UnitRegressionStat.java

  1. package org.drip.regression.core;

  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.  * Copyright (C) 2012 Lakshmi Krishnamurthy
  17.  * 
  18.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  19.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  20.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  21.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  22.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  23.  *      and computational support.
  24.  *  
  25.  *      https://lakshmidrip.github.io/DROP/
  26.  *  
  27.  *  DROP is composed of three modules:
  28.  *  
  29.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  30.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  31.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  32.  * 
  33.  *  DROP Product Core implements libraries for the following:
  34.  *  - Fixed Income Analytics
  35.  *  - Loan Analytics
  36.  *  - Transaction Cost Analytics
  37.  * 
  38.  *  DROP Portfolio Core implements libraries for the following:
  39.  *  - Asset Allocation Analytics
  40.  *  - Asset Liability Management Analytics
  41.  *  - Capital Estimation Analytics
  42.  *  - Exposure Analytics
  43.  *  - Margin Analytics
  44.  *  - XVA Analytics
  45.  * 
  46.  *  DROP Computational Core implements libraries for the following:
  47.  *  - Algorithm Support
  48.  *  - Computation Support
  49.  *  - Function Analysis
  50.  *  - Model Validation
  51.  *  - Numerical Analysis
  52.  *  - Numerical Optimizer
  53.  *  - Spline Builder
  54.  *  - Statistical Learning
  55.  * 
  56.  *  Documentation for DROP is Spread Over:
  57.  * 
  58.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  59.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  60.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  61.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  62.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  63.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  64.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  65.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  66.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  67.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  68.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  69.  * 
  70.  *  Licensed under the Apache License, Version 2.0 (the "License");
  71.  *      you may not use this file except in compliance with the License.
  72.  *   
  73.  *  You may obtain a copy of the License at
  74.  *      http://www.apache.org/licenses/LICENSE-2.0
  75.  *  
  76.  *  Unless required by applicable law or agreed to in writing, software
  77.  *      distributed under the License is distributed on an "AS IS" BASIS,
  78.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  79.  *  
  80.  *  See the License for the specific language governing permissions and
  81.  *      limitations under the License.
  82.  */

  84. /**
  85.  * <i>UnitRegressionStat</i> creates the statistical details for the Unit Regressor. It holds the following:
  86.  *  <ul>
  87.  *      <li>
  88.  *          Execution Initialization Delay
  89.  *      </li>
  90.  *      <li>
  91.  *          Execution time mean, variance, maximum, and minimum
  92.  *      </li>
  93.  *      <li>
  94.  *          The full list of individual execution times
  95.  *      </li>
  96.  *  </ul>
  97.  * 
  98.  * <br><br>
  99.  *  <ul>
  100.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  101.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationSupportLibrary.md">Computation Support</a></li>
  102.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/regression/README.md">Regression Engine Core and the Unit Regressors</a></li>
  103.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/regression/core/README.md">Regression Engine Core - Unit Regressors</a></li>
  104.  *  </ul>
  105.  * <br><br>
  106.  *
  107.  * @author Lakshmi Krishnamurthy
  108.  */

  110. public class UnitRegressionStat {
  111.     private long _lExecTimeMean = 0L;
  112.     private long _lExecTimeMaximum = 0L;
  113.     private long _lExecTimeMinimum = 0L;
  114.     private long _lExecTimeVariance = 0L;
  115.     private long _lInitializationDelay = 0L;
  116.     private java.util.List<java.lang.Long> _llExecTime = null;

  118.     /**
  119.      * Empty Constructor
  120.      */

  122.     public UnitRegressionStat()
  123.     {
  124.         _llExecTime = new java.util.ArrayList<java.lang.Long>();
  125.     }

  127.     /**
  128.      * Add another run execution time
  129.      * 
  130.      * @param lExecTime Execution Time
  131.      * 
  132.      * @return TRUE - Executed time run successfully added
  133.      */

  135.     public boolean addExecTime (
  136.         final long lExecTime)
  137.     {
  138.         _llExecTime.add (lExecTime);

  140.         return true;
  141.     }

  143.     /**
  144.      * Generate the statistics across all the execution times generated
  145.      * 
  146.      * @return TRUE - Statistics successfully generated
  147.      */

  149.     public boolean generateStat()
  150.     {
  151.         boolean bFirstRun = true;

