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statistics library: added functions for grouped statistics and adaptors for them
added example for grouped statistics some improvements to documentation
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@ -84,6 +84,7 @@ addSimpleTest(datastore_iterators)
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addSimpleTest(datastore_statistics)
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addSimpleTest(datastore_statistics_2d)
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addSimpleTest(datastore_regression)
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addSimpleTest(datastore_groupedstat)
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addSimpleTest(contourplot)
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#addSimpleTest(rgbimageplot_opencv)
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#addSimpleTest(imageplot_opencv)
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@ -162,6 +162,9 @@ All test-projects are Qt-projects that use qmake to build. You can load them int
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<tr><td> \image html jkqtplotter_simpletest_datastore_regression_small.png
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<td> \subpage JKQTPlotterBasicJKQTPDatastoreRegression
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<td> Advanced 1-Dimensional Statistical Computation with JKQTPDatastore<br>using the internal statistics library<br>Regression Analysis (with the Statistics Library)<br>robust regression (IRLS)<br>weighted regression<br>non-linear regression<br>polynomial fitting
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<tr><td> \image html jkqtplotter_simpletest_datastore_groupedstat_small.png
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<td> \subpage JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
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<td> Advanced 1-Dimensional Statistical Computation with JKQTPDatastore<br>grouped statistics<br>error indicators from data<br>boxplots
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<tr><td> \image html jkqtplotter_simpletest_datastore_statistics_2d_small.png
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<td> \subpage JKQTPlotterBasicJKQTPDatastoreStatistics2D
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<td> Advanced 2-Dimensional Statistical Computation with JKQTPDatastore<br>using the internal statistics library (see \ref jkqtptools_math_statistics )<br>histograms<br>kernel density estimates (KDE)
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@ -37,7 +37,9 @@ This group assembles a basic set of linear algebra methods, including matrix inv
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This group contains a statistics library, which offers several basic methods and is based on an iterator interface:
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- \ref jkqtptools_math_statistics_basic
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- \ref jkqtptools_math_statistics_grouped
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- \ref jkqtptools_math_statistics_regression
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- \ref jkqtptools_math_statistics_poly
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- \ref jkqtptools_math_statistics_1dhist
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- \ref jkqtptools_math_statistics_2dhist
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- \ref jkqtptools_math_statistics_1dkde
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@ -67,9 +69,15 @@ All statistics functions use all values in the given range and convert each valu
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\defgroup jkqtptools_math_statistics_basic Basic statistics
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\ingroup jkqtptools_math_statistics
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\defgroup jkqtptools_math_statistics_grouped Grouped statistics
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\ingroup jkqtptools_math_statistics
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\defgroup jkqtptools_math_statistics_regression Regression Analysis
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\ingroup jkqtptools_math_statistics
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\defgroup jkqtptools_math_statistics_poly Polynomial Fits/Regression
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\ingroup jkqtptools_math_statistics
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\defgroup jkqtptools_math_statistics_1dhist 1-dimensional Histograms
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\ingroup jkqtptools_math_statistics
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@ -66,6 +66,7 @@ All test-projects are Qt-projects that use qmake to build. You can load them int
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| [](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_iterators) | [Tutorial: Iterator-based access to JKQTPDatastore](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_iterators) | Iterator-based Data Management with JKQTPDatastore |
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| [](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_statistics) | [Tutorial: Advanced 1-Dimensional Statistics with JKQTPDatastore](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_statistics) | Advanced 1-Dimensional Statistical Computation with JKQTPDatastore<br>using the internal statistics library<br>basic statistics (mean, standard deviation, ...)<br>boxplots<br>histograms<br>kernel density estimates (KDE) |
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| [](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_regression) | [Tutorial: Regression Analysis (with the Statistics Library)](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_regression) | Advanced 1-Dimensional Statistical Computation with JKQTPDatastore<br>using the internal statistics library<br>Regression Analysis (with the Statistics Library)<br>robust regression (IRLS)<br>weighted regression<br>non-linear regression<br>polynomial fitting |
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| [](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_groupedstat) | [Tutorial: 1-Dimensional Group Statistics (with the Statistics Library)](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_groupedstat) | Advanced 1-Dimensional Statistical Computation with JKQTPDatastore<br>grouped statistics<br>error indicators from data<br>boxplots |
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| [](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_statistics_2d) | [Tutorial: Advanced 2-Dimensional Statistics with JKQTPDatastore](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_statistics_2d) | Advanced 2-Dimensional Statistical Computation with JKQTPDatastore<br>using the internal statistics library<br>histograms<br>kernel density estimates (KDE) |
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@ -1,6 +1,13 @@
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# Example (JKQTPlotter): Boxplots {#JKQTPlotterBoxplotsGraphs}
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This project (see [`simpletest_boxplot`](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_boxplot) demonstrates how to use JKQTPlotter to draw <a href="https://en.wikipedia.org/wiki/Box_plot">box plots</a> using the classes `JKQTPBoxplotVerticalGraph` and `JKQTPBoxplotHorizontalGraph`.
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[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
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[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
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[JKQTPlotterBoxplotStyling]: @ref JKQTPlotterBoxplotStyling "Styling different aspects of boxplots"
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***Note*** that this example explains how to add boxplots to a graph by hand, i.e. by calculating all the statistical properties for the boxplots by hand. The internal [statisticslibrary] offers methods to perform these calculations, which are explained in the tutorial [JKQTPlotterBasicJKQTPDatastoreStatistics] in detail. Additional advanced styling of boxplots is covered by the example [JKQTPlotterBoxplotStyling].
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The source code of the main application is (see [`jkqtplotter_simpletest_boxplot.cpp`](jkqtplotter_simpletest_boxplot.cpp).
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After adding all necessary data to the JKQTDatastore:
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@ -1,10 +1,10 @@
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# Tutorial (JKQTPDatastore): Basic Usage of JKQTPDatastore {#JKQTPlotterBasicJKQTPDatastore}
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[JKQTPlotterBasicJKQTPDatastore]: @ref JKQTPlotterBasicJKQTPDatastore "Basic Usage of JKQTPDatastore"
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[JKQTPlotterBasicJKQTPDatastoreIterators]: @ref JKQTPlotterBasicJKQTPDatastoreIterators "Iterator-Based usage of JKQTPDatastore"
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[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
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[JKQTPlotterBasicJKQTPDatastoreRegression]: @ref JKQTPlotterBasicJKQTPDatastoreRegression "Regression Analysis (with the Statistics Library)"
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[JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]: @ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat "1-Dimensional Group Statistics with JKQTPDatastore"
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[JKQTPlotterBasicJKQTPDatastoreStatistics2D]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics2D "Advanced 2-Dimensional Statistics with JKQTPDatastore"
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[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
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@ -14,8 +14,10 @@ This tutorial project (see `./examples/simpletest_datastore/`) explains several
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- [JKQTPlotterBasicJKQTPDatastore]
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- [JKQTPlotterBasicJKQTPDatastoreIterators]
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- [JKQTPlotterBasicJKQTPDatastoreStatistics]
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- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
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- [JKQTPlotterBasicJKQTPDatastoreRegression]
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- [JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]
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- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
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[TOC]
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255
examples/simpletest_datastore_groupedstat/README.md
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255
examples/simpletest_datastore_groupedstat/README.md
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@ -0,0 +1,255 @@
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# Tutorial (JKQTPDatastore): 1-Dimensional Group Statistics with JKQTPDatastore {#JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat}
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[JKQTPlotterBasicJKQTPDatastore]: @ref JKQTPlotterBasicJKQTPDatastore "Basic Usage of JKQTPDatastore"
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[JKQTPlotterBasicJKQTPDatastoreIterators]: @ref JKQTPlotterBasicJKQTPDatastoreIterators "Iterator-Based usage of JKQTPDatastore"
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[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
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[JKQTPlotterBasicJKQTPDatastoreRegression]: @ref JKQTPlotterBasicJKQTPDatastoreRegression "Regression Analysis (with the Statistics Library)"
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[JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]: @ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat "1-Dimensional Group Statistics with JKQTPDatastore"
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[JKQTPlotterBasicJKQTPDatastoreStatistics2D]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics2D "Advanced 2-Dimensional Statistics with JKQTPDatastore"
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[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
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This tutorial project (see `./examples/simpletest_datastore_groupedstat/`) explains several advanced functions of JKQTPDatastore in combination with the [[statisticslibrary]] conatined in JKQTPlotter.
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***Note*** that there are additional tutorial explaining other aspects of data mangement in JKQTPDatastore:
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- [JKQTPlotterBasicJKQTPDatastore]
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- [JKQTPlotterBasicJKQTPDatastoreIterators]
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- [JKQTPlotterBasicJKQTPDatastoreStatistics]
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- [JKQTPlotterBasicJKQTPDatastoreRegression]
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- [JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]
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- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
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[TOC]
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The source code of the main application can be found in [`jkqtplotter_simpletest_datastore_groupedstat.cpp`](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_groupedstat/jkqtplotter_simpletest_datastore_groupedstat.cpp).
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This tutorial cites only parts of this code to demonstrate different ways of working with data for the graphs.
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# Barcharts & Boxplots from categorized data
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## Generating a Dataset for Grouped Barcharts
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To demonstrate the grouped statistics, we first have to generate a dataset. The datapoints consist of pairs `<group,value>`, where the groups are encoded by the numbers 1,2,3 and in each group, several measurements are taken:
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```.cpp
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size_t colBarRawGroup=datastore1->addColumn("barchart, rawdata, group");
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size_t colBarRawValue=datastore1->addColumn("barchart, rawdata, value");
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// data for group 1
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datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.1);
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datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.5);
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datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 0.8);
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// ...
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// data for group 2
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datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.2);
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// ...
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// data for group 3
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datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 4.1);
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// ...
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```
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Note that the data does not have to be sorted. You can add the dataset in any order!
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This dataset can be visualized with a simple scatter plot:
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```.cpp
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JKQTPXYLineGraph* gScatterForBar;
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plotbarchart->addGraph(gScatterForBar=new JKQTPXYLineGraph(plotbarchart));
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gScatterForBar->setXYColumns(colBarRawGroup, colBarRawValue);
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gScatterForBar->setDrawLine(false);
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gScatterForBar->setSymbolType(JKQTPCross);
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gScatterForBar->setSymbolSize(5);
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gScatterForBar->setSymbolColor(QColorWithAlphaF(QColor("red"), 0.5));
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```
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## Calculating Grouped Statistics for a Barchart
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Now we want to draw a barchart for every group, which indicates the average in each group. This is done using methods from the statistics library.
