Statistics To Plot Adaptors

Collaboration diagram for Statistics To Plot Adaptors:

Functions
template<class InputCatIt , class InputValueIt , class TGraph >
TGraph *	jkqtpstatAddBoxplots (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, double quantile1Spec=0.25, double quantile2Spec=0.75, double minimumQuantile=0, double maximumQuantile=1.0, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped boxplot data"))
	create horizontal boxplots of type TGraph, from the 5-value-summary of groups in the input data
template<class InputIt >
JKQTPBoxplotHorizontalElement *	jkqtpstatAddHBoxplot (JKQTBasePlotter *plotter, InputIt first, InputIt last, double boxposY, double quantile1Spec=0.25, double quantile2Spec=0.75, double minimumQuantile=0, double maximumQuantile=1.0, JKQTPStat5NumberStatistics *statOutput=nullptr)
	add a JKQTPBoxplotHorizontalElement to the given plotter, where the boxplot values are calculated from the data range first ... last
template<class InputIt >
std::pair< JKQTPBoxplotHorizontalElement *, JKQTPSingleColumnSymbolsGraph * >	jkqtpstatAddHBoxplotAndOutliers (JKQTBasePlotter *plotter, InputIt first, InputIt last, double boxposY, double quantile1Spec=0.25, double quantile2Spec=0.75, double minimumQuantile=0.03, double maximumQuantile=0.97, const QString &outliercolumnBaseName=QString("boxplot"), JKQTPStat5NumberStatistics *statOutput=nullptr)
	add a JKQTPBoxplotHorizontalElement and a JKQTPSingleColumnSymbolsGraph for outliers to the given plotter, where the boxplot values are calculated from the data range first ... last
template<class InputCatIt , class InputValueIt >
std::pair< JKQTPBoxplotHorizontalGraph *, JKQTPXYLineGraph * >	jkqtpstatAddHBoxplotsAndOutliers (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_X, InputValueIt inLastValue_X, double quantile1Spec=0.25, double quantile2Spec=0.75, double minimumQuantile=0.03, double maximumQuantile=0.97, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped boxplot data"))
	create vertical boxplots of type JKQTPBoxplotHorizontalGraph, from the 5-value-summary of groups in the input data, also adds a graph showing the outliers
template<class InputIt , class BinsInputIt >
JKQTPBarVerticalGraph *	jkqtpstatAddHHistogram1D (JKQTBasePlotter *plotter, InputIt first, InputIt last, BinsInputIt binsFirst, BinsInputIt binsLast, bool normalized=true, bool cummulative=false, const QString &histogramcolumnBaseName=QString("histogram"))
	calculate an autoranged histogram and add a JKQTPBarVerticalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their width
template<class InputIt >
JKQTPBarVerticalGraph *	jkqtpstatAddHHistogram1DAutoranged (JKQTBasePlotter *plotter, InputIt first, InputIt last, double binWidth, bool normalized=true, bool cummulative=false, const QString &histogramcolumnBaseName=QString("histogram"))
	calculate an autoranged histogram and add a JKQTPBarVerticalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their width
template<class InputIt >
JKQTPBarVerticalGraph *	jkqtpstatAddHHistogram1DAutoranged (JKQTBasePlotter *plotter, InputIt first, InputIt last, int bins=11, bool normalized=true, bool cummulative=false, const QString &histogramcolumnBaseName=QString("histogram"))
	calculate an autoranged histogram and add a JKQTPBarVerticalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their number
template<class InputItX , class InputItY >
JKQTPColumnContourPlot *	jkqtpstatAddHistogram2DContour (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, double xbinwidth, double ybinwidth, bool normalized=true, const QString &histogramcolumnBaseName=QString("histogram"), double *oxmin=nullptr, double *oxmax=nullptr, double *oymin=nullptr, double *oymax=nullptr)
	calculate calculate a 2-dimensional histogram and add a JKQTPColumnContourPlot to the given plotter, where the histogram is calculated from the given data range firstX / firstY ... lastY / lastY
template<class InputItX , class InputItY >
JKQTPColumnContourPlot *	jkqtpstatAddHistogram2DContour (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, size_t xbins=10, size_t ybins=10, bool normalized=true, const QString &histogramcolumnBaseName=QString("histogram"), double *oxmin=nullptr, double *oxmax=nullptr, double *oymin=nullptr, double *oymax=nullptr)
	calculate calculate a 2-dimensional histogram and add a JKQTPColumnContourPlot to the given plotter, where the histogram is calculated from the given data range firstX / firstY ... lastY / lastY
template<class InputItX , class InputItY >
JKQTPColumnMathImage *	jkqtpstatAddHistogram2DImage (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, double xbinwidth, double ybinwidth, bool normalized=true, const QString &histogramcolumnBaseName=QString("histogram"), double *oxmin=nullptr, double *oxmax=nullptr, double *oymin=nullptr, double *oymax=nullptr)
	calculate calculate a 2-dimensional histogram and add a JKQTPColumnMathImage to the given plotter, where the histogram is calculated from the given data range firstX / firstY ... lastY / lastY
template<class InputItX , class InputItY >
JKQTPColumnMathImage *	jkqtpstatAddHistogram2DImage (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, size_t xbins=10, size_t ybins=10, bool normalized=true, const QString &histogramcolumnBaseName=QString("histogram"), double *oxmin=nullptr, double *oxmax=nullptr, double *oymin=nullptr, double *oymax=nullptr)
	calculate calculate a 2-dimensional histogram and add a JKQTPColumnMathImage to the given plotter, where the histogram is calculated from the given data range firstX / firstY ... lastY / lastY
template<class InputIt , class BinsInputIt >
JKQTPXYLineGraph *	jkqtpstatAddHKDE1D (JKQTBasePlotter *plotter, InputIt first, InputIt last, BinsInputIt binsFirst, BinsInputIt binsLast, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=1.0, bool cummulative=false, const QString &KDEcolumnBaseName=QString("KDE"))
	calculate an autoranged KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their width
template<class InputIt >
JKQTPXYLineGraph *	jkqtpstatAddHKDE1D (JKQTBasePlotter *plotter, InputIt first, InputIt last, double binXLeft, double binXDelta, double binXRight, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=1.0, bool cummulative=false, const QString &KDEcolumnBaseName=QString("KDE"))
	calculate an autoranged KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, evaluation positions are given by the range binXLeft ... binXRight (in steps of binxDelta )
template<class InputIt >
JKQTPXYLineGraph *	jkqtpstatAddHKDE1DAutoranged (JKQTBasePlotter *plotter, InputIt first, InputIt last, double binWidth, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=1.0, bool cummulative=false, const QString &KDEcolumnBaseName=QString("KDE"))
	calculate an autoranged KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their width
template<class InputIt >
JKQTPXYLineGraph *	jkqtpstatAddHKDE1DAutoranged (JKQTBasePlotter *plotter, InputIt first, InputIt last, int Nout=100, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=1.0, bool cummulative=false, const QString &KDEcolumnBaseName=QString("KDE"))
	calculate an autoranged KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their number
template<class InputIt >
JKQTPViolinplotHorizontalElement *	jkqtpstatAddHViolinplotHistogram (JKQTBasePlotter *plotter, InputIt first, InputIt last, double violinposY, const QString &distBasename=QString("violin plot distribution"), int violinDistSamples=21)
	add a JKQTPViolinplotHorizontalElement to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a histogram as density distribution estimate
template<class InputIt >
std::pair< JKQTPViolinplotHorizontalElement *, JKQTPSingleColumnSymbolsGraph * >	jkqtpstatAddHViolinplotHistogramAndOutliers (JKQTBasePlotter *plotter, InputIt first, InputIt last, double violinposY, double minimumQuantile=0.03, double maximumQuantile=0.97, const QString &distBasename=QString("violin plot distribution"), int violinDistSamples=21)
	add a JKQTPViolinplotHorizontalElement and an outliers graph to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a histogram as density distribution estimate
template<class InputIt >
JKQTPViolinplotHorizontalElement *	jkqtpstatAddHViolinplotKDE (JKQTBasePlotter *plotter, InputIt first, InputIt last, double violinposY, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=-1, const QString &distBasename=QString("violin plot distribution"), int violinDistSamples=100)
	add a JKQTPViolinplotHorizontalElement to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a kernel density estimate as density distribution estimate
template<class InputIt >
std::pair< JKQTPViolinplotHorizontalElement *, JKQTPSingleColumnSymbolsGraph * >	jkqtpstatAddHViolinplotKDEAndOutliers (JKQTBasePlotter *plotter, InputIt first, InputIt last, double violinposY, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=-1, double minimumQuantile=0.03, double maximumQuantile=0.97, const QString &distBasename=QString("violin plot distribution"), int violinDistSamples=100)
	add a JKQTPViolinplotHorizontalElement and an outliers graph to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a kernel density estimate as density distribution estimate
template<class InputItX , class InputItY >
JKQTPColumnContourPlot *	jkqtpstatAddKDE2DContour (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, size_t xbins=10, size_t ybins=10, const std::function< double(double, double)> &kernel=std::function< double(double, double)>(&jkqtpstatKernel2DGaussian), double bandwidthX=1.0, double bandwidthY=1.0, const QString &kdecolumnBaseName=QString("histogram"), double *oxmin=nullptr, double *oxmax=nullptr, double *oymin=nullptr, double *oymax=nullptr)
	calculate calculate a 2-dimensional kernel density estimate (KDE) and add a JKQTPColumnContourPlot to the given plotter, where the KDE is calculated from the given data range firstX / firstY ... lastY / lastY
template<class InputItX , class InputItY >
JKQTPColumnMathImage *	jkqtpstatAddKDE2DImage (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, size_t xbins=10, size_t ybins=10, const std::function< double(double, double)> &kernel=std::function< double(double, double)>(&jkqtpstatKernel2DGaussian), double bandwidthX=1.0, double bandwidthY=1.0, const QString &kdecolumnBaseName=QString("histogram"), double *oxmin=nullptr, double *oxmax=nullptr, double *oymin=nullptr, double *oymax=nullptr)
	calculate calculate a 2-dimensional kernel density estimate (KDE) and add a JKQTPColumnMathImage to the given plotter, where the KDE is calculated from the given data range firstX / firstY ... lastY / lastY
template<class InputItX , class InputItY >
JKQTPXFunctionLineGraph *	jkqtpstatAddLinearRegression (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false)
	calculate the linear regression coefficients for a given data range firstX / firstY ... lastX / lastY where the model is
JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph *	jkqtpstatAddLinearRegression (JKQTPXYGraph *datagraph, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false)
	calculate the linear regression coefficients for a given data data used to draw any JKQTPXYGraph datagraph where the model is
template<class InputItX , class InputItY , class InputItW >
JKQTPXFunctionLineGraph *	jkqtpstatAddLinearWeightedRegression (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, InputItW firstW, InputItW lastW, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false, std::function< double(double)> fWeightDataToWi=&jkqtp_identity< double >)
	calculate the weighted linear regression coefficients for a given for a given data range firstX / firstY / firstW ... lastX / lastY / lastW where the model is
JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph *	jkqtpstatAddLinearWeightedRegression (JKQTPXYGraph *datagraph, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false)
	calculate the linear weighted regression coefficients for a given data data used to draw any JKQTPXYGraph datagraph , which also implements JKQTPYGraphErrorData and where the model is
template<class InputItX , class InputItY >
JKQTPXFunctionLineGraph *	jkqtpstatAddPolyFit (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, size_t P)
	fits (in a least-squares sense) a polynomial of order P to a set of N data pairs from a given data range firstX / firstY ... lastX / lastY
template<class InputItX , class InputItY , class OutputItP >
JKQTPXFunctionLineGraph *	jkqtpstatAddPolyFit (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, size_t P, OutputItP firstRes)
	fits (in a least-squares sense) a polynomial of order P to a set of N data pairs from a given data range firstX / firstY ... lastX / lastY
JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph *	jkqtpstatAddPolyFit (JKQTPXYGraph *datagraph, size_t P)
	fits (in a least-squares sense) a polynomial of order P to a set of N data pairs from a given JKQTPXYGraph datagraph
template<class OutputItP >
JKQTPXFunctionLineGraph *	jkqtpstatAddPolyFit (JKQTPXYGraph *datagraph, size_t P, OutputItP firstRes)
