update plot imaged for tutorials: datastore, datastorw_groupstat, datastore_regression, datastore_iterators, datastore_statistics

.gitignore

@@ -136,3 +136,31 @@ Sicherungskopie_*
 /screenshots/datastore_map_small.png
 /screenshots/datastore_sine_small.png
 /screenshots/datastore_sineimg_small.png
+/screenshots/datastore_regression_lin_small.png
+/screenshots/datastore_regression_linrobust_p_small.png
+/screenshots/datastore_regression_linrobust_small.png
+/screenshots/datastore_regression_linweight_small.png
+/screenshots/datastore_regression_nonlinreg_small.png
+/screenshots/datastore_regression_nonlinregdatastore_regression_polynom.png
+/screenshots/datastore_regression_nonlinregdatastore_regression_polynom_small.png
+/screenshots/datastore_regression_polynom_errros_small.png
+/screenshots/datastore_regression_polynom_small.png
+/screenshots/datastore_regression_nonlinreg_exp_small.png
+/screenshots/datastore_regression_nonlinreg_pow_small.png
+/screenshots/datastore_groupedstat_barchart_small.png
+/screenshots/datastore_groupedstat_barchartrawdata_small.png
+/screenshots/datastore_groupedstat_boxplot_small.png
+/screenshots/datastore_groupedstat_scatter_small.png
+/screenshots/datastore_groupedstat_scatterrawdata_small.png
+/screenshots/simpletest_datastore_iterators_cosine_small.png
+/screenshots/simpletest_datastore_iterators_cosine_ysorted_small.png
+/screenshots/datastore_iterators_cosine_small.png
+/screenshots/datastore_iterators_cosine_ysorted_small.png
+/screenshots/simpletest_datastore_iterators_cosine.png
+/screenshots/simpletest_datastore_iterators_cosine_ysorted.png
+/screenshots/datastore_statistics_boxplots_outliers_small.png
+/screenshots/datastore_statistics_boxplots_simple_small.png
+/screenshots/datastore_statistics_cumhistkde_small.png
+/screenshots/datastore_statistics_dataonly_small.png
+/screenshots/datastore_statistics_hist_small.png
+/screenshots/datastore_statistics_kde_small.png

doc/CMakeLists.txt

@@ -201,6 +201,11 @@ if(JKQtPlotter_BUILD_EXAMPLES)
         logaxes/logaxes,logaxes_nolog,logaxes_nominorgrid/--iteratefunctorsteps
         #speed
         datastore/datastore,datastore_sine,datastore_linkedcarray,datastore_map,datastore_calccolumns,datastore_image,datastore_image_sorted,datastore_sineimg/--iteratefunctorsteps
+        datastore_iterators/datastore_iterators,datastore_iterators_cosine,datastore_iterators_cosine_ysorted,datastore_iterators_cosine_yreplaced,/--iteratefunctorsteps
+        datastore_groupedstat/datastore_groupedstat,datastore_groupedstat_barchartrawdata,datastore_groupedstat_barchart,datastore_groupedstat_boxplot,datastore_groupedstat_scatterrawdata,datastore_groupedstat_scatter/--iteratefunctorsteps
+        datastore_regression/datastore_regression,datastore_regression_lin,datastore_regression_linrobust,datastore_regression_linrobust_p,datastore_regression_linweight,datastore_regression_nonlinreg_exp,datastore_regression_nonlinreg_pow,datastore_regression_polynom,datastore_regression_polynom_errros/--iteratefunctorsteps
+        datastore_statistics/datastore_statistics,datastore_statistics_dataonly,datastore_statistics_boxplots_simple,datastore_statistics_boxplots_outliers,datastore_statistics_hist,datastore_statistics_kde,datastore_statistics_cumhistkde/--iteratefunctorsteps
+        datastore_statistics_2d/datastore_statistics_2d
     )
 
