiorCellsOnly, ids + i, distances + i);
    }
 
    return nDistanceEvaluations;
}
 
 
long SurfaceSkdTree::findPointClosestCells(const std::array<double, 3> &point, std::vector<long> &ids, double *distance) const
{
    return findPointClosestCells(point, std::numeric_limits<double>::max(), false, ids, distance);
}
 
long SurfaceSkdTree::findPointClosestCells(const std::array<double, 3> &point, double maxDistance,
                                          std::vector<long> &ids, double *distance) const
{
    return findPointClosestCells(point, maxDistance, false, ids, distance);
}
 
long SurfaceSkdTree::findPointClosestCells(const std::array<double, 3> &point, double maxDistance,
                                          bool interiorCellsOnly, std::vector<long> &ids, double *distance) const
{
    // Tolerance for distance evaluations
    const PatchKernel &patch = getPatch();
    double tolerance = patch.getTol();
 
    // Initialize the cell id
    ids.resize(1, Cell::NULL_ID);
 
    // Get the root of the tree
    std::size_t rootId = 0;
    const SkdNode &root = m_nodes[rootId];
    if (root.isEmpty()) {
        *distance = std::numeric_limits<double>::max();
 
        return 0;
    }
 
    // If threads safe lookups are not needed, a temporary data structure
    // are declared as member of the class to avoid its reallocation every
    // time the function is called.
    ClosestCellCandidates *closestCellCandidates = nullptr;
    std::unique_ptr<ClosestCellCandidates> privateStorage = nullptr;
    if (areLookupsThreadSafe()) {
        privateStorage = std::unique_ptr<ClosestCellCandidates>(new ClosestCellCandidates());
        closestCellCandidates = privateStorage.get();
    } else {
        closestCellCandidates = &m_closestCellCandidates;
    }
    findPointClosestCandidates(point, maxDistance, closestCellCandidates);
 
    // Process the candidates and find the closest cells
    *distance = closestCellCandidates->maxDistance;
    long nDistanceEvaluations = 0;
    for (std::size_t k = 0; k < closestCellCandidates->ids.size(); ++k) {
        // Do not consider nodes with a minimum distance greater than the
        // distance estimate
        if (utils::DoubleFloatingGreater()(closestCellCandidates->minDistances.at(k), *distance, tolerance, tolerance)) {
            continue;
        }
 
        // Evaluate the distance
        std::size_t nodeId = closestCellCandidates->ids.at(k);
        const SkdNode &node = m_nodes[nodeId];
 
        node.updatePointClosestCells(point, interiorCellsOnly, &ids, distance);
        ++nDistanceEvaluations;
    }
 
    return nDistanceEvaluations;
}
 
void SurfaceSkdTree::findPointClosestCandidates(const std::array<double, 3> &point, double maxDistance,
        ClosestCellCandidates *candidates) const
{
    // Clear candidates
    candidates->clear();
 
    // Tolerance for distance evaluations
    const PatchKernel &patch = getPatch();
    double tolerance = patch.getTol();
 
    // Get the root of the tree
    std::size_t rootId = 0;
    const SkdNode &root = m_nodes[rootId];
 
    // Initialize a distance estimate
    //
    // The real distance will be lesser than or equal to the estimate.
    //
    // Care must be taken to avoid overflow when performing the multiplication.
    double squaredMaxDistance;
    if (maxDistance <= 1. || maxDistance < std::numeric_limits<double>::max() / maxDistance) {
        squaredMaxDistance = maxDistance * maxDistance;
    } else {
        squaredMaxDistance = std::numeric_limits<double>::max();
    }
 
    double squareDistanceEstimate = std::min(root.evalPointMaxSquareDistance(point), squaredMaxDistance);
 
    // Get a list of candidates nodes
    //
    // First, we gather all the candidates and then we evaluate the distance
    // of each candidate. Since distance estimate is constantly updated when
    // new nodes are processed, the final estimate may be smaller than the
    // minimum distance of some candidates. Processing the candidates after
    // scanning all the tree, allows to discard some of them without the need
    // of evaluating the exact distance.
 
