Migrated scrobbling stuff
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emeric
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/*
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* Copyright (C) 2018 Emeric Poupon
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*
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* This file is part of LMS.
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*
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* LMS is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* LMS is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with LMS. If not, see <http://www.gnu.org/licenses/>.
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*/
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#pragma once
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#include <algorithm>
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#include <functional>
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#include <unordered_map>
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#include <optional>
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#include <string>
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#include <vector>
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#include "recommendation/IEngine.hpp"
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#include "som/DataNormalizer.hpp"
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#include "som/Network.hpp"
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#include "utils/Utils.hpp"
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#include "FeaturesEngineCache.hpp"
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#include "FeaturesDefs.hpp"
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namespace Database
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{
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class Session;
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}
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namespace Recommendation {
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using FeatureWeight = double;
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class FeaturesEngine : public IEngine
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{
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public:
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FeaturesEngine(Database::Db& db) : _db {db} {}
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FeaturesEngine(const FeaturesEngine&) = delete;
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FeaturesEngine(FeaturesEngine&&) = delete;
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FeaturesEngine& operator=(const FeaturesEngine&) = delete;
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FeaturesEngine& operator=(FeaturesEngine&&) = delete;
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using FeaturesFetchFunc = std::function<std::optional<std::unordered_map<std::string, std::vector<double>>>(Database::TrackId, const std::unordered_set<std::string>& /*features*/)>;
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// Default is to retrieve the features from the database (may be slow).
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// Use this only if you want to train different searchers with some cached data
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static void setFeaturesFetchFunc(FeaturesFetchFunc func) { _featuresFetchFunc = func; }
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static const FeatureSettingsMap& getDefaultTrainFeatureSettings();
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private:
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void load(bool forceReload, const ProgressCallback& progressCallback) override;
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void requestCancelLoad() override;
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void cancelLoad() override {}
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TrackContainer getSimilarTracksFromTrackList(Database::TrackListId tracklistId, std::size_t maxCount) const override;
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TrackContainer getSimilarTracks(const std::vector<Database::TrackId>& tracksId, std::size_t maxCount) const override;
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ReleaseContainer getSimilarReleases(Database::ReleaseId releaseId, std::size_t maxCount) const override;
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ArtistContainer getSimilarArtists(Database::ArtistId artistId, EnumSet<Database::TrackArtistLinkType> linkTypes, std::size_t maxCount) const override;
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void loadFromCache(FeaturesEngineCache cache);
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// Use training (may be very slow)
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struct TrainSettings
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{
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std::size_t iterationCount {10};
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float sampleCountPerNeuron {4};
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FeatureSettingsMap featureSettingsMap;
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};
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void loadFromTraining(const TrainSettings& trainSettings, const ProgressCallback& progressCallback);
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template <typename IdType>
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using ObjectPositions = std::unordered_map<IdType, std::vector<SOM::Position>>;
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using ArtistPositions = ObjectPositions<Database::ArtistId>;
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using ReleasePositions = ObjectPositions<Database::ReleaseId>;
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using TrackPositions = ObjectPositions<Database::TrackId>;
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template <typename IdType>
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using ObjectMatrix = SOM::Matrix<std::vector<IdType>>;
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using ArtistMatrix = ObjectMatrix<Database::ArtistId>;
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using ReleaseMatrix = ObjectMatrix<Database::ReleaseId>;
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using TrackMatrix = ObjectMatrix<Database::TrackId>;
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void load(const SOM::Network& network, const TrackPositions& tracksPosition);
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FeaturesEngineCache toCache() const;
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template <typename IdType>
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static std::vector<SOM::Position> getMatchingRefVectorsPosition(const std::vector<IdType>& ids, const ObjectPositions<IdType>& objectPositions);
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template <typename IdType>
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static std::vector<IdType> getObjectsIds(const std::vector<SOM::Position>& positions, const ObjectMatrix<IdType>& objectsMatrix);
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template <typename IdType>
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std::vector<IdType> getSimilarObjects(const std::vector<IdType>& ids,
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const ObjectMatrix<IdType>& objectMatrix,
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const ObjectPositions<IdType>& objectPositions,
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std::size_t maxCount) const;
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Database::Db& _db;
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bool _loadCancelled {};
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std::unique_ptr<SOM::Network> _network;
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double _networkRefVectorsDistanceMedian {};
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ArtistPositions _artistPositions;
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std::unordered_map<Database::TrackArtistLinkType, ArtistMatrix> _artistMatrix;
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ReleasePositions _releasePositions;
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ReleaseMatrix _releaseMatrix;
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TrackPositions _trackPositions;
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TrackMatrix _trackMatrix;
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static inline FeaturesFetchFunc _featuresFetchFunc;
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};
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template <typename IdType>
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std::vector<SOM::Position>
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FeaturesEngine::getMatchingRefVectorsPosition(const std::vector<IdType>& ids, const ObjectPositions<IdType>& objectPositions)
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{
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std::vector<SOM::Position> res;
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if (ids.empty())
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return res;
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for (const IdType id : ids)
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{
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auto it = objectPositions.find(id);
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if (it == objectPositions.end())
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continue;
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for (const SOM::Position& position : it->second)
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Utils::push_back_if_not_present(res, position);
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}
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return res;
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}
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template <typename IdType>
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std::vector<IdType>
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FeaturesEngine::getObjectsIds(const std::vector<SOM::Position>& positions, const ObjectMatrix<IdType>& objectMatrix)
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{
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std::vector<IdType> res;
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for (const SOM::Position& position : positions)
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{
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for (const IdType id : objectMatrix.get(position))
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Utils::push_back_if_not_present(res, id);
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}
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return res;
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}
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template <typename IdType>
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std::vector<IdType>
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FeaturesEngine::getSimilarObjects(const std::vector<IdType>& ids,
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const ObjectMatrix<IdType>& objectMatrix,
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const ObjectPositions<IdType>& objectPositions,
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std::size_t maxCount) const
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{
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std::vector<IdType> res;
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std::vector<SOM::Position> searchedRefVectorsPosition {getMatchingRefVectorsPosition(ids, objectPositions)};
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if (searchedRefVectorsPosition.empty())
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return res;
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while (1)
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{
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std::vector<IdType> closestObjectIds {getObjectsIds(searchedRefVectorsPosition, objectMatrix)};
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// Remove objects that are already in input or already reported
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closestObjectIds.erase(std::remove_if(std::begin(closestObjectIds), std::end(closestObjectIds),
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[&](IdType id)
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{
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return std::find(std::cbegin(ids), std::cend(ids), id) != std::cend(ids);
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})
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, std::end(closestObjectIds));
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for (IdType id : closestObjectIds)
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{
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if (res.size() == maxCount)
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break;
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Utils::push_back_if_not_present(res, id);
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}
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if (res.size() == maxCount)
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break;
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// If there is not enough objects, try again with closest neighbour until there is too much distance
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const std::optional<SOM::Position> closestRefVectorPosition {_network->getClosestRefVectorPosition(searchedRefVectorsPosition, _networkRefVectorsDistanceMedian * 0.75)};
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if (!closestRefVectorPosition)
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break;
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Utils::push_back_if_not_present(searchedRefVectorsPosition, closestRefVectorPosition.value());
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}
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return res;
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}
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} // ns Recommendation
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