	fits (in a least-squares sense) a polynomial of order P to a set of N data pairs from a given JKQTPXYGraph datagraph
template<class InputItX , class InputItY >
JKQTPXFunctionLineGraph *	jkqtpstatAddRegression (JKQTBasePlotter *plotter, JKQTPStatRegressionModelType type, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false)
	calculate the linear regression coefficients for a given data range firstX / firstY ... lastX / lastY where the model is defined by type
template<class InputItX , class InputItY >
JKQTPXFunctionLineGraph *	jkqtpstatAddRobustIRLSLinearRegression (JKQTBasePlotter *plotter, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false, double p=1.1, int iterations=100)
	calculate the (robust) iteratively reweighted least-squares (IRLS) estimate for the parameters of the model for a given data range firstX / firstY ... lastX / lastY
JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph *	jkqtpstatAddRobustIRLSLinearRegression (JKQTPXYGraph *datagraph, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false, double p=1.1, int iterations=100)
	calculate the (robust) iteratively reweighted least-squares (IRLS) estimate for the parameters of the model for a given data range firstX / firstY ... lastX / lastY
template<class InputItX , class InputItY >
JKQTPXFunctionLineGraph *	jkqtpstatAddRobustIRLSRegression (JKQTBasePlotter *plotter, JKQTPStatRegressionModelType type, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false, double p=1.1, int iterations=100)
	calculate the (robust) iteratively reweighted least-squares (IRLS) estimate for the parameters where the model is defined by type for a given data range firstX / firstY ... lastX / lastY
JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph *	jkqtpstatAddRobustIRLSRegression (JKQTPXYGraph *datagraph, JKQTPStatRegressionModelType type, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false, double p=1.1, int iterations=100)
	calculate the (robust) iteratively reweighted least-squares (IRLS) estimate for the parameters where the model is defined by type for a given data range firstX / firstY ... lastX / lastY
template<class InputIt >
JKQTPBoxplotVerticalElement *	jkqtpstatAddVBoxplot (JKQTBasePlotter *plotter, InputIt first, InputIt last, double boxposX, double quantile1Spec=0.25, double quantile2Spec=0.75, double minimumQuantile=0, double maximumQuantile=1.0, JKQTPStat5NumberStatistics *statOutput=nullptr)
	add a JKQTPBoxplotVerticalElement to the given plotter, where the boxplot values are calculated from the data range first ... last
template<class InputIt >
std::pair< JKQTPBoxplotVerticalElement *, JKQTPSingleColumnSymbolsGraph * >	jkqtpstatAddVBoxplotAndOutliers (JKQTBasePlotter *plotter, InputIt first, InputIt last, double boxposX, double quantile1Spec=0.25, double quantile2Spec=0.75, double minimumQuantile=0.03, double maximumQuantile=0.97, const QString &outliercolumnBaseName=QString("boxplot"), JKQTPStat5NumberStatistics *statOutput=nullptr)
	add a JKQTPBoxplotVerticalElement and a JKQTPSingleColumnSymbolsGraph for outliers to the given plotter, where the boxplot values are calculated from the data range first ... last
template<class InputCatIt , class InputValueIt >
std::pair< JKQTPBoxplotVerticalGraph *, JKQTPXYLineGraph * >	jkqtpstatAddVBoxplotsAndOutliers (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, double quantile1Spec=0.25, double quantile2Spec=0.75, double minimumQuantile=0.03, double maximumQuantile=0.97, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped boxplot data"))
	create vertical boxplots of type JKQTPBoxplotVerticalGraph, from the 5-value-summary of groups in the input data, also adds a graph showing the outliers
template<class InputIt , class BinsInputIt >
JKQTPBarHorizontalGraph *	jkqtpstatAddVHistogram1D (JKQTBasePlotter *plotter, InputIt first, InputIt last, BinsInputIt binsFirst, BinsInputIt binsLast, bool normalized=true, bool cummulative=false, const QString &histogramcolumnBaseName=QString("histogram"))
	calculate an autoranged histogram and add a JKQTPBarHorizontalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their width
template<class InputIt >
JKQTPBarHorizontalGraph *	jkqtpstatAddVHistogram1DAutoranged (JKQTBasePlotter *plotter, InputIt first, InputIt last, double binWidth, bool normalized=true, bool cummulative=false, const QString &histogramcolumnBaseName=QString("histogram"))
	calculate an autoranged histogram and add a JKQTPBarHorizontalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their width
template<class InputIt >
JKQTPBarHorizontalGraph *	jkqtpstatAddVHistogram1DAutoranged (JKQTBasePlotter *plotter, InputIt first, InputIt last, int bins=11, bool normalized=true, bool cummulative=false, const QString &histogramcolumnBaseName=QString("histogram"))
	calculate an autoranged histogram and add a JKQTPBarHorizontalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their number
template<class InputIt , class BinsInputIt >
JKQTPXYLineGraph *	jkqtpstatAddVKDE1D (JKQTBasePlotter *plotter, InputIt first, InputIt last, BinsInputIt binsFirst, BinsInputIt binsLast, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=1.0, bool cummulative=false, const QString &KDEcolumnBaseName=QString("KDE"))
	calculate an autoranged vertical KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their width
template<class InputIt >
JKQTPXYLineGraph *	jkqtpstatAddVKDE1D (JKQTBasePlotter *plotter, InputIt first, InputIt last, double binXLeft, double binXDelta, double binXRight, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=1.0, bool cummulative=false, const QString &KDEcolumnBaseName=QString("KDE"))
	calculate an autoranged vertical KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, evaluation positions are given by the range binXLeft ... binXRight (in steps of binxDelta )
template<class InputIt >
JKQTPXYLineGraph *	jkqtpstatAddVKDE1DAutoranged (JKQTBasePlotter *plotter, InputIt first, InputIt last, double binWidth, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=1.0, bool cummulative=false, const QString &KDEcolumnBaseName=QString("KDE"))
	calculate an autoranged vertical KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their width
template<class InputIt >
JKQTPXYLineGraph *	jkqtpstatAddVKDE1DAutoranged (JKQTBasePlotter *plotter, InputIt first, InputIt last, int Nout=100, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=1.0, bool cummulative=false, const QString &KDEcolumnBaseName=QString("KDE"))
	calculate an autoranged vertical KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their number
template<class InputIt >
JKQTPViolinplotVerticalElement *	jkqtpstatAddVViolinplotHistogram (JKQTBasePlotter *plotter, InputIt first, InputIt last, double violinposY, const QString &distBasename=QString("violin plot distribution"), int violinDistSamples=21)
	add a JKQTPViolinplotVerticalElement to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a histogram as density distribution estimate
template<class InputIt >
std::pair< JKQTPViolinplotVerticalElement *, JKQTPSingleColumnSymbolsGraph * >	jkqtpstatAddVViolinplotHistogramAndOutliers (JKQTBasePlotter *plotter, InputIt first, InputIt last, double violinposY, double minimumQuantile=0.03, double maximumQuantile=0.97, const QString &distBasename=QString("violin plot distribution"), int violinDistSamples=21)
	add a JKQTPViolinplotVerticalElement and an outliers graph to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a histogram as density distribution estimate
template<class InputIt >
JKQTPViolinplotVerticalElement *	jkqtpstatAddVViolinplotKDE (JKQTBasePlotter *plotter, InputIt first, InputIt last, double violinposY, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=-1, const QString &distBasename=QString("violin plot distribution"), int violinDistSamples=100)
	add a JKQTPViolinplotVerticalElement to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a kernel density estimate as density distribution estimate
template<class InputIt >
std::pair< JKQTPViolinplotVerticalElement *, JKQTPSingleColumnSymbolsGraph * >	jkqtpstatAddVViolinplotKDEAndOutliers (JKQTBasePlotter *plotter, InputIt first, InputIt last, double violinposY, const std::function< double(double)> &kernel=std::function< double(double)>(&jkqtpstatKernel1DGaussian), double bandwidth=-1, double minimumQuantile=0.03, double maximumQuantile=0.97, const QString &distBasename=QString("violin plot distribution"), int violinDistSamples=100)
	add a JKQTPViolinplotVerticalElement and an outliers graph to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a kernel density estimate as density distribution estimate
template<class InputItX , class InputItY , class InputItW >
JKQTPXFunctionLineGraph *	jkqtpstatAddWeightedRegression (JKQTBasePlotter *plotter, JKQTPStatRegressionModelType type, InputItX firstX, InputItX lastX, InputItY firstY, InputItY lastY, InputItW firstW, InputItW lastW, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false, std::function< double(double)> fWeightDataToWi=&jkqtp_identity< double >)
	calculate the weighted linear regression coefficients for a given for a given data range firstX / firstY / firstW ... lastX / lastY / lastW where the model is defined by type
JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph *	jkqtpstatAddWeightedRegression (JKQTPXYGraph *datagraph, JKQTPStatRegressionModelType type, double *coeffA=nullptr, double *coeffB=nullptr, bool fixA=false, bool fixB=false)
	calculate the linear weighted regression coefficients for a given data data used to draw any JKQTPXYGraph datagraph , which also implements JKQTPYGraphErrorData and where the model is defined by type
template<class InputCatIt , class InputValueIt >
JKQTPBarHorizontalErrorGraph *	jkqtpstatAddXErrorBarGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPBarHorizontalErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPFilledCurveXErrorGraph *	jkqtpstatAddXErrorFilledCurveGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPFilledCurveXErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt , class TGraph >
TGraph *	jkqtpstatAddXErrorGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a plot with x-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPImpulsesHorizontalErrorGraph *	jkqtpstatAddXErrorImpulsesGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPImpulsesHorizontalErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPXYLineErrorGraph *	jkqtpstatAddXErrorLineGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPXYLineErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPXYParametrizedErrorScatterGraph *	jkqtpstatAddXErrorParametrizedScatterGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPXYParametrizedErrorScatterGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt , class TGraph >
TGraph *	jkqtpstatAddXYErrorGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a plot with x- and y-direction error bars, calculated from directional average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPXYLineErrorGraph *	jkqtpstatAddXYErrorLineGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPXYLineErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPXYParametrizedErrorScatterGraph *	jkqtpstatAddXYErrorParametrizedScatterGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPXYParametrizedErrorScatterGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPBarVerticalErrorGraph *	jkqtpstatAddYErrorBarGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPBarVerticalErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPFilledCurveYErrorGraph *	jkqtpstatAddYErrorFilledCurveGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPFilledCurveYErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt , class TGraph >
TGraph *	jkqtpstatAddYErrorGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a plot with y-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPImpulsesVerticalErrorGraph *	jkqtpstatAddYErrorImpulsesGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPImpulsesVerticalErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPXYLineErrorGraph *	jkqtpstatAddYErrorLineGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPXYLineErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPXYParametrizedErrorScatterGraph *	jkqtpstatAddYErrorParametrizedScatterGraph (JKQTBasePlotter *plotter, InputCatIt inFirstCat_X, InputCatIt inLastCat_X, InputValueIt inFirstValue_Y, InputValueIt inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped data"))
	create a JKQTPXYParametrizedErrorScatterGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
template<class InputCatIt , class InputValueIt >
JKQTPBoxplotVerticalGraph *	jkqtpstatVAddBoxplots (JKQTBasePlotter *plotter, InputCatIt inFirstCat_Y, InputCatIt inLastCat_Y, InputValueIt inFirstValue_X, InputValueIt inLastValue_X, double quantile1Spec=0.25, double quantile2Spec=0.75, double minimumQuantile=0, double maximumQuantile=1.0, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString &columnBaseName=QString("grouped boxplot data"))
	create vertical boxplots of type JKQTPBoxplotVerticalGraph, from the 5-value-summary of groups in the input data

