mirror of
https://github.com/jkriege2/JKQtPlotter.git
synced 2024-11-15 18:15:52 +08:00
328 lines
14 KiB
C++
328 lines
14 KiB
C++
/*
|
|
Copyright (c) 2008-2022 Jan W. Krieger (<jan@jkrieger.de>)
|
|
|
|
last modification: $LastChangedDate$ (revision $Rev$)
|
|
|
|
This software is free software: you can redistribute it and/or modify
|
|
it under the terms of the GNU Lesser General Public License (LGPL) as published by
|
|
the Free Software Foundation, either version 2.1 of the License, or
|
|
(at your option) any later version.
|
|
|
|
This program is distributed in the hope that it will be useful,
|
|
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
GNU Lesser General Public License (LGPL) for more details.
|
|
|
|
You should have received a copy of the GNU Lesser General Public License (LGPL)
|
|
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
|
*/
|
|
|
|
|
|
#ifndef JKQTPSTATHISTOGRAM_H_INCLUDED
|
|
#define JKQTPSTATHISTOGRAM_H_INCLUDED
|
|
|
|
#include <stdint.h>
|
|
#include <cmath>
|
|
#include <stdlib.h>
|
|
#include <string.h>
|
|
#include <iostream>
|
|
#include <stdio.h>
|
|
#include <limits>
|
|
#include <vector>
|
|
#include <utility>
|
|
#include <cfloat>
|
|
#include <ostream>
|
|
#include <iomanip>
|
|
#include <sstream>
|
|
#include "jkqtcommon/jkqtcommon_imexport.h"
|
|
#include "jkqtcommon/jkqtplinalgtools.h"
|
|
#include "jkqtcommon/jkqtparraytools.h"
|
|
#include "jkqtcommon/jkqtpdebuggingtools.h"
|
|
#include "jkqtcommon/jkqtpstatbasics.h"
|
|
|
|
|
|
|
|
|
|
/*! \brief defines where the returned x-coordinates (in histogramXOut) lie inside a histogram bin
|
|
\ingroup jkqtptools_math_statistics_1dhist
|
|
\see jkqtpstatHistogram()
|
|
*/
|
|
enum class JKQTPStatHistogramBinXMode {
|
|
XIsLeft, /*!< \brief x-location is the left edge of the bin */
|
|
XIsMid, /*!< \brief x-location is the middle of the bin */
|
|
XIsRight /*!< \brief x-location is the right edge of the bin */
|
|
};
|
|
|
|
/*! \brief calculate an autoranged 1-dimensional histogram from the given data range \a first ... \a last, bins defined by their number
|
|
\ingroup jkqtptools_math_statistics_1dhist
|
|
|
|
\tparam InputIt standard iterator type of \a first and \a last.
|
|
\tparam OutputIt standard output iterator type used for the outliers output \a histogramXOut and \a histogramYOut, use e.g. std::back_inserter
|
|
\param first iterator pointing to the first item in the dataset to use \f$ X_1 \f$
|
|
\param last iterator pointing behind the last item in the dataset to use \f$ X_N \f$
|
|
\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
|
|
\param[out] histogramYOut output iterator that receives counts/frequencies of the histogram bins
|
|
\param bins number of bins in the output histogram
|
|
\param normalized indicates whether the histogram has to be normalized
|
|
\param cummulative if \c true, a cummulative histogram is calculated
|
|
\param binXMode defines where the returned x-coordinates (in histogramXOut) lie inside the histogram bin (see JKQTPStatHistogramBinXMode)
|
|
|
|
\see jkqtpstatAddHHistogram1DAutoranged()
|
|
*/
|
|
template <class InputIt, class OutputIt>
|
|
inline void jkqtpstatHistogram1DAutoranged(InputIt first, InputIt last, OutputIt histogramXOut, OutputIt histogramYOut, int bins=11, bool normalized=true, bool cummulative=false, JKQTPStatHistogramBinXMode binXMode=JKQTPStatHistogramBinXMode::XIsLeft) {
|
|
double minV=0, maxV=0;
|
|
size_t N=0;
|
|
jkqtpstatMinMax<InputIt>(first, last, minV, maxV, nullptr, nullptr, &N);
|
|
|
|
std::vector<double> histX;
|
|