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First we need to group the data using `jkqtpstatGroupData()`, which assembles the data points in each group groupeddataBar
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```.cpp
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std::map<double, std::vector<double> > groupeddataBar;
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jkqtpstatGroupData(datastore1->begin(colBarRawGroup), datastore1->end(colBarRawGroup),
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datastore1->begin(colBarRawValue), datastore1->end(colBarRawValue),
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groupeddataBar);
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```
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Now we can calculate the statistics for each group separately: Data is collected in new columns `colBarGroup`, `colBarAverage` and `colBarStdDev`. The statistics is then calculated by simply iterating over `groupeddataBar` and calling functions like `jkqtpstatAverage()` for each group:
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```.cpp
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size_t colBarGroup=datastore1->addColumn("barchart, group");
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size_t colBarAverage=datastore1->addColumn("barchart, group-average");
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size_t colBarStdDev=datastore1->addColumn("barchart, group-stddev");
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for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
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datastore1->appendToColumn(colBarGroup, it->first);
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datastore1->appendToColumn(colBarAverage, jkqtpstatAverage(it->second.begin(), it->second.end()));
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datastore1->appendToColumn(colBarStdDev, jkqtpstatStdDev(it->second.begin(), it->second.end()));
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}
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```
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Finally the calculated groups are drawn:
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```.cpp
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JKQTPBarVerticalErrorGraph* gBar;
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plotbarchart->addGraph(gBar=new JKQTPBarVerticalErrorGraph(plotbarchart));
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gBar->setXYColumns(colBarGroup, colBarAverage);
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gBar->setYErrorColumn(static_cast<int>(colBarStdDev));
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```
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In order to safe yo the typing of the code above, shortcuts in the form of adaptors exist:
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```.cpp
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jkqtpstatAddYErrorBarGraph(plotbarchart->getPlotter(),
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datastore1->begin(colBarRawGroup), datastore1->end(colBarRawGroup),
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datastore1->begin(colBarRawValue), datastore1->end(colBarRawValue));
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```
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Also other flavors exist that generate different graphs (see the JKQTPlotter documentation):
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- `jkqtpstatAddYErrorLineGraph()` / `jkqtpstatAddXErrorLineGraph()`
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- `jkqtpstatAddYErrorBarGraph()` / `jkqtpstatAddXErrorBarGraph()`
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- `jkqtpstatAddYErrorImpulsesGraph()` / `jkqtpstatAddXErrorImpulsesGraph()`
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- `jkqtpstatAddYErrorParametrizedScatterGraph()` / `jkqtpstatAddXErrorParametrizedScatterGraph()`
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- `jkqtpstatAddYErrorFilledCurveGraph()` / `jkqtpstatAddXErrorFilledCurveGraph()`
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- `jkqtpstatAddYErrorGraph()` / `jkqtpstatAddXErrorGraph()`
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## Calculating Grouped Statistics for a Boxplot
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With the methods above we can also calculate more advanced statistics, like e.g. boxplots:
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```.cpp
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size_t colBarMedian=datastore1->addColumn("barchart, group-median");
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size_t colBarMin=datastore1->addColumn("barchart, group-min");
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size_t colBarMax=datastore1->addColumn("barchart, group-max");
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size_t colBarQ25=datastore1->addColumn("barchart, group-Q25");
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size_t colBarQ75=datastore1->addColumn("barchart, group-Q75");
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for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
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datastore1->appendToColumn(colBarMedian, jkqtpstatMedian(it->second.begin(), it->second.end()));
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datastore1->appendToColumn(colBarMin, jkqtpstatMinimum(it->second.begin(), it->second.end()));
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datastore1->appendToColumn(colBarMax, jkqtpstatMaximum(it->second.begin(), it->second.end()));
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datastore1->appendToColumn(colBarQ25, jkqtpstatQuantile(it->second.begin(), it->second.end(), 0.25));
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datastore1->appendToColumn(colBarQ75, jkqtpstatQuantile(it->second.begin(), it->second.end(), 0.75));
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}
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```
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The result can be plotted using JKQTPBoxplotVerticalGraph, which receives a column for each value class of the final plot:
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```.cpp
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JKQTPBoxplotVerticalGraph* gBoxplot;
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plotboxplot->addGraph(gBoxplot=new JKQTPBoxplotVerticalGraph(plotboxplot));
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gBoxplot->setPositionColumn(colBarGroup);
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gBoxplot->setMinColumn(colBarMin);
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gBoxplot->setMaxColumn(colBarMax);
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gBoxplot->setMedianColumn(colBarMedian);
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gBoxplot->setPercentile25Column(colBarQ25);
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gBoxplot->setPercentile75Column(colBarQ75);
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```
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In order to safe yo the typing of the code above, shortcuts in the form of adaptors exist:
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```.cpp
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jkqtpstatAddHBoxplotsAndOutliers(plotboxplot->getPlotter(),
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datastore1->begin(colBarRawGroup), datastore1->end(colBarRawGroup),
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datastore1->begin(colBarRawValue), datastore1->end(colBarRawValue));
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```
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Also other flavors exist that generate different graphs (see the JKQTPlotter documentation):
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- `jkqtpstatAddVBoxplotsAndOutliers()` / `jkqtpstatAddHBoxplotsAndOutliers()`
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- `jkqtpstatVAddBoxplots()` / `jkqtpstatHAddBoxplots()`
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- `jkqtpstatAddBoxplots()`
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# (Scatter-)Graphs with X/Y-errors from Categorized Data
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## Dataset for XY Scatter Graphs
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First we generate a second dataset, which is going to be used for a scaterplot. The datapoints consist of pairs `<x,y>`, that are based on a parabula with random deviations, both in x- and y-direction:
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```.cpp
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size_t colScatterRawX=datastore1->addColumn("scatterplot, rawdata, x");
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size_t colScatterRawY=datastore1->addColumn("scatterplot, rawdata, y");
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std::random_device rd; // random number generators:
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std::mt19937 gen{rd()};
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std::normal_distribution<> d1{0,0.5};
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const size_t N=100;
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const double xmax=3.5;
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for (size_t i=0; i<N; i++) {
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const double x=(static_cast<double>(i)-static_cast<double>(N)/2.0)*xmax/(static_cast<double>(N)/2.0);
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const double y=jkqtp_sqr(x)+2.0;
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datastore1->appendToColumns(colScatterRawX, colScatterRawY, x+d1(gen), y+d1(gen));
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}
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```
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This dataset can be visualized:
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```.cpp
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JKQTPXYParametrizedScatterGraph* gScatterRaw;
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plotscattererrors->addGraph(gScatterRaw=new JKQTPXYParametrizedScatterGraph(plotscattererrors));
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gScatterRaw->setXYColumns(colScatterRawX, colScatterRawY);
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gScatterRaw->setDrawLine(false);
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gScatterRaw->setSymbolType(JKQTPCross);
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gScatterRaw->setSymbolSize(5);
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```
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## Calculating x- and y-Errors from Categorized Data
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Now we want to draw a scatterchart of the data, where data-points should be grouped together, in x-intervals of width 0.5. From all the points in each interval, we calculate the in both x- and y-direction the average and standard deviation. First we need to group the data using `jkqtpstatGroupData()`, which assembles the data points in each group groupeddataScatter. For the custom grouping of the datapoints we use the optional functor provided to `jkqtpstatGroupData()`: We use `jkqtpstatGroupingCustomRound1D()` with given parameters 0.25 for the (center) location of the first bin and bin width 0.5. The functor is not built by hand (which would be possible using std::bind), but with the generator function `jkqtpstatMakeGroupingCustomRound1D()`. In addition we use a variant of `jkqtpstatGroupData()`, which outputs a column with the category assigned to every data pair in the input data range:
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```.cpp
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std::map<double, std::pair<std::vector<double>,std::vector<double> > > groupeddataScatter;
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size_t colScatterRawGroup=datastore1->addColumn("scatterplot, rawdata, assigned-group");
|
||||
jkqtpstatGroupData(datastore1->begin(colScatterRawX), datastore1->end(colScatterRawX),
|
||||
datastore1->begin(colScatterRawY), datastore1->end(colScatterRawY),
|
||||
datastore1->backInserter(colScatterRawGroup),
|
||||
groupeddataScatter,
|
||||
jkqtpstatMakeGroupingCustomRound1D(0.25, 0.5));
|
||||
```
|
||||
|
||||
The column colScatterRawGroup can now be used to color the scatter graph:
|
||||
```.cpp
|
||||
gScatterRaw->setColorColumn(colScatterRawGroup);
|
||||
```
|
||||
|
||||
Now we can calculate the statistics for each group separately: Data is collected in two new columns. Then the statistics is calculated by simply iterating over `groupeddataScatter` and calling functions like `jkqtpstatAverage()` for each group:
|
||||
```.cpp
|
||||
size_t colScatterXAvg=datastore1->addColumn("scatter, x, average");
|
||||
size_t colScatterXStd=datastore1->addColumn("scatter, x, stddev");
|
||||
size_t colScatterYAvg=datastore1->addColumn("scatter, y, average");
|
||||
size_t colScatterYStd=datastore1->addColumn("scatter, y, stddev");
|
||||
|
||||
for (auto it=groupeddataScatter.begin(); it!=groupeddataScatter.end(); ++it) {
|
||||
datastore1->appendToColumn(colScatterXAvg, jkqtpstatAverage(it->second.first.begin(), it->second.first.end()));
|
||||
datastore1->appendToColumn(colScatterXStd, jkqtpstatStdDev(it->second.first.begin(), it->second.first.end()));
|
||||
datastore1->appendToColumn(colScatterYAvg, jkqtpstatAverage(it->second.second.begin(), it->second.second.end()));
|
||||
datastore1->appendToColumn(colScatterYStd, jkqtpstatStdDev(it->second.second.begin(), it->second.second.end()));
|
||||
}
|
||||
```
|
||||
|
||||
Finally the calculated groups are drawn
|
||||
```.cpp
|
||||
JKQTPXYLineErrorGraph* gScatterErr;
|
||||
plotscattererrors->addGraph(gScatterErr=new JKQTPXYLineErrorGraph(plotscattererrors));
|
||||
gScatterErr->setXYColumns(colScatterXAvg, colScatterYAvg);
|
||||
gScatterErr->setXErrorColumn(static_cast<int>(colScatterXStd));
|
||||
gScatterErr->setYErrorColumn(static_cast<int>(colScatterYStd));
|
||||
gScatterErr->setSymbolType(JKQTPFilledTriangle);
|
||||
gScatterErr->setDrawLine(false);
|
||||
```
|
||||
|
||||
|
||||
|
||||
|
||||
In order to safe yo the typing of the code above, shortcuts in the form of adaptors exist:
|
||||
```.cpp
|
||||
jkqtpstatAddXYErrorLineGraph(plotscattererrors->getPlotter(),
|
||||
datastore1->begin(colScatterRawX), datastore1->end(colScatterRawX),
|
||||
datastore1->begin(colScatterRawY), datastore1->end(colScatterRawY),
|
||||
jkqtpstatMakeGroupingCustomRound1D(0.25, 0.5));
|
||||
```
|
||||
Also other flavors exist that generate different graphs (see the JKQTPlotter documentation):
|
||||
- `jkqtpstatAddXYErrorLineGraph()`
|
||||
- `jkqtpstatAddXYErrorParametrizedScatterGraph()`
|
||||
- `jkqtpstatAddXYErrorGraph()`
|
||||
|
||||
|
||||
# Screenshot of the full Program
|
||||
|
||||
The output of the full test program [`jkqtplotter_simpletest_datastore_groupedstat.cpp`](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_datastore_groupedstat/jkqtplotter_simpletest_datastore_groupedstat.cpp) looks like this:
|
||||
|
||||
|
||||
|
||||
|
||||
@ -0,0 +1,265 @@
|
||||
/** \example jkqtplotter_simpletest_datastore_groupedstat.cpp
|
||||
* Explains how to use the internal statistics library (see \ref jkqtptools_statistics ) together with JKQTPDatastore to generate grouped statistics (i.e. calculates errorbars or boxplots from groups of datapoints in a x/y-dataset).
|
||||
*
|
||||
* \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
|
||||
#include <QApplication>
|
||||
#include "jkqtplotter/jkqtplotter.h"
|
||||
#include "jkqtplotter/jkqtpgraphsscatter.h"
|
||||
#include "jkqtplotter/jkqtpgraphsbarchart.h"
|
||||
#include "jkqtplotter/jkqtpgraphsstatisticsadaptors.h"
|
||||
#include "jkqtcommon/jkqtpstatisticstools.h"
|
||||
#include "jkqtcommon/jkqtpstringtools.h"
|
||||
#include <random>
|
||||
#include <cmath>
|
||||
#include <vector>
|
||||
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
QApplication app(argc, argv);
|
||||
|
||||
|
||||
// 1. create a window with several plotters and get a pointer to the internal datastores (for convenience)
|
||||
QWidget mainWidget;
|
||||
QGridLayout* lay;
|
||||
mainWidget.setLayout(lay=new QGridLayout);
|
||||
JKQTPlotter* plotbarchart=new JKQTPlotter(&mainWidget);
|
||||
plotbarchart->getPlotter()->setPlotLabel("Barcharts");
|
||||
JKQTPDatastore* datastore1=plotbarchart->getDatastore();
|
||||
lay->addWidget(plotbarchart,0,0);
|
||||
JKQTPlotter* plotboxplot=new JKQTPlotter(datastore1, &mainWidget);
|
||||
plotboxplot->getPlotter()->setPlotLabel("Boxplots");
|
||||
lay->addWidget(plotboxplot,0,1);
|
||||
JKQTPlotter* plotscattererrors=new JKQTPlotter(datastore1, &mainWidget);
|
||||
plotscattererrors->getPlotter()->setPlotLabel("Scatter Plot with Error Indicators");
|
||||
lay->addWidget(plotscattererrors,0,2);
|
||||
lay->setColumnStretch(0,1);
|
||||
lay->setColumnStretch(1,1);
|
||||
lay->setColumnStretch(2,2);
|
||||
|
||||
|
||||
|
||||
// 2. Barcharts from categorized data:
|
||||
// 2.1. First we generate a dataset, which is going to be used for a barchart
|
||||
// The datapoints consist of pairs <group,value>, where the groups are encoded
|
||||
// by the numbers 1,2,3 and in each group, several measurements are taken
|
||||
size_t colBarRawGroup=datastore1->addColumn("barchart, rawdata, group");
|
||||
size_t colBarRawValue=datastore1->addColumn("barchart, rawdata, value");
|
||||
|
||||
// data for group 1
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.1);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.5);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 0.8);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.2);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.4);
|
||||
// data for group 2
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.2);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.4);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 1.9);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.6);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.1);
|
||||
// data for group 3
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 4.1);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 4.4);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 3.8);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 4.5);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 3.7);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 4.0);
|
||||
// now some more datapoint, in mixed order
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 0.9);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.3);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.0);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.0);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 4.2);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.25);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.35);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 3.7);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 0.75);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 1.85);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 4.5);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 0.95);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 1.65);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 3, 4.1);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 1, 1.15);
|
||||
datastore1->appendToColumns(colBarRawGroup, colBarRawValue, 2, 2.15);
|
||||
|
||||
|
||||
// 2.2. This dataset can be visualized with a simple scatter plot:
|
||||
JKQTPXYLineGraph* gScatterForBar;
|
||||
plotbarchart->addGraph(gScatterForBar=new JKQTPXYLineGraph(plotbarchart));
|
||||
gScatterForBar->setXYColumns(colBarRawGroup, colBarRawValue);
|
||||
gScatterForBar->setDrawLine(false);
|
||||
gScatterForBar->setSymbolType(JKQTPCross);
|
||||
gScatterForBar->setSymbolSize(5);
|
||||
gScatterForBar->setSymbolColor(QColorWithAlphaF(QColor("red"), 0.5));
|
||||
|
||||
// 2.3. Now we want to draw a barchart for every group, which indicates the
|
||||
// average in each group. This is done using methods from the statistics
|
||||
// library.