Detailed Description

Function Documentation

jkqtpstatAddBoxplots()

template<class InputCatIt , class InputValueIt , class TGraph >

TGraph * jkqtpstatAddBoxplots ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, double  quantile1Spec = 0.25, double  quantile2Spec = 0.75, double  minimumQuantile = 0, double  maximumQuantile = 1.0, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped boxplot data")  )

inline

create horizontal boxplots of type TGraph, from the 5-value-summary of groups in the input data

Template Parameters

TGraph	type of graph that should be added to the plot, has to offer the same interface as JKQTPBoxplotVerticalGraph or JKQTPBoxplotHorizontalGraph
InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
quantile1Spec	specifies which quantile to calculate for qantile1 (range: 0..1)
quantile2Spec	specifies which quantile to calculate for qantile2 (range: 0..1)
minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the boxplot graph

See also

jkqtpstatGroupData(), Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddHBoxplot()

template<class InputIt >

JKQTPBoxplotHorizontalElement * jkqtpstatAddHBoxplot ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  boxposY, double  quantile1Spec = 0.25, double  quantile2Spec = 0.75, double  minimumQuantile = 0, double  maximumQuantile = 1.0, JKQTPStat5NumberStatistics *  statOutput = nullptr  )

inline

add a JKQTPBoxplotHorizontalElement to the given plotter, where the boxplot values are calculated from the data range first ... last

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

	plotter	the plotter to which to add the resulting graph
	first	iterator pointing to the first item in the dataset to use
	last	iterator pointing behind the last item in the dataset to use
	boxposY	y-coordinate of the boxplot
	quantile1Spec	specifies which quantile to calculate for qantile1 (range: 0..1)
	quantile2Spec	specifies which quantile to calculate for qantile2 (range: 0..1)
	minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
	maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
[out]	statOutput	optionally returns the internally calculated statistics as a JKQTPStat5NumberStatistics

Returns

a boxplot element with its values initialized from the given data range

Example:

jkqtpstatAddHBoxplot(plot1->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -0.3);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstat5NumberStatistics()

jkqtpstatAddHBoxplotAndOutliers()

template<class InputIt >

std::pair< JKQTPBoxplotHorizontalElement *, JKQTPSingleColumnSymbolsGraph * > jkqtpstatAddHBoxplotAndOutliers ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  boxposY, double  quantile1Spec = 0.25, double  quantile2Spec = 0.75, double  minimumQuantile = 0.03, double  maximumQuantile = 0.97, const QString &  outliercolumnBaseName = QString("boxplot"), JKQTPStat5NumberStatistics *  statOutput = nullptr  )

inline

add a JKQTPBoxplotHorizontalElement and a JKQTPSingleColumnSymbolsGraph for outliers to the given plotter, where the boxplot values are calculated from the data range first ... last

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

	plotter	the plotter to which to add the resulting graph
	first	iterator pointing to the first item in the dataset to use
	last	iterator pointing behind the last item in the dataset to use
	boxposY	y-coordinate of the outliers (and the boxplot)
	quantile1Spec	specifies which quantile to calculate for qantile1 (range: 0..1)
	quantile2Spec	specifies which quantile to calculate for qantile2 (range: 0..1)
	minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
	maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
	outliercolumnBaseName	this string is used in building the column names for the outlier columns
[out]	statOutput	optionally returns the internally calculated statistics as a JKQTPStat5NumberStatistics

Returns

a boxplot element with its values initialized from the given data range

Example:

jkqtpstatAddHBoxplotAndOutliers(plot1->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -0.3);
jkqtpstatAddHBoxplotAndOutliers(plot1->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -0.3,
                                0.25, 0.75, // 1. and 3. Quartile for the boxplot box
                                0.05, 0.95 // Quantiles for the boxplot box whiskers' ends

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstat5NumberStatistics()

jkqtpstatAddHBoxplotsAndOutliers()

template<class InputCatIt , class InputValueIt >

std::pair< JKQTPBoxplotHorizontalGraph *, JKQTPXYLineGraph * > jkqtpstatAddHBoxplotsAndOutliers ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_X, InputValueIt  inLastValue_X, double  quantile1Spec = 0.25, double  quantile2Spec = 0.75, double  minimumQuantile = 0.03, double  maximumQuantile = 0.97, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped boxplot data")  )

inline

create vertical boxplots of type JKQTPBoxplotHorizontalGraph, from the 5-value-summary of groups in the input data, also adds a graph showing the outliers

Template Parameters

InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_X and inLastValue_X

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
quantile1Spec	specifies which quantile to calculate for qantile1 (range: 0..1)
quantile2Spec	specifies which quantile to calculate for qantile2 (range: 0..1)
minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the boxplot graph (return.first) and the outliers graph (return.second)

See also

jkqtpstatGroupData(), Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddHHistogram1D()

template<class InputIt , class BinsInputIt >

JKQTPBarVerticalGraph * jkqtpstatAddHHistogram1D ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, BinsInputIt  binsFirst, BinsInputIt  binsLast, bool  normalized = true, bool  cummulative = false, const QString &  histogramcolumnBaseName = QString("histogram")  )

inline

calculate an autoranged histogram and add a JKQTPBarVerticalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their width

Template Parameters

InputIt	standard iterator type of first and last.
BinsInputIt	standard iterator type of binsFirst and binsLast.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binsFirst	iterator pointing to the first item in the set of histogram bins
binsLast	iterator pointing behind the last item in the set of histogram bins
histogramcolumnBaseName	this string is used in building the column names for the histogram columns
normalized	indicates whether the histogram has to be normalized
cummulative	if true, a cummulative histogram is calculated

Returns

a graph class pointer (of type GraphClass ) displaying the histogram data

Example:

std::vector<double> bins{-2,-1.5,-1,-0.75,-0.5,-0.25,0,0.25,0.5,0.75,1,1.5,2,2.5,3,4,5,6,7,8,9,10};
jkqtpstatAddHHistogram1D(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), bins.begin(), bins.end());

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatHistogram1D(), JKQTPBarVerticalGraph

jkqtpstatAddHHistogram1DAutoranged() [1/2]

template<class InputIt >

JKQTPBarVerticalGraph * jkqtpstatAddHHistogram1DAutoranged ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  binWidth, bool  normalized = true, bool  cummulative = false, const QString &  histogramcolumnBaseName = QString("histogram")  )

inline

calculate an autoranged histogram and add a JKQTPBarVerticalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their width

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binWidth	width of the bins
histogramcolumnBaseName	this string is used in building the column names for the histogram columns
normalized	indicates whether the histogram has to be normalized
cummulative	if true, a cummulative histogram is calculated

Returns

a graph class pointer (of type GraphClass ) displaying the histogram data

Example:

jkqtpstatAddHHistogram1DAutoranged(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), 0.5);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatHistogram1DAutoranged(), JKQTPBarVerticalGraph

jkqtpstatAddHHistogram1DAutoranged() [2/2]

template<class InputIt >

JKQTPBarVerticalGraph * jkqtpstatAddHHistogram1DAutoranged ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, int  bins = 11, bool  normalized = true, bool  cummulative = false, const QString &  histogramcolumnBaseName = QString("histogram")  )

inline

calculate an autoranged histogram and add a JKQTPBarVerticalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their number

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
bins	number of bins in the resulting histogram
histogramcolumnBaseName	this string is used in building the column names for the outlier columns
normalized	indicates whether the histogram has to be normalized
cummulative	if true, a cummulative histogram is calculated

Returns

a graph class pointer (of type GraphClass ) displaying the histogram data

Example:

jkqtpstatAddHHistogram1DAutoranged(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), 11);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatHistogram1DAutoranged(), JKQTPBarVerticalGraph

jkqtpstatAddHistogram2DContour() [1/2]

template<class InputItX , class InputItY >

JKQTPColumnContourPlot * jkqtpstatAddHistogram2DContour ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, double  xbinwidth, double  ybinwidth, bool  normalized = true, const QString &  histogramcolumnBaseName = QString("histogram"), double *  oxmin = nullptr, double *  oxmax = nullptr, double *  oymin = nullptr, double *  oymax = nullptr  )

inline

calculate calculate a 2-dimensional histogram and add a JKQTPColumnContourPlot to the given plotter, where the histogram is calculated from the given data range firstX / firstY ... lastY / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first x-position item in the dataset to use
	lastX	iterator pointing behind the last x-position item in the dataset to use
	firstY	iterator pointing to the first y-position item in the dataset to use
	lastY	iterator pointing behind the last y-position item in the dataset to use
	xbinwidth	width of bins in x-direction
	ybinwidth	width of bins in y-direction
	normalized	indicates whether the histogram has to be normalized
	histogramcolumnBaseName	this string is used in building the column names for the histogram data columns
[out]	oxmin	position of the first histogram bin in x-direction
[out]	oxmax	position of the last histogram bin in x-direction
[out]	oymin	position of the first histogram bin in y-direction
[out]	oymax	position of the last histogram bin in y-direction

Returns

a graph class pointer (of type JKQTPColumnContourPlot ) displaying the histogram data as a contour plot