std::vector<double> histY;
|
|
|
|
const double range=maxV-minV;
|
|
const double binw=range/static_cast<double>(bins);
|
|
|
|
// initialize the histogram
|
|
for (int i=0; i<bins; i++) {
|
|
histX.push_back(minV+static_cast<double>(i)*binw);
|
|
histY.push_back(0);
|
|
}
|
|
|
|
// calculate the histogram
|
|
for (auto it=first; it!=last; ++it) {
|
|
const double v=jkqtp_todouble(*it);
|
|
if (JKQTPIsOKFloat(v)) {
|
|
size_t b=jkqtp_bounded<size_t>(0, static_cast<size_t>(floor((v-minV)/binw)), bins-1);
|
|
histY[b]++;
|
|
}
|
|
}
|
|
|
|
|
|
// output the histogram
|
|
double xoffset=0;
|
|
if (binXMode==JKQTPStatHistogramBinXMode::XIsRight) xoffset=binw;
|
|
if (binXMode==JKQTPStatHistogramBinXMode::XIsMid) xoffset=binw/2.0;
|
|
|
|
double NNorm=1;
|
|
if (normalized) {
|
|
NNorm=static_cast<double>(N);
|
|
}
|
|
double h=0;
|
|
for (size_t i=0; i<histX.size(); i++) {
|
|
*histogramXOut=histX[i]+xoffset;
|
|
if (cummulative) h+=(histY[i]/NNorm);
|
|
else h=histY[i]/NNorm;
|
|
*histogramYOut=h;
|
|
++histogramXOut;
|
|
++histogramYOut;
|
|
}
|
|
}
|
|
|
|
/*! \brief calculate an autoranged 1-dimensional histogram from the given data range \a first ... \a last, bins defined by their width
|
|
\ingroup jkqtptools_math_statistics_1dhist
|
|
|
|
\tparam InputIt standard iterator type of \a first and \a last.
|
|
\tparam OutputIt standard output iterator type used for the outliers output \a histogramXOut and \a histogramYOut, use e.g. std::back_inserter
|
|
\param first iterator pointing to the first item in the dataset to use \f$ X_1 \f$
|
|
\param last iterator pointing behind the last item in the dataset to use \f$ X_N \f$
|
|
\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
|
|
\param[out] histogramYOut output iterator that receives counts/frequencies of the histogram bins
|
|
\param binWidth width of the bins
|
|
\param normalized indicates whether the histogram has to be normalized
|
|
\param cummulative if \c true, a cummulative histogram is calculated
|
|
\param binXMode defines where the returned x-coordinates (in histogramXOut) lie inside the histogram bin (see JKQTPStatHistogramBinXMode)
|
|
|
|
\see jkqtpstatAddHHistogram1DAutoranged()
|
|
*/
|
|
template <class InputIt, class OutputIt>
|
|
inline void jkqtpstatHistogram1DAutoranged(InputIt first, InputIt last, OutputIt histogramXOut, OutputIt histogramYOut, double binWidth, bool normalized=true, bool cummulative=false, JKQTPStatHistogramBinXMode binXMode=JKQTPStatHistogramBinXMode::XIsLeft) {
|
|
double minV=0, maxV=0;
|
|
size_t N=0;
|
|
jkqtpstatMinMax<InputIt>(first, last, minV, maxV, nullptr, nullptr, &N);
|
|
|
|
std::vector<double> histX;
|
|
std::vector<double> histY;
|
|
|
|
const double range=maxV-minV;
|
|
const double binw=binWidth;
|
|
const int bins=static_cast<int>(ceil(range/binWidth));
|
|
|
|
// initialize the histogram
|
|
for (int i=0; i<bins; i++) {
|
|
histX.push_back(minV+static_cast<double>(i)*binw);
|
|
histY.push_back(0);
|
|
}
|
|
|
|
// calculate the histogram
|
|
for (auto it=first; it!=last; ++it) {
|
|
const double v=jkqtp_todouble(*it);
|
|
if (JKQTPIsOKFloat(v)) {
|
|
size_t b=jkqtp_bounded<size_t>(0, static_cast<size_t>(floor((v-minV)/binw)), bins-1);
|
|
histY[b]++;
|
|
}
|
|
}
|
|
|
|
|
|
// output the histogram
|
|
double xoffset=0;
|
|
if (binXMode==JKQTPStatHistogramBinXMode::XIsRight) xoffset=binw;
|
|
if (binXMode==JKQTPStatHistogramBinXMode::XIsMid) xoffset=binw/2.0;
|
|
|
|
double NNorm=1;
|
|
if (normalized) {
|
|
NNorm=static_cast<double>(N);
|
|
}
|
|
double h=0;
|
|
for (size_t i=0; i<histX.size(); i++) {