|
||||
// First we need to group the data using jkqtpstatGroupData(), which assembles
|
||||
// the data points in each group groupeddataBar
|
||||
std::map<double, std::vector<double> > groupeddataBar;
|
||||
jkqtpstatGroupData(datastore1->begin(colBarRawGroup), datastore1->end(colBarRawGroup),
|
||||
datastore1->begin(colBarRawValue), datastore1->end(colBarRawValue),
|
||||
groupeddataBar);
|
||||
// now we can calculate the statistics for each group separately:
|
||||
// Data is collected in two new columns
|
||||
size_t colBarGroup=datastore1->addColumn("barchart, group");
|
||||
size_t colBarAverage=datastore1->addColumn("barchart, group-average");
|
||||
size_t colBarStdDev=datastore1->addColumn("barchart, group-stddev");
|
||||
// Statistics is calculated by simply iterating over groupeddataBar
|
||||
// and calling functions like jkqtpstatAverage() for each group
|
||||
for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
|
||||
datastore1->appendToColumn(colBarGroup, it->first);
|
||||
datastore1->appendToColumn(colBarAverage, jkqtpstatAverage(it->second.begin(), it->second.end()));
|
||||
datastore1->appendToColumn(colBarStdDev, jkqtpstatStdDev(it->second.begin(), it->second.end()));
|
||||
}
|
||||
|
||||
// 2.4. Finally the calculated groups are drawn
|
||||
JKQTPBarVerticalErrorGraph* gBar;
|
||||
plotbarchart->addGraph(gBar=new JKQTPBarVerticalErrorGraph(plotbarchart));
|
||||
gBar->setXYColumns(colBarGroup, colBarAverage);
|
||||
gBar->setYErrorColumn(static_cast<int>(colBarStdDev));
|
||||
|
||||
// 2.5. With the methods above we can also calculate more advanced statistics, like e.g. boxplots:
|
||||
size_t colBarMedian=datastore1->addColumn("barchart, group-median");
|
||||
size_t colBarMin=datastore1->addColumn("barchart, group-min");
|
||||
size_t colBarMax=datastore1->addColumn("barchart, group-max");
|
||||
size_t colBarQ25=datastore1->addColumn("barchart, group-Q25");
|
||||
size_t colBarQ75=datastore1->addColumn("barchart, group-Q75");
|
||||
for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
|
||||
datastore1->appendToColumn(colBarMedian, jkqtpstatMedian(it->second.begin(), it->second.end()));
|
||||
datastore1->appendToColumn(colBarMin, jkqtpstatMinimum(it->second.begin(), it->second.end()));
|
||||
datastore1->appendToColumn(colBarMax, jkqtpstatMaximum(it->second.begin(), it->second.end()));
|
||||
datastore1->appendToColumn(colBarQ25, jkqtpstatQuantile(it->second.begin(), it->second.end(), 0.25));
|
||||
datastore1->appendToColumn(colBarQ75, jkqtpstatQuantile(it->second.begin(), it->second.end(), 0.75));
|
||||
}
|
||||
// 2.6. The result can be plotted using JKQTPBoxplotVerticalGraph, which receives a column for each value class of the final plot:
|
||||
JKQTPBoxplotVerticalGraph* gBoxplot;
|
||||
plotboxplot->addGraph(gBoxplot=new JKQTPBoxplotVerticalGraph(plotboxplot));
|
||||
gBoxplot->setPositionColumn(colBarGroup);
|
||||
gBoxplot->setMinColumn(colBarMin);
|
||||
gBoxplot->setMaxColumn(colBarMax);
|
||||
gBoxplot->setMedianColumn(colBarMedian);
|
||||
gBoxplot->setPercentile25Column(colBarQ25);
|
||||
gBoxplot->setPercentile75Column(colBarQ75);
|
||||
// 2.7. In order to safe yo the typing of the code above, shortcuts in the form of adaptors exist:
|
||||
/*
|
||||
jkqtpstatAddYErrorBarGraph(plotbarchart->getPlotter(),
|
||||
datastore1->begin(colBarRawGroup), datastore1->end(colBarRawGroup),
|
||||
datastore1->begin(colBarRawValue), datastore1->end(colBarRawValue));
|
||||
jkqtpstatAddHBoxplotsAndOutliers(plotboxplot->getPlotter(),
|
||||
datastore1->begin(colBarRawGroup), datastore1->end(colBarRawGroup),
|
||||
datastore1->begin(colBarRawValue), datastore1->end(colBarRawValue));
|
||||
*/
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
// 3. Scatterplots from categorized data:
|
||||
// 3.1. First we generate a second dataset, which is going to be used for a scaterplot
|
||||
// The datapoints consist of pairs <x,y>, that are based on a parabula with random
|
||||
// deviations, both in x- and y-direction
|
||||
size_t colScatterRawX=datastore1->addColumn("scatterplot, rawdata, x");
|
||||
size_t colScatterRawY=datastore1->addColumn("scatterplot, rawdata, y");
|
||||
std::random_device rd; // random number generators:
|
||||
std::mt19937 gen{rd()};
|
||||
std::normal_distribution<> d1{0,0.5};
|
||||
const size_t N=100;
|
||||
const double xmax=3.5;
|
||||
for (size_t i=0; i<N; i++) {
|
||||
const double x=(static_cast<double>(i)-static_cast<double>(N)/2.0)*xmax/(static_cast<double>(N)/2.0);
|
||||
const double y=jkqtp_sqr(x)+2.0;
|
||||
datastore1->appendToColumns(colScatterRawX, colScatterRawY, x+d1(gen), y+d1(gen));
|
||||
}
|
||||
// 3.2. Now we can also add the raw dataset to the plot for visualization:
|
||||
JKQTPXYParametrizedScatterGraph* gScatterRaw;
|
||||
plotscattererrors->addGraph(gScatterRaw=new JKQTPXYParametrizedScatterGraph(plotscattererrors));
|
||||
gScatterRaw->setXYColumns(colScatterRawX, colScatterRawY);
|
||||
gScatterRaw->setDrawLine(false);
|
||||
gScatterRaw->setSymbolType(JKQTPCross);
|
||||
gScatterRaw->setSymbolSize(5);
|
||||
|
||||
// 3.3. Now we want to draw a scatterchart of the data, where data-points should be grouped
|
||||
// together, in x-intervals of width 0.5. From all the points in each interval, we calculate the
|
||||
// in both x- and y-direction the average and standard deviation.
|
||||
// First we need to group the data using jkqtpstatGroupData(), which assembles
|
||||
// the data points in each group groupeddataScatter. For the custom grouping of the datapoints
|
||||
// we use the optional functor provided to jkqtpstatGroupData(): We use jkqtpstatGroupingCustomRound1D()
|
||||
// with given parameters 0.25 for the (center) location of the first bin and bin width 0.5. The functor
|
||||
// is not built by hand (which would be possible using std::bind), but with the generator function
|
||||
// jkqtpstatMakeGroupingCustomRound1D().
|
||||
// in addition we use a variant of jkqtpstatGroupData(), which outputs a column with the category
|
||||
// assigned to every data pair in the input data range
|
||||
std::map<double, std::pair<std::vector<double>,std::vector<double> > > groupeddataScatter;
|
||||
size_t colScatterRawGroup=datastore1->addColumn("scatterplot, rawdata, assigned-group");
|
||||
jkqtpstatGroupData(datastore1->begin(colScatterRawX), datastore1->end(colScatterRawX),
|
||||
datastore1->begin(colScatterRawY), datastore1->end(colScatterRawY),
|
||||
datastore1->backInserter(colScatterRawGroup),
|
||||
groupeddataScatter,
|
||||
jkqtpstatMakeGroupingCustomRound1D(0.25, 0.5));
|
||||
// The column colScatterRawGroup can now be used to color the scatter graph:
|
||||
gScatterRaw->setColorColumn(colScatterRawGroup);
|
||||
// now we can calculate the statistics for each group separately:
|
||||
// Data is collected in two new columns
|
||||
size_t colScatterXAvg=datastore1->addColumn("scatter, x, average");
|
||||
size_t colScatterXStd=datastore1->addColumn("scatter, x, stddev");
|
||||
size_t colScatterYAvg=datastore1->addColumn("scatter, y, average");
|
||||
size_t colScatterYStd=datastore1->addColumn("scatter, y, stddev");
|
||||
// Statistics is calculated by simply iterating over groupeddataScatter
|
||||
// and calling functions like jkqtpstatAverage() for each group
|
||||
for (auto it=groupeddataScatter.begin(); it!=groupeddataScatter.end(); ++it) {
|
||||
datastore1->appendToColumn(colScatterXAvg, jkqtpstatAverage(it->second.first.begin(), it->second.first.end()));
|
||||
datastore1->appendToColumn(colScatterXStd, jkqtpstatStdDev(it->second.first.begin(), it->second.first.end()));
|
||||
datastore1->appendToColumn(colScatterYAvg, jkqtpstatAverage(it->second.second.begin(), it->second.second.end()));
|
||||
datastore1->appendToColumn(colScatterYStd, jkqtpstatStdDev(it->second.second.begin(), it->second.second.end()));
|
||||
}
|
||||
|
||||
// 3.4. Finally the calculated groups are drawn
|
||||
JKQTPXYLineErrorGraph* gScatterErr;
|
||||
plotscattererrors->addGraph(gScatterErr=new JKQTPXYLineErrorGraph(plotscattererrors));
|
||||
gScatterErr->setXYColumns(colScatterXAvg, colScatterYAvg);
|
||||
gScatterErr->setXErrorColumn(static_cast<int>(colScatterXStd));
|
||||
gScatterErr->setYErrorColumn(static_cast<int>(colScatterYStd));
|
||||
gScatterErr->setSymbolType(JKQTPFilledTriangle);
|
||||
gScatterErr->setDrawLine(false);
|
||||
|
||||
// 3.5. also here an adaptor exists, which makes the task easier:
|
||||
/*
|
||||
jkqtpstatAddXYErrorLineGraph(plotscattererrors->getPlotter(),
|
||||
datastore1->begin(colScatterRawX), datastore1->end(colScatterRawX),
|
||||
datastore1->begin(colScatterRawY), datastore1->end(colScatterRawY),
|
||||
jkqtpstatMakeGroupingCustomRound1D(0.25, 0.5));
|
||||
*/
|
||||
|
||||
|
||||
|
||||
|
||||
// autoscale the plot so the graph is contained
|
||||
plotboxplot->synchronizeToMaster(plotbarchart, JKQTBasePlotter::sdXYAxes);
|
||||
plotboxplot->zoomToFit();
|
||||
plotboxplot->setGrid(false);
|
||||
plotboxplot->setShowZeroAxes(false);
|
||||
plotboxplot->getPlotter()->setKeyBackgroundColor(QColorWithAlphaF("white", 0.25), Qt::SolidPattern);
|
||||
plotbarchart->setAbsoluteY(0,5);
|
||||
plotboxplot->setAbsoluteY(0,5);
|
||||
plotbarchart->zoomToFit();
|
||||
plotbarchart->setGrid(false);
|
||||
plotbarchart->setShowZeroAxes(false);
|
||||
plotbarchart->getPlotter()->setKeyBackgroundColor(QColorWithAlphaF("white", 0.25), Qt::SolidPattern);
|
||||
plotbarchart->moveGraphTop(gScatterForBar);
|
||||
plotscattererrors->zoomToFit();
|
||||
plotscattererrors->setGrid(false);
|
||||
plotscattererrors->setShowZeroAxes(false);
|
||||
plotscattererrors->getPlotter()->setKeyBackgroundColor(QColorWithAlphaF("white", 0.25), Qt::SolidPattern);
|
||||
|
||||
|
||||
// show plotter and make it a decent size
|
||||
mainWidget.show();
|
||||
mainWidget.resize(1200,400);
|
||||
|
||||
return app.exec();
|
||||
}
|
||||
@ -0,0 +1,27 @@
|
||||
# source code for this simple demo
|
||||
SOURCES = jkqtplotter_simpletest_datastore_groupedstat.cpp
|
||||
|
||||
# configure Qt
|
||||
CONFIG += link_prl qt
|
||||
QT += core gui xml svg
|
||||
greaterThan(QT_MAJOR_VERSION, 4): QT += widgets printsupport
|
||||
|
||||
# output executable name
|
||||
TARGET = jkqtplotter_simpletest_datastore_groupedstat
|
||||
|
||||
# include JKQTPlotter source headers and link against library
|
||||
DEPENDPATH += ../../lib ../../staticlib/jkqtplotterlib
|
||||
INCLUDEPATH += ../../lib
|
||||
CONFIG (debug, debug|release) {
|
||||
LIBS += -L../../staticlib/jkqtplotterlib/debug -ljkqtplotterlib_debug
|
||||
} else {
|
||||
LIBS += -L../../staticlib/jkqtplotterlib/release -ljkqtplotterlib
|
||||
}
|
||||
message("LIBS = $$LIBS")
|
||||
|
||||
win32-msvc*: DEFINES += _USE_MATH_DEFINES
|
||||
win32-msvc*: DEFINES += NOMINMAX
|
||||
|
||||
|
||||
|
||||
|
||||
@ -0,0 +1,8 @@
|
||||
TEMPLATE = subdirs
|
||||
|
||||
SUBDIRS += jkqtplotterlib jkqtplotter_simpletest_datastore_groupedstat
|
||||
|
||||
jkqtplotterlib.file = ../../staticlib/jkqtplotterlib/jkqtplotterlib.pro
|
||||
|
||||
jkqtplotter_simpletest_datastore_groupedstat.file=$$PWD/jkqtplotter_simpletest_datastore_groupedstat.pro
|
||||
jkqtplotter_simpletest_datastore_groupedstat.depends = jkqtplotterlib
|
||||
@ -1,10 +1,10 @@
|
||||
# Tutorial (JKQTPDatastore): Iterator-Based usage of JKQTPDatastore {#JKQTPlotterBasicJKQTPDatastoreIterators}
|
||||
|
||||
|
||||
[JKQTPlotterBasicJKQTPDatastore]: @ref JKQTPlotterBasicJKQTPDatastore "Basic Usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreIterators]: @ref JKQTPlotterBasicJKQTPDatastoreIterators "Iterator-Based usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreRegression]: @ref JKQTPlotterBasicJKQTPDatastoreRegression "Regression Analysis (with the Statistics Library)"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]: @ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat "1-Dimensional Group Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics2D]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics2D "Advanced 2-Dimensional Statistics with JKQTPDatastore"
|
||||
[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
|
||||
|
||||
@ -14,8 +14,10 @@ This tutorial project (see `./examples/simpletest_datastore_iterators/`) explain
|
||||
- [JKQTPlotterBasicJKQTPDatastore]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreIterators]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreRegression]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@ -4,18 +4,19 @@
|
||||
[JKQTPlotterBasicJKQTPDatastoreIterators]: @ref JKQTPlotterBasicJKQTPDatastoreIterators "Iterator-Based usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreRegression]: @ref JKQTPlotterBasicJKQTPDatastoreRegression "Regression Analysis (with the Statistics Library)"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]: @ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat "1-Dimensional Group Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics2D]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics2D "Advanced 2-Dimensional Statistics with JKQTPDatastore"
|
||||
[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
|
||||
|
||||
|
||||
This tutorial project (see `./examples/simpletest_datastore_statistics/`) explains several advanced functions of JKQTPDatastore in combination with the [[statisticslibrary]] conatined in JKQTPlotter.