See also

jkqtpstatHistogram2D(), Tutorial (JKQTPDatastore): Advanced 2-Dimensional Statistics with JKQTPDatastore

jkqtpstatAddHistogram2DContour() [2/2]

template<class InputItX , class InputItY >

JKQTPColumnContourPlot * jkqtpstatAddHistogram2DContour ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, size_t  xbins = 10, size_t  ybins = 10, bool  normalized = true, const QString &  histogramcolumnBaseName = QString("histogram"), double *  oxmin = nullptr, double *  oxmax = nullptr, double *  oymin = nullptr, double *  oymax = nullptr  )

inline

calculate calculate a 2-dimensional histogram and add a JKQTPColumnContourPlot to the given plotter, where the histogram is calculated from the given data range firstX / firstY ... lastY / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first x-position item in the dataset to use
	lastX	iterator pointing behind the last x-position item in the dataset to use
	firstY	iterator pointing to the first y-position item in the dataset to use
	lastY	iterator pointing behind the last y-position item in the dataset to use
	xbins	number of bins in x-direction
	ybins	number of bins in y-direction
	normalized	indicates whether the histogram has to be normalized
	histogramcolumnBaseName	this string is used in building the column names for the histogram data columns
[out]	oxmin	position of the first histogram bin in x-direction
[out]	oxmax	position of the last histogram bin in x-direction
[out]	oymin	position of the first histogram bin in y-direction
[out]	oymax	position of the last histogram bin in y-direction

Returns

a graph class pointer (of type JKQTPColumnContourPlot ) displaying the histogram data as a contour plot

See also

jkqtpstatHistogram2D(), Tutorial (JKQTPDatastore): Advanced 2-Dimensional Statistics with JKQTPDatastore

jkqtpstatAddHistogram2DImage() [1/2]

template<class InputItX , class InputItY >

JKQTPColumnMathImage * jkqtpstatAddHistogram2DImage ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, double  xbinwidth, double  ybinwidth, bool  normalized = true, const QString &  histogramcolumnBaseName = QString("histogram"), double *  oxmin = nullptr, double *  oxmax = nullptr, double *  oymin = nullptr, double *  oymax = nullptr  )

inline

calculate calculate a 2-dimensional histogram and add a JKQTPColumnMathImage to the given plotter, where the histogram is calculated from the given data range firstX / firstY ... lastY / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first x-position item in the dataset to use
	lastX	iterator pointing behind the last x-position item in the dataset to use
	firstY	iterator pointing to the first y-position item in the dataset to use
	lastY	iterator pointing behind the last y-position item in the dataset to use
	xbinwidth	width of bins in x-direction
	ybinwidth	width of bins in y-direction
	normalized	indicates whether the histogram has to be normalized
	histogramcolumnBaseName	this string is used in building the column names for the histogram data columns
[out]	oxmin	position of the first histogram bin in x-direction
[out]	oxmax	position of the last histogram bin in x-direction
[out]	oymin	position of the first histogram bin in y-direction
[out]	oymax	position of the last histogram bin in y-direction

Returns

a graph class pointer (of type JKQTPColumnMathImage ) displaying the histogram data

See also

jkqtpstatHistogram2D(), Tutorial (JKQTPDatastore): Advanced 2-Dimensional Statistics with JKQTPDatastore

jkqtpstatAddHistogram2DImage() [2/2]

template<class InputItX , class InputItY >

JKQTPColumnMathImage * jkqtpstatAddHistogram2DImage ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, size_t  xbins = 10, size_t  ybins = 10, bool  normalized = true, const QString &  histogramcolumnBaseName = QString("histogram"), double *  oxmin = nullptr, double *  oxmax = nullptr, double *  oymin = nullptr, double *  oymax = nullptr  )

inline

calculate calculate a 2-dimensional histogram and add a JKQTPColumnMathImage to the given plotter, where the histogram is calculated from the given data range firstX / firstY ... lastY / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first x-position item in the dataset to use
	lastX	iterator pointing behind the last x-position item in the dataset to use
	firstY	iterator pointing to the first y-position item in the dataset to use
	lastY	iterator pointing behind the last y-position item in the dataset to use
	xbins	number of bins in x-direction
	ybins	number of bins in y-direction
	normalized	indicates whether the histogram has to be normalized
	histogramcolumnBaseName	this string is used in building the column names for the histogram data columns
[out]	oxmin	position of the first histogram bin in x-direction
[out]	oxmax	position of the last histogram bin in x-direction
[out]	oymin	position of the first histogram bin in y-direction
[out]	oymax	position of the last histogram bin in y-direction

Returns

a graph class pointer (of type JKQTPColumnMathImage ) displaying the histogram data

See also

jkqtpstatHistogram2D(), Tutorial (JKQTPDatastore): Advanced 2-Dimensional Statistics with JKQTPDatastore

jkqtpstatAddHKDE1D() [1/2]

template<class InputIt , class BinsInputIt >

JKQTPXYLineGraph * jkqtpstatAddHKDE1D ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, BinsInputIt  binsFirst, BinsInputIt  binsLast, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = 1.0, bool  cummulative = false, const QString &  KDEcolumnBaseName = QString("KDE")  )

inline

calculate an autoranged KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their width

Template Parameters

InputIt	standard iterator type of first and last.
BinsInputIt	standard iterator type of binsFirst and binsLast.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binsFirst	iterator pointing to the first item in the set of KDE bins
binsLast	iterator pointing behind the last item in the set of KDE bins
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE
cummulative	if true, a cummulative KDE is calculated
KDEcolumnBaseName	this string is used in building the column names for the KDE data columns

Returns

a graph class pointer (of type GraphClass ) displaying the KDE data

Example:

std::vector<double> bins{-2,-1.5,-1,-0.75,-0.5,-0.25,0,0.25,0.5,0.75,1,1.5,2,2.5,3,4,5,6,7,8,9,10};
jkqtpstatAddHKDE1D(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), bins.begin(), bins.end());

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatKDE1D(), JKQTPXYLineGraph

jkqtpstatAddHKDE1D() [2/2]

template<class InputIt >

JKQTPXYLineGraph * jkqtpstatAddHKDE1D ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  binXLeft, double  binXDelta, double  binXRight, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = 1.0, bool  cummulative = false, const QString &  KDEcolumnBaseName = QString("KDE")  )

inline

calculate an autoranged KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, evaluation positions are given by the range binXLeft ... binXRight (in steps of binxDelta )

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binXLeft	first x-position, where to evaluate the KDE
binXDelta	distance between two x-positions at which the KDE is evaluated
binXRight	last x-position, where to evaluate the KDE
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE
cummulative	if true, a cummulative KDE is calculated
KDEcolumnBaseName	this string is used in building the column names for the KDE data columns

Returns

a graph class pointer (of type GraphClass ) displaying the KDE data

Example:

std::vector<double> bins{-2,-1.5,-1,-0.75,-0.5,-0.25,0,0.25,0.5,0.75,1,1.5,2,2.5,3,4,5,6,7,8,9,10};
jkqtpstatAddHKDE1D(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), bins.begin(), bins.end());

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatKDE1D(), JKQTPXYLineGraph

jkqtpstatAddHKDE1DAutoranged() [1/2]

template<class InputIt >

JKQTPXYLineGraph * jkqtpstatAddHKDE1DAutoranged ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  binWidth, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = 1.0, bool  cummulative = false, const QString &  KDEcolumnBaseName = QString("KDE")  )

inline

calculate an autoranged KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their width

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binWidth	width of the bins
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE
cummulative	if true, a cummulative KDE is calculated
KDEcolumnBaseName	this string is used in building the column names for the KDE data columns

Returns

a graph class pointer (of type GraphClass ) displaying the KDE data

Example:

jkqtpstatAddHKDE1DAutoranged(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), 0.01);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatKDE1DAutoranged(), JKQTPXYLineGraph

jkqtpstatAddHKDE1DAutoranged() [2/2]

template<class InputIt >

JKQTPXYLineGraph * jkqtpstatAddHKDE1DAutoranged ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, int  Nout = 100, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = 1.0, bool  cummulative = false, const QString &  KDEcolumnBaseName = QString("KDE")  )

inline

calculate an autoranged KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their number

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
Nout	number of points in the resulting KDE
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE
cummulative	if true, a cummulative KDE is calculated
KDEcolumnBaseName	this string is used in building the column names for the KDE data columns

Returns

a graph class pointer (of type GraphClass ) displaying the KDE data

Example:

jkqtpstatAddHKDE1DAutoranged(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), 200);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatKDE1DAutoranged(), JKQTPXYLineGraph

jkqtpstatAddHViolinplotHistogram()

template<class InputIt >

JKQTPViolinplotHorizontalElement * jkqtpstatAddHViolinplotHistogram ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  violinposY, const QString &  distBasename = QString("violin plot distribution"), int  violinDistSamples = 21  )

inline

add a JKQTPViolinplotHorizontalElement to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a histogram as density distribution estimate

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
violinposY	y-coordinate of the Violinplot
distBasename	name basing for added columns
violinDistSamples	number of bin of the distribution (between min and max)

Returns

a Violinplot element with its values initialized from the given data range

Example:

jkqtpstatAddHViolinplotHistogram(plot->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -10);

See also

Example (JKQTPlotter): Violin Plots, JKQTPViolinplotHorizontalElement, jkqtpstatHistogram1DAutoranged()

jkqtpstatAddHViolinplotHistogramAndOutliers()

template<class InputIt >

std::pair< JKQTPViolinplotHorizontalElement *, JKQTPSingleColumnSymbolsGraph * > jkqtpstatAddHViolinplotHistogramAndOutliers ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  violinposY, double  minimumQuantile = 0.03, double  maximumQuantile = 0.97, const QString &  distBasename = QString("violin plot distribution"), int  violinDistSamples = 21  )

inline

add a JKQTPViolinplotHorizontalElement and an outliers graph to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a histogram as density distribution estimate

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
violinposY	y-coordinate of the Violinplot
minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
distBasename	name basing for added columns
violinDistSamples	number of samples of the distribution (between min and max)

Returns

a Violinplot element with its values initialized from the given data range

Example:

jkqtpstatAddHViolinplotHistogramAndOutliers(plot->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -5);

See also

Example (JKQTPlotter): Violin Plots, JKQTPViolinplotHorizontalElement, jkqtpstatHistogram1DAutoranged()

jkqtpstatAddHViolinplotKDE()

template<class InputIt >

JKQTPViolinplotHorizontalElement * jkqtpstatAddHViolinplotKDE ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  violinposY, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = -1, const QString &  distBasename = QString("violin plot distribution"), int  violinDistSamples = 100  )

inline

add a JKQTPViolinplotHorizontalElement to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a kernel density estimate as density distribution estimate

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
violinposY	y-coordinate of the Violinplot
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE, if <0 then jkqtpstatEstimateKDEBandwidth(first,last) is called
distBasename	name basing for added columns
violinDistSamples	number of samples of the distribution (between min and max)

Returns

a Violinplot element with its values initialized from the given data range

Example:

jkqtpstatAddHViolinplotKDE(plot->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -20);

See also

Example (JKQTPlotter): Violin Plots, JKQTPViolinplotHorizontalElement, jkqtpstatKDE1DAutoranged()

jkqtpstatAddHViolinplotKDEAndOutliers()

template<class InputIt >

std::pair< JKQTPViolinplotHorizontalElement *, JKQTPSingleColumnSymbolsGraph * > jkqtpstatAddHViolinplotKDEAndOutliers ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  violinposY, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = -1, double  minimumQuantile = 0.03, double  maximumQuantile = 0.97, const QString &  distBasename = QString("violin plot distribution"), int  violinDistSamples = 100  )

inline

add a JKQTPViolinplotHorizontalElement and an outliers graph to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a kernel density estimate as density distribution estimate

