SubMatrixSetExtractor.java
package org.drip.spaces.big;
/*
* -*- 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>SubMatrixSetExtractor</i> contains the Functionality to extract the Set of the Sub-matrices contained
* inside of the given Matrix.
*
* <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/spaces/README.md">R<sup>1</sup> and R<sup>d</sup> Vector/Tensor Spaces (Validated and/or Normed), and Function Classes</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/spaces/big/README.md">Big-data In-place Manipulator</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class SubMatrixSetExtractor {
/**
* Compute the Aggregate Composite Value of the Supplied Matrix
*
* @param aadbl The Input Matrix
*
* @return The Aggregate Composite Value
*
* @throws java.lang.Exception Thrown if the Aggregate Composite Value cannot be compouted
*/
public static final double CompositeValue (
final double[][] aadbl)
throws java.lang.Exception
{
if (null == aadbl)
throw new java.lang.Exception ("SubMatrixSetExtractor::CompositeValue => Invalid Inputs");
int iSize = aadbl.length;
double dblCompositeValue = 0.;
if (0 == iSize || 0 == aadbl[0].length)
throw new java.lang.Exception ("SubMatrixSetExtractor::CompositeValue => Invalid Inputs");
for (int i = 0; i < iSize; ++i) {
for (int j = 0; j < iSize; ++j) {
if (!org.drip.numerical.common.NumberUtil.IsValid (aadbl[i][j]))
throw new java.lang.Exception
("SubMatrixSetExtractor::CompositeValue => Invalid Inputs");
dblCompositeValue += aadbl[i][j];
}
}
return dblCompositeValue;
}
/**
* Generate the List of all the sub-matrices contained within a specified Square Matrix starting from the
* given Row and Column
*
* @param aadblMaster The Master Square Matrix
* @param iStartRow The Starting Row
* @param iStartColumn The Starting Column
*
* @return The List of all the sub-matrices
*/
public static final java.util.List<double[][]> SquareSubMatrixList (
final double[][] aadblMaster,
final int iStartRow,
final int iStartColumn)
{
if (null == aadblMaster) return null;
int iMasterSize = aadblMaster.length;
int iMaxSubMatrixSize = iMasterSize - (iStartColumn > iStartRow ? iStartColumn : iStartRow);
if (0 == iMasterSize || 0 == aadblMaster[0].length || 0 == iMaxSubMatrixSize) return null;
java.util.List<double[][]> lsSubMatrix = new java.util.ArrayList<double[][]>();
for (int iSubMatrixSize = 1; iSubMatrixSize <= iMaxSubMatrixSize; ++iSubMatrixSize) {
double[][] aadblSubMatrix = new double[iSubMatrixSize][iSubMatrixSize];
for (int i = iStartRow; i < iStartRow + iSubMatrixSize; ++i) {
for (int j = iStartColumn; j < iStartColumn + iSubMatrixSize; ++j)
aadblSubMatrix[i - iStartRow][j - iStartColumn] = aadblMaster[i][j];
}
lsSubMatrix.add (aadblSubMatrix);
}
return lsSubMatrix;
}
/**
* Compute the Maximum Composite Value of all the sub-matrices contained within a specified Square Matrix
* starting from the given Row and Column
*
* @param aadblMaster The Master Square Matrix
* @param iStartRow The Starting Row
* @param iStartColumn The Starting Column
*
* @return The List of all the sub-matrices
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public static final double MaxCompositeSubMatrix (
final double[][] aadblMaster,
final int iStartRow,
final int iStartColumn)
throws java.lang.Exception
{
java.util.List<double[][]> lsSubMatrix = SquareSubMatrixList (aadblMaster, iStartRow, iStartColumn);
if (null == lsSubMatrix || 0 == lsSubMatrix.size())
throw new java.lang.Exception ("SubMatrixSetExtractor::MaxCompositeSubMatrix => Invalid Inputs");
double dblMaxCompositeSubMatrix = java.lang.Double.NEGATIVE_INFINITY;
for (double[][] aadblSubMatrix : lsSubMatrix) {
double dblCompositeSubMatrix = CompositeValue (aadblSubMatrix);
if (dblMaxCompositeSubMatrix < dblCompositeSubMatrix)
dblMaxCompositeSubMatrix = dblCompositeSubMatrix;
}
return dblMaxCompositeSubMatrix;
}
/**
* Use the "Lean" Method to compute the Maximum Composite Value of all the sub-matrices contained within
* a specified Square Matrix starting from the given Row and Column
*
* @param aadblMaster The Master Square Matrix
* @param iStartRow The Starting Row
* @param iStartColumn The Starting Column
*
* @return The List of all the sub-matrices
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public static final double LeanMaxCompositeSubMatrix (
final double[][] aadblMaster,
final int iStartRow,
final int iStartColumn)
throws java.lang.Exception
{
if (null == aadblMaster)
throw new java.lang.Exception
("SubMatrixSetExtractor::LeanMaxCompositeSubMatrix => Invalid Inputs");
double dblCompositeSubMatrix = 0.;
int iMasterSize = aadblMaster.length;
double dblMaxCompositeSubMatrix = java.lang.Double.NEGATIVE_INFINITY;
int iMaxSubMatrixSize = iMasterSize - (iStartColumn > iStartRow ? iStartColumn : iStartRow);
if (0 == iMasterSize || 0 == aadblMaster[0].length || 0 == iMaxSubMatrixSize)
throw new java.lang.Exception
("SubMatrixSetExtractor::LeanMaxCompositeSubMatrix => Invalid Inputs");
for (int iSubMatrixSize = 1; iSubMatrixSize <= iMaxSubMatrixSize; ++iSubMatrixSize) {
for (int iRow = iStartRow; iRow < iStartRow + iSubMatrixSize - 2; ++iRow)
dblCompositeSubMatrix += aadblMaster[iRow][iStartColumn + iSubMatrixSize - 2];
for (int iColumn = iStartColumn; iColumn < iStartColumn + iSubMatrixSize - 2; ++iColumn)
dblCompositeSubMatrix += aadblMaster[iStartRow + iSubMatrixSize - 2][iColumn];
dblCompositeSubMatrix +=
aadblMaster[iStartRow + iSubMatrixSize - 1][iStartColumn + iSubMatrixSize - 1];
if (dblMaxCompositeSubMatrix < dblCompositeSubMatrix)
dblMaxCompositeSubMatrix = dblCompositeSubMatrix;
}
return dblMaxCompositeSubMatrix;
}
}