|
||||
|
||||
***Note*** that there are additional tutorial explaining other aspects of data mangement in JKQTPDatastore:
|
||||
- [JKQTPlotterBasicJKQTPDatastore]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreIterators]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreRegression]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
|
||||
|
||||
|
||||
[TOC]
|
||||
|
||||
@ -1,22 +1,22 @@
|
||||
# Tutorial (JKQTPDatastore): Advanced 1-Dimensional Statistics with JKQTPDatastore {#JKQTPlotterBasicJKQTPDatastoreStatistics}
|
||||
|
||||
|
||||
[JKQTPlotterBasicJKQTPDatastore]: @ref JKQTPlotterBasicJKQTPDatastore "Basic Usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreIterators]: @ref JKQTPlotterBasicJKQTPDatastoreIterators "Iterator-Based usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreRegression]: @ref JKQTPlotterBasicJKQTPDatastoreRegression "Regression Analysis (with the Statistics Library)"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]: @ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat "1-Dimensional Group Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics2D]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics2D "Advanced 2-Dimensional Statistics with JKQTPDatastore"
|
||||
[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
|
||||
|
||||
|
||||
This tutorial project (see `./examples/simpletest_datastore_statistics/`) explains several advanced functions of JKQTPDatastore in combination with the [[statisticslibrary]] conatined in JKQTPlotter.
|
||||
|
||||
***Note*** that there are additional tutorial explaining other aspects of data mangement in JKQTPDatastore:
|
||||
- [JKQTPlotterBasicJKQTPDatastore]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreIterators]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreRegression]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
|
||||
|
||||
[TOC]
|
||||
|
||||
|
||||
@ -1,22 +1,22 @@
|
||||
# Tutorial (JKQTPDatastore): Advanced 2-Dimensional Statistics with JKQTPDatastore {#JKQTPlotterBasicJKQTPDatastoreStatistics2D}
|
||||
|
||||
|
||||
[JKQTPlotterBasicJKQTPDatastore]: @ref JKQTPlotterBasicJKQTPDatastore "Basic Usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreIterators]: @ref JKQTPlotterBasicJKQTPDatastoreIterators "Iterator-Based usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreRegression]: @ref JKQTPlotterBasicJKQTPDatastoreRegression "Regression Analysis (with the Statistics Library)"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]: @ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat "1-Dimensional Group Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics2D]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics2D "Advanced 2-Dimensional Statistics with JKQTPDatastore"
|
||||
[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
|
||||
|
||||
|
||||
This tutorial project (see `./examples/simpletest_datastore_statistics_2d/`) explains several advanced functions of JKQTPDatastore in combination with the [[statisticslibrary]] conatined in JKQTPlotter.
|
||||
|
||||
***Note*** that there are additional tutorial explaining other aspects of data mangement in JKQTPDatastore:
|
||||
- [JKQTPlotterBasicJKQTPDatastore]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreIterators]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreRegression]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]
|
||||
- [JKQTPlotterBasicJKQTPDatastoreStatistics2D]
|
||||
|
||||
[TOC]
|
||||
|
||||
|
||||
@ -1,6 +1,11 @@
|
||||
# Example (JKQTPlotter): Different Types of Errorindicators {#JKQTPlotterErrorBarStyles}
|
||||
This project (see `./examples/simpletest_errorbarstyles/`) simply creates a JKQTPlotter widget (as a new window) and adds several curves show-casing different styles of error indicators. Data is initialized from two QVector<double> objects.
|
||||
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat]: @ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat "1-Dimensional Group Statistics with JKQTPDatastore"
|
||||
[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
|
||||
|
||||
***Note:*** This examples explains how to plot graphs with error indicators, when the data has already been calculated. The tutorial [JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat] explains one way how to use the [statisticslibrary] in order to calculate the errors from data.
|
||||
|
||||
The source code of the main application can be found in [`jkqtplotter_simpletest_errorbarstyles.cpp`](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_errorbarstyles/jkqtplotter_simpletest_errorbarstyles.cpp).
|
||||
|
||||
First some data is added to the internal datastore (mostly, like explained in several other examples, like e.g. [Line Graph with Different Symbols and Line Styles](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_symbols_and_styles)). The (in a loop) several graphs are added, each with a distinct style for its error indicators:
|
||||
|
||||
@ -1,6 +1,19 @@
|
||||
# Example (JKQTPlotter): Plotting a Statistical Distribution of Data {#JKQTPlotterDistributionPlot}
|
||||
This project (see [`test_distributionplot`](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/test_distributionplot) demonstrates how to combine several different graphs and geometric elements to show a set of random values and their statistics.
|
||||
|
||||
|
||||
[JKQTPlotterBasicJKQTPDatastore]: @ref JKQTPlotterBasicJKQTPDatastore "Basic Usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreIterators]: @ref JKQTPlotterBasicJKQTPDatastoreIterators "Iterator-Based usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreRegression]: @ref JKQTPlotterBasicJKQTPDatastoreRegression "Regression Analysis (with the Statistics Library)"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics2D]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics2D "Advanced 2-Dimensional Statistics with JKQTPDatastore"
|
||||
[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
|
||||
[JKQTPlotterBoxplotStyling]: @ref JKQTPlotterBoxplotStyling "Styling different aspects of boxplots"
|
||||
[JKQTPlotterBoxplotsGraphs]: @ref JKQTPlotterBoxplotsGraphs "Boxplots"
|
||||
|
||||
***Note*** that this example explains how to generate the statistics plots by hand, i.e. by calculating all the statistical properties for the boxplots and then adding the necessary graphs. The internal [statisticslibrary] offers methods to perform these calculations, which are explained in the tutorial [JKQTPlotterBasicJKQTPDatastoreStatistics] in detail. Several examples give more details on boxplots: [JKQTPlotterBoxplotsGraphs], [JKQTPlotterBoxplotStyling].
|
||||
|
||||
|
||||
The source code of the main application is (see [`test_distributionplot.cpp`](test_distributionplot.cpp).
|
||||
|
||||
After adding all necessary data to the JKQTDatastore:
|
||||
|
||||
@ -1,6 +1,19 @@
|
||||
# Example (JKQTPlotter): Styling different aspects of boxplots {#JKQTPlotterBoxplotStyling}
|
||||
This project (see [`test_styledboxplot`](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/test_styledboxplot) demonstrates how to style different aspects of boxplots and how to draw different types and styles of boxplots. For a simple introduction into how to use boxplots, see [Plotting Box Plots](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/simpletest_boxplot) and [Plotting a Statistical Distribution of Data](https://github.com/jkriege2/JKQtPlotter/tree/master/examples/test_distributionplot).
|
||||
|
||||
[JKQTPlotterBasicJKQTPDatastore]: @ref JKQTPlotterBasicJKQTPDatastore "Basic Usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreIterators]: @ref JKQTPlotterBasicJKQTPDatastoreIterators "Iterator-Based usage of JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics "Advanced 1-Dimensional Statistics with JKQTPDatastore"
|
||||
[JKQTPlotterBasicJKQTPDatastoreRegression]: @ref JKQTPlotterBasicJKQTPDatastoreRegression "Regression Analysis (with the Statistics Library)"
|
||||
[JKQTPlotterBasicJKQTPDatastoreStatistics2D]: @ref JKQTPlotterBasicJKQTPDatastoreStatistics2D "Advanced 2-Dimensional Statistics with JKQTPDatastore"
|
||||
[statisticslibrary]: @ref jkqtptools_math_statistics "JKQTPlotter Statistics Library"
|
||||
[JKQTPlotterBoxplotStyling]: @ref JKQTPlotterBoxplotStyling "Styling different aspects of boxplots"
|
||||
[JKQTPlotterBoxplotsGraphs]: @ref JKQTPlotterBoxplotsGraphs "Boxplots"
|
||||
|
||||
***Note*** that this example explains how to style boxplots. The example [JKQTPlotterBoxplotsGraphs] explains basics of how to create boxplots. The internal [statisticslibrary] offers methods to calculate the statistical properties necessary for boxplots, which is explained in the tutorial [JKQTPlotterBasicJKQTPDatastoreStatistics] in detail.
|
||||
|
||||
|
||||
|
||||
The link http://vita.had.co.nz/papers/boxplots.pdf leads to a paper that described the history and different types of boxplots.
|
||||
|
||||
The source code of the main application can be found in [`test_styledboxplot.cpp`](test_styledboxplot.cpp).
|
||||
|
||||
@ -40,9 +40,6 @@
|
||||
#include "jkqtcommon/jkqtpdebuggingtools.h"
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
/*! \brief calculates the average of a given data range \a first ... \a last
|
||||
\ingroup jkqtptools_math_statistics_basic
|
||||
|
||||
@ -78,6 +75,8 @@ inline double jkqtpstatAverage(InputIt first, InputIt last, size_t* Noutput=null
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
/*! \brief calculates the weighted average of a given data range \a first ... \a last
|
||||
\ingroup jkqtptools_math_statistics_basic
|
||||
|
||||
|
||||
@ -19,4 +19,22 @@
|
||||
|
||||
|
||||
|
||||
#include "jkqtpstatisticstools.h"
|
||||
#include "jkqtpstatgrouped.h"
|
||||
|
||||
double jkqtpstatGroupingIdentity1D(double v) {
|
||||
return v;
|
||||
}
|
||||
|
||||
double jkqtpstatGroupingRound1D(double v) {
|
||||
return round(v);
|
||||
}
|
||||
|
||||
double jkqtpstatGroupingCustomRound1D(double v, double firstGroupCenter, double groupWidth) {
|
||||
return round((v-firstGroupCenter)/(2.0*groupWidth));
|
||||
}
|
||||
|
||||
|
||||
JKQTPStatGroupDefinitionFunctor1D jkqtpstatMakeGroupingCustomRound1D(double firstGroupCenter, double groupWidth)
|
||||
{
|
||||
return std::bind(&jkqtpstatGroupingCustomRound1D, std::placeholders::_1, firstGroupCenter, groupWidth);
|
||||
}
|
||||
237
lib/jkqtcommon/jkqtpstatgrouped.h
Normal file
237
lib/jkqtcommon/jkqtpstatgrouped.h
Normal file
@ -0,0 +1,237 @@
|
||||
/*
|
||||
Copyright (c) 2008-2019 Jan W. Krieger (<jan@jkrieger.de>)
|
||||
|
||||
last modification: $LastChangedDate$ (revision $Rev$)
|
||||
|
||||
This software is free software: you can redistribute it and/or modify
|
||||
it under the terms of the GNU Lesser General Public License (LGPL) as published by
|
||||
the Free Software Foundation, either version 2.1 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
This program is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU Lesser General Public License (LGPL) for more details.
|
||||
|
||||
You should have received a copy of the GNU Lesser General Public License (LGPL)
|
||||
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
||||
*/
|
||||
|
||||
|
||||
#ifndef JKQTPSTATGROUPED_H_INCLUDED
|
||||
#define JKQTPSTATGROUPED_H_INCLUDED
|
||||
|
||||
#include <stdint.h>
|
||||
#include <cmath>
|
||||
#include <stdlib.h>
|
||||
#include <string.h>
|
||||
#include <iostream>
|
||||
#include <stdio.h>
|
||||
#include <limits>
|
||||
#include <vector>
|
||||
#include <utility>
|
||||
#include <cfloat>
|
||||
#include <ostream>
|
||||
#include <iomanip>
|
||||
#include <sstream>
|
||||
#include "jkqtcommon/jkqtp_imexport.h"
|
||||
#include "jkqtcommon/jkqtplinalgtools.h"
|
||||
#include "jkqtcommon/jkqtparraytools.h"
|
||||
#include "jkqtcommon/jkqtpdebuggingtools.h"
|
||||
#include "jkqtcommon/jkqtpstatbasics.h"
|
||||
|
||||
/*! \brief a functor \f$ f(x): \mathbb{R}\rightarrow\mathbb{R} \f$ which assignes a value \f$ x \f$ to a group center \f$ f(x) \f$
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
The simplest version are e.g.
|
||||
- jkqtpstatGroupingIdentity1D()
|
||||
- jkqtpstatGroupingRound1D()
|
||||
- jkqtpstatGroupingCustomRound1D()
|
||||
.
|
||||
|
||||
\see jkqtpstatGroupData
|
||||
*/
|
||||
typedef std::function<double(double)> JKQTPStatGroupDefinitionFunctor1D;
|
||||
|
||||
|
||||
|
||||
/*! \brief use a column value as group ID directly
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
\see JKQTPStatGroupDefinitionFunctor1D
|
||||
*/
|
||||
double jkqtpstatGroupingIdentity1D(double v);
|
||||
/*! \brief use a rounded column value as group ID directly \f$ f(x)=\mbox{round}(x) \f$
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
\see JKQTPStatGroupDefinitionFunctor1D
|
||||
*/
|
||||
double jkqtpstatGroupingRound1D(double v);
|
||||
/*! \brief assign each value to groups \f$ \mbox{firstGroupCenter}, \mbox{firstGroupCenter}\pm\mbox{groupWidth}/2, \mbox{firstGroupCenter}\pm2\cdot\mbox{groupWidth}/2, , \mbox{firstGroupCenter}\pm3\cdot\mbox{groupWidth}/2, ... \f$
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
This is equivalent to \f$ \mbox{round}\left(\frac{x-\mbox{firstGroupCenter}}{\mbox{groupWidth}/2}\right) \f$
|
||||
|
||||
\see JKQTPStatGroupDefinitionFunctor1D, jkqtpstatMakeGroupingCustomRound1D() for a factory-function that returns a functor of this function bound to specific arguments.