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
violinposY	y-coordinate of the Violinplot
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE, if <0 then jkqtpstatEstimateKDEBandwidth(first,last) is called
minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
distBasename	name basing for added columns
violinDistSamples	number of samples of the distribution (between min and max)

Returns

a Violinplot element with its values initialized from the given data range

Example:

jkqtpstatAddHViolinplotKDEAndOutliers(plot->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -15);

See also

Example (JKQTPlotter): Violin Plots, JKQTPViolinplotHorizontalElement, jkqtpstatKDE1DAutoranged()

jkqtpstatAddKDE2DContour()

template<class InputItX , class InputItY >

JKQTPColumnContourPlot * jkqtpstatAddKDE2DContour ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, size_t  xbins = 10, size_t  ybins = 10, const std::function< double(double, double)> &  kernel = std::function<double(double,double)>(&jkqtpstatKernel2DGaussian), double  bandwidthX = 1.0, double  bandwidthY = 1.0, const QString &  kdecolumnBaseName = QString("histogram"), double *  oxmin = nullptr, double *  oxmax = nullptr, double *  oymin = nullptr, double *  oymax = nullptr  )

inline

calculate calculate a 2-dimensional kernel density estimate (KDE) and add a JKQTPColumnContourPlot to the given plotter, where the KDE is calculated from the given data range firstX / firstY ... lastY / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first x-position item in the dataset to use
	lastX	iterator pointing behind the last x-position item in the dataset to use
	firstY	iterator pointing to the first y-position item in the dataset to use
	lastY	iterator pointing behind the last y-position item in the dataset to use
	xbins	number of bins in x-direction (i.e. width of the output KDE)
	ybins	number of bins in y-direction (i.e. height of the output KDE)
	kernel	the kernel function to use (e.g. jkqtpstatKernel2DGaussian() )
	bandwidthX	x-bandwidth used for the KDE
	bandwidthY	y-bandwidth used for the KDE
	kdecolumnBaseName	this string is used in building the column names for the KDE data columns
[out]	oxmin	position of the first KDE bin in x-direction
[out]	oxmax	position of the last KDE bin in x-direction
[out]	oymin	position of the first KDE bin in y-direction
[out]	oymax	position of the last KDE bin in y-direction

Returns

a graph class pointer (of type JKQTPColumnContourPlot ) displaying the KDE data as a contour plot

See also

jkqtpstatKDE2D(), Tutorial (JKQTPDatastore): Advanced 2-Dimensional Statistics with JKQTPDatastore

jkqtpstatAddKDE2DImage()

template<class InputItX , class InputItY >

JKQTPColumnMathImage * jkqtpstatAddKDE2DImage ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, size_t  xbins = 10, size_t  ybins = 10, const std::function< double(double, double)> &  kernel = std::function<double(double,double)>(&jkqtpstatKernel2DGaussian), double  bandwidthX = 1.0, double  bandwidthY = 1.0, const QString &  kdecolumnBaseName = QString("histogram"), double *  oxmin = nullptr, double *  oxmax = nullptr, double *  oymin = nullptr, double *  oymax = nullptr  )

inline

calculate calculate a 2-dimensional kernel density estimate (KDE) and add a JKQTPColumnMathImage to the given plotter, where the KDE is calculated from the given data range firstX / firstY ... lastY / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first x-position item in the dataset to use
	lastX	iterator pointing behind the last x-position item in the dataset to use
	firstY	iterator pointing to the first y-position item in the dataset to use
	lastY	iterator pointing behind the last y-position item in the dataset to use
	xbins	number of bins in x-direction (i.e. width of the output KDE)
	ybins	number of bins in y-direction (i.e. height of the output KDE)
	kernel	the kernel function to use (e.g. jkqtpstatKernel2DGaussian() )
	bandwidthX	x-bandwidth used for the KDE
	bandwidthY	y-bandwidth used for the KDE
	kdecolumnBaseName	this string is used in building the column names for the KDE data columns
[out]	oxmin	position of the first KDE bin in x-direction
[out]	oxmax	position of the last KDE bin in x-direction
[out]	oymin	position of the first KDE bin in y-direction
[out]	oymax	position of the last KDE bin in y-direction

Returns

a graph class pointer (of type JKQTPColumnMathImage ) displaying the KDE data

See also

jkqtpstatKDE2D(), Tutorial (JKQTPDatastore): Advanced 2-Dimensional Statistics with JKQTPDatastore

jkqtpstatAddLinearRegression() [1/2]

template<class InputItX , class InputItY >

JKQTPXFunctionLineGraph * jkqtpstatAddLinearRegression ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, double *  coeffA = nullptr, double *  coeffB = nullptr, bool  fixA = false, bool  fixB = false  )

inline

calculate the linear regression coefficients for a given data range firstX / firstY ... lastX / lastY where the model is

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first item in the x-dataset to use
	lastX	iterator pointing behind the last item in the x-dataset to use
	firstY	iterator pointing to the first item in the y-dataset to use
	lastY	iterator pointing behind the last item in the y-dataset to use
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Example:

jkqtpstatAddLinearRegression(plot1->getPlotter(), datastore1->begin(colLinX), datastore1->end(colLinX), datastore1->begin(colLinY), datastore1->end(colLinY));

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatLinearRegression()

jkqtpstatAddLinearRegression() [2/2]

JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph * jkqtpstatAddLinearRegression	(	JKQTPXYGraph *	datagraph,
		double *	coeffA = nullptr,
		double *	coeffB = nullptr,
		bool	fixA = false,
		bool	fixB = false
	)

calculate the linear regression coefficients for a given data data used to draw any JKQTPXYGraph datagraph where the model is

Parameters

	datagraph	graph representing the (x,y) datapairs to which to fit the regression line
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Example:

JKQTPXYLineGraph* graphD;
plot1->addGraph(graphD=new JKQTPXYLineGraph(plot1));
graphD->setXYColumns(colLinX, colLinY);
jkqtpstatAddLinearRegression(graphD);

Note

The line graph is added to the same plotter that is the parent of datagraph !

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatLinearRegression()

jkqtpstatAddLinearWeightedRegression() [1/2]

template<class InputItX , class InputItY , class InputItW >

JKQTPXFunctionLineGraph * jkqtpstatAddLinearWeightedRegression ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, InputItW  firstW, InputItW  lastW, double *  coeffA = nullptr, double *  coeffB = nullptr, bool  fixA = false, bool  fixB = false, std::function< double(double)>  fWeightDataToWi = &jkqtp_identity<double>  )

inline

calculate the weighted linear regression coefficients for a given for a given data range firstX / firstY / firstW ... lastX / lastY / lastW where the model is

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.
InputItW	standard iterator type of firstW and lastW.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first item in the x-dataset to use
	lastX	iterator pointing behind the last item in the x-dataset to use
	firstY	iterator pointing to the first item in the y-dataset to use
	lastY	iterator pointing behind the last item in the y-dataset to use
	firstW	iterator pointing to the first item in the weight-dataset to use
	lastW	iterator pointing behind the last item in the weight-dataset to use
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Parameters

fWeightDataToWi

an optional function, which is applied to the data from firstW ... lastW to convert them to weight, i.e. wi=fWeightDataToWi(*itW) e.g. if you use data used to draw error bars, you can use jkqtp_inversePropSaveDefault(). The default is jkqtp_identity(), which just returns the values. In the case of jkqtp_inversePropSaveDefault(), a datapoint x,y, has a large weight, if it's error is small and in the case if jkqtp_identity() it's weight is directly proportional to the given value.

Example:

double coeffA=0, coeffB=0;
jkqtpstatLinearWeightedRegression(datastore1->begin(colWLinX), datastore1->end(colWLinX),
                                  datastore1->begin(colWLinY), datastore1->end(colWLinY),
                                  datastore1->begin(colWLinE), datastore1->end(colWLinE),
                                  coeffA, coeffB, false, false,
                                  &jkqtp_inversePropSaveDefault<double>);

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatLinearRegression()

jkqtpstatAddLinearWeightedRegression() [2/2]

JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph * jkqtpstatAddLinearWeightedRegression	(	JKQTPXYGraph *	datagraph,
		double *	coeffA = nullptr,
		double *	coeffB = nullptr,
		bool	fixA = false,
		bool	fixB = false
	)

calculate the linear weighted regression coefficients for a given data data used to draw any JKQTPXYGraph datagraph , which also implements JKQTPYGraphErrorData and where the model is

Parameters

	datagraph	graph representing the (x,y,error) data triples to which to fit the regression line The errors are used as iverse weights!
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Example:

JKQTPXYLineErrorGraph* graphD;
plot1->addGraph(graphD=new JKQTPXYLineErrorGraph(plot1));
graphD->setXYColumns(colLinX, colLinY);
graphD->setYErrorColumn(static_cast<int>(colWLinE));
jkqtpstatAddLinearWeightedRegression(graphD);

Note

The line graph is added to the same plotter that is the parent of datagraph !

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatLinearRegression()

jkqtpstatAddPolyFit() [1/4]

template<class InputItX , class InputItY >

JKQTPXFunctionLineGraph * jkqtpstatAddPolyFit ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, size_t  P  )

inline

fits (in a least-squares sense) a polynomial of order P to a set of N data pairs from a given data range firstX / firstY ... lastX / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

plotter	the plotter to which to add the resulting graph
firstX	iterator pointing to the first item in the x-dataset to use
lastX	iterator pointing behind the last item in the x-dataset to use
firstY	iterator pointing to the first item in the y-dataset to use
lastY	iterator pointing behind the last item in the y-dataset to use
P	degree of the polynomial (P>=N !!!)

Example:

jkqtpstatAddPolyFit(plot1->getPlotter(), JKQTPStatRegressionModelType::Exponential, datastore1->begin(colLinX), datastore1->end(colLinX), datastore1->begin(colLinY), datastore1->end(colLinY), 3);

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatPolyFit()

jkqtpstatAddPolyFit() [2/4]

template<class InputItX , class InputItY , class OutputItP >

JKQTPXFunctionLineGraph * jkqtpstatAddPolyFit ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, size_t  P, OutputItP  firstRes  )

inline

fits (in a least-squares sense) a polynomial of order P to a set of N data pairs from a given data range firstX / firstY ... lastX / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.
OutputItP	output iterator for the polynomial coefficients

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first item in the x-dataset to use
	lastX	iterator pointing behind the last item in the x-dataset to use
	firstY	iterator pointing to the first item in the y-dataset to use
	lastY	iterator pointing behind the last item in the y-dataset to use
	P	degree of the polynomial (P>=N !!!)
[out]	firstRes	Iterator (of type OutputItP ), which receives the (P+1)-entry vector with the polynomial coefficients

Example:

std::vector<double> pFit;
jkqtpstatAddPolyFit(plot1->getPlotter(), JKQTPStatRegressionModelType::Exponential, datastore1->begin(colLinX), datastore1->end(colLinX), datastore1->begin(colLinY), datastore1->end(colLinY), 3, std::back_inserter(pFit));

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatPolyFit()

jkqtpstatAddPolyFit() [3/4]

JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph * jkqtpstatAddPolyFit	(	JKQTPXYGraph *	datagraph,
		size_t	P
	)

fits (in a least-squares sense) a polynomial of order P to a set of N data pairs from a given JKQTPXYGraph datagraph

Parameters

datagraph	graph representing the (x,y) datapairs to which to fit the regression line
P	degree of the polynomial (P>=N !!!)

