SegmentBestFitResponse.java

  1. package org.drip.spline.params;

  3. /*
  4.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  5.  */

  7. /*!
  8.  * Copyright (C) 2020 Lakshmi Krishnamurthy
  9.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  10.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  11.  * Copyright (C) 2017 Lakshmi Krishnamurthy
  12.  * Copyright (C) 2016 Lakshmi Krishnamurthy
  13.  * Copyright (C) 2015 Lakshmi Krishnamurthy
  14.  * Copyright (C) 2014 Lakshmi Krishnamurthy
  15.  * Copyright (C) 2013 Lakshmi Krishnamurthy
  16.  * 
  17.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  18.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  19.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  20.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  21.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  22.  *      and computational support.
  23.  *  
  24.  *      https://lakshmidrip.github.io/DROP/
  25.  *  
  26.  *  DROP is composed of three modules:
  27.  *  
  28.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  29.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  30.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  31.  * 
  32.  *  DROP Product Core implements libraries for the following:
  33.  *  - Fixed Income Analytics
  34.  *  - Loan Analytics
  35.  *  - Transaction Cost Analytics
  36.  * 
  37.  *  DROP Portfolio Core implements libraries for the following:
  38.  *  - Asset Allocation Analytics
  39.  *  - Asset Liability Management Analytics
  40.  *  - Capital Estimation Analytics
  41.  *  - Exposure Analytics
  42.  *  - Margin Analytics
  43.  *  - XVA Analytics
  44.  * 
  45.  *  DROP Computational Core implements libraries for the following:
  46.  *  - Algorithm Support
  47.  *  - Computation Support
  48.  *  - Function Analysis
  49.  *  - Model Validation
  50.  *  - Numerical Analysis
  51.  *  - Numerical Optimizer
  52.  *  - Spline Builder
  53.  *  - Statistical Learning
  54.  * 
  55.  *  Documentation for DROP is Spread Over:
  56.  * 
  57.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  58.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  59.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  60.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  61.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  62.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  63.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  64.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  65.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  66.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  67.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  68.  * 
  69.  *  Licensed under the Apache License, Version 2.0 (the "License");
  70.  *      you may not use this file except in compliance with the License.
  71.  *   
  72.  *  You may obtain a copy of the License at
  73.  *      http://www.apache.org/licenses/LICENSE-2.0
  74.  *  
  75.  *  Unless required by applicable law or agreed to in writing, software
  76.  *      distributed under the License is distributed on an "AS IS" BASIS,
  77.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  78.  *  
  79.  *  See the License for the specific language governing permissions and
  80.  *      limitations under the License.
  81.  */

  83. /**
  84.  * <i>SegmentBestFitResponse </i>implements basis per-segment Fitness Penalty Parameter Set. Currently it
  85.  * contains the Best Fit Penalty Weight Grid Matrix and the corresponding Segment Local Predictor
  86.  * Ordinate/Response Match Pair.
  87.  *
  88.  * <br><br>
  89.  *  <ul>
  90.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  91.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/SplineBuilderLibrary.md">Spline Builder Library</a></li>
  92.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/spline/README.md">Basis Splines and Linear Compounders across a Broad Family of Spline Basis Functions</a></li>
  93.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/spline/params/README.md">Spline Segment Construction Control Parameters</a></li>
  94.  *  </ul>
  95.  * <br><br>
  96.  *
  97.  * @author Lakshmi Krishnamurthy
  98.  */

  100. public class SegmentBestFitResponse {
  101.     private double[] _adblWeight = null;
  102.     private double[] _adblResponse = null;
  103.     private double[] _adblPredictorOrdinate = null;

  105.     /**
  106.      * Construct the SegmentBestFitResponse Instance from the given Inputs
  107.      * 
  108.      * @param adblPredictorOrdinate Array of Predictor Ordinates
  109.      * @param adblResponseValue Array of Response Values
  110.      * @param adblWeight Array of Weights
  111.      * 
  112.      * @return Instance of SegmentBestFitResponse
  113.      */

  115.     public static final SegmentBestFitResponse Create (
  116.         final double[] adblPredictorOrdinate,
  117.         final double[] adblResponseValue,
  118.         final double[] adblWeight)
  119.     {
  120.         SegmentBestFitResponse frp = null;

  122.         try {
  123.             frp = new SegmentBestFitResponse (adblWeight, adblResponseValue, adblPredictorOrdinate);
  124.         } catch (java.lang.Exception e) {
  125.             e.printStackTrace();

  127.             return null;
  128.         }

  130.         return frp.normalizeWeights() ? frp : null;
  131.     }

  133.     /**
  134.      * Construct the SegmentBestFitResponse Instance from the given Predictor Ordinate/Response Pairs, using
  135.      *  Uniform Weightings.
  136.      * 
  137.      * @param adblPredictorOrdinate Array of Predictor Ordinates
  138.      * @param adblResponseValue Array of Response Values
  139.      * 
  140.      * @return Instance of SegmentBestFitResponse
  141.      */

  143.     public static final SegmentBestFitResponse Create (
  144.         final double[] adblPredictorOrdinate,
  145.         final double[] adblResponseValue)
  146.     {
  147.         if (!org.drip.numerical.common.NumberUtil.IsValid (adblPredictorOrdinate)) return null;