|
||||
*/
|
||||
double jkqtpstatGroupingCustomRound1D(double v, double firstGroupCenter, double groupWidth);
|
||||
/*! \brief generates a functor of jkqtpstatGroupingCustomRound1D() with the two paramaters \a firstGroupCenter and \a groupWidth fixed to the given values
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
This is equivalent to \c std::bind(&jkqtpstatGroupingCustomRound1D,std::placeholders::_1,firstGroupCenter,groupWidth);
|
||||
|
||||
\see JKQTPStatGroupDefinitionFunctor1D, jkqtpstatGroupingCustomRound1D()
|
||||
*/
|
||||
JKQTPStatGroupDefinitionFunctor1D jkqtpstatMakeGroupingCustomRound1D(double firstGroupCenter, double groupWidth);
|
||||
|
||||
|
||||
|
||||
/*! \brief groups data from an input range \a inFirstCat / \a inFirstValue ... \a inLastCat / \a outFirstCat representing pairs \f$ (c_i,v_i) \f$ of a
|
||||
category value \f$ c_i \f$ and a group value \f$ v_i \f$ into groups \f$ V_j=\{v_{i}|c_i\equiv c_{\text{out},j}\} \f$ of data that were assigned
|
||||
to the same group, i.e. \f$ c_i\equiv c_{\text{out},j} \f$ . A functor \a groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat and \a inLastCat
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue and \a inLastValue
|
||||
\param inFirstCat iterator pointing to the first item in the category dataset to use \f$ c_1 \f$
|
||||
\param inLastCat iterator pointing behind the last item in the category dataset to use \f$ c_N \f$
|
||||
\param inFirstValue iterator pointing to the first item in the category dataset to use \f$ v_1 \f$
|
||||
\param inLastValue iterator pointing behind the last item in the category dataset to use \f$ v_N \f$
|
||||
\param[out] groupeddata receives the grouped data, each key in the map represents one group, each map-value contains a vector with the value data
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
|
||||
\note the contents of \a groupeddata is not cleared before usage, so you can also use this fucntion to append to a group!
|
||||
|
||||
\see JKQTPStatGroupDefinitionFunctor1D, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline void jkqtpstatGroupData(InputCatIt inFirstCat, InputCatIt inLastCat, InputValueIt inFirstValue, InputValueIt inLastValue, std::map<double, std::vector<double> >& groupeddata, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D) {
|
||||
auto inCat=inFirstCat;
|
||||
auto inVal=inFirstValue;
|
||||
for (; inCat!=inLastCat && inVal!=inLastValue; ++inCat, ++inVal) {
|
||||
const double c=jkqtp_todouble(*inCat);
|
||||
const double v=jkqtp_todouble(*inVal);
|
||||
if (JKQTPIsOKFloat(c) && JKQTPIsOKFloat(v)) {
|
||||
const double g=groupDefFunc(c);
|
||||
groupeddata[g].push_back(v);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/*! \brief groups data from an input range \a inFirstCat / \a inFirstValue ... \a inLastCat / \a outFirstCat representing pairs \f$ (c_i,v_i) \f$ of a
|
||||
category value \f$ c_i \f$ and a group value \f$ v_i \f$ into groups \f$ V_j=\{v_{i}|c_i\equiv c_{\text{out},j}\} \f$ of data that were assigned
|
||||
to the same group, i.e. \f$ c_i\equiv c_{\text{out},j} \f$ . A functor \a groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat and \a inLastCat
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue and \a inLastValue
|
||||
\tparam OutputGroupIt standard output iterator type of \a outFirstCategory
|
||||
\param inFirstCat iterator pointing to the first item in the category dataset to use \f$ c_1 \f$
|
||||
\param inLastCat iterator pointing behind the last item in the category dataset to use \f$ c_N \f$
|
||||
\param inFirstValue iterator pointing to the first item in the category dataset to use \f$ v_1 \f$
|
||||
\param inLastValue iterator pointing behind the last item in the category dataset to use \f$ v_N \f$
|
||||
\param[out] outFirstCategory for each element in the range \a inFirstCat / \a inFirstValue ... \a inLastCat / \a outFirstCat this receives the calculated category
|
||||
\param[out] groupeddata receives the grouped data, each key in the map represents one group, each map-value contains a vector with the value data
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
|
||||
\note the contents of \a groupeddata is not cleared before usage, so you can also use this fucntion to append to a group!
|
||||
|
||||
\see JKQTPStatGroupDefinitionFunctor1D, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt, class OutputGroupIt>
|
||||
inline void jkqtpstatGroupData(InputCatIt inFirstCat, InputCatIt inLastCat, InputValueIt inFirstValue, InputValueIt inLastValue, OutputGroupIt outFirstCategory, std::map<double, std::vector<double> >& groupeddata, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D) {
|
||||
auto inCat=inFirstCat;
|
||||
auto inVal=inFirstValue;
|
||||
auto outCat=outFirstCategory;
|
||||
for (; inCat!=inLastCat && inVal!=inLastValue; ++inCat, ++inVal) {
|
||||
const double c=jkqtp_todouble(*inCat);
|
||||
const double v=jkqtp_todouble(*inVal);
|
||||
if (JKQTPIsOKFloat(c) && JKQTPIsOKFloat(v)) {
|
||||
const double g=groupDefFunc(c);
|
||||
groupeddata[g].push_back(v);
|
||||
*outCat=g;
|
||||
} else {
|
||||
*outCat=JKQTP_DOUBLE_NAN;
|
||||
}
|
||||
++outCat;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/*! \brief groups data from an input range \a inFirstCat / \a inFirstValue ... \a inLastCat / \a outFirstCat representing pairs \f$ (c_i,v_i) \f$ of a
|
||||
category value \f$ c_i \f$ and a group value \f$ v_i \f$ into groups \f$ V_j=\{v_{i}|c_i\equiv c_{\text{out},j}\} \f$ of data that were assigned
|
||||
to the same group, i.e. \f$ c_i\equiv c_{\text{out},j} \f$ . A functor \a groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat and \a inLastCat
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue and \a inLastValue
|
||||
\param inFirstCat iterator pointing to the first item in the category dataset to use \f$ c_1 \f$
|
||||
\param inLastCat iterator pointing behind the last item in the category dataset to use \f$ c_N \f$
|
||||
\param inFirstValue iterator pointing to the first item in the category dataset to use \f$ v_1 \f$
|
||||
\param inLastValue iterator pointing behind the last item in the category dataset to use \f$ v_N \f$
|
||||
\param[out] groupeddata receives the grouped data, each key in the map represents one group, each map-value contains two vecors with the category and value data respectively
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
|
||||
\note the contents of \a groupeddata is not cleared before usage, so you can also use this fucntion to append to a group!
|
||||
|
||||
\see JKQTPStatGroupDefinitionFunctor1D, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline void jkqtpstatGroupData(InputCatIt inFirstCat, InputCatIt inLastCat, InputValueIt inFirstValue, InputValueIt inLastValue, std::map<double, std::pair<std::vector<double>,std::vector<double> > >& groupeddata, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D) {
|
||||
auto inCat=inFirstCat;
|
||||
auto inVal=inFirstValue;
|
||||
for (; inCat!=inLastCat && inVal!=inLastValue; ++inCat, ++inVal) {
|
||||
const double c=jkqtp_todouble(*inCat);
|
||||
const double v=jkqtp_todouble(*inVal);
|
||||
if (JKQTPIsOKFloat(c) && JKQTPIsOKFloat(v)) {
|
||||
const double g=groupDefFunc(c);
|
||||
groupeddata[g].first.push_back(c);
|
||||
groupeddata[g].second.push_back(v);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/*! \brief groups data from an input range \a inFirstCat / \a inFirstValue ... \a inLastCat / \a outFirstCat representing pairs \f$ (c_i,v_i) \f$ of a
|
||||
category value \f$ c_i \f$ and a group value \f$ v_i \f$ into groups \f$ V_j=\{v_{i}|c_i\equiv c_{\text{out},j}\} \f$ of data that were assigned
|
||||
to the same group, i.e. \f$ c_i\equiv c_{\text{out},j} \f$ . A functor \a groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\ingroup jkqtptools_math_statistics_grouped
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat and \a inLastCat
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue and \a inLastValue
|
||||
\tparam OutputGroupIt standard output iterator type of \a outFirstCategory
|
||||
\param inFirstCat iterator pointing to the first item in the category dataset to use \f$ c_1 \f$
|
||||
\param inLastCat iterator pointing behind the last item in the category dataset to use \f$ c_N \f$
|
||||
\param inFirstValue iterator pointing to the first item in the category dataset to use \f$ v_1 \f$
|
||||
\param inLastValue iterator pointing behind the last item in the category dataset to use \f$ v_N \f$
|
||||
\param[out] outFirstCategory for each element in the range \a inFirstCat / \a inFirstValue ... \a inLastCat / \a outFirstCat this receives the calculated category
|
||||
\param[out] groupeddata receives the grouped data, each key in the map represents one group, each map-value contains two vecors with the category and value data respectively
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
|
||||
\note the contents of \a groupeddata is not cleared before usage, so you can also use this fucntion to append to a group!
|
||||
|
||||
\see JKQTPStatGroupDefinitionFunctor1D, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt, class OutputGroupIt>
|
||||
inline void jkqtpstatGroupData(InputCatIt inFirstCat, InputCatIt inLastCat, InputValueIt inFirstValue, InputValueIt inLastValue, OutputGroupIt outFirstCategory, std::map<double, std::pair<std::vector<double>,std::vector<double> > >& groupeddata, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D) {
|
||||
auto inCat=inFirstCat;
|
||||
auto inVal=inFirstValue;
|
||||
auto outCat=outFirstCategory;
|
||||
for (; inCat!=inLastCat && inVal!=inLastValue; ++inCat, ++inVal) {
|
||||
const double c=jkqtp_todouble(*inCat);
|
||||
const double v=jkqtp_todouble(*inVal);
|
||||
if (JKQTPIsOKFloat(c) && JKQTPIsOKFloat(v)) {
|
||||
const double g=groupDefFunc(c);
|
||||
groupeddata[g].first.push_back(c);
|
||||
groupeddata[g].second.push_back(v);
|
||||
*outCat=g;
|
||||
} else {
|
||||
*outCat=JKQTP_DOUBLE_NAN;
|
||||
}
|
||||
++outCat;
|
||||
}
|
||||
}
|
||||
|
||||
#endif // JKQTPSTATGROUPED_H_INCLUDED
|
||||
|
||||
|
||||
@ -27,6 +27,7 @@
|
||||
#include "jkqtcommon/jkqtpstatkde.h"
|
||||
#include "jkqtcommon/jkqtpstatpoly.h"
|
||||
#include "jkqtcommon/jkqtpstatregression.h"
|
||||
#include "jkqtcommon/jkqtpstatgrouped.h"
|
||||
|
||||
|
||||
#endif // JKQTPSTATISTICSTOOLS_H_INCLUDED
|
||||
|
||||
@ -46,7 +46,6 @@
|
||||
|
||||
/*! \brief fits (in a least-squares sense) a polynomial \f$ f(x)=\sum\limits_{i=0}^Pp_ix^i \f$ of order P to a set of N data pairs \f$ (x_i,y_i) \f$
|
||||
\ingroup jkqtptools_math_statistics_poly
|
||||
\ingroup jkqtptools_math_statistics_regression
|
||||
|
||||
\tparam InputItX standard iterator type of \a firstX and \a lastX.
|
||||
\tparam InputItY standard iterator type of \a firstY and \a lastY.
|
||||
|
||||
@ -35,7 +35,9 @@ isEmpty(JKQTP_COMMON_PRI_INCLUDED) {
|
||||
$$PWD/jkqtcommon/jkqtpstathistogram.h \
|
||||
$$PWD/jkqtcommon/jkqtpstatkde.h \
|
||||
$$PWD/jkqtcommon/jkqtpstatregression.h \
|
||||
$$PWD/jkqtcommon/jkqtpstatpoly.h
|
||||
$$PWD/jkqtcommon/jkqtpstatpoly.h \
|
||||
$$PWD/jkqtcommon/jkqtpstatgrouped.h
|
||||
|
||||
|
||||
|
||||
SOURCES += $$PWD/jkqtcommon/jkqtpdebuggingtools.cpp \
|
||||
@ -51,12 +53,12 @@ isEmpty(JKQTP_COMMON_PRI_INCLUDED) {
|
||||
$$PWD/jkqtcommon/jkqtpmathparser.cpp \
|
||||
$$PWD/jkqtcommon/jkqttools.cpp \
|
||||
$$PWD/jkqtcommon/jkqtparraytools.cpp \
|
||||
$$PWD/jkqtcommon/jkqtpstatisticstools.cpp \
|
||||
$$PWD/jkqtcommon/jkqtpstatbasics.cpp \
|
||||
$$PWD/jkqtcommon/jkqtpstathistogram.cpp \
|
||||
$$PWD/jkqtcommon/jkqtpstatkde.cpp \
|
||||
$$PWD/jkqtcommon/jkqtpstatregression.cpp \
|
||||
$$PWD/jkqtcommon/jkqtpstatpoly.cpp
|
||||
$$PWD/jkqtcommon/jkqtpstatpoly.cpp \
|
||||
$$PWD/jkqtcommon/jkqtpstatgrouped.cpp
|
||||
|
||||
|
||||
INCLUDEPATH += $$PWD
|
||||
|
||||
@ -54,7 +54,7 @@
|
||||
You can use JKQTPlotter::addHorizontalBargraph() to add a series of bargraphs, where the width and shift are determined
|
||||
automatically. The y-columns are given as a QVector<int> to this function.