|
|
*histogramXOut=histX[i]+xoffset;
|
|
if (cummulative) h+=(histY[i]/NNorm);
|
|
else h=histY[i]/NNorm;
|
|
*histogramYOut=h;
|
|
++histogramXOut;
|
|
++histogramYOut; }
|
|
}
|
|
|
|
|
|
|
|
/*! \brief calculate an autoranged 1-dimensional histogram from the given data range \a first ... \a last, bins defined the range \a binsFirst ... \a binsLast
|
|
\ingroup jkqtptools_math_statistics_1dhist
|
|
|
|
\tparam InputIt standard iterator type of \a first and \a last.
|
|
\tparam BinsInputIt standard iterator type of \a binsFirst and \a binsLast.
|
|
\tparam OutputIt standard output iterator type used for the outliers output \a histogramXOut and \a histogramYOut, use e.g. std::back_inserter
|
|
\param first iterator pointing to the first item in the dataset to use \f$ X_1 \f$
|
|
\param last iterator pointing behind the last item in the dataset to use \f$ X_N \f$
|
|
\param binsFirst iterator pointing to the first item in the set of histogram bins
|
|
\param binsLast iterator pointing behind the last item in the set of histogram bins
|
|
\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
|
|
\param[out] histogramYOut output iterator that receives counts/frequencies of the histogram bins
|
|
\param normalized indicates whether the histogram has to be normalized
|
|
\param cummulative if \c true, a cummulative histogram is calculated
|
|
\param binXMode defines where the returned x-coordinates (in histogramXOut) lie inside the histogram bin (see JKQTPStatHistogramBinXMode)
|
|
|
|
\see jkqtpstatAddHHistogram1D()
|
|
*/
|
|
template <class InputIt, class BinsInputIt, class OutputIt>
|
|
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) {
|
|
double minV=0, maxV=0;
|
|
size_t N=0;
|
|
jkqtpstatMinMax<InputIt>(first, last, minV, maxV, nullptr, nullptr, &N);
|
|
|
|
std::vector<double> histX;
|
|
std::vector<double> histY;
|
|
|
|
|
|
// initialize the histogram
|
|
for (auto it=binsFirst; it!=binsLast; ++it) {
|
|
histX.push_back(jkqtp_todouble(*it));
|
|
histY.push_back(0);
|
|
}
|
|
std::sort(histX.begin(), histX.end());
|
|
|
|
// calculate the histogram
|
|
for (auto it=first; it!=last; ++it) {
|
|
const double v=jkqtp_todouble(*it);
|
|
if (JKQTPIsOKFloat(v)) {
|
|
auto itb=std::lower_bound(histX.begin(), histX.end(), v);
|
|
size_t bin=jkqtp_bounded<size_t>(0,static_cast<size_t>(std::abs(std::distance(histX.begin(), itb))), histY.size()-1);
|
|
histY[bin]++;
|
|
}
|
|
}
|
|
|
|
|
|
// output the histogram
|
|
double NNorm=1;
|
|
if (normalized) {
|
|
NNorm=static_cast<double>(N);
|
|
}
|
|
double h=0;
|
|
for (size_t i=0; i<histX.size(); i++) {
|
|
double xoffset=0;
|
|
double binw=1;
|
|
if (binXMode!=JKQTPStatHistogramBinXMode::XIsLeft) {
|
|
if (i==0 && i+1<histX.size()) binw=histX[1]-histX[0];
|
|
else if (i==histX.size()-1 && static_cast<int>(i)-1>0) binw=histX[histX.size()-1]-histX[histX.size()-2];
|
|
else if (i<histX.size() && i+1<histX.size()) binw=histX[i+1]-histX[i];
|
|
if (binXMode==JKQTPStatHistogramBinXMode::XIsRight) xoffset=binw;
|
|
if (binXMode==JKQTPStatHistogramBinXMode::XIsMid) xoffset=binw/2.0;
|
|
}
|
|
|
|
*histogramXOut=histX[i]+xoffset;
|
|
if (cummulative) h+=(histY[i]/NNorm);
|
|
else h=histY[i]/NNorm;
|
|
*histogramYOut=h;
|
|
++histogramXOut;
|
|
++histogramYOut; }
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
/*! \brief calculate a 2-dimensional histogram from the given data range \a firstX / \a firstY ... \a lastY / \a lastY
|
|
\ingroup jkqtptools_math_statistics_2dhist
|
|
|
|
\tparam InputItX standard iterator type of \a firstX and \a lastX.
