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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.
112 lines
7.3 KiB
C#
112 lines
7.3 KiB
C#
// Accord Statistics 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.Statistics.Visualizations
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{
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using System;
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using Accord.Math;
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using Accord.Compat;
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/// <summary>
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/// Histogram Bin
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/// </summary>
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///
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/// <remarks>
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/// <para>
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/// A "bin" is a container, where each element stores the total number of observations of a sample
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/// whose values lie within a given range. A histogram of a sample consists of a list of such bins
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/// whose range does not overlap with each other; or in other words, bins that are mutually exclusive.</para>
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/// <para>
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/// Unless <see cref="Histogram.InclusiveUpperBound"/> is true, the ranges of all bins <c>i</c> are
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/// defined as Edge[i] <= x < Edge[i+1]. Otherwise, the last bin will have an inclusive upper
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/// bound (i.e. will be defined as Edge[i] <= x <= Edge[i+1].</para>
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/// </remarks>
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///
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[Serializable]
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public class HistogramBin
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{
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private int index;
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private Histogram histogram;
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internal HistogramBin(Histogram histogram, int index)
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{
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this.index = index;
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this.histogram = histogram;
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}
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/// <summary>
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/// Gets the actual range of data this bin represents.
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/// </summary>
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///
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public DoubleRange Range
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{
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get
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{
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double min = histogram.Edges[index];
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double max = histogram.Edges[index + 1];
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return new DoubleRange(min, max);
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}
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}
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/// <summary>
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/// Gets the Width (range) for this histogram bin.
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/// </summary>
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///
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public double Width
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{
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get { return histogram.Edges[index + 1] - histogram.Edges[index]; }
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}
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/// <summary>
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/// Gets the Value (number of occurrences of a variable in a range)
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/// for this histogram bin.
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/// </summary>
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///
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public int Value
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{
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get { return histogram.Values[index]; }
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set { histogram.Values[index] = value; }
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}
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/// <summary>
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/// Gets whether the Histogram Bin contains the given value.
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/// </summary>
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///
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public bool Contains(double value)
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{
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if (histogram.InclusiveUpperBound &&
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index == histogram.Bins.Count - 1)
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{
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return value >= histogram.Edges[index] &&
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value <= histogram.Edges[index + 1];
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}
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else
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{
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return value >= histogram.Edges[index] &&
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value < histogram.Edges[index + 1];
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}
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}
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}
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}
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