 

examples/datastore/datastore.cpp

@@ -177,9 +177,9 @@ int main(int argc, char* argv[])
     app.addExportStepFunctor([&]() { setVisible(1); plot.getPlotter()->setShowKey(false); plot.zoomToFit(); plot.redrawPlot(); plot.resize(400,400*4/6); });
     app.addExportStepFunctor([&]() { setVisible(2); plot.getPlotter()->setShowKey(false); plot.zoomToFit(); plot.redrawPlot(); plot.resize(400,400*4/6); });
     app.addExportStepFunctor([&]() { setVisible(3); plot.getPlotter()->setShowKey(false); plot.zoomToFit(); plot.redrawPlot(); plot.resize(400,400*4/6); });
-    app.addExportStepFunctor([&]() { setVisibleV({4,5}); plot.getPlotter()->setShowKey(false); plot.zoomToFit(); plot.redrawPlot(); plot.resize(400,400*4/6); });
+    app.addExportStepFunctor([&]() { setVisibleV({4,5}); plot.getPlotter()->setShowKey(false); plot.zoomToFit(); plot.redrawPlot(); plot.resize(600,400*4/6); });
     app.addExportStepFunctor([&]() { std::sort(datastore->begin(colLinXY.second), datastore->end(colLinXY.second)); setVisibleV({4,5});plot.getPlotter()->setShowKey(false);  plot.zoomToFit(); plot.redrawPlot(); });
-    app.addExportStepFunctor([&]() { setVisible(6); plot.zoomToFit(); plot.getPlotter()->setShowKey(false); plot.redrawPlot(); plot.resize(400,400); });
+    app.addExportStepFunctor([&]() { setVisible(6); plot.zoomToFit(); plot.getPlotter()->setShowKey(false); plot.redrawPlot(); plot.resize(300,300); });
 
     return app.exec();
 }

examples/datastore_groupedstat/datastore_groupedstat.cpp

@@ -171,6 +171,7 @@ int main(int argc, char* argv[])
     size_t colScatterRawY=datastore1->addColumn("scatterplot, rawdata, y");
     std::random_device rd; // random number generators:
     std::mt19937 gen{rd()};
+    gen.seed(12345);
     std::normal_distribution<> d1{0,0.5};
     const size_t N=100;
     const double xmax=3.5;
@@ -263,7 +264,13 @@ int main(int argc, char* argv[])
 
     // show plotter and make it a decent size
     mainWidget.show();
-    mainWidget.resize(1200,400);
+    mainWidget.resize(900,300);
+
+    app.addExportStepPlotFunctor([&]() { gBar->setVisible(false); plotbarchart->redrawPlot(); return plotbarchart;});
+    app.addExportStepPlotFunctor([&]() { gBar->setVisible(true); plotbarchart->redrawPlot(); return plotbarchart;});
+    app.addExportStepPlotFunctor([&]() { return plotboxplot; });
+    app.addExportStepPlotFunctor([&]() { gScatterErr->setVisible(false); plotscattererrors->redrawPlot(); return plotscattererrors;});
+    app.addExportStepPlotFunctor([&]() { gScatterErr->setVisible(true); plotscattererrors->redrawPlot(); return plotscattererrors;});
 
     return app.exec();
 }

examples/datastore_iterators/README.md

@@ -48,7 +48,7 @@ In other tutorials we used e.g. `JKQTPDatastore::set()` to set values in data co
 ```
 Here we added two columns with 50 entries. `XCol` contains linearly spaced values between 0 and 2*pi and `YCol` contains 50 uninitialized values. Then we iterate an index `i` over all these items (`datastore->getRows(XCol)` returns the rows in a column, i.e. 50 in the example above) and used `JKQTPDatastore::set()` to store the calculated values in the two columns. The current x-values is read from `XCol` using `JKQTPDatastore::get()`. The resulting plot looks like this:
 
-![simpletest_datastore_iterators_cosine](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_iterators_cosine.png)
+![datastore_iterators_cosine](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_iterators_cosine.png)
 
 The same loop can be written using iterators:
 ```.cpp
@@ -90,14 +90,14 @@ Of course you can now also interface other algorithms, like e.g. [`std::sort()`]
 
