jacoco/org.drip.sequence.random/Poisson.java.html

<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"><html xmlns="http://www.w3.org/1999/xhtml" lang="en"><head><meta http-equiv="Content-Type" content="text/html;charset=UTF-8"/><link rel="stylesheet" href="../jacoco-resources/report.css" type="text/css"/><link rel="shortcut icon" href="../jacoco-resources/report.gif" type="image/gif"/><title>Poisson.java</title><link rel="stylesheet" href="../jacoco-resources/prettify.css" type="text/css"/><script type="text/javascript" src="../jacoco-resources/prettify.js"></script></head><body onload="window['PR_TAB_WIDTH']=4;prettyPrint()"><div class="breadcrumb" id="breadcrumb"><span class="info"><a href="../jacoco-sessions.html" class="el_session">Sessions</a></span><a href="../index.html" class="el_report">DROP</a> &gt; <a href="index.source.html" class="el_package">org.drip.sequence.random</a> &gt; <span class="el_source">Poisson.java</span></div><h1>Poisson.java</h1><pre class="source lang-java linenums">
package org.drip.sequence.random;

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

/*!
 * 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 risk, transaction costs, exposure, margin
 *  	calculations, and portfolio construction within and across fixed income, credit, commodity, equity,
 *  	FX, and structured products.
 *  
 *  	https://lakshmidrip.github.io/DROP/
 *  
 *  DROP is composed of three main modules:
 *  
 *  - DROP Analytics Core - https://lakshmidrip.github.io/DROP-Analytics-Core/
 *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
 *  - DROP Numerical Core - https://lakshmidrip.github.io/DROP-Numerical-Core/
 * 
 * 	DROP Analytics Core implements libraries for the following:
 * 	- Fixed Income Analytics
 * 	- Asset Backed Analytics
 * 	- XVA Analytics
 * 	- Exposure and Margin Analytics
 * 
 * 	DROP Portfolio Core implements libraries for the following:
 * 	- Asset Allocation Analytics
 * 	- Transaction Cost Analytics
 * 
 * 	DROP Numerical Core implements libraries for the following:
 * 	- Statistical Learning Library
 * 	- Numerical Optimizer Library
 * 	- Machine Learning Library
 * 	- Spline Builder Library
 * 
 * 	Documentation for DROP is Spread Over:
 * 
 * 	- Main                     =&gt; https://lakshmidrip.github.io/DROP/
 * 	- Wiki                     =&gt; https://github.com/lakshmiDRIP/DROP/wiki
 * 	- GitHub                   =&gt; https://github.com/lakshmiDRIP/DROP
 * 	- Javadoc                  =&gt; https://lakshmidrip.github.io/DROP/Javadoc/index.html
 * 	- Technical Specifications =&gt; https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
 * 	- Release Versions         =&gt; https://lakshmidrip.github.io/DROP/version.html
 * 	- Community Credits        =&gt; https://lakshmidrip.github.io/DROP/credits.html
 * 	- Issues Catalog           =&gt; https://github.com/lakshmiDRIP/DROP/issues
 * 	- JUnit                    =&gt; https://lakshmidrip.github.io/DROP/junit/index.html
 * 	- Jacoco                   =&gt; https://lakshmidrip.github.io/DROP/jacoco/index.html
 * 
 *  Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);
 *   	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 &quot;AS IS&quot; 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.
 */

/**
 * &lt;i&gt;Poisson&lt;/i&gt; implements the Poisson Random Number Generator.
 * 
 * &lt;br&gt;&lt;br&gt;
 *  &lt;ul&gt;
 *		&lt;li&gt;&lt;b&gt;Module &lt;/b&gt; = &lt;a href = &quot;https://github.com/lakshmiDRIP/DROP/tree/master/NumericalCore.md&quot;&gt;Numerical Core Module&lt;/a&gt;&lt;/li&gt;
 *		&lt;li&gt;&lt;b&gt;Library&lt;/b&gt; = &lt;a href = &quot;https://github.com/lakshmiDRIP/DROP/tree/master/StatisticalLearningLibrary.md&quot;&gt;Statistical Learning Library&lt;/a&gt;&lt;/li&gt;
 *		&lt;li&gt;&lt;b&gt;Project&lt;/b&gt; = &lt;a href = &quot;https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sequence&quot;&gt;Sequence&lt;/a&gt;&lt;/li&gt;
 *		&lt;li&gt;&lt;b&gt;Package&lt;/b&gt; = &lt;a href = &quot;https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sequence/random&quot;&gt;Random&lt;/a&gt;&lt;/li&gt;
 *  &lt;/ul&gt;
 * &lt;br&gt;&lt;br&gt;
 *
 * @author Lakshmi Krishnamurthy
 */

public class Poisson extends org.drip.sequence.random.UnivariateSequenceGenerator {
<span class="fc" id="L86">	private double _dblLambda = java.lang.Double.NaN;</span>
<span class="fc" id="L87">	private double _dblExponentialLambda = java.lang.Double.NaN;</span>

	/**
	 * Construct a Poisson Random Number Generator
	 * 
	 * @param dblLambda Lambda
	 * 
	 * @throws java.lang.Exception Thrown if the inputs are invalid
	 */

	public Poisson (
		final double dblLambda)
		throws java.lang.Exception
<span class="fc" id="L100">	{</span>
<span class="pc bpc" id="L101" title="2 of 4 branches missed.">		if (!org.drip.numerical.common.NumberUtil.IsValid (_dblLambda = dblLambda) || 0. &gt;= _dblLambda)</span>
<span class="nc" id="L102">			throw new java.lang.Exception (&quot;Poisson constructor: Invalid inputs&quot;);</span>

<span class="fc" id="L104">		_dblExponentialLambda = java.lang.Math.exp (-1. * _dblLambda);</span>
<span class="fc" id="L105">	}</span>

	/**
	 * Retrieve Lambda
	 * 
	 * @return Lambda
	 */

	public double lambda()
	{
<span class="nc" id="L115">		return _dblLambda;</span>
	}

	@Override public double random()
	{
<span class="fc" id="L120">		int i = 0;</span>
<span class="fc" id="L121">		double dblPoissonProduct = 1.;</span>

<span class="fc" id="L123">		java.util.Random r = new java.util.Random();</span>

<span class="fc bfc" id="L125" title="All 2 branches covered.">		while (dblPoissonProduct &gt; _dblExponentialLambda) {</span>
<span class="fc" id="L126">			++i;</span>

<span class="fc" id="L128">			dblPoissonProduct *= r.nextDouble();</span>
		}

<span class="fc" id="L131">		return i;</span>
	}

	@Override public org.drip.sequence.metrics.SingleSequenceAgnosticMetrics sequence (
		final int iNumEntry,
		final org.drip.measure.continuous.R1Univariate distPopulation)
	{
<span class="fc" id="L138">		double[] adblSequence = new double[iNumEntry];</span>

<span class="fc bfc" id="L140" title="All 2 branches covered.">		for (int i = 0; i &lt; iNumEntry; ++i)</span>
<span class="fc" id="L141">			adblSequence[i] = random();</span>

		try {
<span class="fc bfc" id="L144" title="All 2 branches covered.">			return new org.drip.sequence.metrics.PoissonSequenceAgnosticMetrics (adblSequence, null ==</span>
<span class="fc" id="L145">				distPopulation ? java.lang.Double.NaN : distPopulation.mean());</span>
<span class="nc" id="L146">		} catch (java.lang.Exception e) {</span>
<span class="nc" id="L147">			e.printStackTrace();</span>
		}

<span class="nc" id="L150">		return null;</span>
	}
}
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