R1CombinatorialVector.java
package org.drip.spaces.tensor;
/*
* -*- 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>R1CombinatorialVector</i> exposes the normed/non-normed Discrete Spaces with R<sup>1</sup>
* Combinatorial Vector Elements.
*
* <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/StatisticalLearningLibrary.md">Statistical Learning Library</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/spaces/README.md">R<sup>1</sup> and R<sup>d</sup> Vector/Tensor Spaces (Validated and/or Normed), and Function Classes</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/spaces/tensor/README.md">R<sup>x</sup> Continuous/Combinatorial Tensor Spaces</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class R1CombinatorialVector implements org.drip.spaces.tensor.R1GeneralizedVector {
private java.util.List<java.lang.Double> _lsElementSpace = new java.util.ArrayList<java.lang.Double>();
/**
* R1CombinatorialVector Constructor
*
* @param lsElementSpace The List Space of Elements
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public R1CombinatorialVector (
final java.util.List<java.lang.Double> lsElementSpace)
throws java.lang.Exception
{
if (null == (_lsElementSpace = lsElementSpace) || 0 == _lsElementSpace.size())
throw new java.lang.Exception ("R1CombinatorialVector ctr: Invalid Inputs");
}
/**
* Retrieve the Full Candidate List of Elements
*
* @return The Full Candidate List of Elements
*/
public java.util.List<java.lang.Double> elementSpace()
{
return _lsElementSpace;
}
@Override public double leftEdge()
{
double dblLeftEdge = java.lang.Double.NaN;
for (double dblElement : _lsElementSpace) {
if (java.lang.Double.NEGATIVE_INFINITY == dblElement) return dblElement;
if (!org.drip.numerical.common.NumberUtil.IsValid (dblLeftEdge))
dblLeftEdge = dblElement;
else {
if (dblLeftEdge > dblElement) dblLeftEdge = dblElement;
}
}
return dblLeftEdge;
}
@Override public double rightEdge()
{
double dblRightEdge = java.lang.Double.NaN;
for (double dblElement : _lsElementSpace) {
if (java.lang.Double.POSITIVE_INFINITY == dblElement) return dblElement;
if (!org.drip.numerical.common.NumberUtil.IsValid (dblRightEdge))
dblRightEdge = dblElement;
else {
if (dblRightEdge < dblElement) dblRightEdge = dblElement;
}
}
return dblRightEdge;
}
@Override public boolean validateInstance (
final double dblX)
{
return _lsElementSpace.contains (dblX);
}
@Override public org.drip.spaces.tensor.Cardinality cardinality()
{
return org.drip.spaces.tensor.Cardinality.CountablyFinite (_lsElementSpace.size());
}
@Override public boolean match (
final org.drip.spaces.tensor.GeneralizedVector gvOther)
{
if (null == gvOther || !(gvOther instanceof R1CombinatorialVector)) return false;
R1CombinatorialVector r1cvOther = (R1CombinatorialVector) gvOther;
if (!cardinality().match (r1cvOther.cardinality())) return false;
java.util.List<java.lang.Double> lsElementSpaceOther = r1cvOther.elementSpace();
for (double dblElement : _lsElementSpace) {
if (!lsElementSpaceOther.contains (dblElement)) return false;
}
return true;
}
@Override public boolean subset (
final org.drip.spaces.tensor.GeneralizedVector gvOther)
{
if (null == gvOther || !(gvOther instanceof R1CombinatorialVector)) return false;
R1CombinatorialVector r1cvOther = (R1CombinatorialVector) gvOther;
if (cardinality().number() < r1cvOther.cardinality().number()) return false;
java.util.List<java.lang.Double> lsElementSpaceOther = r1cvOther.elementSpace();
for (double dblElement : _lsElementSpace) {
if (!lsElementSpaceOther.contains (dblElement)) return false;
}
return true;
}
@Override public boolean isPredictorBounded()
{
return leftEdge() != java.lang.Double.NEGATIVE_INFINITY && rightEdge() !=
java.lang.Double.POSITIVE_INFINITY;
}
@Override public double hyperVolume()
throws java.lang.Exception
{
if (!isPredictorBounded())
throw new java.lang.Exception ("R1CombinatorialVector::hyperVolume => Space not Bounded");
return rightEdge() - leftEdge();
}
}