Example:

JKQTPXYLineGraph* graphD;
plot1->addGraph(graphD=new JKQTPXYLineGraph(plot1));
graphD->setXYColumns(colLinX, colLinY);
jkqtpstatAddPolyFit(graphD, 3);

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatPolyFit()

jkqtpstatAddPolyFit() [4/4]

template<class OutputItP >

JKQTPXFunctionLineGraph * jkqtpstatAddPolyFit ( JKQTPXYGraph *  datagraph, size_t  P, OutputItP  firstRes  )

inline

fits (in a least-squares sense) a polynomial of order P to a set of N data pairs from a given JKQTPXYGraph datagraph

Template Parameters

OutputItP

output iterator for the polynomial coefficients

Parameters

	datagraph	graph representing the (x,y) datapairs to which to fit the regression line
	P	degree of the polynomial (P>=N !!!)
[out]	firstRes	Iterator (of type OutputItP ), which receives the (P+1)-entry vector with the polynomial coefficients

Example:

JKQTPXYLineGraph* graphD;
plot1->addGraph(graphD=new JKQTPXYLineGraph(plot1));
graphD->setXYColumns(colLinX, colLinY);
std::vector<double> pFit;
jkqtpstatAddPolyFit(graphD, 3,std::back_inserter(pFit));

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatPolyFit()

jkqtpstatAddRegression()

template<class InputItX , class InputItY >

JKQTPXFunctionLineGraph * jkqtpstatAddRegression ( JKQTBasePlotter *  plotter, JKQTPStatRegressionModelType  type, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, double *  coeffA = nullptr, double *  coeffB = nullptr, bool  fixA = false, bool  fixB = false  )

inline

calculate the linear regression coefficients for a given data range firstX / firstY ... lastX / lastY where the model is defined by type

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	type	model to be fitted
	firstX	iterator pointing to the first item in the x-dataset to use
	lastX	iterator pointing behind the last item in the x-dataset to use
	firstY	iterator pointing to the first item in the y-dataset to use
	lastY	iterator pointing behind the last item in the y-dataset to use
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Example:

jkqtpstatRegression(plot1->getPlotter(), JKQTPStatRegressionModelType::Exponential, datastore1->begin(colLinX), datastore1->end(colLinX), datastore1->begin(colLinY), datastore1->end(colLinY));

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatRegression()

jkqtpstatAddRobustIRLSLinearRegression() [1/2]

template<class InputItX , class InputItY >

JKQTPXFunctionLineGraph * jkqtpstatAddRobustIRLSLinearRegression ( JKQTBasePlotter *  plotter, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, double *  coeffA = nullptr, double *  coeffB = nullptr, bool  fixA = false, bool  fixB = false, double  p = 1.1, int  iterations = 100  )

inline

calculate the (robust) iteratively reweighted least-squares (IRLS) estimate for the parameters of the model for a given data range firstX / firstY ... lastX / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	firstX	iterator pointing to the first item in the x-dataset to use
	lastX	iterator pointing behind the last item in the x-dataset to use
	firstY	iterator pointing to the first item in the y-dataset to use
	lastY	iterator pointing behind the last item in the y-dataset to use
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Parameters

p	regularization parameter, the optimization problem is formulated in the norm, using this p (see image below for an example)
iterations	the number of iterations the IRLS algorithm performs

Example:

jkqtpstatAddRobustIRLSLinearRegression(plot1->getPlotter(), datastore1->begin(colLinX), datastore1->end(colLinX), datastore1->begin(colLinY), datastore1->end(colLinY));

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatRobustIRLSLinearRegression()

jkqtpstatAddRobustIRLSLinearRegression() [2/2]

JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph * jkqtpstatAddRobustIRLSLinearRegression	(	JKQTPXYGraph *	datagraph,
		double *	coeffA = nullptr,
		double *	coeffB = nullptr,
		bool	fixA = false,
		bool	fixB = false,
		double	p = 1.1,
		int	iterations = 100
	)

calculate the (robust) iteratively reweighted least-squares (IRLS) estimate for the parameters of the model for a given data range firstX / firstY ... lastX / lastY

Parameters

	datagraph	graph representing the (x,y) datapairs to which to fit the regression line
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Parameters

p	regularization parameter, the optimization problem is formulated in the norm, using this p (see image below for an example)
iterations	the number of iterations the IRLS algorithm performs

Example:

JKQTPXYLineGraph* graphD;
plot1->addGraph(graphD=new JKQTPXYLineGraph(plot1));
graphD->setXYColumns(colLinX, colLinY);
jkqtpstatAddRobustIRLSLinearRegression(graphD);

Note

The line graph is added to the same plotter that is the parent of datagraph !

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatRobustIRLSLinearRegression()

jkqtpstatAddRobustIRLSRegression() [1/2]

template<class InputItX , class InputItY >

JKQTPXFunctionLineGraph * jkqtpstatAddRobustIRLSRegression ( JKQTBasePlotter *  plotter, JKQTPStatRegressionModelType  type, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, double *  coeffA = nullptr, double *  coeffB = nullptr, bool  fixA = false, bool  fixB = false, double  p = 1.1, int  iterations = 100  )

inline

calculate the (robust) iteratively reweighted least-squares (IRLS) estimate for the parameters where the model is defined by type for a given data range firstX / firstY ... lastX / lastY

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.

Parameters

	plotter	the plotter to which to add the resulting graph
	type	model to be fitted
	firstX	iterator pointing to the first item in the x-dataset to use
	lastX	iterator pointing behind the last item in the x-dataset to use
	firstY	iterator pointing to the first item in the y-dataset to use
	lastY	iterator pointing behind the last item in the y-dataset to use
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Parameters

p	regularization parameter, the optimization problem is formulated in the norm, using this p (see image below for an example)
iterations	the number of iterations the IRLS algorithm performs

Example:

jkqtpstatAddRobustIRLSRegression(plot1->getPlotter(), JKQTPStatRegressionModelType::Exponential, datastore1->begin(colLinX), datastore1->end(colLinX), datastore1->begin(colLinY), datastore1->end(colLinY));

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatRobustIRLSRegression()

jkqtpstatAddRobustIRLSRegression() [2/2]

JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph * jkqtpstatAddRobustIRLSRegression	(	JKQTPXYGraph *	datagraph,
		JKQTPStatRegressionModelType	type,
		double *	coeffA = nullptr,
		double *	coeffB = nullptr,
		bool	fixA = false,
		bool	fixB = false,
		double	p = 1.1,
		int	iterations = 100
	)

calculate the (robust) iteratively reweighted least-squares (IRLS) estimate for the parameters where the model is defined by type for a given data range firstX / firstY ... lastX / lastY

Parameters

	datagraph	graph representing the (x,y) datapairs to which to fit the regression line
	type	model to be fitted
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Parameters

p	regularization parameter, the optimization problem is formulated in the norm, using this p (see image below for an example)
iterations	the number of iterations the IRLS algorithm performs

Example:

JKQTPXYLineGraph* graphD;
plot1->addGraph(graphD=new JKQTPXYLineGraph(plot1));
graphD->setXYColumns(colLinX, colLinY);
jkqtpstatAddRobustIRLSRegression(graphD, JKQTPStatRegressionModelType::Exponential);

Note

The line graph is added to the same plotter that is the parent of datagraph !

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatRobustIRLSRegression()

jkqtpstatAddVBoxplot()

template<class InputIt >

JKQTPBoxplotVerticalElement * jkqtpstatAddVBoxplot ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  boxposX, double  quantile1Spec = 0.25, double  quantile2Spec = 0.75, double  minimumQuantile = 0, double  maximumQuantile = 1.0, JKQTPStat5NumberStatistics *  statOutput = nullptr  )

inline

add a JKQTPBoxplotVerticalElement to the given plotter, where the boxplot values are calculated from the data range first ... last

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

	plotter	the plotter to which to add the resulting graph
	first	iterator pointing to the first item in the dataset to use
	last	iterator pointing behind the last item in the dataset to use
	boxposX	x-coordinate of the boxplot
	quantile1Spec	specifies which quantile to calculate for qantile1 (range: 0..1)
	quantile2Spec	specifies which quantile to calculate for qantile2 (range: 0..1)
	minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
	maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
[out]	statOutput	optionally returns the internally calculated statistics as a JKQTPStat5NumberStatistics

Returns

a boxplot element with its values initialized from the given data range

Example:

jkqtpstatAddVBoxplot(plot1->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -0.3);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstat5NumberStatistics()

jkqtpstatAddVBoxplotAndOutliers()

template<class InputIt >

std::pair< JKQTPBoxplotVerticalElement *, JKQTPSingleColumnSymbolsGraph * > jkqtpstatAddVBoxplotAndOutliers ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  boxposX, double  quantile1Spec = 0.25, double  quantile2Spec = 0.75, double  minimumQuantile = 0.03, double  maximumQuantile = 0.97, const QString &  outliercolumnBaseName = QString("boxplot"), JKQTPStat5NumberStatistics *  statOutput = nullptr  )

inline

add a JKQTPBoxplotVerticalElement and a JKQTPSingleColumnSymbolsGraph for outliers to the given plotter, where the boxplot values are calculated from the data range first ... last

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

	plotter	the plotter to which to add the resulting graph
	first	iterator pointing to the first item in the dataset to use
	last	iterator pointing behind the last item in the dataset to use
	boxposX	x-coordinate of the outliers (and the boxplot)
	quantile1Spec	specifies which quantile to calculate for qantile1 (range: 0..1)
	quantile2Spec	specifies which quantile to calculate for qantile2 (range: 0..1)
	minimumQuantile	specifies a quantile for the return value minimum (default is 0.03, i.e. the 3% quantile!)
	maximumQuantile	specifies a quantile for the return value maximum (default is 0.97, i.e. the 97% quantile!)
	outliercolumnBaseName	this string is used in building the column names for the outlier columns
[out]	statOutput	optionally returns the internally calculated statistics as a JKQTPStat5NumberStatistics

Returns

a boxplot element with its values initialized from the given data range

Example:

jkqtpstatAddVBoxplotAndOutliers(plot1->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -0.3);
jkqtpstatAddVBoxplotAndOutliers(plot1->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -0.3,
                                0.25, 0.75, // 1. and 3. Quartile for the boxplot box
                                0.05, 0.95 // Quantiles for the boxplot box whiskers' ends

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstat5NumberStatistics()

jkqtpstatAddVBoxplotsAndOutliers()

template<class InputCatIt , class InputValueIt >

std::pair< JKQTPBoxplotVerticalGraph *, JKQTPXYLineGraph * > jkqtpstatAddVBoxplotsAndOutliers ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, double  quantile1Spec = 0.25, double  quantile2Spec = 0.75, double  minimumQuantile = 0.03, double  maximumQuantile = 0.97, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped boxplot data")  )

inline

create vertical boxplots of type JKQTPBoxplotVerticalGraph, from the 5-value-summary of groups in the input data, also adds a graph showing the outliers

