mirror of
https://github.com/jkriege2/JKQtPlotter.git
synced 2024-11-15 10:05:47 +08:00
328 lines
14 KiB
C++
328 lines
14 KiB
C++
/*
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Copyright (c) 2008-2024 Jan W. Krieger (<jan@jkrieger.de>)
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last modification: $LastChangedDate$ (revision $Rev$)
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This software is free software: you can redistribute it and/or modify
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it under the terms of the GNU Lesser General Public License (LGPL) as published by
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the Free Software Foundation, either version 2.1 of the License, or
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(at your option) any later version.
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This program 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 Lesser General Public License (LGPL) for more details.
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You should have received a copy of the GNU Lesser General Public License (LGPL)
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#ifndef JKQTPSTATHISTOGRAM_H_INCLUDED
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#define JKQTPSTATHISTOGRAM_H_INCLUDED
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#include <stdint.h>
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#include <cmath>
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#include <stdlib.h>
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#include <string.h>
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#include <iostream>
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#include <stdio.h>
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#include <limits>
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#include <vector>
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#include <utility>
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#include <cfloat>
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#include <ostream>
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#include <iomanip>
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#include <sstream>
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#include "jkqtmath/jkqtmath_imexport.h"
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#include "jkqtmath/jkqtplinalgtools.h"
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#include "jkqtmath/jkqtparraytools.h"
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#include "jkqtcommon/jkqtpdebuggingtools.h"
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#include "jkqtmath/jkqtpstatbasics.h"
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/*! \brief defines where the returned x-coordinates (in histogramXOut) lie inside a histogram bin
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\ingroup jkqtptools_math_statistics_1dhist
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\see jkqtpstatHistogram()
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*/
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enum class JKQTPStatHistogramBinXMode {
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XIsLeft, /*!< \brief x-location is the left edge of the bin */
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XIsMid, /*!< \brief x-location is the middle of the bin */
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XIsRight /*!< \brief x-location is the right edge of the bin */
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};
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/*! \brief calculate an autoranged 1-dimensional histogram from the given data range \a first ... \a last, bins defined by their number
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\ingroup jkqtptools_math_statistics_1dhist
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\tparam InputIt standard iterator type of \a first and \a last.
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\tparam OutputIt standard output iterator type used for the outliers output \a histogramXOut and \a histogramYOut, use e.g. std::back_inserter
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\param first iterator pointing to the first item in the dataset to use \f$ X_1 \f$
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\param last iterator pointing behind the last item in the dataset to use \f$ X_N \f$
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\param[out] histogramXOut output iterator that receives x-positions of the histogram bins. Location of this value inside the bin range is defined by \a binXMode
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\param[out] histogramYOut output iterator that receives counts/frequencies of the histogram bins
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\param bins number of bins in the output histogram
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\param normalized indicates whether the histogram has to be normalized
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\param cummulative if \c true, a cummulative histogram is calculated
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\param binXMode defines where the returned x-coordinates (in histogramXOut) lie inside the histogram bin (see JKQTPStatHistogramBinXMode)
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\see jkqtpstatAddHHistogram1DAutoranged()
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*/
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template <class InputIt, class OutputIt>
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inline void jkqtpstatHistogram1DAutoranged(InputIt first, InputIt last, OutputIt histogramXOut, OutputIt histogramYOut, int bins=11, bool normalized=true, bool cummulative=false, JKQTPStatHistogramBinXMode binXMode=JKQTPStatHistogramBinXMode::XIsLeft) {
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double minV=0, maxV=0;
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size_t N=0;
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jkqtpstatMinMax<InputIt>(first, last, minV, maxV, nullptr, nullptr, &N);
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std::vector<double> histX;
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std::vector<double> histY;
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const double range=maxV-minV;
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const double binw=range/static_cast<double>(bins);
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// initialize the histogram
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for (int i=0; i<bins; i++) {
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histX.push_back(minV+static_cast<double>(i)*binw);
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histY.push_back(0);
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}
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// calculate the histogram
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for (auto it=first; it!=last; ++it) {
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const double v=jkqtp_todouble(*it);
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if (JKQTPIsOKFloat(v)) {
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size_t b=jkqtp_bounded<size_t>(0, static_cast<size_t>(floor((v-minV)/binw)), bins-1);
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histY[b]++;
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}
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}
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// output the histogram
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double xoffset=0;
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if (binXMode==JKQTPStatHistogramBinXMode::XIsRight) xoffset=binw;
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if (binXMode==JKQTPStatHistogramBinXMode::XIsMid) xoffset=binw/2.0;
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double NNorm=1;
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if (normalized) {
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NNorm=static_cast<double>(N);
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}
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double h=0;
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for (size_t i=0; i<histX.size(); i++) {
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*histogramXOut=histX[i]+xoffset;
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if (cummulative) h+=(histY[i]/NNorm);
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else h=histY[i]/NNorm;
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*histogramYOut=h;
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++histogramXOut;
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++histogramYOut;
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}
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}
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/*! \brief calculate an autoranged 1-dimensional histogram from the given data range \a first ... \a last, bins defined by their width
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\ingroup jkqtptools_math_statistics_1dhist
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\tparam InputIt standard iterator type of \a first and \a last.
