Coverage Report - org.apache.commons.math.distribution.CauchyDistributionImpl

Classes in this File	Line Coverage	Branch Coverage	Complexity
CauchyDistributionImpl	59%	50%	1.9090909090909092;1.909

1		/*
2		* Copyright 2005 The Apache Software Foundation.
3		*
4		* Licensed under the Apache License, Version 2.0 (the "License");
5		* you may not use this file except in compliance with the License.
6		* You may obtain a copy of the License at
7		*
8		* http://www.apache.org/licenses/LICENSE-2.0
9		*
10		* Unless required by applicable law or agreed to in writing, software
11		* distributed under the License is distributed on an "AS IS" BASIS,
12		* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13		* See the License for the specific language governing permissions and
14		* limitations under the License.
15		*/
16
17		package org.apache.commons.math.distribution;
18
19		import java.io.Serializable;
20
21		/**
22		* Default implementation of
23		* {@link org.apache.commons.math.distribution.CauchyDistribution}.
24		*
25		* @since 1.1
26		* @version $Revision$ $Date: 2005-06-26 15:20:57 -0700 (Sun, 26 Jun 2005) $
27		*/
28		public class CauchyDistributionImpl extends AbstractContinuousDistribution
29		implements CauchyDistribution, Serializable {
30
31		/** Serializable version identifier */
32		static final long serialVersionUID = 8589540077390120676L;
33
34		/** The median of this distribution. */
35	20	private double median = 0;
36
37		/** The scale of this distribution. */
38	20	private double scale = 1;
39
40		/**
41		* Creates cauchy distribution with the medain equal to zero and scale
42		* equal to one.
43		*/
44		public CauchyDistributionImpl(){
45	0	this(0.0, 1.0);
46	0	}
47
48		/**
49		* Create a cauchy distribution using the given median and scale.
50		* @param median median for this distribution
51		* @param s scale parameter for this distribution
52		*/
53		public CauchyDistributionImpl(double median, double s){
54	20	super();
55	20	setMedian(median);
56	20	setScale(s);
57	16	}
58
59		/**
60		* For this disbution, X, this method returns P(X &lt; <code>x</code>).
61		* @param x the value at which the CDF is evaluated.
62		* @return CDF evaluted at <code>x</code>.
63		*/
64		public double cumulativeProbability(double x) {
65	128	return 0.5 + (Math.atan((x - median) / scale) / Math.PI);
66		}
67
68		/**
69		* Access the median.
70		* @return median for this distribution
71		*/
72		public double getMedian() {
73	2	return median;
74		}
75
76		/**
77		* Access the scale parameter.
78		* @return scale parameter for this distribution
79		*/
80		public double getScale() {
81	2	return scale;
82		}
83
84		/**
85		* For this distribution, X, this method returns the critical point x, such
86		* that P(X &lt; x) = <code>p</code>.
87		* <p>
88		* Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and
89		* <code>Double.POSITIVE_INFINITY</code> for p=1.
90		*
91		* @param p the desired probability
92		* @return x, such that P(X &lt; x) = <code>p</code>
93		* @throws IllegalArgumentException if <code>p</code> is not a valid
94		* probability.
95		*/
96		public double inverseCumulativeProbability(double p) {
97		double ret;
98	28	if (p < 0.0 || p > 1.0) {
99	4	throw new IllegalArgumentException
100		("probability argument must be between 0 and 1 (inclusive)");
101	24	} else if (p == 0) {
102	2	ret = Double.NEGATIVE_INFINITY;
103	22	} else if (p == 1) {
104	2	ret = Double.POSITIVE_INFINITY;
105		} else {
106	20	ret = median + scale * Math.tan(Math.PI * (p - .5));
107		}
108	24	return ret;
109		}
110
111		/**
112		* Modify the median.
113		* @param median for this distribution
114		*/
115		public void setMedian(double median) {
116	22	this.median = median;
117	22	}
118
119		/**
120		* Modify the scale parameter.
121		* @param s scale parameter for this distribution
122		* @throws IllegalArgumentException if <code>sd</code> is not positive.
123		*/
124		public void setScale(double s) {
125	26	if (s <= 0.0) {
126	8	throw new IllegalArgumentException(
127		"Scale must be positive.");
128		}
129	18	scale = s;
130	18	}
131
132		/**
133		* Access the domain value lower bound, based on <code>p</code>, used to
134		* bracket a CDF root. This method is used by
135		* {@link #inverseCumulativeProbability(double)} to find critical values.
136		*
137		* @param p the desired probability for the critical value
138		* @return domain value lower bound, i.e.
139		* P(X &lt; <i>lower bound</i>) &lt; <code>p</code>
140		*/
141		protected double getDomainLowerBound(double p) {
142		double ret;
143
144	0	if (p < .5) {
145	0	ret = -Double.MAX_VALUE;
146		} else {
147	0	ret = getMedian();
148		}
149
150	0	return ret;
151		}
152
153		/**
154		* Access the domain value upper bound, based on <code>p</code>, used to
155		* bracket a CDF root. This method is used by
156		* {@link #inverseCumulativeProbability(double)} to find critical values.
157		*
158		* @param p the desired probability for the critical value
159		* @return domain value upper bound, i.e.
160		* P(X &lt; <i>upper bound</i>) &gt; <code>p</code>
161		*/
162		protected double getDomainUpperBound(double p) {
163		double ret;
164
165	0	if (p < .5) {
166	0	ret = getMedian();
167		} else {
168	0	ret = Double.MAX_VALUE;
169		}
170
171	0	return ret;
172		}
173
174		/**
175		* Access the initial domain value, based on <code>p</code>, used to
176		* bracket a CDF root. This method is used by
177		* {@link #inverseCumulativeProbability(double)} to find critical values.
178		*
179		* @param p the desired probability for the critical value
180		* @return initial domain value
181		*/
182		protected double getInitialDomain(double p) {
183		double ret;
184
185	0	if (p < .5) {
186	0	ret = getMedian() - getScale();
187	0	} else if (p > .5) {
188	0	ret = getMedian() + getScale();
189		} else {
190	0	ret = getMedian();
191		}
192
193	0	return ret;
194		}
195		}