R2ArrayPathwiseProcessing.java
package org.drip.sample.algo;
import org.drip.numerical.common.FormatUtil;
import org.drip.service.env.EnvManager;
import org.drip.spaces.big.BigR2Array;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2020 Lakshmi Krishnamurthy
* Copyright (C) 2019 Lakshmi Krishnamurthy
* Copyright (C) 2018 Lakshmi Krishnamurthy
* Copyright (C) 2017 Lakshmi Krishnamurthy
* Copyright (C) 2016 Lakshmi Krishnamurthy
* Copyright (C) 2015 Lakshmi Krishnamurthy
*
* This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
* asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
* analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
* equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
* numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
* and computational support.
*
* https://lakshmidrip.github.io/DROP/
*
* DROP is composed of three modules:
*
* - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
* - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
* - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
*
* DROP Product Core implements libraries for the following:
* - Fixed Income Analytics
* - Loan Analytics
* - Transaction Cost Analytics
*
* DROP Portfolio Core implements libraries for the following:
* - Asset Allocation Analytics
* - Asset Liability Management Analytics
* - Capital Estimation Analytics
* - Exposure Analytics
* - Margin Analytics
* - XVA Analytics
*
* DROP Computational Core implements libraries for the following:
* - Algorithm Support
* - Computation Support
* - Function Analysis
* - Model Validation
* - Numerical Analysis
* - Numerical Optimizer
* - Spline Builder
* - Statistical Learning
*
* 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>R2ArrayPathwiseProcessing</i> demonstrates the Functionality that conducts an in-place Path-wise
* Processing of an Instance of Big R<sup>2</sup> Array.
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/StatisticalLearningLibrary.md">Statistical Learning Library</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sample/README.md">DROP API Construction and Usage</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sample/algo/README.md">C<sup>x</sup> R<sup>x</sup> In-Place Manipulation</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class R2ArrayPathwiseProcessing {
private static final void MaxPathwiseProduct (
final int iSize,
final int iNumSim)
throws Exception
{
double dblExpectedMaxPathResponse = 0.;
final double[][] aadblA = new double[iSize][iSize];
for (int iRun = 0; iRun < iNumSim; ++iRun) {
for (int i = 0; i < iSize; ++i) {
for (int j = 0; j < iSize; ++j)
aadblA[i][j] = Math.random();
}
dblExpectedMaxPathResponse += new BigR2Array (aadblA) {
@Override public double pathResponse (
final int iX,
final int iY,
final double dblPriorPathResponse)
throws Exception
{
return dblPriorPathResponse * aadblA[iX][iY];
}
@Override public double maxPathResponse()
throws Exception
{
return maxPathResponse (
0,
0,
1.
);
}
}.maxPathResponse();
}
System.out.println (
"\t|| EXPECTED MAX PATH PRODUCT => " +
FormatUtil.FormatDouble (dblExpectedMaxPathResponse / iNumSim, 1, 4, 1.) + " ||"
);
}
private static final void MaxPathwiseSum (
final int iSize,
final int iNumSim)
throws Exception
{
double dblExpectedMaxPathResponse = 0.;
final double[][] aadblA = new double[iSize][iSize];
for (int iRun = 0; iRun < iNumSim; ++iRun) {
for (int i = 0; i < iSize; ++i) {
for (int j = 0; j < iSize; ++j)
aadblA[i][j] = Math.random();
}
dblExpectedMaxPathResponse += new BigR2Array (aadblA) {
@Override public double pathResponse (
final int iX,
final int iY,
final double dblPriorPathResponse)
throws Exception
{
return dblPriorPathResponse + aadblA[iX][iY];
}
@Override public double maxPathResponse()
throws Exception
{
return maxPathResponse (
0,
0,
0.
);
}
}.maxPathResponse();
}
System.out.println (
"\t|| EXPECTED MAX PATH SUM => " +
FormatUtil.FormatDouble (dblExpectedMaxPathResponse / iNumSim, 1, 4, 1.) + " ||"
);
}
public static final void main (
final String[] astrArgs)
throws Exception
{
EnvManager.InitEnv (
"",
true
);
int iSize = 5;
int iNumSim = 1000000;
int iNumRunSet = 5;
System.out.println ();
for (int i = 0; i < iNumRunSet; ++i) {
System.out.println ("\t||--------------------------------------||");
MaxPathwiseProduct (
iSize,
iNumSim
);
MaxPathwiseSum (
iSize,
iNumSim
);
System.out.println ("\t||--------------------------------------||");
}
EnvManager.TerminateEnv();
}
}