|
|
\tparam InputItY standard iterator type of \a firstY and \a lastY.
|
|
\tparam OutputIt standard output iterator type used for the outliers output \a histogramXOut and \a histogramYOut, use e.g. std::back_inserter
|
|
\param firstX iterator pointing to the first x-position item in the dataset to use \f$ X_1 \f$
|
|
\param lastX iterator pointing behind the last x-position item in the dataset to use \f$ X_N \f$
|
|
\param firstY iterator pointing to the first y-position item in the dataset to use \f$ Y_1 \f$
|
|
\param lastY iterator pointing behind the last y-position item in the dataset to use \f$ Y_N \f$
|
|
\param[out] histogramImgOut output iterator that receives counts of the histogram bins in row-major ordering
|
|
\param xmin position of the first histogram bin in x-direction
|
|
\param xmax position of the last histogram bin in x-direction
|
|
\param ymin position of the first histogram bin in y-direction
|
|
\param ymax position of the last histogram bin in y-direction
|
|
\param xbins number of bins in x-direction (i.e. width of the output histogram \a histogramImgOut )
|
|
\param ybins number of bins in y-direction (i.e. height of the output histogram \a histogramImgOut )
|
|
\param normalized indicates whether the histogram has to be normalized
|
|
|
|
\see jkqtpstatAddHHistogram1DAutoranged()
|
|
*/
|
|
template <class InputItX, class InputItY, class OutputIt>
|
|
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) {
|
|
|
|
const double binwx=fabs(xmax-xmin)/static_cast<double>(xbins);
|
|
const double binwy=fabs(ymax-ymin)/static_cast<double>(ybins);
|
|
|
|
std::vector<double> hist;
|
|
std::fill_n(std::back_inserter(hist), xbins*ybins, 0.0);
|
|
|
|
// calculate the histogram
|
|
auto itX=firstX;
|
|
auto itY=firstY;
|
|
size_t N=0;
|
|
for (; (itX!=lastX) && (itY!=lastY); ++itX, ++itY) {
|
|
const double vx=jkqtp_todouble(*itX);
|
|
const double vy=jkqtp_todouble(*itY);
|
|
if (JKQTPIsOKFloat(vx) && JKQTPIsOKFloat(vy)) {
|
|
const size_t bx=jkqtp_bounded<size_t>(0, static_cast<size_t>(floor((vx-xmin)/binwx)), xbins-1);
|
|
const size_t by=jkqtp_bounded<size_t>(0, static_cast<size_t>(floor((vy-ymin)/binwy)), ybins-1);
|
|
hist[by*xbins+bx]++;
|
|
N++;
|
|
}
|
|
}
|
|
|
|
|
|
// output the histogram
|
|
double NNorm=1;
|
|
if (normalized) {
|
|
NNorm=static_cast<double>(N);
|
|
}
|
|
std::transform(hist.begin(), hist.end(), histogramImgOut, [NNorm](double v) { return v/NNorm; });
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
#endif // JKQTPSTATHISTOGRAM_H_INCLUDED
|
|
|
|
|