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<h1>itkGaussianDistribution.h</h1><a href="itkGaussianDistribution_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">/*=========================================================================</span>
<a name="l00002"></a>00002 <span class="comment"></span>
<a name="l00003"></a>00003 <span class="comment"> Program: Insight Segmentation & Registration Toolkit</span>
<a name="l00004"></a>00004 <span class="comment"> Module: $RCSfile: itkGaussianDistribution.h,v $</span>
<a name="l00005"></a>00005 <span class="comment"> Language: C++</span>
<a name="l00006"></a>00006 <span class="comment"> Date: $Date: 2007-02-24 13:47:32 $</span>
<a name="l00007"></a>00007 <span class="comment"> Version: $Revision: 1.1 $</span>
<a name="l00008"></a>00008 <span class="comment"></span>
<a name="l00009"></a>00009 <span class="comment"> Copyright (c) Insight Software Consortium. All rights reserved.</span>
<a name="l00010"></a>00010 <span class="comment"> See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.</span>
<a name="l00011"></a>00011 <span class="comment"></span>
<a name="l00012"></a>00012 <span class="comment"> This software is distributed WITHOUT ANY WARRANTY; without even </span>
<a name="l00013"></a>00013 <span class="comment"> the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR </span>
<a name="l00014"></a>00014 <span class="comment"> PURPOSE. See the above copyright notices for more information.</span>
<a name="l00015"></a>00015 <span class="comment"></span>
<a name="l00016"></a>00016 <span class="comment">=========================================================================*/</span>
<a name="l00017"></a>00017 <span class="preprocessor">#ifndef __itkGaussianDistribution_h</span>
<a name="l00018"></a>00018 <span class="preprocessor"></span><span class="preprocessor">#define __itkGaussianDistribution_h</span>
<a name="l00019"></a>00019 <span class="preprocessor"></span>
<a name="l00020"></a>00020 <span class="preprocessor">#include "<a class="code" href="itkProbabilityDistribution_8h.html">itkProbabilityDistribution.h</a>"</span>
<a name="l00021"></a>00021
<a name="l00022"></a>00022 <span class="keyword">namespace </span>itk {
<a name="l00023"></a>00023 <span class="keyword">namespace </span>Statistics {
<a name="l00024"></a>00024
<a name="l00053"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html">00053</a> <span class="keyword">class </span><a class="code" href="itkWin32Header_8h.html#7d4384322557205d75f0719c012dded6">ITK_EXPORT</a> <a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html" title="GaussianDistribution class defines the interface for a univariate Gaussian distribution...">GaussianDistribution</a> :
<a name="l00054"></a>00054 <span class="keyword">public</span> <a class="code" href="classitk_1_1Statistics_1_1ProbabilityDistribution.html" title="ProbabilityDistribution class defines common interface for statistical distributions...">ProbabilityDistribution</a>
<a name="l00055"></a>00055 {
<a name="l00056"></a>00056 <span class="keyword">public</span>:
<a name="l00058"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#a4d06d64fbd4d4aebe8335f46ca61d1b">00058</a> <span class="keyword">typedef</span> <a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html" title="GaussianDistribution class defines the interface for a univariate Gaussian distribution...">GaussianDistribution</a> <a class="code" href="classitk_1_1LightObject.html" title="Light weight base class for most itk classes.">Self</a>;
<a name="l00059"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#882dc859abf1fdee31f4cf1bc721310b">00059</a> <span class="keyword">typedef</span> <a class="code" href="classitk_1_1Statistics_1_1ProbabilityDistribution.html" title="ProbabilityDistribution class defines common interface for statistical distributions...">ProbabilityDistribution</a> <a class="code" href="classitk_1_1LightObject.html" title="Light weight base class for most itk classes.">Superclass</a>;
<a name="l00060"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#90948d53e9502f4ef3719afccc251f11">00060</a> <span class="keyword">typedef</span> <a class="code" href="classitk_1_1SmartPointer.html">SmartPointer<Self></a> <a class="code" href="classitk_1_1SmartPointer.html">Pointer</a>;
<a name="l00061"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#ec544f4f83c7d71a62a05f0f3e953b5f">00061</a> <span class="keyword">typedef</span> <a class="code" href="classitk_1_1SmartPointer.html">SmartPointer<const Self></a> <a class="code" href="classitk_1_1SmartPointer.html">ConstPointer</a>;
<a name="l00062"></a>00062
