/*********************************************************************
* Software License Agreement (BSD License)
*
*  Copyright (c) 2011, Rice University
*  All rights reserved.
*
*  Redistribution and use in source and binary forms, with or without
*  modification, are permitted provided that the following conditions
*  are met:
*
*   * Redistributions of source code must retain the above copyright
*     notice, this list of conditions and the following disclaimer.
*   * Redistributions in binary form must reproduce the above
*     copyright notice, this list of conditions and the following
*     disclaimer in the documentation and/or other materials provided
*     with the distribution.
*   * Neither the name of the Rice University nor the names of its
*     contributors may be used to endorse or promote products derived
*     from this software without specific prior written permission.
*
*  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
*  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
*  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
*  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
*  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
*  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
*  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
*  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
*  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
*  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
*  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
*  POSSIBILITY OF SUCH DAMAGE.
*********************************************************************/

/* Author: Ryan Luna */

#include "ompl/control/planners/est/EST.h"
#include "ompl/base/goals/GoalSampleableRegion.h"
#include "ompl/tools/config/SelfConfig.h"
#include <limits>
#include <cassert>

ompl::control::EST::EST(const SpaceInformationPtr &si) : base::Planner(si, "EST")
{
    specs_.approximateSolutions = true;
    goalBias_ = 0.05;
    maxDistance_ = 0.0;
    siC_ = si.get();
    lastGoalMotion_ = nullptr;

    Planner::declareParam<double>("range", this, &EST::setRange, &EST::getRange, "0.:1.:10000.");
    Planner::declareParam<double>("goal_bias", this, &EST::setGoalBias, &EST::getGoalBias, "0.:.05:1.");
}

ompl::control::EST::~EST()
{
    freeMemory();
}

void ompl::control::EST::setup()
{
    Planner::setup();
    tools::SelfConfig sc(si_, getName());
    sc.configureProjectionEvaluator(projectionEvaluator_);
    sc.configurePlannerRange(maxDistance_);

    tree_.grid.setDimension(projectionEvaluator_->getDimension());
}

void ompl::control::EST::clear()
{
    Planner::clear();
    sampler_.reset();
    controlSampler_.reset();
    freeMemory();
    tree_.grid.clear();
    tree_.size = 0;
    pdf_.clear();
    lastGoalMotion_ = nullptr;
}

void ompl::control::EST::freeMemory()
{
    for (const auto &it : tree_.grid)
    {
        for (const auto &motion : it.second->data.motions_)
        {
            if (motion->state)
                si_->freeState(motion->state);
            if (motion->control)
                siC_->freeControl(motion->control);
            delete motion;
        }
    }
}

ompl::base::PlannerStatus ompl::control::EST::solve(const base::PlannerTerminationCondition &ptc)
{
    checkValidity();
    base::Goal *goal = pdef_->getGoal().get();
    base::GoalSampleableRegion *goal_s = dynamic_cast<base::GoalSampleableRegion *>(goal);

    // Initializing tree with start state(s)
    while (const base::State *st = pis_.nextStart())
    {
        auto *motion = new Motion(siC_);
        si_->copyState(motion->state, st);
        siC_->nullControl(motion->control);
        addMotion(motion);
    }

    if (tree_.grid.size() == 0)
    {
        OMPL_ERROR("%s: There are no valid initial states!", getName().c_str());
        return base::PlannerStatus::INVALID_START;
    }

    // Ensure that we have a state sampler AND a control sampler
    if (!sampler_)
        sampler_ = si_->allocValidStateSampler();
    if (!controlSampler_)
        controlSampler_ = siC_->allocDirectedControlSampler();

    OMPL_INFORM("%s: Starting planning with %u states already in datastructure", getName().c_str(), tree_.size);

    Motion *solution = nullptr;
    Motion *approxsol = nullptr;
    double approxdif = std::numeric_limits<double>::infinity();
    auto *rmotion = new Motion(siC_);
    bool solved = false;

    while (!ptc)
    {
        // Select a state to expand the tree from
        Motion *existing = selectMotion();
        assert(existing);