|
||||
|
||||
|
||||
\see JKQTPBarHorizontalGraph, \ref JKQTPlotterBarcharts, jkqtpstatAddHHistogram1D(), jkqtpstatAddHHistogram1DAutoranged()
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBarVerticalGraph: public JKQTPXYGraph, public JKQTPGraphLineStyleMixin, public JKQTPGraphFillStyleMixin {
|
||||
Q_OBJECT
|
||||
@ -173,6 +173,7 @@ class JKQTP_LIB_EXPORT JKQTPBarVerticalGraph: public JKQTPXYGraph, public JKQTPG
|
||||
* Draw stacked barcharts by connecting several plots by calling \c setStackedParent(belowPlot) for each plot
|
||||
* \image html JKQTPBarVerticalGraphStacked.png
|
||||
*
|
||||
* \see JKQTPBarVerticalGraph, \ref JKQTPlotterStackedBarChart
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBarVerticalStackableGraph: public JKQTPBarVerticalGraph {
|
||||
Q_OBJECT
|
||||
@ -212,6 +213,7 @@ class JKQTP_LIB_EXPORT JKQTPBarVerticalStackableGraph: public JKQTPBarVerticalGr
|
||||
* This works much the same as JKQTPBarHorizontalGraph. Here is an example output:
|
||||
* \image html plot_bargraphverploterr.png
|
||||
*
|
||||
* \see jkqtpstatAddYErrorBarGraph(), JKQTPBarVerticalGraph, \ref JKQTPlotterBarcharts
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBarVerticalErrorGraph: public JKQTPBarVerticalGraph, public JKQTPYGraphErrors {
|
||||
Q_OBJECT
|
||||
@ -241,8 +243,11 @@ class JKQTP_LIB_EXPORT JKQTPBarVerticalErrorGraph: public JKQTPBarVerticalGraph,
|
||||
\ingroup jkqtplotter_barssticks
|
||||
|
||||
This works much the same as JKQTPBarHorizontalGraph. Here is an example output:
|
||||
|
||||
\image html plot_bargraphhorplot.png
|
||||
|
||||
|
||||
\see \ref JKQTPlotterBarcharts, jkqtpstatAddVHistogram1D(), jkqtpstatAddVHistogram1DAutoranged()
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBarHorizontalGraph: public JKQTPBarVerticalGraph {
|
||||
Q_OBJECT
|
||||
@ -279,6 +284,8 @@ class JKQTP_LIB_EXPORT JKQTPBarHorizontalGraph: public JKQTPBarVerticalGraph {
|
||||
* Draw stacked barcharts by connecting several plots by calling \c setStackedParent(belowPlot) for each plot
|
||||
* \image html JKQTPBarHorizontalGraphStacked.png
|
||||
*
|
||||
*
|
||||
* \see JKQTPBarHorizontalGraph, \ref JKQTPlotterStackedBarChart
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBarHorizontalStackableGraph: public JKQTPBarHorizontalGraph {
|
||||
Q_OBJECT
|
||||
@ -318,6 +325,8 @@ class JKQTP_LIB_EXPORT JKQTPBarHorizontalStackableGraph: public JKQTPBarHorizont
|
||||
* This works much the same as JKQTPBarHorizontalGraph. Here is an example output:
|
||||
* \image html plot_bargraphhorploterr.png
|
||||
*
|
||||
* \see jkqtpstatAddXErrorBarGraph(), JKQTPBarHorizontalGraph, \ref JKQTPlotterBarcharts
|
||||
*
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBarHorizontalErrorGraph: public JKQTPBarHorizontalGraph, public JKQTPXGraphErrors {
|
||||
Q_OBJECT
|
||||
|
||||
@ -95,7 +95,7 @@
|
||||
graphOutliers->setSymbolSize(7);
|
||||
\endcode
|
||||
|
||||
\see \ref JKQTPlotterBoxplotsGraphs
|
||||
\see \ref JKQTPlotterBoxplotsGraphs, jkqtpstatVAddBoxplots(),\ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat, \ref JKQTPlotterBasicJKQTPDatastoreStatistics, \ref JKQTPlotterBoxplotStyling
|
||||
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBoxplotVerticalGraph: public JKQTPGraph, public JKQTPGraphBoxplotStyleMixin {
|
||||
@ -252,7 +252,7 @@ class JKQTP_LIB_EXPORT JKQTPBoxplotVerticalGraph: public JKQTPGraph, public JKQT
|
||||
|
||||
\note See the documentation of JKQTPBoxplotVerticalGraph for details on the properties of this class!
|
||||
|
||||
\see JKQTPBoxplotVerticalGraph \ref JKQTPlotterBoxplotsGraphs
|
||||
\see JKQTPBoxplotVerticalGraph \ref JKQTPlotterBoxplotsGraphs, jkqtpstatHAddBoxplots(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat, \ref JKQTPlotterBasicJKQTPDatastoreStatistics, \ref JKQTPlotterBoxplotStyling
|
||||
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBoxplotHorizontalGraph: public JKQTPBoxplotVerticalGraph {
|
||||
@ -306,6 +306,8 @@ class JKQTP_LIB_EXPORT JKQTPBoxplotHorizontalGraph: public JKQTPBoxplotVerticalG
|
||||
|
||||
\image html test_styledboxplot.png
|
||||
|
||||
\see jkqtpstatVAddBoxplot(), \ref JKQTPlotterBasicJKQTPDatastoreStatistics, \ref JKQTPlotterBoxplotsGraphs, \ref JKQTPlotterBoxplotStyling, jkqtpstatAddVBoxplotAndOutliers()
|
||||
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBoxplotVerticalElement: public JKQTPPlotObject, public JKQTPGraphBoxplotStyleMixin {
|
||||
Q_OBJECT
|
||||
@ -428,7 +430,8 @@ class JKQTP_LIB_EXPORT JKQTPBoxplotVerticalElement: public JKQTPPlotObject, publ
|
||||
|
||||
\note See JKQTPBoxplotVerticalElement for a detailed documentation
|
||||
|
||||
\see JKQTPBoxplotVerticalElement
|
||||
\see JKQTPBoxplotVerticalElement, jkqtpstatHAddBoxplot(), \ref JKQTPlotterBasicJKQTPDatastoreStatistics, \ref JKQTPlotterBoxplotsGraphs, \ref JKQTPlotterBoxplotStyling, jkqtpstatAddHBoxplotAndOutliers()
|
||||
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPBoxplotHorizontalElement: public JKQTPBoxplotVerticalElement {
|
||||
Q_OBJECT
|
||||
|
||||
@ -247,6 +247,8 @@ class JKQTP_LIB_EXPORT JKQTPContourPlot: public JKQTPMathImage, public JKQTPGrap
|
||||
* \ingroup jkqtplotter_imagelots_contour
|
||||
*
|
||||
* \copydetails JKQTPContourPlot
|
||||
*
|
||||
* \see jkqtpstatAddKDE2DContour(), jkqtpstatAddHistogram2DContour(), \ref JKQTPlotterContourPlot, \ref JKQTPlotterBasicJKQTPDatastoreStatistics2D
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPColumnContourPlot: public JKQTPContourPlot {
|
||||
Q_OBJECT
|
||||
|
||||
@ -65,6 +65,8 @@ typedef std::function<double(double)> jkqtpSimplePlotFunctionType;
|
||||
|
||||
the following image
|
||||
\image html plot_functionplots.png
|
||||
|
||||
\see \ref JKQTPlotterFunctionPlots, jkqtpstatAddPolyFit(), jkqtpstatAddWeightedRegression(), jkqtpstatAddRobustIRLSRegression(), jkqtpstatAddRegression(), jkqtpstatAddLinearWeightedRegression(), jkqtpstatAddRobustIRLSLinearRegression(), jkqtpstatAddLinearRegression()
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPXFunctionLineGraph: public JKQTPGraph, public JKQTPGraphLineStyleMixin, public JKQTPGraphFillStyleMixin {
|
||||
Q_OBJECT
|
||||
@ -392,6 +394,7 @@ class JKQTP_LIB_EXPORT JKQTPXFunctionLineGraph: public JKQTPGraph, public JKQTPG
|
||||
/*! \brief This implements line plots where the data is taken from a user supplied function \f$ x=f(y) \f$
|
||||
\ingroup jkqtplotter_functiongraphs
|
||||
|
||||
\see \ref JKQTPlotterFunctionPlots
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPYFunctionLineGraph: public JKQTPXFunctionLineGraph {
|
||||
Q_OBJECT
|
||||
|
||||
@ -54,7 +54,7 @@ class JKQTP_LIB_EXPORT JKQTPFilledCurveXGraph: public JKQTPSpecialLineHorizontal
|
||||
\image html plot_filledcurvexerrorplots.png
|
||||
|
||||
|
||||
\see \ref JKQTPlotterFilledGraphs
|
||||
\see \ref JKQTPlotterFilledGraphs, jkqtpstatAddXErrorFilledCurveGraph()
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPFilledCurveXErrorGraph: public JKQTPFilledCurveXGraph, public JKQTPYGraphErrors {
|
||||
Q_OBJECT
|
||||
@ -103,7 +103,7 @@ class JKQTP_LIB_EXPORT JKQTPFilledCurveYGraph: public JKQTPSpecialLineVerticalGr
|
||||
|
||||
\image html plot_filledcurveyerrorplots.png
|
||||
|
||||
\see \ref JKQTPlotterFilledGraphs
|
||||
\see \ref JKQTPlotterFilledGraphs, jkqtpstatAddYErrorFilledCurveGraph()
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPFilledCurveYErrorGraph: public JKQTPFilledCurveYGraph, public JKQTPXGraphErrors {
|
||||
Q_OBJECT
|
||||
|
||||
@ -334,6 +334,8 @@ class JKQTP_LIB_EXPORT JKQTPMathImageBase: public JKQTPImageBase {
|
||||
\ingroup jkqtplotter_imagelots_elements
|
||||
|
||||
\image html jkqtplotter_simpletest_rgbimageplot_qt.png
|
||||
|
||||
\see \ref JKQTPlotterImagePlotQImageRGB
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPImage: public JKQTPImageBase {
|
||||
Q_OBJECT
|
||||
@ -467,6 +469,8 @@ class JKQTP_LIB_EXPORT JKQTPImage: public JKQTPImageBase {
|
||||
\image html jkqtplotter_simpletest_imageplot.png
|
||||
\image html jkqtplotter_simpletest_imageplot_modifier.png
|
||||
\image html jkqtplotter_simpletest_imageplot__smallscaletransparent.png
|
||||
|
||||
\see \ref JKQTPlotterImagePlotNoDatastore
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPMathImage: public JKQTPMathImageBase {
|
||||
Q_OBJECT
|
||||
@ -994,6 +998,7 @@ int JKQTPMathImage::getModifierSampleSize() const {
|
||||
\image html jkqtplotter_simpletest_imageplot_modifier.png
|
||||
\image html jkqtplotter_simpletest_imageplot__smallscaletransparent.png
|
||||
|
||||
\see jkqtpstatAddKDE2DImage(), jkqtpstatAddHistogram2DImage(), \ref JKQTPlotterImagePlot, \ref JKQTPlotterImagePlotModifier, \ref JKQTPlotterImagePlotOpenCV
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPColumnMathImage: public JKQTPMathImage {
|
||||
Q_OBJECT
|
||||
|
||||
@ -31,6 +31,8 @@
|
||||
\ingroup jkqtplotter_barssticks
|
||||
|
||||
\image html plot_impulsesxplots.png
|
||||
|
||||
\see JKQTPImpulsesVerticalGraph, \ref JKQTPlotterImpulsePlots
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPImpulsesHorizontalGraph: public JKQTPXYGraph, public JKQTPGraphLineStyleMixin, public JKQTPGraphSymbolStyleMixin{
|
||||
Q_OBJECT
|
||||
@ -80,6 +82,8 @@ class JKQTP_LIB_EXPORT JKQTPImpulsesHorizontalGraph: public JKQTPXYGraph, public
|
||||
\ingroup jkqtplotter_barssticks
|
||||
|
||||
\image html plot_impulsesxerrorsplots.png
|
||||
|
||||
\see jkqtpstatAddXErrorImpulsesGraph(), JKQTPImpulsesHorizontalGraph, \ref JKQTPlotterImpulsePlots
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPImpulsesHorizontalErrorGraph: public JKQTPImpulsesHorizontalGraph, public JKQTPXGraphErrors {
|
||||
Q_OBJECT
|
||||
@ -103,6 +107,8 @@ class JKQTP_LIB_EXPORT JKQTPImpulsesHorizontalErrorGraph: public JKQTPImpulsesHo
|
||||
\ingroup jkqtplotter_barssticks
|
||||
|
||||
\image html plot_impulsesyplots.png
|
||||
|
||||
\see \ref JKQTPlotterImpulsePlots
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPImpulsesVerticalGraph: public JKQTPImpulsesHorizontalGraph {
|
||||
Q_OBJECT
|
||||
@ -122,6 +128,8 @@ class JKQTP_LIB_EXPORT JKQTPImpulsesVerticalGraph: public JKQTPImpulsesHorizonta
|
||||
\ingroup jkqtplotter_barssticks
|
||||
|
||||
\image html plot_impulsesyerrorsplots.png
|
||||
|
||||
\see JKQTPImpulsesVerticalGraph, jkqtpstatAddYErrorImpulsesGraph(), \ref JKQTPlotterImpulsePlots
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPImpulsesVerticalErrorGraph: public JKQTPImpulsesVerticalGraph, public JKQTPYGraphErrors {
|
||||
Q_OBJECT
|
||||
|
||||
@ -42,6 +42,8 @@ class JKQTPlotter;
|
||||
Parameters may also be given from a data column. Then first the params from the column and the the parameters from the vector are numbered.
|
||||
|
||||
Use the variable \c x in an equation to refer to the free parameter of the curve.
|
||||
|
||||
\see \ref JKQTPlotterParsedFunctionPlot, JKQTPMathParser
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPXParsedFunctionLineGraph: public JKQTPXFunctionLineGraph {
|
||||
Q_OBJECT
|
||||
@ -108,6 +110,9 @@ class JKQTP_LIB_EXPORT JKQTPXParsedFunctionLineGraph: public JKQTPXFunctionLineG
|
||||
Parameters may also be given from a data column. Then first the params from the column and the the parameters from the vector are numbered.
|
||||
|
||||
Use the variable \c y in an equation to refer to the free parameter of the curve (\c is also understood for convenience).
