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.
172 lines
5.3 KiB
C#
172 lines
5.3 KiB
C#
// Accord Math 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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// Copyright © Diego Catalano, 2013
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// diego.catalano at live.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.Math
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{
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using System;
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using AForge.Math;
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/// <summary>
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/// Discrete Sine Transform
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/// </summary>
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///
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/// <remarks>
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/// <para>
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/// In mathematics, the discrete sine transform (DST) is a Fourier-related transform
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/// similar to the discrete Fourier transform (DFT), but using a purely real matrix. It
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/// is equivalent to the imaginary parts of a DFT of roughly twice the length, operating
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/// on real data with odd symmetry (since the Fourier transform of a real and odd function
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/// is imaginary and odd), where in some variants the input and/or output data are shifted
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/// by half a sample.</para>
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///
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/// <para>
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/// References:
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/// <list type="bullet">
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/// <item><description>
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/// Wikipedia contributors, "Discrete sine transform," Wikipedia, The Free Encyclopedia,
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/// available at: http://en.wikipedia.org/w/index.php?title=Discrete_sine_transform </description></item>
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/// <item><description>
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/// K. R. Castleman, Digital Image Processing. Chapter 13, p.288.
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/// Prentice. Hall, 1998.</description></item>
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/// </list></para>
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/// </remarks>
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///
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public static class SineTransform
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{
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/// <summary>
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/// Forward Discrete Sine Transform.
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/// </summary>
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///
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public static void DST(double[] data)
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{
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double[] result = new double[data.Length];
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for (int k = 1; k < result.Length + 1; k++)
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{
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double sum = 0;
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for (int i = 1; i < data.Length + 1; i++)
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sum += data[i - 1] * Math.Sin(Math.PI * ((k * i) / (data.Length + 1.0)));
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result[k - 1] = sum;
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}
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for (int i = 0; i < data.Length; i++)
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data[i] = result[i];
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}
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/// <summary>
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/// Inverse Discrete Sine Transform.
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/// </summary>
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///
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public static void IDST(double[] data)
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{
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double[] result = new double[data.Length];
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double inverse = 2.0 / (data.Length + 1);
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for (int k = 1; k < result.Length + 1; k++)
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{
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double sum = 0;
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for (int i = 1; i < data.Length + 1; i++)
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sum += data[i - 1] * Math.Sin(Math.PI * ((k * i) / (data.Length + 1.0)));
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result[k - 1] = sum * inverse;
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}
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for (int i = 0; i < data.Length; i++)
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data[i] = result[i];
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}
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/// <summary>
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/// Forward Discrete Sine Transform.
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/// </summary>
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///
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public static void DST(double[][] data)
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{
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int rows = data.Length;
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int cols = data[0].Length;
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double[] row = new double[cols];
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double[] col = new double[rows];
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for (int i = 0; i < rows; i++)
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{
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for (int j = 0; j < row.Length; j++)
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row[j] = data[i][j];
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DST(row);
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for (int j = 0; j < row.Length; j++)
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data[i][j] = row[j];
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}
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for (int j = 0; j < cols; j++)
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{
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for (int i = 0; i < col.Length; i++)
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col[i] = data[i][j];
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DST(col);
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for (int i = 0; i < col.Length; i++)
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data[i][j] = col[i];
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}
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}
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/// <summary>
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/// Inverse Discrete Sine Transform.
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/// </summary>
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///
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public static void IDST(double[][] data)
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{
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int rows = data.Length;
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int cols = data[0].Length;
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double[] row = new double[cols];
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double[] col = new double[rows];
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for (int j = 0; j < cols; j++)
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{
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for (int i = 0; i < row.Length; i++)
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col[i] = data[i][j];
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IDST(col);
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for (int i = 0; i < col.Length; i++)
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data[i][j] = col[i];
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}
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for (int i = 0; i < rows; i++)
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{
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for (int j = 0; j < row.Length; j++)
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row[j] = data[i][j];
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IDST(row);
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for (int j = 0; j < row.Length; j++)
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data[i][j] = row[j];
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}
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}
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}
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}
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