    candidates->nodeStack.push_back(rootId);
    while (!candidates->nodeStack.empty()) {
        std::size_t nodeId = candidates->nodeStack.back();
        const SkdNode &node = m_nodes[nodeId];
        candidates->nodeStack.pop_back();
 
        // Do not consider nodes with a minimum distance greater than
        // the distance estimate
        double nodeMinSquareDistance = node.evalPointMinSquareDistance(point);
        if (utils::DoubleFloatingGreater()(nodeMinSquareDistance, squareDistanceEstimate, tolerance, tolerance)) {
            continue;
        }
 
        // Update the distance estimate
        //
        // The real distance will be less than or equal to the estimate.
        double nodeMaxSquareDistance = node.evalPointMaxSquareDistance(point);
        squareDistanceEstimate = std::min(nodeMaxSquareDistance, squareDistanceEstimate);
 
        // If the node is a leaf add it to the candidates, otherwise add its
        // children to the stack.
        bool isLeaf = true;
        for (int i = SkdNode::CHILD_BEGIN; i != SkdNode::CHILD_END; ++i) {
            SkdNode::ChildLocation childLocation = static_cast<SkdNode::ChildLocation>(i);
            std::size_t childId = node.getChildId(childLocation);
            if (childId != SkdNode::NULL_ID) {
                isLeaf = false;
                candidates->nodeStack.push_back(childId);
            }
        }
 
        if (isLeaf) {
            candidates->ids.push_back(nodeId);
            candidates->minDistances.push_back(std::sqrt(nodeMinSquareDistance));
        }
    }
 
    // Set the distance estimate
    if (!candidates->ids.empty()) {
        candidates->maxDistance = std::sqrt(squareDistanceEstimate);
    } else {
        candidates->maxDistance = std::numeric_limits<double>::max();
    }
}
 
#if BITPIT_ENABLE_MPI
long SurfaceSkdTree::findPointClosestGlobalCell(int nPoints, const std::array<double, 3> *points,
                                                long *ids, int *ranks, double *distances) const
{
    return findPointClosestGlobalCell(nPoints, points, std::numeric_limits<double>::max(), ids, ranks, distances);
}
 
long SurfaceSkdTree::findPointClosestGlobalCell(int nPoints, const std::array<double, 3> *points, double maxDistance,
                                                long *ids, int *ranks, double *distances) const
{
    std::vector<double> maxDistances(nPoints, maxDistance);
 
    return findPointClosestGlobalCell(nPoints, points, maxDistances.data(), ids, ranks, distances);
}
 
long SurfaceSkdTree::findPointClosestGlobalCell(int nPoints, const std::array<double, 3> *points, const double *maxDistances,
                                                long *ids, int *ranks, double *distances) const
{
    long nDistanceEvaluations = 0;
 
    // Early return is the patch is not partitioned
    const PatchKernel &patch = getPatch();
    if (!patch.isPartitioned()) {
        for (int i = 0; i < nPoints; ++i) {
            // Evaluate distance
            nDistanceEvaluations += findPointClosestCell(points[i], maxDistances[i], ids + i, distances + i);
 
            // The patch is not partitioned, all cells are local
            ranks[i] = patch.getRank();
        }
 
        return nDistanceEvaluations;
    }
 
    // Get MPI communicator
    if (!isCommunicatorSet()) {
        throw std::runtime_error("Skd-tree communicator has not been set.");
    }
 
    MPI_Comm communicator = getCommunicator();
 
    // Gather the number of points associated to each process
    std::vector<int> pointsCount(m_nProcessors);
    MPI_Allgather(&nPoints, 1, MPI_INT, pointsCount.data(), 1, MPI_INT, communicator);
 
