100 lines
2.9 KiB
C++
100 lines
2.9 KiB
C++
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/*********************************************************************
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*
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* 文 件: NormalDistribution.cpp
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*
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* 版权所有: Shanghai Baosight Software Co., Ltd.
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* zoufuzhou
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*********************************************************************/
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#include <eqpalg/stat_tools/NormalDistribution.h>
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#include <boost/accumulators/accumulators.hpp>
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#include <boost/accumulators/statistics/stats.hpp>
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#include <boost/accumulators/statistics/mean.hpp>
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#include <boost/accumulators/statistics/moment.hpp>
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#include <boost/accumulators/statistics/variance.hpp>
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#include <boost/math/distibutions/normal.hpp>
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#include <iDA/iDA.h>
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#include <log4cplus/LOG.h>
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#include <dao/DbStandardDBAX.h>
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using namespace std;
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using namespace boost::accumulators;
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extern iDA::Connection cn;
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using namespace log4cplus;
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NormalDistribution::NormalDistribution(void)
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{
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m_avg = 0;
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m_stddev = 0;
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}
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NormalDistribution::NormalDistribution(const vector<double> vdat)
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{
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this->ReSet(vdat);
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}
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void NormalDistribution::ReSet(const vector<double> vdat)
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{
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// accumulator_set<double, stats<tag::mean, tag::moment<2> > > acc;
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accumulator_set<double, stats<tag::mean, tag::variance > > acc;
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for(int i=0; i<vdat.size(); i++)
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{
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acc(vdat[i]);
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}
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m_avg = mean(acc);
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m_stddev = sqrt(variance(acc));//boost::accumulators::moment<2>(acc);
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}
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//int NormalDistribution::ReadDBSample(const string& where)
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//{
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// LOG d("NormalDistribution::ReadDBSample");
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// if( where.length() == 0) return -1;
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// accumulator_set<double, stats<tag::mean, tag::moment<2> > > acc;
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//
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// string sql = "select data,datajson from T_RULE_SAMPLE WHERE "+where;
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//
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// iDA::Command cmd;
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// cmd.SetConnection( &cn);
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// cmd.SetCommandText( sql);
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// try{
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// cmd.Execute();
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// }catch( iDA::Exception &e)
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// {
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// d.Error()<<sql<<endl;
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// d.Error()<<e.ErrMsg()<<endl;
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// return (-1);
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// }
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//
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// while( cmd.FetchNext())
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// {
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// acc(cmd.Field(1).AsDouble());
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// }
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//
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// m_avg = mean(acc);
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// m_stddev = boost::accumulators::moment<2>(acc);
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// return 0;
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//}
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int NormalDistribution::Analysis(double probability,ConfidenceInterval* cfdi)
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{
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LOG d("NormalDistribution::Analysis",AUTO_CATCH_PID);
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d.Debug() << "m_avg:" << m_avg <<" m_stddev:" << m_stddev << std::endl;
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if(probability < 0 || probability > 1 || m_stddev == 0)
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{
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return -1;
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}
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boost::math::normal_distibution<> normal(m_avg, m_stddev);
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d.Debug() << "Prob" << probability << std::endl;
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// cfdi->up = boost::math::quantile(normal,probability) + m_stddev*1.0; // add 0.2 avg to up in order to increase mistake alarm
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// cfdi->low = 2.0*m_avg - cfdi->up - m_stddev*1.0;// sub 0.2 avg to up in order to increase mistake alarm
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cfdi->up = boost::math::quantile(normal,probability);
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cfdi->low = 2.0*m_avg - cfdi->up;
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double diff = fabs(cfdi->up-cfdi->low);
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cfdi->up += diff*0.1;
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cfdi->low -= diff*0.1;
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cfdi->probability = probability;
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cfdi->avg = m_avg;
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cfdi->std_dev = m_stddev;
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return 0;
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}
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