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tools/sctk-2.4.10/src/asclite/core/statistics.cpp
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/*
* ASCLITE
* Author: Jerome Ajot, Jon Fiscus, Nicolas Radde, Chris Laprun
*
* This software was developed at the National Institute of Standards and Technology by
* employees of the Federal Government in the course of their official duties. Pursuant
* to title 17 Section 105 of the United States Code this software is not subject to
* copyright protection and is in the public domain. ASCLITE is an experimental system.
* NIST assumes no responsibility whatsoever for its use by other parties, and makes no
* guarantees, expressed or implied, about its quality, reliability, or any other
* characteristic. We would appreciate acknowledgement if the software is used.
*
* THIS SOFTWARE IS PROVIDED "AS IS." With regard to this software, NIST MAKES NO EXPRESS
* OR IMPLIED WARRANTY AS TO ANY MATTER WHATSOEVER, INCLUDING MERCHANTABILITY,
* OR FITNESS FOR A PARTICULAR PURPOSE.
*/
#include "statistics.h"
Statistics::Statistics(const vector<int> & _vecValues)
{
for(size_t i=0; i< _vecValues.size(); ++i)
m_VecValues.push_back((double) _vecValues[i]);
Compute();
}
Statistics::Statistics(const vector<double> & _vecValues) : m_VecValues(_vecValues)
{
Compute();
}
void Statistics::Compute()
{
if(!m_VecValues.empty())
{
size_t i;
double n = (double)m_VecValues.size();
double sumSqr = 0.0;
sort(m_VecValues.begin(), m_VecValues.end());
m_Mean = m_SD = m_Sum = 0.0;
m_MaxSize = 0;
for(i=0; i<m_VecValues.size(); ++i)
{
m_Sum += m_VecValues[i];
sumSqr += m_VecValues[i]*m_VecValues[i];
m_MaxSize = max(m_MaxSize, (int)( ceil(log((double)m_VecValues[i])/log(10.0)) ) );
}
m_Mean = m_Sum/((double) m_VecValues.size());
m_SD = sqrt((n * sumSqr - m_Sum*m_Sum) / ( n * (n-1)));
if(m_VecValues.size()%2 == 0)
m_Median = (m_VecValues[m_VecValues.size()/2]+m_VecValues[m_VecValues.size()/2-1])/2.0;
else
m_Median = m_VecValues[m_VecValues.size()/2];
m_MaxSize = max(m_MaxSize, (int)( ceil(log(m_Sum)/log(10.0)) ) +2);
m_MaxSize = max(m_MaxSize, (int)( ceil(log(m_Mean)/log(10.0)) ) +2);
m_MaxSize = max(m_MaxSize, (int)( ceil(log(m_SD)/log(10.0)) ) +2);
m_MaxSize = max(m_MaxSize, (int)( ceil(log(m_Median)/log(10.0)) ) +2);
}
else
{
m_Sum = m_Mean = m_SD = m_Median = 0.0;
m_MaxSize = 1;
}
}
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