    // Evaluate information for data communications
    std::vector<int> globalPointsDispls(m_nProcessors, 0);
    std::vector<int> globalPointsOffsets(m_nProcessors, 0);
    std::vector<int> globalPointsDataCount(m_nProcessors, 0);
 
    globalPointsDataCount[0] = 3 * pointsCount[0];
    for (int i = 1; i < m_nProcessors; ++i) {
        globalPointsDispls[i]     = globalPointsDispls[i - 1] + 3 * pointsCount[i - 1];
        globalPointsOffsets[i]    = globalPointsOffsets[i - 1] + pointsCount[i - 1];
        globalPointsDataCount[i]  = 3 * pointsCount[i];
    }
 
    int nGlobalPoints = globalPointsDispls.back() + pointsCount.back();
 
    // Gather point coordinates
    std::vector<std::array<double,3>> globalPoints(nGlobalPoints);
    int pointsDataCount = 3 * nPoints;
    MPI_Allgatherv(points, pointsDataCount, MPI_DOUBLE, globalPoints.data(),
                globalPointsDataCount.data(), globalPointsDispls.data(), MPI_DOUBLE, communicator);
 
    // Gather vector with all maximum distances
    std::vector<double> globalMaxDistances(nGlobalPoints);
    MPI_Allgatherv(maxDistances, nPoints, MPI_DOUBLE, globalMaxDistances.data(),
                    pointsCount.data(), globalPointsOffsets.data(), MPI_DOUBLE, communicator);
 
    // Initialize distance information
    std::vector<SkdGlobalCellDistance> globalCellDistances(nGlobalPoints);
 
    // Call local find point closest cell for each global point collected
    for (int i = 0; i < nGlobalPoints; ++i) {
        // Get point information
        const std::array<double, 3> &point = globalPoints[i];
 
        // Use a maximum distance for each point given by an estimation
        // based on partition bounding boxes. The distance will be lesser
        // than or equal to the point maximum distance.
        double pointMaxDistance = globalMaxDistances[i];
        for (int rank = 0; rank < m_nProcessors; ++rank) {
            pointMaxDistance = std::min(getPartitionBox(rank).evalPointMaxDistance(point, std::numeric_limits<double>::max()), pointMaxDistance);
        }
 
        // Get cell distance information
        SkdGlobalCellDistance &globalCellDistance = globalCellDistances[i];
        int &cellRank = globalCellDistance.getRank();
        long &cellId = globalCellDistance.getId();
        double &cellDistance = globalCellDistance.getDistance();
 
        // Evaluate local distance from the point
        bool interiorCellsOnly = true;
        nDistanceEvaluations += findPointClosestCell(point, pointMaxDistance, interiorCellsOnly, &cellId, &cellDistance);
 
        // Set cell rank
        if (cellId != Cell::NULL_ID) {
            cellRank = patch.getCellOwner(cellId);
        }
    }
 
    // Exchange distance information
    MPI_Datatype globalCellDistanceDatatype = SkdGlobalCellDistance::getMPIDatatype();
    MPI_Op globalCellDistanceMinOp = SkdGlobalCellDistance::getMPIMinOperation();
    for (int rank = 0; rank < m_nProcessors; ++rank) {
        SkdGlobalCellDistance *globalCellDistance = globalCellDistances.data() + globalPointsOffsets[rank];
        if (m_rank == rank) {
            MPI_Reduce(MPI_IN_PLACE, globalCellDistance, pointsCount[rank], globalCellDistanceDatatype, globalCellDistanceMinOp, rank, communicator);
        } else {
            MPI_Reduce(globalCellDistance, globalCellDistance, pointsCount[rank], globalCellDistanceDatatype, globalCellDistanceMinOp, rank, communicator);
        }
    }
 
    // Update output arguments
    for (int i = 0; i < nPoints; ++i) {
        int globalIndex = i + globalPointsOffsets[m_rank];
        SkdGlobalCellDistance &globalCellDistance = globalCellDistances[globalIndex];
        globalCellDistance.exportData(ranks + i, ids + i, distances + i);
    }
 
    return nDistanceEvaluations;
}
#endif
 
}