[mob][photos] Remove ClusterResult old deprecated code

mobile/lib/services/machine_learning/face_ml/face_ml_result.dart

@@ -7,278 +7,12 @@ import "package:photos/models/file/file.dart";
 import 'package:photos/models/ml/ml_typedefs.dart';
 import "package:photos/models/ml/ml_versions.dart";
 import 'package:photos/services/machine_learning/face_ml/face_alignment/alignment_result.dart';
-import 'package:photos/services/machine_learning/face_ml/face_clustering/cosine_distance.dart';
 import 'package:photos/services/machine_learning/face_ml/face_detection/detection.dart';
 import 'package:photos/services/machine_learning/face_ml/face_filtering/face_filtering_constants.dart';
 import 'package:photos/services/machine_learning/face_ml/face_ml_methods.dart';
 
 final _logger = Logger('ClusterResult_FaceMlResult');
 
-// TODO: should I add [faceMlVersion] and [clusterMlVersion] to the [ClusterResult] class?
-@Deprecated('We are now just storing the cluster results directly in DB')
-class ClusterResult {
-  final int personId;
-  String? userDefinedName;
-  bool get hasUserDefinedName => userDefinedName != null;
-
-  String _thumbnailFaceId;
-  bool thumbnailFaceIdIsUserDefined;
-
-  final List<int> _fileIds;
-  final List<String> _faceIds;
-
-  final Embedding medoid;
-  double medoidDistanceThreshold;
-
-  List<int> get uniqueFileIds => _fileIds.toSet().toList();
-  List<int> get fileIDsIncludingPotentialDuplicates => _fileIds;
-
-  List<String> get faceIDs => _faceIds;
-
-  String get thumbnailFaceId => _thumbnailFaceId;
-
-  int get thumbnailFileId => getFileIdFromFaceId(_thumbnailFaceId);
-
-  /// Sets the thumbnail faceId to the given faceId.
-  /// Throws an exception if the faceId is not in the list of faceIds.
-  set setThumbnailFaceId(String faceId) {
-    if (!_faceIds.contains(faceId)) {
-      throw Exception(
-        "The faceId $faceId is not in the list of faceIds: $faceId",
-      );
-    }
-    _thumbnailFaceId = faceId;
-    thumbnailFaceIdIsUserDefined = true;
-  }
-
-  /// Sets the [userDefinedName] to the given [customName]
-  set setUserDefinedName(String customName) {
-    userDefinedName = customName;
-  }
-
-  int get clusterSize => _fileIds.toSet().length;
-
-  ClusterResult({
-    required this.personId,
-    required String thumbnailFaceId,
-    required List<int> fileIds,
-    required List<String> faceIds,
-    required this.medoid,
-    required this.medoidDistanceThreshold,
-    this.userDefinedName,
-    this.thumbnailFaceIdIsUserDefined = false,
-  })  : _thumbnailFaceId = thumbnailFaceId,
-        _faceIds = faceIds,
-        _fileIds = fileIds;
-
-  void addFileIDsAndFaceIDs(List<int> fileIDs, List<String> faceIDs) {
-    assert(fileIDs.length == faceIDs.length);
-    _fileIds.addAll(fileIDs);
-    _faceIds.addAll(faceIDs);
-  }
-
-  // TODO: Consider if we should recalculated the medoid and threshold when deleting or adding a file from the cluster
-  int removeFileId(int fileId) {
-    assert(_fileIds.length == _faceIds.length);
-    if (!_fileIds.contains(fileId)) {
-      throw Exception(
-        "The fileId $fileId is not in the list of fileIds: $fileId, so it's not in the cluster and cannot be removed.",
-      );
-    }
-
-    int removedCount = 0;
-    for (var i = 0; i < _fileIds.length; i++) {
-      if (_fileIds[i] == fileId) {
-        assert(getFileIdFromFaceId(_faceIds[i]) == fileId);
-        _fileIds.removeAt(i);
-        _faceIds.removeAt(i);
-        debugPrint(
-          "Removed fileId $fileId from cluster $personId at index ${i + removedCount}}",
-        );
-        i--; // Adjust index due to removal
-        removedCount++;
-      }
-    }
-
-    _ensureClusterSizeIsAboveMinimum();
-
-    return removedCount;
-  }
-
-  int addFileID(int fileID) {
-    assert(_fileIds.length == _faceIds.length);
-    if (_fileIds.contains(fileID)) {
-      return 0;
-    }
-
-    _fileIds.add(fileID);
-    _faceIds.add(FaceDetectionRelative.toFaceIDEmpty(fileID: fileID));
-
-    return 1;
-  }
-
-  void ensureThumbnailFaceIdIsInCluster() {
-    if (!_faceIds.contains(_thumbnailFaceId)) {
-      _thumbnailFaceId = _faceIds[0];
-    }
-  }
-
-  void _ensureClusterSizeIsAboveMinimum() {
-    if (clusterSize < minimumClusterSize) {
-      throw Exception(
-        "Cluster size is below minimum cluster size of $minimumClusterSize",
-      );
-    }
-  }
-
-  Map<String, dynamic> _toJson() => {
-        'personId': personId,
-        'thumbnailFaceId': _thumbnailFaceId,
-        'fileIds': _fileIds,
-        'faceIds': _faceIds,
-        'medoid': medoid,
-        'medoidDistanceThreshold': medoidDistanceThreshold,
-        if (userDefinedName != null) 'userDefinedName': userDefinedName,
-        'thumbnailFaceIdIsUserDefined': thumbnailFaceIdIsUserDefined,