Template Parameters

InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
quantile1Spec	specifies which quantile to calculate for qantile1 (range: 0..1)
quantile2Spec	specifies which quantile to calculate for qantile2 (range: 0..1)
minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the boxplot graph (return.first) and the outliers graph (return.second)

See also

jkqtpstatGroupData(), Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddVHistogram1D()

template<class InputIt , class BinsInputIt >

JKQTPBarHorizontalGraph * jkqtpstatAddVHistogram1D ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, BinsInputIt  binsFirst, BinsInputIt  binsLast, bool  normalized = true, bool  cummulative = false, const QString &  histogramcolumnBaseName = QString("histogram")  )

inline

calculate an autoranged histogram and add a JKQTPBarHorizontalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their width

Template Parameters

InputIt	standard iterator type of first and last.
BinsInputIt	standard iterator type of binsFirst and binsLast.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binsFirst	iterator pointing to the first item in the set of histogram bins
binsLast	iterator pointing behind the last item in the set of histogram bins
histogramcolumnBaseName	this string is used in building the column names for the histogram columns
normalized	indicates whether the histogram has to be normalized
cummulative	if true, a cummulative histogram is calculated

Returns

a graph class pointer (of type GraphClass ) displaying the histogram data

Example:

std::vector<double> bins{-2,-1.5,-1,-0.75,-0.5,-0.25,0,0.25,0.5,0.75,1,1.5,2,2.5,3,4,5,6,7,8,9,10};
jkqtpstatAddVHistogram1D(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), bins.begin(), bins.end());

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatHistogram1D(), JKQTPBarHorizontalGraph

jkqtpstatAddVHistogram1DAutoranged() [1/2]

template<class InputIt >

JKQTPBarHorizontalGraph * jkqtpstatAddVHistogram1DAutoranged ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  binWidth, bool  normalized = true, bool  cummulative = false, const QString &  histogramcolumnBaseName = QString("histogram")  )

inline

calculate an autoranged histogram and add a JKQTPBarHorizontalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their width

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binWidth	width of the bins
histogramcolumnBaseName	this string is used in building the column names for the histogram columns
normalized	indicates whether the histogram has to be normalized
cummulative	if true, a cummulative histogram is calculated

Returns

a graph class pointer (of type GraphClass ) displaying the histogram data

Example:

jkqtpstatAddVHistogram1DAutoranged(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), 0.5);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatHistogram1DAutoranged(), JKQTPBarHorizontalGraph

jkqtpstatAddVHistogram1DAutoranged() [2/2]

template<class InputIt >

JKQTPBarHorizontalGraph * jkqtpstatAddVHistogram1DAutoranged ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, int  bins = 11, bool  normalized = true, bool  cummulative = false, const QString &  histogramcolumnBaseName = QString("histogram")  )

inline

calculate an autoranged histogram and add a JKQTPBarHorizontalGraph to the given plotter, where the histogram is calculated from the data range first ... last, bins defined by their number

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
bins	number of bins in the resulting histogram
histogramcolumnBaseName	this string is used in building the column names for the histogram columns
normalized	indicates whether the histogram has to be normalized
cummulative	if true, a cummulative histogram is calculated

Returns

a graph class pointer (of type GraphClass ) displaying the histogram data

Example:

jkqtpstatAddVHistogram1DAutoranged(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), 11);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatHistogram1DAutoranged(), JKQTPBarHorizontalGraph

jkqtpstatAddVKDE1D() [1/2]

template<class InputIt , class BinsInputIt >

JKQTPXYLineGraph * jkqtpstatAddVKDE1D ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, BinsInputIt  binsFirst, BinsInputIt  binsLast, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = 1.0, bool  cummulative = false, const QString &  KDEcolumnBaseName = QString("KDE")  )

inline

calculate an autoranged vertical KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their width

Template Parameters

InputIt	standard iterator type of first and last.
BinsInputIt	standard iterator type of binsFirst and binsLast.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binsFirst	iterator pointing to the first item in the set of KDE bins
binsLast	iterator pointing behind the last item in the set of KDE bins
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE
cummulative	if true, a cummulative KDE is calculated
KDEcolumnBaseName	this string is used in building the column names for the KDE data columns

Returns

a graph class pointer (of type GraphClass ) displaying the KDE data

Example:

std::vector<double> bins{-2,-1.5,-1,-0.75,-0.5,-0.25,0,0.25,0.5,0.75,1,1.5,2,2.5,3,4,5,6,7,8,9,10};
jkqtpstatAddVKDE1D(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), bins.begin(), bins.end());

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatKDE1D(), JKQTPXYLineGraph

jkqtpstatAddVKDE1D() [2/2]

template<class InputIt >

JKQTPXYLineGraph * jkqtpstatAddVKDE1D ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  binXLeft, double  binXDelta, double  binXRight, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = 1.0, bool  cummulative = false, const QString &  KDEcolumnBaseName = QString("KDE")  )

inline

calculate an autoranged vertical KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, evaluation positions are given by the range binXLeft ... binXRight (in steps of binxDelta )

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binXLeft	first x-position, where to evaluate the KDE
binXDelta	distance between two x-positions at which the KDE is evaluated
binXRight	last x-position, where to evaluate the KDE
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE
cummulative	if true, a cummulative KDE is calculated
KDEcolumnBaseName	this string is used in building the column names for the KDE data columns

Returns

a graph class pointer (of type GraphClass ) displaying the KDE data

Example:

std::vector<double> bins{-2,-1.5,-1,-0.75,-0.5,-0.25,0,0.25,0.5,0.75,1,1.5,2,2.5,3,4,5,6,7,8,9,10};
jkqtpstatAddVKDE1D(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), bins.begin(), bins.end());

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatKDE1D(), JKQTPXYLineGraph

jkqtpstatAddVKDE1DAutoranged() [1/2]

template<class InputIt >

JKQTPXYLineGraph * jkqtpstatAddVKDE1DAutoranged ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  binWidth, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = 1.0, bool  cummulative = false, const QString &  KDEcolumnBaseName = QString("KDE")  )

inline

calculate an autoranged vertical KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their width

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
binWidth	width of the bins
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE
cummulative	if true, a cummulative KDE is calculated
KDEcolumnBaseName	this string is used in building the column names for the KDE data columns

Returns

a graph class pointer (of type GraphClass ) displaying the KDE data

Example:

jkqtpstatAddVKDE1DAutoranged(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), 0.01);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatKDE1DAutoranged(), JKQTPXYLineGraph

jkqtpstatAddVKDE1DAutoranged() [2/2]

template<class InputIt >

JKQTPXYLineGraph * jkqtpstatAddVKDE1DAutoranged ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, int  Nout = 100, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = 1.0, bool  cummulative = false, const QString &  KDEcolumnBaseName = QString("KDE")  )

inline

calculate an autoranged vertical KDE and add a JKQTPXYLineGraph to the given plotter, where the KDE is calculated from the data range first ... last, bins defined by their number

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
Nout	number of points in the resulting KDE
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE
cummulative	if true, a cummulative KDE is calculated
KDEcolumnBaseName	this string is used in building the column names for the KDE data columns

Returns

a graph class pointer (of type GraphClass ) displaying the KDE data

Example:

jkqtpstatAddVKDE1DAutoranged(plot1->getPlotter(),  datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), 200);

See also

Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore, jkqtpstatKDE1DAutoranged(), JKQTPXYLineGraph

jkqtpstatAddVViolinplotHistogram()

template<class InputIt >

JKQTPViolinplotVerticalElement * jkqtpstatAddVViolinplotHistogram ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  violinposY, const QString &  distBasename = QString("violin plot distribution"), int  violinDistSamples = 21  )

inline

add a JKQTPViolinplotVerticalElement to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a histogram as density distribution estimate

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
violinposY	y-coordinate of the Violinplot
distBasename	name basing for added columns
violinDistSamples	number of bin of the distribution (between min and max)

Returns

a Violinplot element with its values initialized from the given data range

Example:

jkqtpstatAddVViolinplotHistogram(plot->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -10);

See also

Example (JKQTPlotter): Violin Plots, JKQTPViolinplotVerticalElement, jkqtpstatHistogram1DAutoranged()

jkqtpstatAddVViolinplotHistogramAndOutliers()

template<class InputIt >

std::pair< JKQTPViolinplotVerticalElement *, JKQTPSingleColumnSymbolsGraph * > jkqtpstatAddVViolinplotHistogramAndOutliers ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  violinposY, double  minimumQuantile = 0.03, double  maximumQuantile = 0.97, const QString &  distBasename = QString("violin plot distribution"), int  violinDistSamples = 21  )

inline

add a JKQTPViolinplotVerticalElement and an outliers graph to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a histogram as density distribution estimate

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
violinposY	y-coordinate of the Violinplot
minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
distBasename	name basing for added columns
violinDistSamples	number of samples of the distribution (between min and max)

Returns

a Violinplot element with its values initialized from the given data range

Example:

jkqtpstatAddVViolinplotHistogramAndOutliers(plot->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -5);

See also

Example (JKQTPlotter): Violin Plots, JKQTPViolinplotVerticalElement, jkqtpstatHistogram1DAutoranged()

jkqtpstatAddVViolinplotKDE()

template<class InputIt >

JKQTPViolinplotVerticalElement * jkqtpstatAddVViolinplotKDE ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  violinposY, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = -1, const QString &  distBasename = QString("violin plot distribution"), int  violinDistSamples = 100  )

inline

add a JKQTPViolinplotVerticalElement to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a kernel density estimate as density distribution estimate

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
violinposY	y-coordinate of the Violinplot
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE, if <0 then jkqtpstatEstimateKDEBandwidth(first,last) is called
distBasename	name basing for added columns
violinDistSamples	number of samples of the distribution (between min and max)

Returns

a Violinplot element with its values initialized from the given data range

Example:

jkqtpstatAddVViolinplotKDE(plot->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -20);

See also

Example (JKQTPlotter): Violin Plots, JKQTPViolinplotVerticalElement, jkqtpstatKDE1DAutoranged()

jkqtpstatAddVViolinplotKDEAndOutliers()

template<class InputIt >

std::pair< JKQTPViolinplotVerticalElement *, JKQTPSingleColumnSymbolsGraph * > jkqtpstatAddVViolinplotKDEAndOutliers ( JKQTBasePlotter *  plotter, InputIt  first, InputIt  last, double  violinposY, const std::function< double(double)> &  kernel = std::function<double(double)>(&jkqtpstatKernel1DGaussian), double  bandwidth = -1, double  minimumQuantile = 0.03, double  maximumQuantile = 0.97, const QString &  distBasename = QString("violin plot distribution"), int  violinDistSamples = 100  )

inline

add a JKQTPViolinplotVerticalElement and an outliers graph to the given plotter, where the Violinplot values are calculated from the data range first ... last , uses a kernel density estimate as density distribution estimate

Template Parameters

InputIt

standard iterator type of first and last.