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\tparam OutputIt standard output iterator type used for the outliers output \a histogramXOut and \a histogramYOut, use e.g. std::back_inserter
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\param first iterator pointing to the first item in the dataset to use \f$ X_1 \f$
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\param last iterator pointing behind the last item in the dataset to use \f$ X_N \f$
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\param[out] histogramXOut output iterator that receives x-positions of the histogram bins. Location of this value inside the bin range is defined by \a binXMode
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\param[out] histogramYOut output iterator that receives counts/frequencies of the histogram bins
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\param binWidth width of the bins
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\param normalized indicates whether the histogram has to be normalized
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\param cummulative if \c true, a cummulative histogram is calculated
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\param binXMode defines where the returned x-coordinates (in histogramXOut) lie inside the histogram bin (see JKQTPStatHistogramBinXMode)
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\see jkqtpstatAddHHistogram1DAutoranged()
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*/
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template <class InputIt, class OutputIt>
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inline void jkqtpstatHistogram1DAutoranged(InputIt first, InputIt last, OutputIt histogramXOut, OutputIt histogramYOut, double binWidth, bool normalized=true, bool cummulative=false, JKQTPStatHistogramBinXMode binXMode=JKQTPStatHistogramBinXMode::XIsLeft) {
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double minV=0, maxV=0;
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size_t N=0;
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jkqtpstatMinMax<InputIt>(first, last, minV, maxV, nullptr, nullptr, &N);
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std::vector<double> histX;
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std::vector<double> histY;
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const double range=maxV-minV;
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const double binw=binWidth;
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const int bins=static_cast<int>(ceil(range/binWidth));
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// initialize the histogram
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for (int i=0; i<bins; i++) {
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histX.push_back(minV+static_cast<double>(i)*binw);
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histY.push_back(0);
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}
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// calculate the histogram
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for (auto it=first; it!=last; ++it) {
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const double v=jkqtp_todouble(*it);
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if (JKQTPIsOKFloat(v)) {
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size_t b=jkqtp_bounded<size_t>(0, static_cast<size_t>(floor((v-minV)/binw)), bins-1);
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histY[b]++;
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}
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}
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// output the histogram
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double xoffset=0;
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if (binXMode==JKQTPStatHistogramBinXMode::XIsRight) xoffset=binw;
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if (binXMode==JKQTPStatHistogramBinXMode::XIsMid) xoffset=binw/2.0;
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double NNorm=1;
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if (normalized) {
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NNorm=static_cast<double>(N);
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}
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double h=0;
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for (size_t i=0; i<histX.size(); i++) {
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*histogramXOut=histX[i]+xoffset;
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if (cummulative) h+=(histY[i]/NNorm);
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else h=histY[i]/NNorm;
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*histogramYOut=h;
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++histogramXOut;
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++histogramYOut; }
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}
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/*! \brief calculate an autoranged 1-dimensional histogram from the given data range \a first ... \a last, bins defined the range \a binsFirst ... \a binsLast
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\ingroup jkqtptools_math_statistics_1dhist
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\tparam InputIt standard iterator type of \a first and \a last.
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\tparam BinsInputIt standard iterator type of \a binsFirst and \a binsLast.
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\tparam OutputIt standard output iterator type used for the outliers output \a histogramXOut and \a histogramYOut, use e.g. std::back_inserter
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\param first iterator pointing to the first item in the dataset to use \f$ X_1 \f$
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\param last iterator pointing behind the last item in the dataset to use \f$ X_N \f$
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\param binsFirst iterator pointing to the first item in the set of histogram bins
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\param binsLast iterator pointing behind the last item in the set of histogram bins
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\param[out] histogramXOut output iterator that receives x-positions of the histogram bins. Location of this value inside the bin range is defined by \a binXMode
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\param[out] histogramYOut output iterator that receives counts/frequencies of the histogram bins
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\param normalized indicates whether the histogram has to be normalized
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\param cummulative if \c true, a cummulative histogram is calculated
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\param binXMode defines where the returned x-coordinates (in histogramXOut) lie inside the histogram bin (see JKQTPStatHistogramBinXMode)
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\see jkqtpstatAddHHistogram1D()
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*/
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template <class InputIt, class BinsInputIt, class OutputIt>
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inline void jkqtpstatHistogram1D(InputIt first, InputIt last, BinsInputIt binsFirst, BinsInputIt binsLast, OutputIt histogramXOut, OutputIt histogramYOut, bool normalized=true, bool cummulative=false, JKQTPStatHistogramBinXMode binXMode=JKQTPStatHistogramBinXMode::XIsLeft) {
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double minV=0, maxV=0;
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size_t N=0;
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jkqtpstatMinMax<InputIt>(first, last, minV, maxV, nullptr, nullptr, &N);
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std::vector<double> histX;
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std::vector<double> histY;
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// initialize the histogram
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for (auto it=binsFirst; it!=binsLast; ++it) {
