lms/src/libs/services/recommendation/impl/features/FeaturesEngine.hpp

/*
 * Copyright (C) 2018 Emeric Poupon
 *
 * This file is part of LMS.
 *
 * LMS is free software: 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 3 of the License, or
 * (at your option) any later version.
 *
 * LMS 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 General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with LMS.  If not, see <http://www.gnu.org/licenses/>.
 */

#pragma once

#include <algorithm>
#include <functional>
#include <optional>
#include <string>
#include <unordered_map>
#include <vector>

#include "core/Utils.hpp"
#include "som/DataNormalizer.hpp"
#include "som/Network.hpp"

#include "FeaturesDefs.hpp"
#include "FeaturesEngineCache.hpp"
#include "IEngine.hpp"

namespace lms::db
{
    class Session;
}

namespace lms::recommendation
{
    using FeatureWeight = double;

    class FeaturesEngine : public IEngine
    {
    public:
        FeaturesEngine(db::Db& db)
            : _db{ db } {}

        FeaturesEngine(const FeaturesEngine&) = delete;
        FeaturesEngine(FeaturesEngine&&) = delete;
        FeaturesEngine& operator=(const FeaturesEngine&) = delete;
        FeaturesEngine& operator=(FeaturesEngine&&) = delete;

        static const FeatureSettingsMap& getDefaultTrainFeatureSettings();

    private:
        void load(bool forceReload, const ProgressCallback& progressCallback) override;
        void requestCancelLoad() override;

        TrackContainer findSimilarTracksFromTrackList(db::TrackListId tracklistId, std::size_t maxCount) const override;
        TrackContainer findSimilarTracks(const std::vector<db::TrackId>& tracksId, std::size_t maxCount) const override;
        ReleaseContainer getSimilarReleases(db::ReleaseId releaseId, std::size_t maxCount) const override;
        ArtistContainer getSimilarArtists(db::ArtistId artistId, core::EnumSet<db::TrackArtistLinkType> linkTypes, std::size_t maxCount) const override;

        void loadFromCache(FeaturesEngineCache&& cache);

        // Use training (may be very slow)
        struct TrainSettings
        {
            std::size_t iterationCount{ 10 };
            float sampleCountPerNeuron{ 4 };
            FeatureSettingsMap featureSettingsMap;
        };
        void loadFromTraining(const TrainSettings& trainSettings, const ProgressCallback& progressCallback);

        template<typename IdType>
        using ObjectPositions = std::unordered_map<IdType, std::vector<som::Position>>;

        using ArtistPositions = ObjectPositions<db::ArtistId>;
        using ReleasePositions = ObjectPositions<db::ReleaseId>;
        using TrackPositions = ObjectPositions<db::TrackId>;

        template<typename IdType>
        using ObjectMatrix = som::Matrix<std::vector<IdType>>;
        using ArtistMatrix = ObjectMatrix<db::ArtistId>;
        using ReleaseMatrix = ObjectMatrix<db::ReleaseId>;
        using TrackMatrix = ObjectMatrix<db::TrackId>;

        void load(const som::Network& network, const TrackPositions& tracksPosition);

        FeaturesEngineCache toCache() const;

        template<typename IdType>
        static std::vector<som::Position> getMatchingRefVectorsPosition(const std::vector<IdType>& ids, const ObjectPositions<IdType>& objectPositions);

        template<typename IdType>
        static std::vector<IdType> getObjectsIds(const std::vector<som::Position>& positions, const ObjectMatrix<IdType>& objectsMatrix);

        template<typename IdType>
        std::vector<IdType> getSimilarObjects(const std::vector<IdType>& ids,
            const ObjectMatrix<IdType>& objectMatrix,
            const ObjectPositions<IdType>& objectPositions,
            std::size_t maxCount) const;

        db::Db& _db;
        bool _loadCancelled{};
        std::unique_ptr<som::Network> _network;
        double _networkRefVectorsDistanceMedian{};

        ArtistPositions _artistPositions;
        std::unordered_map<db::TrackArtistLinkType, ArtistMatrix> _artistMatrix;

        ReleasePositions _releasePositions;
        ReleaseMatrix _releaseMatrix;

        TrackPositions _trackPositions;
        TrackMatrix _trackMatrix;
    };

    template<typename IdType>
    std::vector<som::Position> FeaturesEngine::getMatchingRefVectorsPosition(const std::vector<IdType>& ids, const ObjectPositions<IdType>& objectPositions)
    {
        std::vector<som::Position> res;

        if (ids.empty())
            return res;

        for (const IdType id : ids)
        {
            auto it = objectPositions.find(id);
            if (it == objectPositions.end())
                continue;

            for (const som::Position& position : it->second)
                core::utils::push_back_if_not_present(res, position);
        }

        return res;
    }

    template<typename IdType>
    std::vector<IdType> FeaturesEngine::getObjectsIds(const std::vector<som::Position>& positions, const ObjectMatrix<IdType>& objectMatrix)
    {
        std::vector<IdType> res;

        for (const som::Position& position : positions)
        {
            for (const IdType id : objectMatrix.get(position))
                core::utils::push_back_if_not_present(res, id);
        }

        return res;
    }

    template<typename IdType>
    std::vector<IdType> FeaturesEngine::getSimilarObjects(const std::vector<IdType>& ids,
        const ObjectMatrix<IdType>& objectMatrix,
        const ObjectPositions<IdType>& objectPositions,
        std::size_t maxCount) const
    {
        std::vector<IdType> res;

        std::vector<som::Position> searchedRefVectorsPosition{ getMatchingRefVectorsPosition(ids, objectPositions) };
        if (searchedRefVectorsPosition.empty())
            return res;

        while (1)
        {
            std::vector<IdType> closestObjectIds{ getObjectsIds(searchedRefVectorsPosition, objectMatrix) };

            // Remove objects that are already in input or already reported
            closestObjectIds.erase(std::remove_if(std::begin(closestObjectIds), std::end(closestObjectIds),
                                       [&](IdType id) {
                                           return std::find(std::cbegin(ids), std::cend(ids), id) != std::cend(ids);
                                       }),
                std::end(closestObjectIds));

            for (IdType id : closestObjectIds)
            {
                if (res.size() == maxCount)
                    break;

                core::utils::push_back_if_not_present(res, id);
            }

            if (res.size() == maxCount)
                break;

            // If there is not enough objects, try again with closest neighbour until there is too much distance
            const std::optional<som::Position> closestRefVectorPosition{ _network->getClosestRefVectorPosition(searchedRefVectorsPosition, _networkRefVectorsDistanceMedian * 0.75) };
            if (!closestRefVectorPosition)
                break;

            core::utils::push_back_if_not_present(searchedRefVectorsPosition, closestRefVectorPosition.value());
        }

        return res;
    }
} // namespace lms::recommendation