ObjectiveFunctionPointMetrics.java
package org.drip.function.rdtor1solver;
/*
* -*- 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
*
* 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>ObjectiveFunctionPointMetrics</i> holds the R<sup>d</sup> Point Base and Sensitivity Metrics of the
* Objective Function.
*
* <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/NumericalOptimizerLibrary.md">Numerical Optimizer</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/feed/README.md">Function</a></li>
* <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>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class ObjectiveFunctionPointMetrics
{
private double[] _jacobian = null;
private double[][] _hessian = null;
/**
* ObjectiveFunctionPointMetrics Constructor
*
* @param jacobian The Jacobian Array
* @param hessian The Hessian Matrix
*
* @throws java.lang.Exception Thrown if Inputs are Invalid
*/
public ObjectiveFunctionPointMetrics (
final double[] jacobian,
final double[][] hessian)
throws java.lang.Exception
{
if (null == (_jacobian = jacobian) ||
null == (_hessian = hessian))
{
throw new java.lang.Exception ("ObjectiveFunctionPointMetrics Constructor => Invalid Inputs");
}
int dimensionCount = _jacobian.length;
if (0 == dimensionCount || dimensionCount != _hessian.length)
{
throw new java.lang.Exception ("ObjectiveFunctionPointMetrics Constructor => Invalid Inputs");
}
for (int dimensionIndex = 0;
dimensionIndex < dimensionCount;
++dimensionIndex)
{
if (!org.drip.numerical.common.NumberUtil.IsValid (
_jacobian[dimensionIndex]
) || null == _hessian[dimensionIndex] ||
dimensionCount != _hessian[dimensionIndex].length ||
!org.drip.numerical.common.NumberUtil.IsValid (
_hessian[dimensionIndex]
))
{
throw new java.lang.Exception
("ObjectiveFunctionPointMetrics Constructor => Invalid Inputs");
}
}
}
/**
* Retrieve the Dimension
*
* @return The Dimension
*/
public int dimension()
{
return _jacobian.length;
}
/**
* Retrieve the Jacobian Array
*
* @return The Jacobian Array
*/
public double[] jacobian()
{
return _jacobian;
}
/**
* Retrieve the Hessian Matrix
*
* @return The Hessian Matrix
*/
public double[][] hessian()
{
return _hessian;
}
}