LinearizationOutput.java

  1. package org.drip.numerical.linearalgebra;

  2. /*
  3.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  4.  */

  5. /*!
  6.  * Copyright (C) 2020 Lakshmi Krishnamurthy
  7.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  8.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  9.  * Copyright (C) 2017 Lakshmi Krishnamurthy
  10.  * Copyright (C) 2016 Lakshmi Krishnamurthy
  11.  * Copyright (C) 2015 Lakshmi Krishnamurthy
  12.  * Copyright (C) 2014 Lakshmi Krishnamurthy
  13.  * Copyright (C) 2013 Lakshmi Krishnamurthy
  14.  *
  15.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  16.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  17.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  18.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  19.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  20.  *      and computational support.
  21.  *  
  22.  *      https://lakshmidrip.github.io/DROP/
  23.  *  
  24.  *  DROP is composed of three modules:
  25.  *  
  26.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  27.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  28.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  29.  *
  30.  *  DROP Product Core implements libraries for the following:
  31.  *  - Fixed Income Analytics
  32.  *  - Loan Analytics
  33.  *  - Transaction Cost Analytics
  34.  *
  35.  *  DROP Portfolio Core implements libraries for the following:
  36.  *  - Asset Allocation Analytics
  37.  *  - Asset Liability Management Analytics
  38.  *  - Capital Estimation Analytics
  39.  *  - Exposure Analytics
  40.  *  - Margin Analytics
  41.  *  - XVA Analytics
  42.  *
  43.  *  DROP Computational Core implements libraries for the following:
  44.  *  - Algorithm Support
  45.  *  - Computation Support
  46.  *  - Function Analysis
  47.  *  - Model Validation
  48.  *  - Numerical Analysis
  49.  *  - Numerical Optimizer
  50.  *  - Spline Builder
  51.  *  - Statistical Learning
  52.  *
  53.  *  Documentation for DROP is Spread Over:
  54.  *
  55.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  56.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  57.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  58.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  59.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  60.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  61.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  62.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  63.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  64.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  65.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  66.  *
  67.  *  Licensed under the Apache License, Version 2.0 (the "License");
  68.  *      you may not use this file except in compliance with the License.
  69.  *  
  70.  *  You may obtain a copy of the License at
  71.  *      http://www.apache.org/licenses/LICENSE-2.0
  72.  *  
  73.  *  Unless required by applicable law or agreed to in writing, software
  74.  *      distributed under the License is distributed on an "AS IS" BASIS,
  75.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  76.  *  
  77.  *  See the License for the specific language governing permissions and
  78.  *      limitations under the License.
  79.  */

  80. /**
  81.  * <i>LinearizationOutput</i> holds the output of a sequence of linearization operations. It contains the
  82.  * transformed original matrix, the transformed RHS, and the method used for the linearization operation.
  83.  *
  84.  * <br><br>
  85.  *  <ul>
  86.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  87.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalAnalysisLibrary.md">Numerical Analysis Library</a></li>
  88.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/numerical/README.md">Numerical Quadrature, Differentiation, Eigenization, Linear Algebra, and Utilities</a></li>
  89.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/numerical/linearalgebra/README.md">Linear Algebra Matrix Transform Library</a></li>
  90.  *  </ul>
  91.  * <br><br>
  92.  *
  93.  * @author Lakshmi Krishnamurthy
  94.  */

  95. public class LinearizationOutput {
  96.     private double[] _adblTransformedRHS = null;
  97.     private double[][] _aadblTransformedMatrix = null;
  98.     private java.lang.String _strLinearizationMethod = "";

  99.     /**
  100.      * LinearizationOutput constructor
  101.      *
  102.      * @param adblTransformedRHS The Transformed RHS
  103.      * @param aadblTransformedMatrix The Transformed Matrix
  104.      * @param strLinearizationMethod Method used for the Linearization
  105.      *
  106.      * @throws java.lang.Exception Thrown if the inputs are invalid
  107.      */

  108.     public LinearizationOutput (
  109.         final double[] adblTransformedRHS,
  110.         final double[][] aadblTransformedMatrix,
  111.         final java.lang.String strLinearizationMethod)
  112.         throws java.lang.Exception
  113.     {
  114.         if (null == (_adblTransformedRHS = adblTransformedRHS) || null == (_aadblTransformedMatrix =
  115.             aadblTransformedMatrix) || null == (_strLinearizationMethod = strLinearizationMethod) ||
  116.                 _strLinearizationMethod.isEmpty())
  117.             throw new java.lang.Exception ("LinearizationOutput ctr: Invalid Inputs");

  118.         int iSize = _adblTransformedRHS.length;

  119.         if (0 == iSize || iSize != _aadblTransformedMatrix.length || null == _aadblTransformedMatrix[0] ||
  120.             iSize != _aadblTransformedMatrix[0].length)
  121.             throw new java.lang.Exception ("LinearizationOutput ctr: Invalid Inputs");
  122.     }

  123.     /**
  124.      * The RHS
  125.      *
  126.      * @return The RHS
  127.      */

  128.     public double[] getTransformedRHS()
  129.     {
  130.         return _adblTransformedRHS;
  131.     }

  132.     /**
  133.      * The Transformed Matrix
  134.      *
  135.      * @return The Transformed Matrix
  136.      */

  137.     public double[][] getTransformedMatrix()
  138.     {
  139.         return _aadblTransformedMatrix;
  140.     }

  141.     /**
  142.      * The Linearization Method
  143.      *
  144.      * @return The Linearization Method
  145.      */

  146.     public java.lang.String getLinearizationMethod()
  147.     {
  148.         return _strLinearizationMethod;
  149.     }
  150. }