 With this line of code, the `YCol` is sorted in ascending order and the plot becomes:
 
-![simpletest_datastore_iterators_cosine_ysorted](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_iterators_cosine_ysorted.png)
+![datastore_iterators_cosine_ysorted](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_iterators_cosine_ysorted.png)
 
 Another example would be to replace all value `y<-0.5` with the value `1.0` using  [`std::replace_if()`](https://de.cppreference.com/w/cpp/algorithm/replace):
 ```.cpp
     std::replace_if(datastore->begin(YCol), datastore->end(YCol), [](double v) { return v<-0.5; }, 1.0);
 ```
 
-![simpletest_datastore_iterators_cosine_yreplaced](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_iterators_cosine_yreplaced.png)
+![datastore_iterators_cosine_yreplaced](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_iterators_cosine_yreplaced.png)
 
 Finally also the [erase-remove idiom](https://en.wikipedia.org/wiki/Erase%E2%80%93remove_idiom) (e.g. known from `std::vector`) is supported:
 ```.cpp

examples/datastore_iterators/datastore_iterators.cpp

@@ -52,7 +52,9 @@ int main(int argc, char* argv[])
     // 2.3 combining with addLinearColumn() you can also use C++ STL algorithms:
     //size_t XCol=datastore->addLinearColumn(50, 0, 4.0*JKQTPSTATISTICS_PI, "cos curve: x-data");
     //size_t YCol=datastore->addColumn("cos curve: y-data");
+    size_t YCol2=datastore->addColumn("cos curve: y-data");
     //std::transform(datastore->begin(XCol), datastore->end(XCol), datastore->backInserter(YCol), cos);
+    std::transform(datastore->begin(XCol), datastore->end(XCol), datastore->backInserter(YCol2), cos);
     // 2.4. Just for fun we can now sort the data:
     //std::sort(datastore->begin(YCol), datastore->end(YCol));
     //      or replace any value <-0.5 with 1:
@@ -74,5 +76,10 @@ int main(int argc, char* argv[])
     plot.show();
     plot.resize(600,400);
 
+
+    app.addExportStepFunctor([&]() { std::sort(datastore->begin(YCol), datastore->end(YCol)); });
+    app.addExportStepFunctor([&]() {
+        std::replace_if(datastore->begin(YCol2), datastore->end(YCol2), [](double v) { return v<-0.5; }, 1.0); linegraph->setYColumn(YCol2); plot.zoomToFit(); });
+
     return app.exec();
 }

examples/datastore_regression/README.md

@@ -282,7 +282,8 @@ The regression models can be plotted using a `JKQTPXFunctionLineGraph`. the fucn
 
 The resulting plot looks like this:
 
-![datastore_regression_nonlinreg](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_regression_nonlinreg.png)
+![datastore_regression_nonlinreg_exp](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_regression_nonlinreg_exp.png)
+![datastore_regression_nonlinreg_pow](https://raw.githubusercontent.com/jkriege2/JKQtPlotter/master/screenshots/datastore_regression_nonlinreg_pow.png)
 
 Of course also "adaptors" exist that allow to perform the steps above in a single function call:
 

examples/datastore_regression/datastore_regression.cpp

@@ -54,6 +54,7 @@ int main(int argc, char* argv[])
     //      columns and added gaussian noise
     std::random_device rd; // random number generators:
     std::mt19937 gen{rd()};