<a name="l00064"></a>00064 <a class="code" href="itkMacro_8h.html#574c1f86661d409dd32c742307a0e96a">itkTypeMacro</a>(<a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html" title="GaussianDistribution class defines the interface for a univariate Gaussian distribution...">GaussianDistribution</a>, <a class="code" href="classitk_1_1Statistics_1_1ProbabilityDistribution.html" title="ProbabilityDistribution class defines common interface for statistical distributions...">ProbabilityDistribution</a>);
<a name="l00065"></a>00065
<a name="l00067"></a>00067 <a class="code" href="itkMacro_8h.html#0fdc15685afa271857c57e7cd482f30c">itkNewMacro</a>(<a class="code" href="classitk_1_1LightObject.html" title="Light weight base class for most itk classes.">Self</a>);
<a name="l00068"></a>00068
<a name="l00071"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#e21542e33994a9fbae3637945c232fd2">00071</a> <span class="keyword">virtual</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span> <a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#e21542e33994a9fbae3637945c232fd2">GetNumberOfParameters</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> 2; }
<a name="l00072"></a>00072
<a name="l00075"></a>00075 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluatePDF(<span class="keywordtype">double</span> x) <span class="keyword">const</span>;
<a name="l00076"></a>00076
<a name="l00080"></a>00080 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluatePDF(<span class="keywordtype">double</span> x, <span class="keyword">const</span> ParametersType&) <span class="keyword">const</span>;
<a name="l00081"></a>00081
<a name="l00084"></a>00084 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluatePDF(<span class="keywordtype">double</span> x, <span class="keywordtype">double</span> mean, <span class="keywordtype">double</span> variance) <span class="keyword">const</span>;
<a name="l00085"></a>00085
<a name="l00088"></a>00088 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluateCDF(<span class="keywordtype">double</span> x) <span class="keyword">const</span>;
<a name="l00089"></a>00089
<a name="l00093"></a>00093 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluateCDF(<span class="keywordtype">double</span> x, <span class="keyword">const</span> ParametersType&) <span class="keyword">const</span>;
<a name="l00094"></a>00094
<a name="l00097"></a>00097 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluateCDF(<span class="keywordtype">double</span> x, <span class="keywordtype">double</span> mean, <span class="keywordtype">double</span> variance) <span class="keyword">const</span>;
<a name="l00098"></a>00098
<a name="l00102"></a>00102 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluateInverseCDF(<span class="keywordtype">double</span> p) <span class="keyword">const</span>;
<a name="l00103"></a>00103
<a name="l00108"></a>00108 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluateInverseCDF(<span class="keywordtype">double</span> p, <span class="keyword">const</span> ParametersType&) <span class="keyword">const</span>;
<a name="l00109"></a>00109
<a name="l00113"></a>00113 <span class="keyword">virtual</span> <span class="keywordtype">double</span> EvaluateInverseCDF(<span class="keywordtype">double</span> p,
<a name="l00114"></a>00114 <span class="keywordtype">double</span> mean,
<a name="l00115"></a>00115 <span class="keywordtype">double</span> variance) <span class="keyword">const</span>;
<a name="l00116"></a>00116
<a name="l00119"></a>00119 <span class="keyword">virtual</span> <span class="keywordtype">void</span> SetMean(<span class="keywordtype">double</span>);
<a name="l00120"></a>00120
<a name="l00123"></a>00123 <span class="keyword">virtual</span> <span class="keywordtype">double</span> GetMean() <span class="keyword">const</span>;
<a name="l00124"></a>00124
<a name="l00126"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#e88abe2905a3d985399492140d86893d">00126</a> <span class="keyword">virtual</span> <span class="keywordtype">bool</span> <a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#e88abe2905a3d985399492140d86893d">HasMean</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <span class="keyword">true</span>; }
<a name="l00127"></a>00127
<a name="l00131"></a>00131 <span class="keyword">virtual</span> <span class="keywordtype">void</span> SetVariance(<span class="keywordtype">double</span>);
<a name="l00132"></a>00132
<a name="l00135"></a>00135 <span class="keyword">virtual</span> <span class="keywordtype">double</span> GetVariance() <span class="keyword">const</span>;
<a name="l00136"></a>00136