-      };
-
-  String toJsonString() => jsonEncode(_toJson());
-
-  static ClusterResult _fromJson(Map<String, dynamic> json) {
-    return ClusterResult(
-      personId: json['personId'] ?? -1,
-      thumbnailFaceId: json['thumbnailFaceId'] ?? '',
-      fileIds:
-          (json['fileIds'] as List?)?.map((item) => item as int).toList() ?? [],
-      faceIds:
-          (json['faceIds'] as List?)?.map((item) => item as String).toList() ??
-              [],
-      medoid:
-          (json['medoid'] as List?)?.map((item) => item as double).toList() ??
-              [],
-      medoidDistanceThreshold: json['medoidDistanceThreshold'] ?? 0,
-      userDefinedName: json['userDefinedName'],
-      thumbnailFaceIdIsUserDefined:
-          json['thumbnailFaceIdIsUserDefined'] as bool,
-    );
-  }
-
-  static ClusterResult fromJsonString(String jsonString) {
-    return _fromJson(jsonDecode(jsonString));
-  }
-}
-
-class ClusterResultBuilder {
-  int personId = -1;
-  String? userDefinedName;
-  String thumbnailFaceId = '';
-  bool thumbnailFaceIdIsUserDefined = false;
-
-  List<int> fileIds = <int>[];
-  List<String> faceIds = <String>[];
-
-  List<Embedding> embeddings = <Embedding>[];
-  Embedding medoid = <double>[];
-  double medoidDistanceThreshold = 0;
-  bool medoidAndThresholdCalculated = false;
-  final int k = 5;
-
-  ClusterResultBuilder.createFromIndices({
-    required List<int> clusterIndices,
-    required List<int> labels,
-    required List<Embedding> allEmbeddings,
-    required List<int> allFileIds,
-    required List<String> allFaceIds,
-  }) {
-    final clusteredFileIds =
-        clusterIndices.map((fileIndex) => allFileIds[fileIndex]).toList();
-    final clusteredFaceIds =
-        clusterIndices.map((fileIndex) => allFaceIds[fileIndex]).toList();
-    final clusteredEmbeddings =
-        clusterIndices.map((fileIndex) => allEmbeddings[fileIndex]).toList();
-    personId = labels[clusterIndices[0]];
-    fileIds = clusteredFileIds;
-    faceIds = clusteredFaceIds;
-    thumbnailFaceId = faceIds[0];
-    embeddings = clusteredEmbeddings;
-  }
-
-  void calculateAndSetMedoidAndThreshold() {
-    if (embeddings.isEmpty) {
-      throw Exception("Cannot calculate medoid and threshold for empty list");
-    }
-
-    // Calculate the medoid and threshold
-    final (tempMedoid, distanceThreshold) =
-        _calculateMedoidAndDistanceTreshold(embeddings);
-
-    // Update the medoid
-    medoid = List.from(tempMedoid);
-
-    // Update the medoidDistanceThreshold as the distance of the medoid to its k-th nearest neighbor
-    medoidDistanceThreshold = distanceThreshold;
-
-    medoidAndThresholdCalculated = true;
-  }
-
-  (List<double>, double) _calculateMedoidAndDistanceTreshold(
-    List<List<double>> embeddings,
-  ) {
-    double minDistance = double.infinity;
-    List<double>? medoid;
-
-    // Calculate the distance between all pairs
-    for (int i = 0; i < embeddings.length; ++i) {
-      double totalDistance = 0;
-      for (int j = 0; j < embeddings.length; ++j) {
-        if (i != j) {
-          totalDistance += cosineDistance(embeddings[i], embeddings[j]);
-
-          // Break early if we already exceed minDistance
-          if (totalDistance > minDistance) {
-            break;
-          }
-        }
-      }
-
-      // Find the minimum total distance
-      if (totalDistance < minDistance) {
-        minDistance = totalDistance;
-        medoid = embeddings[i];
-      }
-    }
-
-    // Now, calculate k-th nearest neighbor for the medoid
-    final List<double> distancesToMedoid = [];
-    for (List<double> embedding in embeddings) {
-      if (embedding != medoid) {
-        distancesToMedoid.add(cosineDistance(medoid!, embedding));
-      }
-    }
-    distancesToMedoid.sort();
-    // TODO: empirically find the best k. Probably it should be dynamic in some way, so for instance larger for larger clusters and smaller for smaller clusters, especially since there are a lot of really small clusters and a few really large ones.
-    final double kthDistance = distancesToMedoid[
-        distancesToMedoid.length >= k ? k - 1 : distancesToMedoid.length - 1];
-
-    return (medoid!, kthDistance);
-  }
-
-  void changeThumbnailFaceId(String faceId) {
-    if (!faceIds.contains(faceId)) {
-      throw Exception(
-        "The faceId $faceId is not in the list of faceIds: $faceIds",
-      );
-    }
-    thumbnailFaceId = faceId;
-  }
-
-  void addFileIDsAndFaceIDs(List<int> addedFileIDs, List<String> addedFaceIDs) {
-    assert(addedFileIDs.length == addedFaceIDs.length);
-    fileIds.addAll(addedFileIDs);
-    faceIds.addAll(addedFaceIDs);
-  }
-}
-
 @immutable
 class FaceMlResult {
   final int fileId;