+    gen.seed(12345);
     std::normal_distribution<> d1{0,1};
     double a0=-5;
     double b0=2;
@@ -96,8 +97,8 @@ int main(int argc, char* argv[])
     size_t colWLinE=datastore1->addColumn("wlin data, errors");
     for (double x=-5; x<=10; x++) {
         double factor=1;
-        if (ddecide(gen)==4) {
-            factor=4;
+        if (ddecide(gen)>=3) {
+            factor=6;
         }
         const double err=de(gen)*factor;
         datastore1->appendToColumn(colWLinX, x);
@@ -192,12 +193,15 @@ int main(int argc, char* argv[])
     p=1.5;
     g=jkqtpstatAddRobustIRLSLinearRegression(graphD, nullptr, nullptr, false, false, p);
     g->setTitle(g->getTitle()+", $p="+jkqtp_floattolatexqstr(p)+"$");
+    auto gp1=g;
     p=1.7;
     g=jkqtpstatAddRobustIRLSLinearRegression(graphD, nullptr, nullptr, false, false, p);
     g->setTitle(g->getTitle()+", $p="+jkqtp_floattolatexqstr(p)+"$");
+    auto gp2=g;
     p=2;
     g=jkqtpstatAddRobustIRLSLinearRegression(graphD, nullptr, nullptr, false, false, p);
     g->setTitle(g->getTitle()+", $p="+jkqtp_floattolatexqstr(p)+"$");
+    auto gp3=g;
 
 
 
@@ -276,16 +280,20 @@ int main(int argc, char* argv[])
     std::vector<double> pPoly {1,2,-2,0.5};
     size_t colPolyX=datastore1->addColumn("polynomial data, x");
     size_t colPolyY=datastore1->addColumn("polynomial data, y");
+    size_t colPolyYNN=datastore1->addColumn("polynomial data, y, no noise");
     for (double x=-10; x<=10; x++) {
         datastore1->appendToColumn(colPolyX, x);
         datastore1->appendToColumn(colPolyY, jkqtp_polyEval(x, pPoly.begin(), pPoly.end())+d1(gen)*50.0);
+        datastore1->appendToColumn(colPolyYNN, jkqtp_polyEval(x, pPoly.begin(), pPoly.end()));
     }
     //     we visualize this data with a simple scatter graph:
+    QVector<JKQTPGraph*> plotPNoise, plotsPNN;
     JKQTPXYLineGraph* graphP;
     plot6->addGraph(graphP=new JKQTPXYLineGraph(plot6));
     graphP->setXYColumns(colPolyX, colPolyY);
     graphP->setDrawLine(false);
     graphP->setTitle(QString("data $%1+\\mathcal{N}(0,50)$").arg(jkqtp_polynomialModel2Latex(pPoly.begin(), pPoly.end())));
+    plotPNoise<<graphP;
     // 6.2. now we can fit polynomials with different number of coefficients:
     for (size_t p=0; p<=5; p++) {
         std::vector<double> pFit;
@@ -294,6 +302,25 @@ int main(int argc, char* argv[])
         plot6->addGraph(gPoly=new JKQTPXFunctionLineGraph(plot6));
         gPoly->setPlotFunctionFunctor(jkqtp_generatePolynomialModel(pFit.begin(), pFit.end()));
         gPoly->setTitle(QString("regression: $%1$").arg(jkqtp_polynomialModel2Latex(pFit.begin(), pFit.end())));
+        plotPNoise<<gPoly;
+    }
+    JKQTPXYLineGraph* graphPNN;
+    plot6->addGraph(graphPNN=new JKQTPXYLineGraph(plot6));
+    graphPNN->setXYColumns(colPolyX, colPolyYNN);
+    graphPNN->setDrawLine(false);
+    graphPNN->setTitle(QString("data $%1$").arg(jkqtp_polynomialModel2Latex(pPoly.begin(), pPoly.end())));
+    graphPNN->setVisible(false);
+    plotsPNN<<graphPNN;
+    // 6.2. now we can fit polynomials with different number of coefficients:
+    for (size_t p=0; p<=5; p++) {
+        std::vector<double> pFit;
