RdUniform.java
package org.drip.measure.lebesgue;
/*
* -*- 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>RdUniform</i> implements the R<sup>d</sup> Lebesgue Measure Distribution that corresponds to a Uniform
* R<sup>d</sup> d-Volume Space.
*
* <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/measure/README.md">R<sup>d</sup> Continuous/Discrete Probability Measures</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/measure/lebesgue/README.md">Uniform Piece-wise Lebesgue Measure</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class RdUniform extends org.drip.measure.continuous.Rd {
private org.drip.spaces.tensor.RdGeneralizedVector _gmvs = null;
/**
* RdUniform Constructor
*
* @param gmvs The Vector Space Underlying the Measure
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public RdUniform (
final org.drip.spaces.tensor.RdGeneralizedVector gmvs)
throws java.lang.Exception
{
if (null == (_gmvs = gmvs)) throw new java.lang.Exception ("RdUniform ctr: Invalid Inputs");
}
/**
* Retrieve the Vector Space Underlying the Measure
*
* @return The Vector Space Underlying the Measure
*/
public org.drip.spaces.tensor.RdGeneralizedVector measureSpace()
{
return _gmvs;
}
@Override public double cumulative (
final double[] adblX)
throws java.lang.Exception
{
double[] adblLeftEdge = _gmvs.leftDimensionEdge();
double dblCumulative = 1.;
int iDimension = adblLeftEdge.length;
if (null == adblX || iDimension != adblX.length)
throw new java.lang.Exception ("RdLebesgue::cumulative => Invalid Inputs");
double[] adblRightEdge = _gmvs.rightDimensionEdge();
for (int i = 0; i < iDimension; ++i) {
if (!org.drip.numerical.common.NumberUtil.IsValid (adblX[i]) || adblX[i] > adblRightEdge[i])
throw new java.lang.Exception ("RdUniform::cumulative => Invalid Inputs");
dblCumulative *= (adblX[i] - adblLeftEdge[i]) / (adblRightEdge[i] - adblLeftEdge[i]);
}
return dblCumulative;
}
@Override public double incremental (
final double[] adblXLeft,
final double[] adblXRight)
throws java.lang.Exception
{
if (null == adblXLeft || null == adblXRight)
throw new java.lang.Exception ("RdUniform::incremental => Invalid Inputs");
double[] adblLeftEdge = _gmvs.leftDimensionEdge();
double dblIncremental = 1.;
int iDimension = adblLeftEdge.length;
if (iDimension != adblXLeft.length || iDimension != adblXRight.length)
throw new java.lang.Exception ("RdUniform::incremental => Invalid Inputs");
double[] adblRightEdge = _gmvs.rightDimensionEdge();
for (int i = 0; i < iDimension; ++i) {
if (!org.drip.numerical.common.NumberUtil.IsValid (adblXLeft[i]) || adblXLeft[i] < adblLeftEdge[i] ||
!org.drip.numerical.common.NumberUtil.IsValid (adblXRight[i]) || adblXRight[i] >
adblRightEdge[i])
throw new java.lang.Exception ("RdUniform::incremental => Invalid Inputs");
dblIncremental *= (adblXRight[i] - adblXLeft[i]) / (adblRightEdge[i] - adblLeftEdge[i]);
}
return dblIncremental;
}
@Override public double density (
final double[] adblX)
throws java.lang.Exception
{
return 1. / _gmvs.hyperVolume();
}
}