SylvesterInterpolantReconciler.java
package org.drip.sample.matrix;
import java.util.Map;
import org.drip.function.definition.R1ToR1;
import org.drip.function.matrix.FrobeniusCovariance;
import org.drip.function.matrix.Square;
import org.drip.numerical.common.NumberUtil;
import org.drip.numerical.eigen.EigenOutput;
import org.drip.numerical.eigen.QREigenComponentExtractor;
import org.drip.numerical.linearalgebra.Matrix;
import org.drip.service.env.EnvManager;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2019 Lakshmi Krishnamurthy
*
* This file is part of DROP, an open-source library targeting risk, transaction costs, exposure, margin
* calculations, valuation adjustment, and portfolio construction within and across fixed income,
* credit, commodity, equity, FX, and structured products.
*
* https://lakshmidrip.github.io/DROP/
*
* DROP is composed of three modules:
*
* - DROP Analytics Core - https://lakshmidrip.github.io/DROP-Analytics-Core/
* - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
* - DROP Numerical Core - https://lakshmidrip.github.io/DROP-Numerical-Core/
*
* DROP Analytics Core implements libraries for the following:
* - Fixed Income Analytics
* - Asset Backed Analytics
* - XVA Analytics
* - Exposure and Margin Analytics
*
* DROP Portfolio Core implements libraries for the following:
* - Asset Allocation Analytics
* - Transaction Cost Analytics
*
* DROP Numerical Core implements libraries for the following:
* - Statistical Learning
* - Numerical Optimizer
* - Spline Builder
* - Algorithm Support
*
* Documentation for DROP is Spread Over:
*
* - Main => https://lakshmidrip.github.io/DROP/
* - Wiki => https://github.com/lakshmiDRIP/DROP/wiki
* - GitHub => https://github.com/lakshmiDRIP/DROP
* - Repo Layout Taxonomy => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
* - Javadoc => https://lakshmidrip.github.io/DROP/Javadoc/index.html
* - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
* - Release Versions => https://lakshmidrip.github.io/DROP/version.html
* - Community Credits => https://lakshmidrip.github.io/DROP/credits.html
* - Issues Catalog => https://github.com/lakshmiDRIP/DROP/issues
* - JUnit => https://lakshmidrip.github.io/DROP/junit/index.html
* - Jacoco => https://lakshmidrip.github.io/DROP/jacoco/index.html
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
*
* You may obtain a copy of the License at
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
*
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/**
* <i>SylvesterInterpolantReconciler</i> demonstrates the Construction and Usage of the Sylvester Matrix
* Interpolant. The References are:
*
* <br><br>
* <ul>
* <li>
* Claerbout, J. F. (1985): <i>Fundamentals of Geo-physical Data Processing</i> <b>Blackwell
* Scientific</b>
* </li>
* <li>
* Horn, R. A., and C. R. Johnson (1991): <i>Topics in Matrix Analysis</i> <b>Cambridge University
* Press</b>
* </li>
* <li>
* Schwerdtfeger, A. (1938): <i>Les Fonctions de Matrices: Les Fonctions Univalentes I</i>
* <b>Hermann</b> Paris, France
* </li>
* <li>
* Sylvester, J. J. (1883): On the Equation to the Secular Inequalities in the Planetary Theory
* <i>The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science</i> <b>16
* (100)</b> 267-269
* </li>
* <li>
* Wikipedia (2019): Sylvester Formula https://en.wikipedia.org/wiki/Sylvester%27s_formula
* </li>
* </ul>
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalCore.md">Numerical Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalSupportLibrary.md">Numerical Support Library</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sample/README.md">Sample</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sample/matrix/README.md">Linear Algebra and Matrix Utilities</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class SylvesterInterpolantReconciler
{
public static final void main (
final String[] argumentArray)
throws Exception
{
EnvManager.InitEnv (
""
);
double[][] a =
{
{1, 3},
{4, 2},
};
QREigenComponentExtractor qrece = new QREigenComponentExtractor (
50,
0.00001
);
EigenOutput eigenOutput = qrece.eigenize (
a
);
double[] eigenValueArray = eigenOutput.eigenValueArray();
System.out.println ("\t|-----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| ORIGINAL MATRIX",
a
);
System.out.println ("\t|-----------------------------------------|");
System.out.println();