+        JKQTPXFunctionLineGraph* gPoly;
+        jkqtpstatPolyFit(datastore1->begin(colPolyX), datastore1->end(colPolyX), datastore1->begin(colPolyYNN), datastore1->end(colPolyYNN), p, std::back_inserter(pFit));
+        plot6->addGraph(gPoly=new JKQTPXFunctionLineGraph(plot6));
+        gPoly->setPlotFunctionFunctor(jkqtp_generatePolynomialModel(pFit.begin(), pFit.end()));
+        gPoly->setTitle(QString("regression: $%1$").arg(jkqtp_polynomialModel2Latex(pFit.begin(), pFit.end())));
+        gPoly->setVisible(false);
+        plotsPNN<<gPoly;
     }
     // 6.3. of course also the "adaptor" shortcuts are available:
     //for (size_t p=0; p<=5; p++) {
@@ -338,5 +365,14 @@ int main(int argc, char* argv[])
     mainWidget.show();
     mainWidget.resize(1600,800);
 
+    app.addExportStepPlotFunctor([&]() { mainWidget.resize(2000, 900); return plot1; });
+    app.addExportStepPlotFunctor([&]() { gp1->setVisible(false); gp2->setVisible(false); gp3->setVisible(false); plot3->redrawPlot(); return plot3; });
+    app.addExportStepPlotFunctor([&]() { gp1->setVisible(true); gp2->setVisible(true); gp3->setVisible(true); plot3->redrawPlot(); return plot3; });
+    app.addExportStepPlot(plot2);
+    app.addExportStepPlot(plot4);
+    app.addExportStepPlot(plot5);
+    app.addExportStepPlotFunctor([&]() { std::for_each(plotPNoise.begin(), plotPNoise.end(), [](JKQTPGraph* g) {g->setVisible(false);}); std::for_each(plotsPNN.begin(), plotsPNN.end(), [](JKQTPGraph* g) {g->setVisible(true);}); plot6->setX(-12.5,12.5); plot6->redrawPlot(); return plot6; });
+    app.addExportStepPlotFunctor([&]() { std::for_each(plotPNoise.begin(), plotPNoise.end(), [](JKQTPGraph* g) {g->setVisible(true);}); std::for_each(plotsPNN.begin(), plotsPNN.end(), [](JKQTPGraph* g) {g->setVisible(false);}); plot6->setX(-12.5,12.5); plot6->redrawPlot(); return plot6; });
+
     return app.exec();
 }

examples/datastore_statistics/datastore_statistics.cpp

@@ -54,6 +54,7 @@ int main(int argc, char* argv[])
     size_t randomdatacol3=datastore1->addColumn("random data 3");
     std::random_device rd; // random number generators:
     std::mt19937 gen{rd()};
+    gen.seed(12345);
     std::uniform_int_distribution<> ddecide(0,1);
     std::normal_distribution<> d1{0,1};
     std::normal_distribution<> d2{6,1.2};
@@ -146,26 +147,29 @@ int main(int argc, char* argv[])
 
 
     // 4.1. We repeat the JKQTPPeakStreamGraph visualization from above:
-    plot1->addGraph(gData1=new JKQTPPeakStreamGraph(plot1));
-    gData1->setDataColumn(randomdatacol1);
-    gData1->setBaseline(-0.1);
-    gData1->setPeakHeight(-0.05);
-    gData1->setDrawBaseline(false);
-    gData1->setTitle("random data $"+d1_latex+"+"+d2_latex+"$");
+    JKQTPPeakStreamGraph* pgData1;
+    plot1->addGraph(pgData1=new JKQTPPeakStreamGraph(plot1));
+    pgData1->setDataColumn(randomdatacol1);
+    pgData1->setBaseline(-0.1);
+    pgData1->setPeakHeight(-0.05);
+    pgData1->setDrawBaseline(false);
+    pgData1->setTitle("random data $"+d1_latex+"+"+d2_latex+"$");
 
     // 4.2. same as 3.1-3.2, but for the second and thirdcolumn of data:
-    plot1->addGraph(gData2=new JKQTPPeakStreamGraph(plot1));