  149.         int iNumWeight = adblPredictorOrdinate.length;
  150.         double[] adblWeight = new double[iNumWeight];

  152.         for (int i = 0; i < iNumWeight; ++i)
  153.             adblWeight[i] = 1.;

  155.         return Create (adblPredictorOrdinate, adblResponseValue, adblWeight);
  156.     }

  158.     private SegmentBestFitResponse (
  159.         final double[] adblWeight,
  160.         final double[] adblResponse,
  161.         final double[] adblPredictorOrdinate)
  162.         throws java.lang.Exception
  163.     {
  164.         if (!org.drip.numerical.common.NumberUtil.IsValid (_adblWeight = adblWeight) ||
  165.             !org.drip.numerical.common.NumberUtil.IsValid (_adblResponse = adblResponse) ||
  166.                 !org.drip.numerical.common.NumberUtil.IsValid (_adblPredictorOrdinate = adblPredictorOrdinate))
  167.             throw new java.lang.Exception ("SegmentBestFitResponse ctr: Invalid Inputs");

  169.         int iNumPointsToFit = _adblWeight.length;

  171.         if (0 == iNumPointsToFit || _adblResponse.length != iNumPointsToFit ||
  172.             _adblPredictorOrdinate.length != iNumPointsToFit)
  173.             throw new java.lang.Exception ("SegmentBestFitResponse ctr: Invalid Inputs");
  174.     }

  176.     private boolean normalizeWeights()
  177.     {
  178.         double dblCumulativeWeight = 0.;
  179.         int iNumPointsToFit = _adblWeight.length;

  181.         for (int i = 0; i < iNumPointsToFit; ++i) {
  182.             if (_adblWeight[i] < 0.) return false;

  184.             dblCumulativeWeight += _adblWeight[i];
  185.         }

  187.         if (0. >= dblCumulativeWeight) return false;

  189.         for (int i = 0; i < iNumPointsToFit; ++i)
  190.             _adblWeight[i] /= dblCumulativeWeight;

  192.         return true;
  193.     }

  195.     /**
  196.      * Retrieve the Array of the Fitness Weights
  197.      * 
  198.      * @return The Array of the Fitness Weights
  199.      */

  201.     public double[] weight()
  202.     {
  203.         return _adblWeight;
  204.     }

  206.     /**
  207.      * Retrieve the Indexed Fitness Weight Element
  208.      * 
  209.      * @param iIndex The Element Index
  210.      * 
  211.      * @return The Indexed Fitness Weight Element
  212.      * 
  213.      * @throws java.lang.Exception Thrown if the Index is Invalid
  214.      */

  216.     public double weight (
  217.         final int iIndex)
  218.         throws java.lang.Exception
  219.     {
  220.         if (iIndex >= numPoint())
  221.             throw new java.lang.Exception ("SegmentBestFitResponse::weight => Invalid Index");

  223.         return _adblWeight[iIndex];
  224.     }

  226.     /**
  227.      * Retrieve the Array of Predictor Ordinates
  228.      * 
  229.      * @return The Array of Predictor Ordinates
  230.      */

  232.     public double[] predictorOrdinate()
  233.     {
  234.         return _adblPredictorOrdinate;
  235.     }

  237.     /**
  238.      * Retrieve the Indexed Predictor Ordinate Element
  239.      * 
  240.      * @param iIndex The Element Index
  241.      * 
  242.      * @return The Indexed Predictor Ordinate Element
  243.      * 
  244.      * @throws java.lang.Exception Thrown if the Index is Invalid
  245.      */

  247.     public double predictorOrdinate (
  248.         final int iIndex)
  249.         throws java.lang.Exception
  250.     {
  251.         if (iIndex >= numPoint())
  252.             throw new java.lang.Exception ("SegmentBestFitResponse::predictorOrdinate => Invalid Index");

  254.         return _adblPredictorOrdinate[iIndex];
  255.     }

  257.     /**
  258.      * Retrieve the Array of Responses
  259.      * 
  260.      * @return The Array of Responses
  261.      */

  263.     public double[] response()
  264.     {
  265.         return _adblResponse;
  266.     }

  268.     /**
  269.      * Retrieve the Indexed Response Element
  270.      * 
  271.      * @param iIndex The Element Index
  272.      * 
  273.      * @return The Indexed Response Element
  274.      * 
  275.      * @throws java.lang.Exception Thrown if the Index is Invalid
  276.      */

  278.     public double response (
  279.         final int iIndex)
  280.         throws java.lang.Exception
  281.     {
  282.         if (iIndex >= numPoint())
  283.             throw new java.lang.Exception ("SegmentBestFitResponse::response => Invalid Index");

  285.         return _adblResponse[iIndex];
  286.     }

  288.     /**
  289.      * Retrieve the Number of Fitness Points
  290.      * 
  291.      * @return The Number of Fitness Points
  292.      */

  294.     public int numPoint()
  295.     {
  296.         return null == _adblResponse ? 0 : _adblResponse.length;
  297.     }
  298. }
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