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109 lines
4.0 KiB
C++
109 lines
4.0 KiB
C++
/** \example jkqtplotter_simpletest_imageplot_modifier.cpp
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* Shows how to plot colored math images/matrices modified by a second data-column/image with JKQtPlotter
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*
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* \ref JKQtPlotterImagePlotModifier
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*/
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#include <QApplication>
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#include <cmath>
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#include "jkqtplotter/jkqtplotter.h"
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#include "jkqtplotter/jkqtpgraphsimage.h"
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#ifndef M_PI
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#define M_PI 3.14159265358979323846
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#endif
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int main(int argc, char* argv[])
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{
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QApplication app(argc, argv);
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JKQtPlotter plot;
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// 1. create a plotter window and get a pointer to the internal datastore (for convenience)
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plot.get_plotter()->set_useAntiAliasingForGraphs(true); // nicer (but slower) plotting
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plot.get_plotter()->set_useAntiAliasingForSystem(true); // nicer (but slower) plotting
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plot.get_plotter()->set_useAntiAliasingForText(true); // nicer (but slower) text rendering
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JKQTPdatastore* ds=plot.getDatastore();
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// 2. now we create data for the charts (taken from https://commons.wikimedia.org/wiki/File:Energiemix_Deutschland.svg)
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const int NX=150; // image dimension in x-direction [pixels]
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const int NY=150; // image dimension in x-direction [pixels]
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double image[NX*NY]; // row-major image
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double modifier[NX*NY]; // row-major modfier image
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// 2 calculate image of airy disk in a row-major array
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double x, y=-static_cast<double>(NY)/2.0;
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for (int iy=0; iy<NY; iy++ ) {
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x=-static_cast<double>(NX)/2.0;
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for (int ix=0; ix<NX; ix++ ) {
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const double r=sqrt(x*x+y*y);
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image[iy*NX+ix] = cos(M_PI*r/20.0);
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modifier[iy*NX+ix] = 1.0-r/sqrt(NX*NX/4.0+NY*NY/4.0);
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x+=1;
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}
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y+=1;
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}
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// 3. make data available to JKQtPlotter by adding it to the internal datastore.
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// In this step the contents of C-array airydisk is copied into a column
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// of the datastore in row-major order
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size_t cImage=ds->addCopiedImageAsColumn(image, NX, NY, "imagedata");
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size_t cModifier=ds->addCopiedImageAsColumn(modifier, NX, NY, "modifier");
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// 4. create a graph (JKQTPColumnMathImage) with the column created above as data
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// The data is color-coded with the color-palette JKQTPMathImageMATLAB
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// the converted range of data is determined automatically because set_autoImageRange(true)
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JKQTPColumnMathImage* graph=new JKQTPColumnMathImage(&plot);
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graph->set_title("");
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// image column with the data
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graph->set_imageColumn(cImage);
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// now set the modifier image:
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graph->set_modifierColumn(cModifier);
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graph->set_autoModifierRange(true);
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// ... and specify which image property is modified (here the saturation, but ModifyAlpha for the transparency and ModifyValue from the HSV color-model are also possible):
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graph->set_modifierMode(JKQTPMathImageBase::ModifySaturation);
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// set size of the data (the datastore does not contain this info, as it only manages 1D columns of data and this is used to assume a row-major ordering
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graph->set_Nx(NX);
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graph->set_Ny(NY);
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// where does the image start in the plot, given in plot-axis-coordinates (bottom-left corner)
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graph->set_x(-NX/2.0);
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graph->set_y(-NX/2.0);
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// width and height of the image in plot-axis-coordinates
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graph->set_width(NX);
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graph->set_height(NY);
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// color-map is "MATLAB"
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graph->set_palette(JKQTPMathImageMATLAB);
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// determine min/max of data automatically and use it to set the range of the color-scale
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graph->set_autoImageRange(true);
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// 5. add the graphs to the plot, so it is actually displayed
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plot.addGraph(graph);
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// 6. set axis labels
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plot.get_xAxis()->set_axisLabel("x [{\\mu}m]");
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plot.get_yAxis()->set_axisLabel("y [{\\mu}m]");
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// 7. fix axis and plot aspect ratio to 1
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plot.get_plotter()->set_maintainAspectRatio(true);
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plot.get_plotter()->set_maintainAxisAspectRatio(true);
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// 8 autoscale the plot so the graph is contained
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plot.zoomToFit();
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// show plotter and make it a decent size
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plot.show();
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plot.resize(500,500);
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plot.setWindowTitle("JKQTPColumnMathImage");
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return app.exec();
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}
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