|
||||
|
||||
\see \ref JKQTPlotterParsedFunctionPlot, JKQTPMathParser
|
||||
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPYParsedFunctionLineGraph: public JKQTPYFunctionLineGraph {
|
||||
Q_OBJECT
|
||||
|
||||
@ -42,6 +42,8 @@ class JKQTPDatastore;
|
||||
|
||||
\image html JKQTPPeakStreamGraphY.png "yPeaks=true"
|
||||
\image html JKQTPPeakStreamGraphX.png "yPeaks=false"
|
||||
|
||||
\see \ref JKQTPlotterBasicJKQTPDatastoreStatistics
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPPeakStreamGraph: public JKQTPSingleColumnGraph, public JKQTPGraphLineStyleMixin {
|
||||
Q_OBJECT
|
||||
|
||||
@ -50,6 +50,8 @@ class JKQTPDatastore;
|
||||
\ingroup jkqtplotter_linesymbolgraphs_simple
|
||||
|
||||
\image html plot_lineplots.png
|
||||
|
||||
\see \ref JKQTPlotterAdvancedLineAndFillStyling, \ref JKQTPlotterSimpleTest, \ref JKQTPlotterSymbolsAndStyles, jkqtpstatAddVKDE1D(), jkqtpstatAddVKDE1DAutoranged(), jkqtpstatAddHKDE1D(), jkqtpstatAddHKDE1DAutoranged()
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPXYLineGraph: public JKQTPXYGraph, public JKQTPGraphLineStyleMixin, public JKQTPGraphSymbolStyleMixin {
|
||||
Q_OBJECT
|
||||
@ -109,7 +111,7 @@ class JKQTP_LIB_EXPORT JKQTPXYLineGraph: public JKQTPXYGraph, public JKQTPGraphL
|
||||
\image html JKQTPXYParametrizedScatterGraph_SymbolFunctor.png
|
||||
|
||||
|
||||
\see JKQTPXYParametrizedErrorScatterGraph, \ref JKQTPlotterParamScatter , \ref JKQTPlotterParamScatterImage
|
||||
\see JKQTPXYParametrizedErrorScatterGraph, \ref JKQTPlotterParamScatter , \ref JKQTPlotterParamScatterImage, \ref JKQTPlotterParametricCurves
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPXYParametrizedScatterGraph: public JKQTPXYLineGraph, public JKQTPColorPaletteStyleAndToolsMixin {
|
||||
Q_OBJECT
|
||||
@ -367,6 +369,8 @@ class JKQTP_LIB_EXPORT JKQTPXYParametrizedScatterGraph: public JKQTPXYLineGraph,
|
||||
\image html plot_errorbarlineplots.png
|
||||
\image html plot_errorlinelineplots.png
|
||||
\image html plot_errorpolygonlineplots.png
|
||||
|
||||
\see jkqtpstatAddXYErrorLineGraph(), jkqtpstatAddXErrorLineGraph(), jkqtpstatAddYErrorLineGraph(), \ref JKQTPlotterErrorBarStyles, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPXYLineErrorGraph: public JKQTPXYLineGraph, public JKQTPXYGraphErrors {
|
||||
Q_OBJECT
|
||||
@ -403,7 +407,7 @@ class JKQTP_LIB_EXPORT JKQTPXYLineErrorGraph: public JKQTPXYLineGraph, public JK
|
||||
|
||||
\image html screen_parmetrizedplots_datatable.png
|
||||
|
||||
\see JKQTPXYParametrizedScatterGraph, \ref JKQTPlotterParamScatter
|
||||
\see JKQTPXYParametrizedScatterGraph, \ref JKQTPlotterParamScatter, jkqtpstatAddXErrorParametrizedScatterGraph(), jkqtpstatAddYErrorParametrizedScatterGraph()
|
||||
*/
|
||||
class JKQTP_LIB_EXPORT JKQTPXYParametrizedErrorScatterGraph: public JKQTPXYParametrizedScatterGraph, public JKQTPXYGraphErrors {
|
||||
Q_OBJECT
|
||||
|
||||
@ -30,6 +30,8 @@
|
||||
#include "jkqtplotter/jkqtpgraphsevaluatedfunction.h"
|
||||
#include "jkqtplotter/jkqtpgraphsimage.h"
|
||||
#include "jkqtplotter/jkqtpgraphscontour.h"
|
||||
#include "jkqtplotter/jkqtpgraphsimpulses.h"
|
||||
#include "jkqtplotter/jkqtpgraphsfilledcurve.h"
|
||||
|
||||
|
||||
#ifndef JKQTPGRAPHSSTATISTICSADAPTORS_H_INCLUDED
|
||||
@ -1788,4 +1790,735 @@ JKQTP_LIB_EXPORT JKQTPXFunctionLineGraph* jkqtpstatAddPolyFit(JKQTPXYGraph *data
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
/*! \brief create a plot with y-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam TGraph type of graph that should be added to the plot
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt, class TGraph>
|
||||
inline 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")) {
|
||||
std::map<double, std::vector<double> > groupeddataBar;
|
||||
jkqtpstatGroupData(inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupeddataBar, groupDefFunc);
|
||||
|
||||
size_t colGroup=plotter->getDatastore()->addColumn(columnBaseName+", group");
|
||||
size_t colAverage=plotter->getDatastore()->addColumn(columnBaseName+", average");
|
||||
size_t colStdDev=plotter->getDatastore()->addColumn(columnBaseName+", stddev");
|
||||
|
||||
for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
|
||||
plotter->getDatastore()->appendToColumn(colGroup, it->first);
|
||||
plotter->getDatastore()->appendToColumn(colAverage, jkqtpstatAverage(it->second.begin(), it->second.end()));
|
||||
plotter->getDatastore()->appendToColumn(colStdDev, jkqtpstatStdDev(it->second.begin(), it->second.end()));
|
||||
}
|
||||
|
||||
// 2.4. Finally the calculated groups are drawn
|
||||
TGraph* graph;
|
||||
plotter->addGraph(graph=new TGraph(plotter));
|
||||
graph->setXColumn(colGroup);
|
||||
graph->setYColumn(colAverage);
|
||||
graph->setYErrorColumn(static_cast<int>(colStdDev));
|
||||
|
||||
return graph;
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPXYLineErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPXYLineErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddYErrorGraph<InputCatIt,InputValueIt,JKQTPXYLineErrorGraph>(plotter,inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPBarVerticalErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPBarVerticalErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddYErrorGraph<InputCatIt,InputValueIt,JKQTPBarVerticalErrorGraph>(plotter,inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPImpulsesVerticalErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPImpulsesVerticalErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddYErrorGraph<InputCatIt,InputValueIt,JKQTPImpulsesVerticalErrorGraph>(plotter,inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPXYParametrizedErrorScatterGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPXYParametrizedErrorScatterGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddYErrorGraph<InputCatIt,InputValueIt,JKQTPXYParametrizedErrorScatterGraph>(plotter,inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPFilledCurveYErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddYErrorGraph(), JKQTPFilledCurveYErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddYErrorGraph<InputCatIt,InputValueIt,JKQTPFilledCurveYErrorGraph>(plotter,inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
/*! \brief create a plot with x-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam TGraph type of graph that should be added to the plot
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt, class TGraph>
|
||||
inline 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")) {
|
||||
std::map<double, std::vector<double> > groupeddataBar;
|
||||
jkqtpstatGroupData(inFirstCat_Y, inLastCat_Y, inFirstValue_Y, inLastValue_Y, groupeddataBar, groupDefFunc);
|
||||
|
||||
size_t colGroup=plotter->getDatastore()->addColumn(columnBaseName+", group");
|
||||
size_t colAverage=plotter->getDatastore()->addColumn(columnBaseName+", average");
|
||||
size_t colStdDev=plotter->getDatastore()->addColumn(columnBaseName+", stddev");
|
||||
|
||||
for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
|
||||
plotter->getDatastore()->appendToColumn(colGroup, it->first);
|
||||
plotter->getDatastore()->appendToColumn(colAverage, jkqtpstatAverage(it->second.begin(), it->second.end()));
|
||||
plotter->getDatastore()->appendToColumn(colStdDev, jkqtpstatStdDev(it->second.begin(), it->second.end()));
|
||||
}
|
||||
|
||||
// 2.4. Finally the calculated groups are drawn
|
||||
TGraph* graph;
|
||||
plotter->addGraph(graph=new TGraph(plotter));
|
||||
graph->setXColumn(colAverage);
|
||||
graph->setYColumn(colGroup);
|
||||
graph->setXErrorColumn(static_cast<int>(colStdDev));
|
||||
|
||||
return graph;
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPXYLineErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPXYLineErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddXErrorGraph<InputCatIt,InputValueIt,JKQTPXYLineErrorGraph>(plotter,inFirstCat_Y, inLastCat_Y, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPBarHorizontalErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPBarHorizontalErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddXErrorGraph<InputCatIt,InputValueIt,JKQTPBarHorizontalErrorGraph>(plotter,inFirstCat_Y, inLastCat_Y, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPImpulsesHorizontalErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPImpulsesHorizontalErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddXErrorGraph<InputCatIt,InputValueIt,JKQTPImpulsesHorizontalErrorGraph>(plotter,inFirstCat_Y, inLastCat_Y, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPXYParametrizedErrorScatterGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPXYParametrizedErrorScatterGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddXErrorGraph<InputCatIt,InputValueIt,JKQTPXYParametrizedErrorScatterGraph>(plotter,inFirstCat_Y, inLastCat_Y, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPFilledCurveXErrorGraph with x-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddXErrorGraph(), JKQTPFilledCurveXErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddXErrorGraph<InputCatIt,InputValueIt,JKQTPFilledCurveXErrorGraph>(plotter,inFirstCat_Y, inLastCat_Y, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
/*! \brief create a plot with x- and y-direction error bars, calculated from directional average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam TGraph type of graph that should be added to the plot
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt, class TGraph>
|
||||
inline 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")) {
|
||||
std::map<double, std::pair< std::vector<double>, std::vector<double> > > groupeddataBar;
|
||||
jkqtpstatGroupData(inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupeddataBar, groupDefFunc);
|
||||
|
||||
size_t colGroup=plotter->getDatastore()->addColumn(columnBaseName+", group");
|
||||
size_t colAverageX=plotter->getDatastore()->addColumn(columnBaseName+", category-average");
|
||||
size_t colStdDevX=plotter->getDatastore()->addColumn(columnBaseName+", category-stddev");
|
||||
size_t colAverageY=plotter->getDatastore()->addColumn(columnBaseName+", value-average");
|
||||
size_t colStdDevY=plotter->getDatastore()->addColumn(columnBaseName+", value-stddev");
|
||||
|
||||
for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
|
||||
plotter->getDatastore()->appendToColumn(colGroup, it->first);
|
||||
plotter->getDatastore()->appendToColumn(colAverageX, jkqtpstatAverage(it->second.first.begin(), it->second.first.end()));
|
||||
plotter->getDatastore()->appendToColumn(colStdDevX, jkqtpstatStdDev(it->second.first.begin(), it->second.first.end()));
|
||||
plotter->getDatastore()->appendToColumn(colAverageY, jkqtpstatAverage(it->second.second.begin(), it->second.second.end()));
|
||||
plotter->getDatastore()->appendToColumn(colStdDevY, jkqtpstatStdDev(it->second.second.begin(), it->second.second.end()));
|
||||
}
|
||||
|
||||
// 2.4. Finally the calculated groups are drawn
|
||||
TGraph* graph;
|
||||
plotter->addGraph(graph=new TGraph(plotter));
|
||||
graph->setXColumn(colAverageX);
|
||||
graph->setYColumn(colAverageY);
|
||||
graph->setXErrorColumn(static_cast<int>(colStdDevX));
|
||||
graph->setYErrorColumn(static_cast<int>(colStdDevY));
|
||||
|
||||
return graph;
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create a JKQTPXYLineErrorGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddXYErrorGraph(), JKQTPXYLineErrorGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddXYErrorGraph<InputCatIt,InputValueIt,JKQTPXYLineErrorGraph>(plotter,inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
|
||||
/*! \brief create a JKQTPXYParametrizedErrorScatterGraph with y-direction error bars, calculated from average +/- stddev of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for x-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for x-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for y-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for y-coordinates)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the graph showing \f$ c_{\text{out},j} \f$ and average +/- stddev for each group \f$ j \f$
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), jkqtpstatAddXYErrorGraph(), JKQTPXYParametrizedErrorScatterGraph, \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
return jkqtpstatAddXYErrorGraph<InputCatIt,InputValueIt,JKQTPXYParametrizedErrorScatterGraph>(plotter,inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
/*! \brief create horizontal boxplots of type \a TGraph, from the 5-value-summary of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
\internal
|
||||
|
||||
\tparam TGraph type of graph that should be added to the plot, has to offer the same interface as JKQTPBoxplotVerticalGraph or JKQTPBoxplotHorizontalGraph
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param quantile1Spec specifies which quantile to calculate for \a qantile1 (range: 0..1)
|
||||
\param quantile2Spec specifies which quantile to calculate for \a qantile2 (range: 0..1)
|
||||
\param 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!)
