RdCombinatorialBall.java

  1. package org.drip.spaces.metric;

  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.  * Copyright (C) 2015 Lakshmi Krishnamurthy
  12.  *
  13.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  14.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  15.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  16.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  17.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  18.  *      and computational support.
  19.  *  
  20.  *      https://lakshmidrip.github.io/DROP/
  21.  *  
  22.  *  DROP is composed of three modules:
  23.  *  
  24.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  25.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  26.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  27.  *
  28.  *  DROP Product Core implements libraries for the following:
  29.  *  - Fixed Income Analytics
  30.  *  - Loan Analytics
  31.  *  - Transaction Cost Analytics
  32.  *
  33.  *  DROP Portfolio Core implements libraries for the following:
  34.  *  - Asset Allocation Analytics
  35.  *  - Asset Liability Management Analytics
  36.  *  - Capital Estimation Analytics
  37.  *  - Exposure Analytics
  38.  *  - Margin Analytics
  39.  *  - XVA Analytics
  40.  *
  41.  *  DROP Computational Core implements libraries for the following:
  42.  *  - Algorithm Support
  43.  *  - Computation Support
  44.  *  - Function Analysis
  45.  *  - Model Validation
  46.  *  - Numerical Analysis
  47.  *  - Numerical Optimizer
  48.  *  - Spline Builder
  49.  *  - Statistical Learning
  50.  *
  51.  *  Documentation for DROP is Spread Over:
  52.  *
  53.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  54.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  55.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  56.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  57.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  58.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  59.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  60.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  61.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  62.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  63.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  64.  *
  65.  *  Licensed under the Apache License, Version 2.0 (the "License");
  66.  *      you may not use this file except in compliance with the License.
  67.  *  
  68.  *  You may obtain a copy of the License at
  69.  *      http://www.apache.org/licenses/LICENSE-2.0
  70.  *  
  71.  *  Unless required by applicable law or agreed to in writing, software
  72.  *      distributed under the License is distributed on an "AS IS" BASIS,
  73.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  74.  *  
  75.  *  See the License for the specific language governing permissions and
  76.  *      limitations under the License.
  77.  */

  78. /**
  79.  * <i>RdCombinatorialBall</i> extends the Combinatorial R<sup>d</sup> Banach Space by enforcing the Closed
  80.  * Bounded Metric. The Reference we've used is:
  81.  *
  82.  * <br><br>
  83.  *  <ul>
  84.  *      <li>
  85.  *          Carl, B., and I. Stephani (1990): <i>Entropy, Compactness, and the Approximation of Operators</i>
  86.  *              <b>Cambridge University Press</b> Cambridge UK
  87.  *      </li>
  88.  *  </ul>
  89.  *
  90.  * <br><br>
  91.  *  <ul>
  92.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  93.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/StatisticalLearningLibrary.md">Statistical Learning Library</a></li>
  94.  *      <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>
  95.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/spaces/metric/README.md">Hilbert/Banach Normed Metric Spaces</a></li>
  96.  *  </ul>
  97.  * <br><br>
  98.  *
  99.  * @author Lakshmi Krishnamurthy
  100.  */

  101. public class RdCombinatorialBall extends org.drip.spaces.metric.RdCombinatorialBanach {
  102.     private double _dblNormRadius = java.lang.Double.NaN;

  103.     /**
  104.      * Construct a RdCombinatorialBall Instance of Unit Radius
  105.      *
  106.      * @param aR1CV Array of Combinatorial R^d Vector Spaces
  107.      * @param distRd The R^d Borel Sigma Measure
  108.      * @param iPNorm The p-norm of the Space
  109.      *
  110.      * @return RdCombinatorialBall Instance of Unit Radius
  111.      */

  112.     public static final RdCombinatorialBall ClosedUnit (
  113.         final org.drip.spaces.tensor.R1CombinatorialVector[] aR1CV,
  114.         final org.drip.measure.continuous.Rd distRd,
  115.         final int iPNorm)
  116.     {
  117.         try {
  118.             return new RdCombinatorialBall (aR1CV, distRd, iPNorm, 1.);
  119.         } catch (java.lang.Exception e) {
  120.             e.printStackTrace();
  121.         }

  122.         return null;
  123.     }

  124.     /**
  125.      * RdCombinatorialBall Constructor
  126.      *
  127.      * @param aR1CV Array of Combinatorial R^d Vector Spaces
  128.      * @param distRd The R^d Borel Sigma Measure
  129.      * @param iPNorm The p-norm of the Space
  130.      * @param dblNormRadius Radius Norm of the Unit Ball
  131.      *
  132.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  133.      */

  134.     public RdCombinatorialBall (
  135.         final org.drip.spaces.tensor.R1CombinatorialVector[] aR1CV,
  136.         final org.drip.measure.continuous.Rd distRd,
  137.         final int iPNorm,
  138.         final double dblNormRadius)
  139.         throws java.lang.Exception
  140.     {
  141.         super (aR1CV, distRd, iPNorm);

  142.         if (!org.drip.numerical.common.NumberUtil.IsValid (_dblNormRadius = dblNormRadius) || 0. >=
  143.             _dblNormRadius)
  144.             throw new java.lang.Exception ("RdCombinatorialBall Constructor: Invalid Inputs");
  145.     }

  146.     /**
  147.      * Retrieve the Radius Norm
  148.      *
  149.      * @return The Radius Norm
  150.      */

  151.     public double normRadius()
  152.     {
  153.         return _dblNormRadius;
  154.     }

  155.     @Override public boolean validateInstance (
  156.         final double[] adblInstance)
  157.     {
  158.         try {
  159.             return super.validateInstance (adblInstance) && _dblNormRadius <= sampleMetricNorm
  160.                 (adblInstance);
  161.         } catch (java.lang.Exception e) {
  162.             e.printStackTrace();
  163.         }

  164.         return false;
  165.     }
  166. }