mirror of
https://github.com/hanzoai/jube-fork.git
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richard-churchman
cc0a2bee21
Included open-source Accord.net library code natively to the solution given the deprecated state of that project. Accord.net will be supported inside Jube for own needs (such as upgrading to .Net 7+). Accord.net libraries modified to compile to .Net 6. Modified Accord.net libraries to better support Newtonsoft Json.net serialisation. Included annotations in the Accord.net libraries to house important dependency statistics. Serialised json can be used independently of Jube to recall a Neural Network. Removal of Binary Serializer totally as a precursor to the projects support of .Net 7+. Extensive bug fixing in crucial functions of Neural Network training and recall. While this part of the system remains in Alpha, it is substantially more fit for purpose.
181 lines
7.1 KiB
C#
181 lines
7.1 KiB
C#
// Accord Machine Learning Library
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// The Accord.NET Framework
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// http://accord-framework.net
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//
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// Copyright © César Souza, 2009-2017
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// cesarsouza at gmail.com
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//
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// This library is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 2.1 of the License, or (at your option) any later version.
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//
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// This library 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 GNU
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// Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License along with this library; if not, write to the Free Software
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// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
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//
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namespace Accord.Collections
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{
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#if !MONO
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using Accord;
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using Accord.Collections;
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using Accord.Math;
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using Accord.Math.Distances;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Collections;
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using Accord.Compat;
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/// <summary>
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/// Vantage-Point Tree.
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/// </summary>
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///
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/// <seealso cref="SPTree"/>
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/// <seealso cref="VPTree"/>
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/// <seealso cref="KDTree"/>
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///
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[Serializable]
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public class VPTree : VPTree<double[]>
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{
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/// <summary>
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/// Creates a new vantage-point tree from the given points.
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/// </summary>
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///
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/// <param name="points">The points to be added to the tree.</param>
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/// <param name="inPlace">Whether to perform operations in place, altering the
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/// original array of points instead of creating an extra copy.</param>
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///
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/// <returns>A <see cref="VPTree"/> populated with the given data points.</returns>
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///
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public static VPTree FromData(double[][] points, bool inPlace = false)
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{
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var tree = new VPTree();
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tree.Root = tree.buildFromPoints(points, 0, points.Length, inPlace);
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return tree;
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}
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/// <summary>
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/// Creates a new vantage-point tree from the given points.
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/// </summary>
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///
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/// <param name="points">The points to be added to the tree.</param>
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/// <param name="inPlace">Whether to perform operations in place, altering the
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/// original array of points instead of creating an extra copy.</param>
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///
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/// <returns>A <see cref="VPTree"/> populated with the given data points.</returns>
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///
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public static VPTree<double> FromData(double[] points, bool inPlace = false)
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{
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return VPTree<double>.FromData(points, new Euclidean(), inPlace);
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}
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/// <summary>
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/// Creates a new vantage-point tree from the given points.
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/// </summary>
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///
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/// <param name="points">The points to be added to the tree.</param>
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/// <param name="distance">The distance function to use.</param>
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/// <param name="inPlace">Whether to perform operations in place, altering the
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/// original array of points instead of creating an extra copy.</param>
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///
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/// <returns>A <see cref="VPTree"/> populated with the given data points.</returns>
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///
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public static VPTree FromData(double[][] points, IDistance distance, bool inPlace = false)
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{
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var tree = new VPTree(distance);
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tree.Root = tree.buildFromPoints(points, 0, points.Length, inPlace);
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return tree;
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}
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/// <summary>
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/// Creates a new vantage-point tree from the given points.
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/// </summary>
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///
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/// <typeparam name="TPoint">The type for the position vectors.</typeparam>
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///
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/// <param name="points">The points to be added to the tree.</param>
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/// <param name="distance">The distance function to use.</param>
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/// <param name="inPlace">Whether to perform operations in place, altering the
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/// original array of points instead of creating an extra copy.</param>
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///
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/// <returns>A <see cref="VPTree{TPoint}"/> populated with the given data points.</returns>
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///
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public static VPTree<TPoint> FromData<TPoint>(TPoint[] points, IDistance<TPoint> distance, bool inPlace = false)
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{
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return VPTree<TPoint>.FromData(points, distance, inPlace);
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}
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/// <summary>
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/// Creates a new vantage-point tree from the given points.
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/// </summary>
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///
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/// <typeparam name="TData">The type of the value to be stored.</typeparam>
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///
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/// <param name="points">The points to be added to the tree.</param>
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/// <param name="values">The corresponding values at each data point.</param>
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/// <param name="inPlace">Whether to perform operations in place, altering the
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/// original array of points instead of creating an extra copy.</param>
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///
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/// <returns>A <see cref="VPTree{TPoint, TData}"/> populated with the given data points.</returns>
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///
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public static VPTree<double[], TData> FromData<TData>(double[][] points, TData[] values, bool inPlace = false)
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{
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return VPTree<double[], TData>.FromData(points, values, new Euclidean(), inPlace);
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}
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/// <summary>
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/// Creates a new vantage-point tree from the given points.
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/// </summary>
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///
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/// <typeparam name="TPoint">The type for the position vectors.</typeparam>
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/// <typeparam name="TData">The type of the value to be stored.</typeparam>
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///
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/// <param name="points">The points to be added to the tree.</param>
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/// <param name="values">The corresponding values at each data point.</param>
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/// <param name="distance">The distance function to use.</param>
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/// <param name="inPlace">Whether to perform operations in place, altering the
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/// original array of points instead of creating an extra copy.</param>
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///
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/// <returns>A <see cref="VPTree{TPoint, TData}"/> populated with the given data points.</returns>
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///
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public static VPTree<TPoint, TData> FromData<TPoint, TData>(TPoint[] points, TData[] values, IDistance<TPoint> distance, bool inPlace = false)
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{
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return VPTree<TPoint, TData>.FromData(points, values, distance, inPlace);
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}
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/// <summary>
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/// Initializes a new instance of the <see cref="VPTree"/> class.
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/// </summary>
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///
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/// <param name="distance">The distance to use when comparing points. Default is
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/// <see cref="Accord.Math.Distance.Euclidean(double[], double[])"/>.</param>
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///
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public VPTree(IDistance distance)
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: base(distance)
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{
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}
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/// <summary>
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/// Initializes a new instance of the <see cref="VPTree"/> class.
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/// </summary>
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///
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public VPTree()
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: base(new Euclidean())
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{
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}
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}
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#endif
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}
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