|
||||
\param 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!)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the boxplot graph
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt, class TGraph>
|
||||
inline 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")) {
|
||||
std::map<double, std::vector<double> > groupeddataBar;
|
||||
jkqtpstatGroupData(inFirstCat_Y, inLastCat_Y, inFirstValue_Y, inLastValue_Y, groupeddataBar, groupDefFunc);
|
||||
|
||||
size_t colGroup=plotter->getDatastore()->addColumn(columnBaseName+", group");
|
||||
size_t colMin=plotter->getDatastore()->addColumn(columnBaseName+", minimum");
|
||||
size_t colQ25=plotter->getDatastore()->addColumn(columnBaseName+", quartile25");
|
||||
size_t colMedian=plotter->getDatastore()->addColumn(columnBaseName+", median");
|
||||
size_t colIQRSig=plotter->getDatastore()->addColumn(columnBaseName+", MedianSignificance");
|
||||
size_t colAverage=plotter->getDatastore()->addColumn(columnBaseName+", average");
|
||||
size_t colQ75=plotter->getDatastore()->addColumn(columnBaseName+", quartile75");
|
||||
size_t colMax=plotter->getDatastore()->addColumn(columnBaseName+", maximum");
|
||||
|
||||
for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
|
||||
|
||||
auto stat5=jkqtpstat5NumberStatistics(it->second.begin(), it->second.end(), quantile1Spec, quantile2Spec, minimumQuantile, maximumQuantile);
|
||||
|
||||
plotter->getDatastore()->appendToColumn(colGroup, it->first);
|
||||
plotter->getDatastore()->appendToColumn(colAverage, jkqtpstatAverage(it->second.begin(), it->second.end()));
|
||||
plotter->getDatastore()->appendToColumn(colMin, stat5.minimum);
|
||||
plotter->getDatastore()->appendToColumn(colQ25, stat5.quantile1);
|
||||
plotter->getDatastore()->appendToColumn(colMedian, stat5.median);
|
||||
plotter->getDatastore()->appendToColumn(colQ75, stat5.quantile2);
|
||||
plotter->getDatastore()->appendToColumn(colMax, stat5.maximum);
|
||||
plotter->getDatastore()->appendToColumn(colIQRSig, stat5.IQRSignificanceEstimate());
|
||||
}
|
||||
|
||||
// 2.4. Finally the calculated groups are drawn
|
||||
TGraph* graph;
|
||||
plotter->addGraph(graph=new TGraph(plotter));
|
||||
graph->setPositionColumn(colGroup);
|
||||
graph->setMinColumn(colMin);
|
||||
graph->setMaxColumn(colMax);
|
||||
graph->setMedianColumn(colMedian);
|
||||
graph->setMeanColumn(colAverage);
|
||||
graph->setPercentile25Column(colQ25);
|
||||
graph->setPercentile75Column(colQ75);
|
||||
graph->setMedianConfidenceColumn(colIQRSig);
|
||||
|
||||
return graph;
|
||||
}
|
||||
|
||||
/*! \brief create vertical boxplots of type \a JKQTPBoxplotVerticalGraph, from the 5-value-summary of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
\internal
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_X and \a inLastValue_X
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_X iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_X iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param quantile1Spec specifies which quantile to calculate for \a qantile1 (range: 0..1)
|
||||
\param quantile2Spec specifies which quantile to calculate for \a qantile2 (range: 0..1)
|
||||
\param 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!)
|
||||
\param 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!)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the boxplot graph
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
|
||||
return jkqtpstatAddBoxplots<InputCatIt,InputValueIt,JKQTPBoxplotVerticalGraph>(plotter, inFirstCat_Y, inLastCat_Y, inFirstValue_X, inLastValue_X, quantile1Spec, quantile2Spec, minimumQuantile, maximumQuantile, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
/*! \brief create horizontal boxplots of type \a JKQTPBoxplotHorizontalGraph, from the 5-value-summary of groups in the input data
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
\internal
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param quantile1Spec specifies which quantile to calculate for \a qantile1 (range: 0..1)
|
||||
\param quantile2Spec specifies which quantile to calculate for \a qantile2 (range: 0..1)
|
||||
\param 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!)
|
||||
\param 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!)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the boxplot graph
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline JKQTPBoxplotHorizontalGraph* jkqtpstatVAddBoxplots(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, double maximumQuantile=1.0, JKQTPStatGroupDefinitionFunctor1D groupDefFunc=&jkqtpstatGroupingIdentity1D, const QString& columnBaseName=QString("grouped boxplot data")) {
|
||||
|
||||
return jkqtpstatAddBoxplots<InputCatIt,InputValueIt,JKQTPBoxplotHorizontalGraph>(plotter, inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, quantile1Spec, quantile2Spec, minimumQuantile, maximumQuantile, groupDefFunc, columnBaseName);
|
||||
}
|
||||
|
||||
/*! \brief create vertical boxplots of type \a JKQTPBoxplotVerticalGraph, from the 5-value-summary of groups in the input data, also adds a graph showing the outliers
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_X and \a inLastCat_X
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_Y and \a inLastValue_Y
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_X iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_X iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_Y iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_Y iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param quantile1Spec specifies which quantile to calculate for \a qantile1 (range: 0..1)
|
||||
\param quantile2Spec specifies which quantile to calculate for \a qantile2 (range: 0..1)
|
||||
\param 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!)
|
||||
\param 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!)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the boxplot graph (return.first) and the outliers graph (return.second)
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
std::map<double, std::vector<double> > groupeddataBar;
|
||||
jkqtpstatGroupData(inFirstCat_X, inLastCat_X, inFirstValue_Y, inLastValue_Y, groupeddataBar, groupDefFunc);
|
||||
|
||||
size_t colGroup=plotter->getDatastore()->addColumn(columnBaseName+", group");
|
||||
size_t colMin=plotter->getDatastore()->addColumn(columnBaseName+", minimum");
|
||||
size_t colQ25=plotter->getDatastore()->addColumn(columnBaseName+", quartile25");
|
||||
size_t colMedian=plotter->getDatastore()->addColumn(columnBaseName+", median");
|
||||
size_t colIQRSig=plotter->getDatastore()->addColumn(columnBaseName+", MedianSignificance");
|
||||
size_t colAverage=plotter->getDatastore()->addColumn(columnBaseName+", average");
|
||||
size_t colQ75=plotter->getDatastore()->addColumn(columnBaseName+", quartile75");
|
||||
size_t colMax=plotter->getDatastore()->addColumn(columnBaseName+", maximum");
|
||||
size_t colOutlierG=plotter->getDatastore()->addColumn(columnBaseName+", outlier-group");
|
||||
size_t colOutlierV=plotter->getDatastore()->addColumn(columnBaseName+", outlier-value");
|
||||
|
||||
for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
|
||||
|
||||
auto stat5=jkqtpstat5NumberStatistics(it->second.begin(), it->second.end(), quantile1Spec, quantile2Spec, minimumQuantile, maximumQuantile);
|
||||
|
||||
plotter->getDatastore()->appendToColumn(colGroup, it->first);
|
||||
plotter->getDatastore()->appendToColumn(colAverage, jkqtpstatAverage(it->second.begin(), it->second.end()));
|
||||
plotter->getDatastore()->appendToColumn(colMin, stat5.minimum);
|
||||
plotter->getDatastore()->appendToColumn(colQ25, stat5.quantile1);
|
||||
plotter->getDatastore()->appendToColumn(colMedian, stat5.median);
|
||||
plotter->getDatastore()->appendToColumn(colQ75, stat5.quantile2);
|
||||
plotter->getDatastore()->appendToColumn(colMax, stat5.maximum);
|
||||
plotter->getDatastore()->appendToColumn(colIQRSig, stat5.IQRSignificanceEstimate());
|
||||
std::fill_n(plotter->getDatastore()->backInserter(colOutlierG), stat5.outliers.size(), jkqtp_todouble(it->first));
|
||||
plotter->getDatastore()->appendToColumn(colOutlierV, stat5.outliers.begin(), stat5.outliers.end());
|
||||
}
|
||||
|
||||
JKQTPBoxplotVerticalGraph* graph;
|
||||
plotter->addGraph(graph=new JKQTPBoxplotVerticalGraph(plotter));
|
||||
graph->setPositionColumn(colGroup);
|
||||
graph->setMinColumn(colMin);
|
||||
graph->setMaxColumn(colMax);
|
||||
graph->setMedianColumn(colMedian);
|
||||
graph->setMeanColumn(colAverage);
|
||||
graph->setPercentile25Column(colQ25);
|
||||
graph->setPercentile75Column(colQ75);
|
||||
graph->setMedianConfidenceColumn(colIQRSig);
|
||||
|
||||
JKQTPXYLineGraph* graphOL;
|
||||
plotter->addGraph(graphOL=new JKQTPXYLineGraph(plotter));
|
||||
graphOL->setXColumn(colOutlierG);
|
||||
graphOL->setYColumn(colOutlierV);
|
||||
graphOL->setDrawLine(false);
|
||||
graphOL->setSymbolSize(graphOL->getSymbolSize()/2.0);
|
||||
graphOL->setColor(graph->getLineColor());
|
||||
return std::pair<JKQTPBoxplotVerticalGraph*, JKQTPXYLineGraph*>(graph, graphOL);
|
||||
}
|
||||
|
||||
|
||||
/*! \brief create vertical boxplots of type \a JKQTPBoxplotHorizontalGraph, from the 5-value-summary of groups in the input data, also adds a graph showing the outliers
|
||||
\ingroup jkqtptools_math_statistics_adaptors
|
||||
|
||||
\tparam InputCatIt standard iterator type of \a inFirstCat_Y and \a inLastCat_Y
|
||||
\tparam InputValueIt standard iterator type of \a inFirstValue_X and \a inLastValue_X
|
||||
\param plotter the plotter to which to add the resulting graph
|
||||
\param inFirstCat_Y iterator pointing to the first item in the category dataset to use \f$ c_1 \f$ (used for y-coordinates)
|
||||
\param inLastCat_Y iterator pointing behind the last item in the category dataset to use \f$ c_N \f$ (used for y-coordinates)
|
||||
\param inFirstValue_X iterator pointing to the first item in the category dataset to use \f$ v_1 \f$ (used for x-coordinates)
|
||||
\param inLastValue_X iterator pointing behind the last item in the category dataset to use \f$ v_N \f$ (used for x-coordinates)
|
||||
\param quantile1Spec specifies which quantile to calculate for \a qantile1 (range: 0..1)
|
||||
\param quantile2Spec specifies which quantile to calculate for \a qantile2 (range: 0..1)
|
||||
\param 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!)
|
||||
\param 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!)
|
||||
\param groupDefFunc assigns a group \f$ c_{\text{out},j} \f$ to each category value \f$ c_i \f$ .
|
||||
\param columnBaseName string component used to build the names of the columns generated by this function
|
||||
\return the boxplot graph (return.first) and the outliers graph (return.second)
|
||||
|
||||
|
||||
|
||||
\see jkqtpstatGroupData(), \ref JKQTPlotterBasicJKQTPDatastoreStatisticsGroupedStat
|
||||
*/
|
||||
template <class InputCatIt, class InputValueIt>
|
||||
inline 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")) {
|
||||
std::map<double, std::vector<double> > groupeddataBar;
|
||||
jkqtpstatGroupData(inFirstCat_Y, inLastCat_Y, inFirstValue_X, inLastValue_X, groupeddataBar, groupDefFunc);
|
||||
|
||||
size_t colGroup=plotter->getDatastore()->addColumn(columnBaseName+", group");
|
||||
size_t colMin=plotter->getDatastore()->addColumn(columnBaseName+", minimum");
|
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size_t colQ25=plotter->getDatastore()->addColumn(columnBaseName+", quartile25");
|
||||
size_t colMedian=plotter->getDatastore()->addColumn(columnBaseName+", median");
|
||||
size_t colIQRSig=plotter->getDatastore()->addColumn(columnBaseName+", MedianSignificance");
|
||||
size_t colAverage=plotter->getDatastore()->addColumn(columnBaseName+", average");
|
||||
size_t colQ75=plotter->getDatastore()->addColumn(columnBaseName+", quartile75");
|
||||
size_t colMax=plotter->getDatastore()->addColumn(columnBaseName+", maximum");
|
||||
size_t colOutlierG=plotter->getDatastore()->addColumn(columnBaseName+", outlier-group");
|
||||
size_t colOutlierV=plotter->getDatastore()->addColumn(columnBaseName+", outlier-value");
|
||||
|
||||
for (auto it=groupeddataBar.begin(); it!=groupeddataBar.end(); ++it) {
|
||||
|
||||
auto stat5=jkqtpstat5NumberStatistics(it->second.begin(), it->second.end(), quantile1Spec, quantile2Spec, minimumQuantile, maximumQuantile);
|
||||
|
||||
plotter->getDatastore()->appendToColumn(colGroup, it->first);
|
||||
plotter->getDatastore()->appendToColumn(colAverage, jkqtpstatAverage(it->second.begin(), it->second.end()));
|
||||
plotter->getDatastore()->appendToColumn(colMin, stat5.minimum);
|
||||
plotter->getDatastore()->appendToColumn(colQ25, stat5.quantile1);
|
||||
plotter->getDatastore()->appendToColumn(colMedian, stat5.median);
|
||||
plotter->getDatastore()->appendToColumn(colQ75, stat5.quantile2);
|
||||
plotter->getDatastore()->appendToColumn(colMax, stat5.maximum);
|
||||
plotter->getDatastore()->appendToColumn(colIQRSig, stat5.IQRSignificanceEstimate());
|
||||
std::fill_n(plotter->getDatastore()->backInserter(colOutlierG), stat5.outliers.size(), jkqtp_todouble(it->first));
|
||||
plotter->getDatastore()->appendToColumn(colOutlierV, stat5.outliers.begin(), stat5.outliers.end());
|
||||
}
|
||||
|
||||
JKQTPBoxplotHorizontalGraph* graph;
|
||||
plotter->addGraph(graph=new JKQTPBoxplotHorizontalGraph(plotter));
|
||||
graph->setPositionColumn(colGroup);
|
||||
graph->setMinColumn(colMin);
|
||||
graph->setMaxColumn(colMax);
|
||||
graph->setMedianColumn(colMedian);
|
||||
graph->setMeanColumn(colAverage);
|
||||
graph->setPercentile25Column(colQ25);
|
||||
graph->setPercentile75Column(colQ75);
|
||||
graph->setMedianConfidenceColumn(colIQRSig);
|
||||
|
||||
JKQTPXYLineGraph* graphOL;
|
||||
plotter->addGraph(graphOL=new JKQTPXYLineGraph(plotter));
|
||||
graphOL->setYColumn(colOutlierG);
|
||||
graphOL->setXColumn(colOutlierV);
|
||||
graphOL->setDrawLine(false);
|
||||
graphOL->setSymbolSize(graphOL->getSymbolSize()/2.0);
|
||||
graphOL->setColor(graph->getLineColor());
|
||||
return std::pair<JKQTPBoxplotHorizontalGraph*, JKQTPXYLineGraph*>(graph, graphOL);
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
#endif // JKQTPGRAPHSSTATISTICSADAPTORS_H_INCLUDED
|
||||
|
||||
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screenshots/jkqtplotter_simpletest_datastore_groupedstat.png
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Loading…
Reference in New Issue
Block a user