-    gData2->setDataColumn(randomdatacol2);
-    gData2->setBaseline(-0.1);
-    gData2->setPeakHeight(0.05);
-    gData2->setDrawBaseline(false);
-    gData2->setTitle("random data subset $"+d1_latex+"$");
-    plot1->addGraph(gData3=new JKQTPPeakStreamGraph(plot1));
-    gData3->setDataColumn(randomdatacol3);
-    gData3->setBaseline(-0.15);
-    gData3->setPeakHeight(-0.05);
-    gData3->setDrawBaseline(false);
-    gData3->setTitle("random data subset $"+d2_latex+"$");
+    JKQTPPeakStreamGraph* pgData2;
+    plot1->addGraph(pgData2=new JKQTPPeakStreamGraph(plot1));
+    pgData2->setDataColumn(randomdatacol2);
+    pgData2->setBaseline(-0.1);
+    pgData2->setPeakHeight(0.05);
+    pgData2->setDrawBaseline(false);
+    pgData2->setTitle("random data subset $"+d1_latex+"$");
+    JKQTPPeakStreamGraph* pgData3;
+    plot1->addGraph(pgData3=new JKQTPPeakStreamGraph(plot1));
+    pgData3->setDataColumn(randomdatacol3);
+    pgData3->setBaseline(-0.15);
+    pgData3->setPeakHeight(-0.05);
+    pgData3->setDrawBaseline(false);
+    pgData3->setTitle("random data subset $"+d2_latex+"$");
 
     // 4.3. for comparison we add plots of the initial distributions:
     plot1->addGraph(new JKQTPXFunctionLineGraph(std::bind(&jkqtp_gaussdist, std::placeholders::_1, d1.mean(), d1.stddev()), d1_latex, plot1));
@@ -289,5 +293,12 @@ int main(int argc, char* argv[])
     mainWidget.show();
     mainWidget.resize(1200,800);
 
+    app.addExportStepPlotFunctor([&]() { gData1->setVisible(true); gBox1.first->setVisible(false); gBox1.second->setVisible(false); gData2->setVisible(true); gBox2->setVisible(false); gData3->setVisible(true); gBox3->setVisible(false); plot1box->redrawPlot(); return plot1box; });
+    app.addExportStepPlotFunctor([&]() { gData1->setVisible(false); gBox1.first->setVisible(false); gBox1.second->setVisible(false); gData2->setVisible(true); gBox2->setVisible(true); gData3->setVisible(true); gBox3->setVisible(true); plot1box->redrawPlot(); return plot1box; });
+    app.addExportStepPlotFunctor([&]() { gData1->setVisible(true); gBox1.first->setVisible(true); gBox1.second->setVisible(true); gData2->setVisible(false); gBox2->setVisible(false); gData3->setVisible(false); gBox3->setVisible(false); plot1box->redrawPlot(); return plot1box; });
+    app.addExportStepPlotFunctor([&]() { return plot1; });
+    app.addExportStepPlotFunctor([&]() { return plot1kde; });
+    app.addExportStepPlotFunctor([&]() { return plot1cum; });
+
     return app.exec();
 }

examples/datastore_statistics_2d/datastore_statistics_2d.cpp

@@ -102,6 +102,7 @@ int main(int argc, char* argv[])
     // random number generators:
     std::random_device rd;
     std::mt19937 gen{rd()};
+    gen.seed(12345);
     std::uniform_int_distribution<> ddecide(0,2);
     std::normal_distribution<> d1x{5,3};
     std::normal_distribution<> d1y{5,1};

lib/jkqtplotter/graphs/jkqtppeakstream.cpp

@@ -40,6 +40,7 @@ JKQTPPeakStreamGraph::JKQTPPeakStreamGraph(JKQTBasePlotter *parent):
     yPeaks=true;
     peakHeight=1;
     drawBaseline=true;
+    parentPlotStyle=-1;
     initLineStyle(parent, parentPlotStyle, JKQTPPlotStyleType::Default);
 }