Parameters

plotter	the plotter to which to add the resulting graph
first	iterator pointing to the first item in the dataset to use
last	iterator pointing behind the last item in the dataset to use
violinposY	y-coordinate of the Violinplot
kernel	the kernel function to use (e.g. jkqtpstatKernel1DGaussian() )
bandwidth	bandwidth used for the KDE, if <0 then jkqtpstatEstimateKDEBandwidth(first,last) is called
minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
distBasename	name basing for added columns
violinDistSamples	number of samples of the distribution (between min and max)

Returns

a Violinplot element with its values initialized from the given data range

Example:

jkqtpstatAddVViolinplotKDEAndOutliers(plot->getPlotter(), datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1), -15);

See also

Example (JKQTPlotter): Violin Plots, JKQTPViolinplotVerticalElement, jkqtpstatKDE1DAutoranged()

jkqtpstatAddWeightedRegression() [1/2]

template<class InputItX , class InputItY , class InputItW >

JKQTPXFunctionLineGraph * jkqtpstatAddWeightedRegression ( JKQTBasePlotter *  plotter, JKQTPStatRegressionModelType  type, InputItX  firstX, InputItX  lastX, InputItY  firstY, InputItY  lastY, InputItW  firstW, InputItW  lastW, double *  coeffA = nullptr, double *  coeffB = nullptr, bool  fixA = false, bool  fixB = false, std::function< double(double)>  fWeightDataToWi = &jkqtp_identity<double>  )

inline

calculate the weighted linear regression coefficients for a given for a given data range firstX / firstY / firstW ... lastX / lastY / lastW where the model is defined by type

Template Parameters

InputItX	standard iterator type of firstX and lastX.
InputItY	standard iterator type of firstY and lastY.
InputItW	standard iterator type of firstW and lastW.

Parameters

	plotter	the plotter to which to add the resulting graph
	type	model to be fitted
	firstX	iterator pointing to the first item in the x-dataset to use
	lastX	iterator pointing behind the last item in the x-dataset to use
	firstY	iterator pointing to the first item in the y-dataset to use
	lastY	iterator pointing behind the last item in the y-dataset to use
	firstW	iterator pointing to the first item in the weight-dataset to use
	lastW	iterator pointing behind the last item in the weight-dataset to use
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Parameters

fWeightDataToWi

an optional function, which is applied to the data from firstW ... lastW to convert them to weight, i.e. wi=fWeightDataToWi(*itW) e.g. if you use data used to draw error bars, you can use jkqtp_inversePropSaveDefault(). The default is jkqtp_identity(), which just returns the values. In the case of jkqtp_inversePropSaveDefault(), a datapoint x,y, has a large weight, if it's error is small and in the case if jkqtp_identity() it's weight is directly proportional to the given value.

Example:

double coeffA=0, coeffB=0;
jkqtpstatAddWeightedRegression(plotter, JKQTPStatRegressionModelType::Exponential,
                                  datastore1->begin(colWLinX), datastore1->end(colWLinX),
                                  datastore1->begin(colWLinY), datastore1->end(colWLinY),
                                  datastore1->begin(colWLinE), datastore1->end(colWLinE),
                                  coeffA, coeffB, false, false,
                                  &jkqtp_inversePropSaveDefault<double>);

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatWeightedRegression()

jkqtpstatAddWeightedRegression() [2/2]

JKQTPLOTTER_LIB_EXPORT JKQTPXFunctionLineGraph * jkqtpstatAddWeightedRegression	(	JKQTPXYGraph *	datagraph,
		JKQTPStatRegressionModelType	type,
		double *	coeffA = nullptr,
		double *	coeffB = nullptr,
		bool	fixA = false,
		bool	fixB = false
	)

calculate the linear weighted regression coefficients for a given data data used to draw any JKQTPXYGraph datagraph , which also implements JKQTPYGraphErrorData and where the model is defined by type

Parameters

	datagraph	graph representing the (x,y,error) data triples to which to fit the regression line The errors are used as iverse weights!
	type	model to be fitted
[in,out]	coeffA	returns the offset of the linear model
[in,out]	coeffB	returns the slope of the linear model
	fixA	if true, the offset coefficient is not determined by the fit, but the value provided in coeffA is used

Note

If fixA ==true, You need to provide a value for A in coeffA

Parameters

fixB	if true, the slope coefficient is not determined by the fit, but the value provided in coeffB is used

Note

If fixB ==true, You need to provide a value for B in coeffB

Example:

JKQTPXYLineErrorGraph* graphD;
plot1->addGraph(graphD=new JKQTPXYLineErrorGraph(plot1));
graphD->setXYColumns(colLinX, colLinY);
graphD->setYErrorColumn(static_cast<int>(colWLinE));
jkqtpstatAddWeightedRegression(graphD, JKQTPStatRegressionModelType::Exponential);

Note

The line graph is added to the same plotter that is the parent of datagraph !

See also

Tutorial (JKQTPDatastore): Regression Analysis (with the Statistics Library), jkqtpstatWeightedRegression()

jkqtpstatAddXErrorBarGraph()

template<class InputCatIt , class InputValueIt >

JKQTPBarHorizontalErrorGraph * jkqtpstatAddXErrorBarGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPBarHorizontalErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPBarHorizontalErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddXErrorFilledCurveGraph()

template<class InputCatIt , class InputValueIt >

JKQTPFilledCurveXErrorGraph * jkqtpstatAddXErrorFilledCurveGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPFilledCurveXErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPFilledCurveXErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddXErrorGraph()

template<class InputCatIt , class InputValueIt , class TGraph >

TGraph * jkqtpstatAddXErrorGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a plot with x-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

TGraph	type of graph that should be added to the plot
InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddXErrorImpulsesGraph()

template<class InputCatIt , class InputValueIt >

JKQTPImpulsesHorizontalErrorGraph * jkqtpstatAddXErrorImpulsesGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPImpulsesHorizontalErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPImpulsesHorizontalErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddXErrorLineGraph()

template<class InputCatIt , class InputValueIt >

JKQTPXYLineErrorGraph * jkqtpstatAddXErrorLineGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPXYLineErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPXYLineErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddXErrorParametrizedScatterGraph()

template<class InputCatIt , class InputValueIt >

JKQTPXYParametrizedErrorScatterGraph * jkqtpstatAddXErrorParametrizedScatterGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPXYParametrizedErrorScatterGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPXYParametrizedErrorScatterGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddXYErrorGraph()

template<class InputCatIt , class InputValueIt , class TGraph >

TGraph * jkqtpstatAddXYErrorGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a plot with x- and y-direction error bars, calculated from directional average +/- stddev of groups in the input data

Template Parameters

TGraph	type of graph that should be added to the plot
InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddXYErrorLineGraph()

template<class InputCatIt , class InputValueIt >

JKQTPXYLineErrorGraph * jkqtpstatAddXYErrorLineGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPXYLineErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddXYErrorGraph(), JKQTPXYLineErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddXYErrorParametrizedScatterGraph()

template<class InputCatIt , class InputValueIt >

JKQTPXYParametrizedErrorScatterGraph * jkqtpstatAddXYErrorParametrizedScatterGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPXYParametrizedErrorScatterGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddXYErrorGraph(), JKQTPXYParametrizedErrorScatterGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddYErrorBarGraph()

template<class InputCatIt , class InputValueIt >

JKQTPBarVerticalErrorGraph * jkqtpstatAddYErrorBarGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPBarVerticalErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPBarVerticalErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddYErrorFilledCurveGraph()

template<class InputCatIt , class InputValueIt >

JKQTPFilledCurveYErrorGraph * jkqtpstatAddYErrorFilledCurveGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPFilledCurveYErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPFilledCurveYErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddYErrorGraph()

template<class InputCatIt , class InputValueIt , class TGraph >

TGraph * jkqtpstatAddYErrorGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a plot with y-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

TGraph	type of graph that should be added to the plot
InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddYErrorImpulsesGraph()

template<class InputCatIt , class InputValueIt >

JKQTPImpulsesVerticalErrorGraph * jkqtpstatAddYErrorImpulsesGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPImpulsesVerticalErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPImpulsesVerticalErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddYErrorLineGraph()

template<class InputCatIt , class InputValueIt >

JKQTPXYLineErrorGraph * jkqtpstatAddYErrorLineGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPXYLineErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPXYLineErrorGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatAddYErrorParametrizedScatterGraph()

template<class InputCatIt , class InputValueIt >

JKQTPXYParametrizedErrorScatterGraph * jkqtpstatAddYErrorParametrizedScatterGraph ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_X, InputCatIt  inLastCat_X, InputValueIt  inFirstValue_Y, InputValueIt  inLastValue_Y, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped data")  )

inline

create a JKQTPXYParametrizedErrorScatterGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_X and inLastCat_X
InputValueIt	standard iterator type of inFirstValue_Y and inLastValue_Y

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastCat_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
inFirstValue_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastValue_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the graph showing and average +/- stddev for each group

See also

jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPXYParametrizedErrorScatterGraph, Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore

jkqtpstatVAddBoxplots()

template<class InputCatIt , class InputValueIt >

JKQTPBoxplotVerticalGraph * jkqtpstatVAddBoxplots ( JKQTBasePlotter *  plotter, InputCatIt  inFirstCat_Y, InputCatIt  inLastCat_Y, InputValueIt  inFirstValue_X, InputValueIt  inLastValue_X, double  quantile1Spec = 0.25, double  quantile2Spec = 0.75, double  minimumQuantile = 0, double  maximumQuantile = 1.0, JKQTPStatGroupDefinitionFunctor1D  groupDefFunc = &jkqtpstatGroupingIdentity1D, const QString &  columnBaseName = QString("grouped boxplot data")  )

inline

create vertical boxplots of type JKQTPBoxplotVerticalGraph, from the 5-value-summary of groups in the input data

Template Parameters

InputCatIt	standard iterator type of inFirstCat_Y and inLastCat_Y
InputValueIt	standard iterator type of inFirstValue_X and inLastValue_X

Parameters

plotter	the plotter to which to add the resulting graph
inFirstCat_Y	iterator pointing to the first item in the category dataset to use (used for y-coordinates)
inLastCat_Y	iterator pointing behind the last item in the category dataset to use (used for y-coordinates)
inFirstValue_X	iterator pointing to the first item in the category dataset to use (used for x-coordinates)
inLastValue_X	iterator pointing behind the last item in the category dataset to use (used for x-coordinates)
quantile1Spec	specifies which quantile to calculate for qantile1 (range: 0..1)
quantile2Spec	specifies which quantile to calculate for qantile2 (range: 0..1)
minimumQuantile	specifies a quantile for the return value minimum (default is 0 for the real minimum, but you could e.g. use 0.05 for the 5% quantile!)
maximumQuantile	specifies a quantile for the return value maximum (default is 1 for the real maximum, but you could e.g. use 0.95 for the 95% quantile!)
groupDefFunc	assigns a group to each category value .
columnBaseName	string component used to build the names of the columns generated by this function

Returns

the boxplot graph

See also

jkqtpstatGroupData(), Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore