Files
richard-churchman cc0a2bee21 Extensive modifications to the serialisation of Neural Network models to support Newtonsoft Json.net rather than Binary Serializer.
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.
2023-12-24 10:22:22 +01:00

151 lines
5.3 KiB
C#

// Accord Machine Learning Library
// The Accord.NET Framework
// http://accord-framework.net
//
// Copyright © César Souza, 2009-2017
// cesarsouza at gmail.com
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 2.1 of the License, or (at your option) any later version.
//
// This library 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
// Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License along with this library; if not, write to the Free Software
// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
//
namespace Accord.Collections
{
using System;
using System.Collections.Generic;
using Accord.Compat;
/// <summary>
/// Base class for binary trees. This class does not implement a binary search
/// tree, but can used to implement one. For binary search trees, please refer
/// to <see cref="RedBlackTree{T}"/>, KDTree and VPTree.
/// </summary>
///
/// <example>
/// <para>
/// The <see cref="BinaryTree{TNode}"/> class is a base class for other tree classes
/// such as <see cref="RedBlackTree{T}"/>, KDTree and VPTree. For examples on how to
/// use those classes, please see their respective documentation pages.</para>
///
/// <para>
/// If you would like to implement your own binary tree that inherits from this class,
/// then you can do so as shown in the following example. First, make sure your custom
/// node class inherits from <see cref="BinaryNode{T}"/> and passes itself as the generic
/// argument of <see cref="BinaryNode{T}"/>:</para>
/// <code source="Unit Tests\Accord.Tests.Core\BinaryTreeTest.cs" region="doc_ctor_1" />
///
/// <para>
/// Now, once the tree node has been implemented, we can create a new <see cref="BinaryTree{TNode}"/>
/// and explore the tree in different ways as shown below:</para>
/// <code source="Unit Tests\Accord.Tests.Core\BinaryTreeTest.cs" region="doc_ctor_2" />
/// </example>
///
/// <typeparam name="TNode">The class type for the nodes of the tree.</typeparam>
///
[Serializable]
public class BinaryTree<TNode> : IEnumerable<TNode>
where TNode : BinaryNode<TNode>
{
/// <summary>
/// Gets the root node of this tree.
/// </summary>
///
public TNode Root { get; set; }
/// <summary>
/// Returns an enumerator that iterates through the tree.
/// </summary>
///
/// <returns>
/// An <see cref="T:System.Collections.IEnumerator"/> object
/// that can be used to iterate through the collection.
/// </returns>
///
public virtual IEnumerator<TNode> GetEnumerator()
{
if (Root == null)
yield break;
var stack = new Stack<TNode>(new[] { Root });
while (stack.Count != 0)
{
TNode current = stack.Pop();
yield return current;
if (current.Left != null)
stack.Push(current.Left);
if (current.Right != null)
stack.Push(current.Right);
}
}
/// <summary>
/// Traverse the tree using a <see cref="TreeTraversal">tree traversal
/// method</see>. Can be iterated with a foreach loop.
/// </summary>
///
/// <param name="method">The tree traversal method. Common methods are
/// available in the <see cref="TreeTraversal"/>static class.</param>
///
/// <returns>An <see cref="IEnumerable{T}"/> object which can be used to
/// traverse the tree using the chosen traversal method.</returns>
///
public IEnumerable<TNode> Traverse(BinaryTraversalMethod<TNode> method)
{
return new BinaryTreeTraversal(this, method);
}
/// <summary>
/// Returns an enumerator that iterates through the tree.
/// </summary>
///
/// <returns>
/// An <see cref="T:System.Collections.IEnumerator"/> object that can be used to iterate through the collection.
/// </returns>
///
System.Collections.IEnumerator System.Collections.IEnumerable.GetEnumerator()
{
return GetEnumerator();
}
private class BinaryTreeTraversal : IEnumerable<TNode>
{
private BinaryTree<TNode> tree;
private BinaryTraversalMethod<TNode> method;
public BinaryTreeTraversal(BinaryTree<TNode> tree, BinaryTraversalMethod<TNode> method)
{
this.tree = tree;
this.method = method;
}
public IEnumerator<TNode> GetEnumerator()
{
return method(tree);
}
System.Collections.IEnumerator System.Collections.IEnumerable.GetEnumerator()
{
return method(tree);
}
}
}
}