ObjectiveFunctionPointMetrics.java

  1. package org.drip.function.rdtor1solver;

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

  77. /**
  78.  * <i>ObjectiveFunctionPointMetrics</i> holds the R<sup>d</sup> Point Base and Sensitivity Metrics of the
  79.  * Objective Function.
  80.  *
  81.  *  <br><br>
  82.  *  <ul>
  83.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalCore.md">Numerical Core Module</a></li>
  84.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalOptimizerLibrary.md">Numerical Optimizer</a></li>
  85.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/feed/README.md">Function</a></li>
  86.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/feed/rdtor1solver/README.md">R<sup>d</sup> To R<sup>1</sup> Solver</a></li>
  87.  *  </ul>
  88.  *
  89.  * @author Lakshmi Krishnamurthy
  90.  */

  91. public class ObjectiveFunctionPointMetrics
  92. {
  93.     private double[] _jacobian = null;
  94.     private double[][] _hessian = null;

  95.     /**
  96.      * ObjectiveFunctionPointMetrics Constructor
  97.      *
  98.      * @param jacobian The Jacobian Array
  99.      * @param hessian The Hessian Matrix
  100.      *
  101.      * @throws java.lang.Exception Thrown if Inputs are Invalid
  102.      */

  103.     public ObjectiveFunctionPointMetrics (
  104.         final double[] jacobian,
  105.         final double[][] hessian)
  106.         throws java.lang.Exception
  107.     {
  108.         if (null == (_jacobian = jacobian) ||
  109.             null == (_hessian = hessian))
  110.         {
  111.             throw new java.lang.Exception ("ObjectiveFunctionPointMetrics Constructor => Invalid Inputs");
  112.         }

  113.         int dimensionCount = _jacobian.length;

  114.         if (0 == dimensionCount || dimensionCount != _hessian.length)
  115.         {
  116.             throw new java.lang.Exception ("ObjectiveFunctionPointMetrics Constructor => Invalid Inputs");
  117.         }

  118.         for (int dimensionIndex = 0;
  119.             dimensionIndex < dimensionCount;
  120.             ++dimensionIndex)
  121.         {
  122.             if (!org.drip.numerical.common.NumberUtil.IsValid (
  123.                 _jacobian[dimensionIndex]
  124.             ) || null == _hessian[dimensionIndex] ||
  125.                 dimensionCount != _hessian[dimensionIndex].length ||
  126.                 !org.drip.numerical.common.NumberUtil.IsValid (
  127.                     _hessian[dimensionIndex]
  128.             ))
  129.             {
  130.                 throw new java.lang.Exception
  131.                     ("ObjectiveFunctionPointMetrics Constructor => Invalid Inputs");
  132.             }
  133.         }
  134.     }

  135.     /**
  136.      * Retrieve the Dimension
  137.      *
  138.      * @return The Dimension
  139.      */

  140.     public int dimension()
  141.     {
  142.         return _jacobian.length;
  143.     }

  144.     /**
  145.      * Retrieve the Jacobian Array
  146.      *
  147.      * @return The Jacobian Array
  148.      */

  149.     public double[] jacobian()
  150.     {
  151.         return _jacobian;
  152.     }

  153.     /**
  154.      * Retrieve the Hessian Matrix
  155.      *
  156.      * @return The Hessian Matrix
  157.      */

  158.     public double[][] hessian()
  159.     {
  160.         return _hessian;
  161.     }
  162. }