  153.         int iNumRuns = _llExecTime.size();

  155.         if (0 == iNumRuns) return false;

  157.         for (long lExecTime : _llExecTime) {
  158.             if (bFirstRun) {
  159.                 _lExecTimeMaximum = lExecTime;
  160.                 _lExecTimeMinimum = lExecTime;
  161.                 _lInitializationDelay = lExecTime;
  162.             } else {
  163.                 _lExecTimeMean += lExecTime;

  165.                 if (_lExecTimeMaximum < lExecTime) _lExecTimeMaximum = lExecTime;

  167.                 if (_lExecTimeMinimum > lExecTime) _lExecTimeMinimum = lExecTime;
  168.             }

  170.             bFirstRun = false;
  171.         }

  173.         _lExecTimeMean /= (iNumRuns - 1);
  174.         bFirstRun = true;

  176.         for (long lExecTime : _llExecTime) {
  177.             if (!bFirstRun)
  178.                 _lExecTimeVariance += (lExecTime - _lExecTimeMean) * (lExecTime - _lExecTimeMean);

  180.             bFirstRun = false;
  181.         }

  183.         _lExecTimeVariance = (long) java.lang.Math.sqrt (_lExecTimeVariance / (iNumRuns - 1));

  185.         _lInitializationDelay -= _lExecTimeMean;
  186.         return true;
  187.     }

  189.     /**
  190.      * Get the number of runs for the statistics
  191.      * 
  192.      * @return Number of runs
  193.      */

  195.     public int getRuns()
  196.     {
  197.         return _llExecTime.size();
  198.     }

  200.     /**
  201.      * Get the Mean in the execution time
  202.      * 
  203.      * @return Execution Time Mean
  204.      */

  206.     public long getMean()
  207.     {
  208.         return _lExecTimeMean;
  209.     }

  211.     /**
  212.      * Get the Minimum in the execution time
  213.      * 
  214.      * @return Execution Time Minimum
  215.      */

  217.     public long getMin()
  218.     {
  219.         return _lExecTimeMinimum;
  220.     }

  222.     /**
  223.      * Get the Maximum in the execution time
  224.      * 
  225.      * @return Execution Time Maximum
  226.      */

  228.     public long getMax()
  229.     {
  230.         return _lExecTimeMaximum;
  231.     }

  233.     /**
  234.      * Get the variance in the execution time
  235.      * 
  236.      * @return Execution Time Variance
  237.      */

  239.     public long getVariance()
  240.     {
  241.         return _lExecTimeVariance;
  242.     }

  244.     /**
  245.      * Get the delay when the regressor is invoked for the first time
  246.      * 
  247.      * @return Initialization Delay
  248.      */

  250.     public long getInitializationDelay()
  251.     {
  252.         return _lInitializationDelay;
  253.     }

  255.     /**
  256.      * Return the string version of the statistics
  257.      * 
  258.      * @param strRegressionUnit Name the unit for which the regression run was done
  259.      * 
  260.      * @return String holding the content of the unit regression statistics
  261.      */

  263.     public java.lang.String displayString (
  264.         final java.lang.String strRegressionUnit)
  265.     {
  266.         if (null == strRegressionUnit || strRegressionUnit.isEmpty()) return null;

  268.         java.lang.StringBuffer sb = new java.lang.StringBuffer();

  270.         sb.append ("\t" + strRegressionUnit + ".Stat.NumRuns=" + _llExecTime.size() + "\n");

  272.         sb.append ("\t" + strRegressionUnit + ".Stat.ExecTimeMean=" + _lExecTimeMean + "\n");

  274.         sb.append ("\t" + strRegressionUnit + ".Stat.ExecTimeMaximum=" + _lExecTimeMaximum + "\n");

  276.         sb.append ("\t" + strRegressionUnit + ".Stat.ExecTimeMinimum=" + _lExecTimeMinimum + "\n");

  278.         sb.append ("\t" + strRegressionUnit + ".Stat.ExecTimeVariance=" + _lExecTimeVariance + "\n");

  280.         sb.append ("\t" + strRegressionUnit + ".Stat.InitializationDelay=" + _lInitializationDelay + "\n");

  282.         sb.append ("\t" + strRegressionUnit + ".Stat.ExecTimeList=" + _llExecTime.toString() + "\n");

  284.         return sb.toString();
  285.     }
  286. }
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