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histX.push_back(jkqtp_todouble(*it));
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histY.push_back(0);
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}
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std::sort(histX.begin(), histX.end());
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// calculate the histogram
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for (auto it=first; it!=last; ++it) {
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const double v=jkqtp_todouble(*it);
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if (JKQTPIsOKFloat(v)) {
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auto itb=std::lower_bound(histX.begin(), histX.end(), v);
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size_t bin=jkqtp_bounded<size_t>(0,static_cast<size_t>(std::abs(std::distance(histX.begin(), itb))), histY.size()-1);
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histY[bin]++;
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}
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}
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// output the histogram
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double NNorm=1;
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if (normalized) {
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NNorm=static_cast<double>(N);
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}
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double h=0;
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for (size_t i=0; i<histX.size(); i++) {
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double xoffset=0;
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double binw=1;
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if (binXMode!=JKQTPStatHistogramBinXMode::XIsLeft) {
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if (i==0 && i+1<histX.size()) binw=histX[1]-histX[0];
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else if (i==histX.size()-1 && static_cast<int>(i)-1>0) binw=histX[histX.size()-1]-histX[histX.size()-2];
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else if (i<histX.size() && i+1<histX.size()) binw=histX[i+1]-histX[i];
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if (binXMode==JKQTPStatHistogramBinXMode::XIsRight) xoffset=binw;
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if (binXMode==JKQTPStatHistogramBinXMode::XIsMid) xoffset=binw/2.0;
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}
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*histogramXOut=histX[i]+xoffset;
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if (cummulative) h+=(histY[i]/NNorm);
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else h=histY[i]/NNorm;
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*histogramYOut=h;
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++histogramXOut;
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++histogramYOut; }
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}
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/*! \brief calculate a 2-dimensional histogram from the given data range \a firstX / \a firstY ... \a lastY / \a lastY
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\ingroup jkqtptools_math_statistics_2dhist
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\tparam InputItX standard iterator type of \a firstX and \a lastX.
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\tparam InputItY standard iterator type of \a firstY and \a lastY.
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\tparam OutputIt standard output iterator type used for the outliers output \a histogramXOut and \a histogramYOut, use e.g. std::back_inserter
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\param firstX iterator pointing to the first x-position item in the dataset to use \f$ X_1 \f$
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\param lastX iterator pointing behind the last x-position item in the dataset to use \f$ X_N \f$
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\param firstY iterator pointing to the first y-position item in the dataset to use \f$ Y_1 \f$
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\param lastY iterator pointing behind the last y-position item in the dataset to use \f$ Y_N \f$
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\param[out] histogramImgOut output iterator that receives counts of the histogram bins in row-major ordering
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\param xmin position of the first histogram bin in x-direction
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\param xmax position of the last histogram bin in x-direction
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\param ymin position of the first histogram bin in y-direction
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\param ymax position of the last histogram bin in y-direction
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\param xbins number of bins in x-direction (i.e. width of the output histogram \a histogramImgOut )
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\param ybins number of bins in y-direction (i.e. height of the output histogram \a histogramImgOut )
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\param normalized indicates whether the histogram has to be normalized
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\see jkqtpstatAddHHistogram1DAutoranged()
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*/
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template <class InputItX, class InputItY, class OutputIt>
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inline void jkqtpstatHistogram2D(InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, OutputIt histogramImgOut, double xmin, double xmax, double ymin, double ymax, size_t xbins=10, size_t ybins=10, bool normalized=true) {
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const double binwx=fabs(xmax-xmin)/static_cast<double>(xbins);
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const double binwy=fabs(ymax-ymin)/static_cast<double>(ybins);
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std::vector<double> hist;
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std::fill_n(std::back_inserter(hist), xbins*ybins, 0.0);
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// calculate the histogram
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auto itX=firstX;
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auto itY=firstY;
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size_t N=0;
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for (; (itX!=lastX) && (itY!=lastY); ++itX, ++itY) {
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const double vx=jkqtp_todouble(*itX);
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const double vy=jkqtp_todouble(*itY);
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if (JKQTPIsOKFloat(vx) && JKQTPIsOKFloat(vy)) {
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const size_t bx=jkqtp_bounded<size_t>(0, static_cast<size_t>(floor((vx-xmin)/binwx)), xbins-1);
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const size_t by=jkqtp_bounded<size_t>(0, static_cast<size_t>(floor((vy-ymin)/binwy)), ybins-1);
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hist[by*xbins+bx]++;
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N++;
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}
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}
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// output the histogram
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double NNorm=1;
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if (normalized) {
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NNorm=static_cast<double>(N);
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}
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std::transform(hist.begin(), hist.end(), histogramImgOut, [NNorm](double v) { return v/NNorm; });
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}
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#endif // JKQTPSTATHISTOGRAM_H_INCLUDED
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