<a name="l00138"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#fe004e901ca8ab6ca5e78924ba868f23">00138</a> <span class="keyword">virtual</span> <span class="keywordtype">bool</span> <a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#fe004e901ca8ab6ca5e78924ba868f23">HasVariance</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <span class="keyword">true</span>; }
<a name="l00139"></a>00139
<a name="l00144"></a>00144 <span class="keyword">static</span> <span class="keywordtype">double</span> PDF(<span class="keywordtype">double</span> x);
<a name="l00145"></a>00145
<a name="l00151"></a>00151 <span class="keyword">static</span> <span class="keywordtype">double</span> PDF(<span class="keywordtype">double</span> x, <span class="keyword">const</span> ParametersType&);
<a name="l00152"></a>00152
<a name="l00157"></a>00157 <span class="keyword">static</span> <span class="keywordtype">double</span> PDF(<span class="keywordtype">double</span> x, <span class="keywordtype">double</span> mean, <span class="keywordtype">double</span> variance);
<a name="l00158"></a>00158
<a name="l00163"></a>00163 <span class="keyword">static</span> <span class="keywordtype">double</span> CDF(<span class="keywordtype">double</span> x);
<a name="l00164"></a>00164
<a name="l00170"></a>00170 <span class="keyword">static</span> <span class="keywordtype">double</span> CDF(<span class="keywordtype">double</span> x, <span class="keyword">const</span> ParametersType&);
<a name="l00171"></a>00171
<a name="l00176"></a>00176 <span class="keyword">static</span> <span class="keywordtype">double</span> CDF(<span class="keywordtype">double</span> x, <span class="keywordtype">double</span> mean, <span class="keywordtype">double</span> variance);
<a name="l00177"></a>00177
<a name="l00208"></a>00208 <span class="keyword">static</span> <span class="keywordtype">double</span> InverseCDF(<span class="keywordtype">double</span> p);
<a name="l00210"></a>00210
<a name="l00217"></a>00217 <span class="keyword">static</span> <span class="keywordtype">double</span> InverseCDF(<span class="keywordtype">double</span> p, <span class="keyword">const</span> ParametersType&);
<a name="l00218"></a>00218
<a name="l00224"></a>00224 <span class="keyword">static</span> <span class="keywordtype">double</span> InverseCDF(<span class="keywordtype">double</span> p, <span class="keywordtype">double</span> mean, <span class="keywordtype">double</span> variance);
<a name="l00225"></a>00225
<a name="l00226"></a>00226 <span class="keyword">protected</span>:
<a name="l00227"></a>00227 <a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html" title="GaussianDistribution class defines the interface for a univariate Gaussian distribution...">GaussianDistribution</a>(<span class="keywordtype">void</span>);
<a name="l00228"></a><a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#4d1535ae55d68087b96ca8a3b7f18d6b">00228</a> <span class="keyword">virtual</span> <a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html#4d1535ae55d68087b96ca8a3b7f18d6b">~GaussianDistribution</a>(<span class="keywordtype">void</span>) {}
<a name="l00229"></a>00229
<a name="l00230"></a>00230 <span class="keywordtype">void</span> <a class="code" href="namespaceHardConnectedComponentImageFilter.html#920ae03048a5ad715d803ca2e92b52de">PrintSelf</a>(std::ostream& os, <a class="code" href="classitk_1_1Indent.html" title="Control indentation during Print() invocation.">Indent</a> indent) <span class="keyword">const</span>;
<a name="l00231"></a>00231
<a name="l00232"></a>00232 <span class="keyword">private</span>:
<a name="l00233"></a>00233 <a class="code" href="classitk_1_1Statistics_1_1GaussianDistribution.html" title="GaussianDistribution class defines the interface for a univariate Gaussian distribution...">GaussianDistribution</a>(<span class="keyword">const</span> <a class="code" href="namespaceHardConnectedComponentImageFilter.html#ac7d0120fe5292cdcdddb6163b8cb150">Self</a>&); <span class="comment">//purposely not implemented</span>
<a name="l00234"></a>00234 <span class="keywordtype">void</span> operator=(<span class="keyword">const</span> <a class="code" href="namespaceHardConnectedComponentImageFilter.html#ac7d0120fe5292cdcdddb6163b8cb150">Self</a>&); <span class="comment">//purposely not implemented</span>
<a name="l00235"></a>00235
<a name="l00236"></a>00236 }; <span class="comment">// end of class</span>
<a name="l00237"></a>00237
<a name="l00238"></a>00238 } <span class="comment">// end of namespace Statistics</span>
<a name="l00239"></a>00239 } <span class="comment">// end namespace itk</span>
<a name="l00240"></a>00240
<a name="l00241"></a>00241 <span class="preprocessor">#endif</span>
<a name="l00242"></a>00242 <span class="preprocessor"></span>
</pre></div></div>
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