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80 lines
2.6 KiB
80 lines
2.6 KiB
using System;
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namespace ZeroLevel.HNSW
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{
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/// <summary>
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/// Type of heuristic to select best neighbours for a node.
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/// </summary>
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public enum NeighbourSelectionHeuristic
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{
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/// <summary>
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/// Marker for the Algorithm 3 (SELECT-NEIGHBORS-SIMPLE) from the article. Implemented in <see cref="Algorithms.Algorithm3{TItem, TDistance}"/>
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/// </summary>
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SelectSimple,
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/// <summary>
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/// Marker for the Algorithm 4 (SELECT-NEIGHBORS-HEURISTIC) from the article. Implemented in <see cref="Algorithms.Algorithm4{TItem, TDistance}"/>
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/// </summary>
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SelectHeuristic
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}
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public sealed class NSWOptions<TItem>
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{
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/// <summary>
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/// Mox node connections on Layer
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/// </summary>
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public readonly int M;
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/// <summary>
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/// Max search buffer
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/// </summary>
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public readonly int EF;
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/// <summary>
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/// Max search buffer for inserting
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/// </summary>
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public readonly int EFConstruction;
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/// <summary>
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/// Distance function beetween vectors
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/// </summary>
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public readonly Func<TItem, TItem, float> Distance;
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public readonly bool ExpandBestSelection;
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public readonly bool KeepPrunedConnections;
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public readonly NeighbourSelectionHeuristic SelectionHeuristic;
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public readonly int LayersCount;
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private NSWOptions(int layersCount,
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int m,
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int ef,
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int ef_construction,
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Func<TItem, TItem, float> distance,
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bool expandBestSelection,
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bool keepPrunedConnections,
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NeighbourSelectionHeuristic selectionHeuristic)
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{
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LayersCount = layersCount;
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M = m;
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EF = ef;
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EFConstruction = ef_construction;
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Distance = distance;
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ExpandBestSelection = expandBestSelection;
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KeepPrunedConnections = keepPrunedConnections;
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SelectionHeuristic = selectionHeuristic;
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}
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public static NSWOptions<TItem> Create(int layersCount,
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int M,
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int EF,
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int EF_construction,
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Func<TItem, TItem, float> distance,
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bool expandBestSelection = false,
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bool keepPrunedConnections = false,
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NeighbourSelectionHeuristic selectionHeuristic = NeighbourSelectionHeuristic.SelectSimple) =>
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new NSWOptions<TItem>(layersCount, M, EF, EF_construction, distance, expandBestSelection, keepPrunedConnections, selectionHeuristic);
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}
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}
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