UnitVector.java
package org.drip.function.definition;
/*
* -*- 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>UnitVector</i> implements the Normalized R<sup>d</sup> Unit Vector.
*
* <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/NumericalAnalysisLibrary.md">Numerical Analysis Library</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/function/README.md">R<sup>d</sup> To R<sup>d</sup> Function Analysis</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/function/definition/README.md">Function Implementation Ancillary Support Objects</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class UnitVector {
private double[] _adblComponent;
/**
* Construct an Instance of the Unit Vector from the Input Vector
*
* @param adbl The Input Double Vector
*
* @return The Unit Vector Instance
*/
public static final UnitVector Standard (
final double[] adbl)
{
if (null == adbl) return null;
int iDimension = adbl.length;
double dblGradientModulus = 0.;
double[] adblComponent = new double[iDimension];
if (0 == iDimension) return null;
for (int i = 0; i < iDimension; ++i) {
if (!org.drip.numerical.common.NumberUtil.IsValid (adbl[i])) return null;
dblGradientModulus += adbl[i] * adbl[i];
}
if (0. == dblGradientModulus) return null;
dblGradientModulus = java.lang.Math.sqrt (dblGradientModulus);
for (int i = 0; i < iDimension; ++i)
adblComponent[i] = adbl[i] / dblGradientModulus;
return new UnitVector (adblComponent);
}
protected UnitVector (
final double[] adblComponent)
{
_adblComponent = adblComponent;
}
/**
* Retrieve the Unit Vector's Component Array
*
* @return The Unit Vector's Component Array
*/
public double[] component()
{
return _adblComponent;
}
/**
* Compute the Directional Increment along the Vector
*
* @param adblVariate The Starting R^d Variate
* @param dblStepLength The Step Length
*
* @return The Directionally Incremented Vector
*/
public double[] directionalIncrement (
final double[] adblVariate,
final double dblStepLength)
{
if (null == adblVariate || !org.drip.numerical.common.NumberUtil.IsValid (dblStepLength)) return null;
int iVariateDimension = adblVariate.length;
double[] adblIncrementedVariate = new double[iVariateDimension];
if (iVariateDimension != _adblComponent.length) return null;
for (int i = 0; i < iVariateDimension; ++i) {
if (!org.drip.numerical.common.NumberUtil.IsValid (adblVariate[i])) return null;
adblIncrementedVariate[i] = adblVariate[i] + dblStepLength * _adblComponent[i];
}
return adblIncrementedVariate;
}
}