System.out.println ("\t|-----------------------------------------|");
System.out.println ("\t| EIGEN VALUES |");
System.out.println ("\t|-----------------------------------------|");
System.out.println ("\t| " + eigenValueArray[0] + " | " + eigenValueArray[1]);
System.out.println ("\t|-----------------------------------------|");
double[][] frobeniusCovariant0 = new double[2][2];
double[][] frobeniusCovariant1 = new double[2][2];
frobeniusCovariant0[0][0] = (a[0][0] - eigenValueArray[1]) / (eigenValueArray[0] - eigenValueArray[1]);
frobeniusCovariant0[1][1] = (a[1][1] - eigenValueArray[1]) / (eigenValueArray[0] - eigenValueArray[1]);
frobeniusCovariant0[0][1] = a[0][1] / (eigenValueArray[0] - eigenValueArray[1]);
frobeniusCovariant0[1][0] = a[1][0] / (eigenValueArray[0] - eigenValueArray[1]);
frobeniusCovariant1[0][0] = (a[0][0] - eigenValueArray[0]) / (eigenValueArray[1] - eigenValueArray[0]);
frobeniusCovariant1[1][1] = (a[1][1] - eigenValueArray[0]) / (eigenValueArray[1] - eigenValueArray[0]);
frobeniusCovariant1[0][1] = a[0][1] / (eigenValueArray[1] - eigenValueArray[0]);
frobeniusCovariant1[1][0] = a[1][0] / (eigenValueArray[1] - eigenValueArray[0]);
System.out.println();
System.out.println ("\t|-----------------------------------------|");
System.out.println ("\t| SYLVESTER RECONCILER |");
System.out.println ("\t|-----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| FROBENIUS COVARIANT 0",
frobeniusCovariant0
);
System.out.println ("\t|-----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| FROBENIUS COVARIANT 1",
frobeniusCovariant1
);
System.out.println ("\t|-----------------------------------------|");
double[][] recoveredA = Matrix.Scale2D (
frobeniusCovariant0,
eigenValueArray[0]
);
double[][] recoveredA1 = Matrix.Scale2D (
frobeniusCovariant1,
eigenValueArray[1]
);
recoveredA[0][0] += recoveredA1[0][0];
recoveredA[0][1] += recoveredA1[0][1];
recoveredA[1][0] += recoveredA1[1][0];
recoveredA[1][1] += recoveredA1[1][1];
System.out.println ("\t|------------------------------------------|");
NumberUtil.PrintMatrix (
"\t| RECOVERED MATRIX",
recoveredA
);
System.out.println ("\t|------------------------------------------|");
double[][] inverseA = Matrix.Scale2D (
frobeniusCovariant0,
1. / eigenValueArray[0]
);
double[][] inverseA1 = Matrix.Scale2D (
frobeniusCovariant1,
1. / eigenValueArray[1]
);
inverseA[0][0] += inverseA1[0][0];
inverseA[0][1] += inverseA1[0][1];
inverseA[1][0] += inverseA1[1][0];
inverseA[1][1] += inverseA1[1][1];
System.out.println ("\t|----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| INVERSE MATRIX",
inverseA
);
System.out.println ("\t|----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| INVERSE MATRIX",
Matrix.Invert (
a,
""
)
);
System.out.println ("\t|----------------------------------------|");
Square aSquare = new Square (
a
);
FrobeniusCovariance frobeniusCovariance = aSquare.frobeniusCovariance();
Map<Double, Square> componentMap = frobeniusCovariance.componentMap();
Object[] eigenValueKey = componentMap.keySet().toArray();
frobeniusCovariant0 = componentMap.get (
eigenValueKey[0]
).grid();
frobeniusCovariant1 = frobeniusCovariance.componentMap().get (
eigenValueKey[1]
).grid();
System.out.println ("\t|-----------------------------------------|");
System.out.println ("\t| SYLVESTER RECONCILER |");
System.out.println ("\t|-----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| FROBENIUS COVARIANT 0",
frobeniusCovariant0
);
System.out.println ("\t|-----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| FROBENIUS COVARIANT 1",
frobeniusCovariant1
);
System.out.println ("\t|-----------------------------------------|");
recoveredA = aSquare.evaluate (
new R1ToR1 (
null
)
{
@Override public double evaluate (
final double x)
throws Exception
{
return x;
}
}
);
System.out.println ("\t|----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| RECOVERED MATRIX",
recoveredA
);
System.out.println ("\t|----------------------------------------|");
inverseA = aSquare.evaluate (
new R1ToR1 (
null
)
{
@Override public double evaluate (
final double x)
throws Exception
{
return 1. / x;
}
}
);
System.out.println ("\t|----------------------------------------|");
NumberUtil.PrintMatrix (
"\t| INVERSE MATRIX",
inverseA
);
System.out.println ("\t|----------------------------------------|");
EnvManager.TerminateEnv();
}
}