mirror of
https://github.com/aportelli/LatAnalyze.git
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229 lines
6.0 KiB
C++
229 lines
6.0 KiB
C++
/*
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* Histogram.cpp, part of LatAnalyze 3
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*
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* Copyright (C) 2013 - 2016 Antonin Portelli
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*
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* LatAnalyze 3 is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* LatAnalyze 3 is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include <LatAnalyze/Histogram.hpp>
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#include <LatAnalyze/includes.hpp>
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#include <gsl/gsl_histogram.h>
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#include <gsl/gsl_sf.h>
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#include <gsl/gsl_sort.h>
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using namespace std;
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using namespace Latan;
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#define DECL_GSL_HIST(h) \
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gsl_histogram h{static_cast<size_t>(bin_.size()), x_.data(), bin_.data()}
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#define DECL_CONST_GSL_HIST(h) \
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const gsl_histogram h{static_cast<size_t>(bin_.size()),\
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const_cast<double *>(x_.data()),\
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const_cast<double *>(bin_.data())}
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/******************************************************************************
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* Histogram implementation *
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******************************************************************************/
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// constructor /////////////////////////////////////////////////////////////////
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Histogram::Histogram(const DVec &data, const double xMin, const double xMax,
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const Index nBin)
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: Histogram()
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{
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setFromData(data, xMin, xMax, nBin);
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}
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Histogram::Histogram(const DVec &data, const DVec &w, const double xMin,
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const double xMax, const Index nBin)
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: Histogram()
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{
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setFromData(data, w, xMin, xMax, nBin);
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}
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// resize //////////////////////////////////////////////////////////////////////
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void Histogram::resize(const Index nBin)
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{
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x_.resize(nBin + 1);
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bin_.resize(nBin);
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}
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// generate from data //////////////////////////////////////////////////////////
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void Histogram::setFromData(const DVec &data, const DVec &w, const double xMin,
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const double xMax, const Index nBin)
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{
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if (data.size() != w.size())
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{
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LATAN_ERROR(Size, "data vector and weight vector size mismatch");
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}
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resize(nBin);
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data_ = data.array();
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w_ = w.array();
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xMax_ = xMax;
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xMin_ = xMin;
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makeHistogram();
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}
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void Histogram::setFromData(const DVec &data, const double xMin,
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const double xMax, const Index nBin)
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{
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resize(nBin);
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data_ = data.array();
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xMax_ = xMax;
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xMin_ = xMin;
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w_.resize(data.size());
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w_.fill(1.);
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makeHistogram();
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}
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// histogram calculation ///////////////////////////////////////////////////////
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void Histogram::makeHistogram(void)
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{
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DECL_GSL_HIST(h);
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gsl_histogram_set_ranges_uniform(&h, xMin_, xMax_);
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FOR_STAT_ARRAY(data_, i)
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{
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gsl_histogram_accumulate(&h, data_[i], w_[i]);
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}
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total_ = w_.sum();
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sortIndices();
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computeNorm();
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}
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// generate sorted indices /////////////////////////////////////////////////////
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void Histogram::sortIndices(void)
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{
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sInd_.resize(data_.size());
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gsl_sort_index(sInd_.data(), data_.data(), 1, data_.size());
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}
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// compute normalization factor ////////////////////////////////////////////////
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void Histogram::computeNorm(void)
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{
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norm_ = static_cast<double>(bin_.size())/(total_*(xMax_ - xMin_));
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}
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// normalize as a probablility /////////////////////////////////////////////////
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void Histogram::normalize(const bool n)
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{
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normalize_ = n;
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}
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bool Histogram::isNormalized(void) const
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{
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return normalize_;
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}
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// access //////////////////////////////////////////////////////////////////////
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Index Histogram::size(void) const
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{
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return bin_.size();
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}
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const StatArray<double> & Histogram::getData(void) const
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{
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return data_;
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}
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const StatArray<double> & Histogram::getWeight(void) const
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{
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return w_;
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}
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double Histogram::getX(const Index i) const
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{
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return x_(i);
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}
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double Histogram::operator[](const Index i) const
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{
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return bin_(i)*(isNormalized() ? norm_ : 1.);
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}
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double Histogram::operator()(const double x) const
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{
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size_t i;
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DECL_CONST_GSL_HIST(h);
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gsl_histogram_find(&h, x, &i);
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return (*this)[static_cast<Index>(i)];
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}
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// percentiles & confidence interval ///////////////////////////////////////////
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double Histogram::percentile(const double p) const
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{
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if ((p < 0.0) or (p > 100.0))
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{
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LATAN_ERROR(Range, "percentile (" + strFrom(p) + ")"
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" is outside the [0, 100] range");
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}
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// cf. http://en.wikipedia.org/wiki/Percentile
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double wPSum, p_i, p_im1, w_i, res = 0.;
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bool haveResult;
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wPSum = w_[sInd_[0]];
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p_i = (100./total_)*wPSum*0.5;
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if (p < p_i)
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{
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res = data_[sInd_[0]];
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}
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else
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{
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haveResult = false;
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p_im1 = p_i;
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for (Index i = 1; i < data_.size(); ++i)
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{
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w_i = w_[sInd_[i]];
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wPSum += w_i;
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p_i = (100./total_)*(wPSum-0.5*w_i);
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if ((p >= p_im1) and (p < p_i))
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{
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double d_i = data_[sInd_[i]], d_im1 = data_[sInd_[i-1]];
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res = d_im1 + (p-p_im1)/(p_i-p_im1)*(d_i-d_im1);
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haveResult = true;
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break;
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}
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}
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if (!haveResult)
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{
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res = data_[sInd_[data_.size()-1]];
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}
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}
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return res;
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}
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double Histogram::median(void) const
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{
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return percentile(50.);
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}
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pair<double, double> Histogram::confidenceInterval(const double nSigma) const
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{
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pair<double, double> interval, p;
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double cl;
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cl = gsl_sf_erf(nSigma/sqrt(2.));
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p.first = 50.*(1. - cl);
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p.second = 50.*(1. + cl);
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interval.first = percentile(p.first);
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interval.second = percentile(p.second);
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return interval;
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}
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