        // sample a random state (with goal biasing) near the state selected for expansion
        if (goal_s && rng_.uniform01() < goalBias_ && goal_s->canSample())
            goal_s->sampleGoal(rmotion->state);
        else
        {
            if (!sampler_->sampleNear(rmotion->state, existing->state, maxDistance_))
                continue;
        }

        // Extend a motion toward the state we just sampled
        unsigned int duration =
            controlSampler_->sampleTo(rmotion->control, existing->control, existing->state, rmotion->state);

        // If the system was propagated for a meaningful amount of time, save into the tree
        if (duration >= siC_->getMinControlDuration())
        {
            // create a motion to the resulting state
            auto *motion = new Motion(siC_);
            si_->copyState(motion->state, rmotion->state);
            siC_->copyControl(motion->control, rmotion->control);
            motion->steps = duration;
            motion->parent = existing;

            // save the state
            addMotion(motion);

            // Check if this state is the goal state, or improves the best solution so far
            double dist = 0.0;
            solved = goal->isSatisfied(motion->state, &dist);
            if (solved)
            {
                approxdif = dist;
                solution = motion;
                break;
            }
            if (dist < approxdif)
            {
                approxdif = dist;
                approxsol = motion;
            }
        }
    }

    bool approximate = false;
    if (solution == nullptr)
    {
        solution = approxsol;
        approximate = true;
    }

    // Constructing the solution path
    if (solution != nullptr)
    {
        lastGoalMotion_ = solution;

        std::vector<Motion *> mpath;
        while (solution != nullptr)
        {
            mpath.push_back(solution);
            solution = solution->parent;
        }

        auto path(std::make_shared<PathControl>(si_));
        for (int i = mpath.size() - 1; i >= 0; --i)
            if (mpath[i]->parent)
                path->append(mpath[i]->state, mpath[i]->control, mpath[i]->steps * siC_->getPropagationStepSize());
            else
                path->append(mpath[i]->state);
        solved = true;
        pdef_->addSolutionPath(path, approximate, approxdif, getName());
    }

    // Cleaning up memory
    if (rmotion->state)
        si_->freeState(rmotion->state);
    if (rmotion->control)
        siC_->freeControl(rmotion->control);
    delete rmotion;

    OMPL_INFORM("%s: Created %u states in %u cells", getName().c_str(), tree_.size, tree_.grid.size());

    return base::PlannerStatus(solved, approximate);
}

ompl::control::EST::Motion *ompl::control::EST::selectMotion()
{
    GridCell *cell = pdf_.sample(rng_.uniform01());
    return cell && !cell->data.empty() ? cell->data[rng_.uniformInt(0, cell->data.size() - 1)] : nullptr;
}

void ompl::control::EST::addMotion(Motion *motion)
{
    Grid<MotionInfo>::Coord coord;
    projectionEvaluator_->computeCoordinates(motion->state, coord);
    GridCell *cell = tree_.grid.getCell(coord);
    if (cell)
    {
        cell->data.push_back(motion);
        pdf_.update(cell->data.elem_, 1.0 / cell->data.size());
    }
    else
    {
        cell = tree_.grid.createCell(coord);
        cell->data.push_back(motion);
        tree_.grid.add(cell);
        cell->data.elem_ = pdf_.add(cell, 1.0);
    }
    tree_.size++;
}

void ompl::control::EST::getPlannerData(base::PlannerData &data) const
{
    Planner::getPlannerData(data);

    std::vector<MotionInfo> motionInfo;
    tree_.grid.getContent(motionInfo);

    double stepSize = siC_->getPropagationStepSize();

    if (lastGoalMotion_)
        data.addGoalVertex(base::PlannerDataVertex(lastGoalMotion_->state));

    for (auto &mi : motionInfo)
        for (auto &motion : mi.motions_)
        {
            if (motion->parent)
            {
                if (data.hasControls())
                    data.addEdge(base::PlannerDataVertex(motion->parent->state), base::PlannerDataVertex(motion->state),
                                 PlannerDataEdgeControl(motion->control, motion->steps * stepSize));
                else
                    data.addEdge(base::PlannerDataVertex(motion->parent->state),
                                 base::PlannerDataVertex(motion->state));
            }
            else
                data.addStartVertex(base::PlannerDataVertex(motion->state));
        }
}
