/** \example jkqtplotter_simpletest_imageplot_opencv.cpp * Simple math image plot, showin a 1-channel OpenCV cv::Mat * * \ref JKQTPlotterImagePlotOpenCV */ #include #include #include "jkqtplotter/jkqtplotter.h" #include "jkqtplotter/jkqtpgraphs.h" #include "jkqtplotter/jkqtpgraphsimage.h" #include "jkqtplotter/jkqtpopencvinterface.h" #include #ifndef M_PI #define M_PI 3.14159265358979323846 #endif int main(int argc, char* argv[]) { QApplication app(argc, argv); JKQTPlotter plot; // 1. create a plotter window and get a pointer to the internal datastore (for convenience) plot.get_plotter()->set_useAntiAliasingForGraphs(true); // nicer (but slower) plotting plot.get_plotter()->set_useAntiAliasingForSystem(true); // nicer (but slower) plotting plot.get_plotter()->set_useAntiAliasingForText(true); // nicer (but slower) text rendering JKQTPDatastore* ds=plot.getDatastore(); // 2. now we create data for the charts (taken from https://commons.wikimedia.org/wiki/File:Energiemix_Deutschland.svg) cv::Mat airydisk(150, 150, CV_64FC1); // OpenCV-Image for the data const double dx=1e-2; // size of a pixel in x-direction [micrometers] const double dy=1e-2; // size of a pixel in x-direction [micrometers] const double w=static_cast(airydisk.cols)*dx; const double h=static_cast(airydisk.rows)*dy; // 2.1 Parameters for airy disk plot (see https://en.wikipedia.org/wiki/Airy_disk) double NA=1.1; // numerical aperture of lens double wavelength=488e-3; // wavelength of the light [micrometers] // 2.2 calculate image of airy disk in a row-major array double x, y=-h/2.0; for (int iy=0; iy(iy,ix) = pow(2.0*j1(v)/v, 2); x+=dx; } y+=dy; } // 3. make data available to JKQTPlotter by adding it to the internal datastore. // In this step the contents of one channel of the openCV cv::Mat is copied into a column // of the datastore in row-major order size_t cAiryDisk=JKQTPCopyCvMatToColumn(ds, airydisk, "imagedata"); // 4. create a graph (JKQTPColumnMathImage) with the column created above as data // The data is color-coded with the color-palette JKQTPMathImageMATLAB // the converted range of data is determined automatically because set_autoImageRange(true) JKQTPColumnMathImage* graph=new JKQTPColumnMathImage(&plot); graph->set_title(""); // image column with the data graph->set_imageColumn(cAiryDisk); // 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 graph->set_Nx(airydisk.cols); graph->set_Ny(airydisk.rows); // where does the image start in the plot, given in plot-axis-coordinates (bottom-left corner) graph->set_x(-w/2.0); graph->set_y(-h/2.0); // width and height of the image in plot-axis-coordinates graph->set_width(w); graph->set_height(h); // color-map is "MATLAB" graph->set_palette(JKQTPMathImageMATLAB); // get coordinate axis of color-bar and set its label graph->get_colorBarRightAxis()->set_axisLabel("light intensity [A.U.]"); // determine min/max of data automatically and use it to set the range of the color-scale graph->set_autoImageRange(true); // you can set the color-scale range manually by using: // graph->set_autoImageRange(false); // graph->set_imageMin(0); // graph->set_imageMax(10); // 5. add the graphs to the plot, so it is actually displayed plot.addGraph(graph); // 6. set axis labels plot.get_xAxis()->set_axisLabel("x [{\\mu}m]"); plot.get_yAxis()->set_axisLabel("y [{\\mu}m]"); // 7. fix axis and plot aspect ratio to 1 plot.get_plotter()->set_maintainAspectRatio(true); plot.get_plotter()->set_maintainAxisAspectRatio(true); // 8 autoscale the plot so the graph is contained plot.zoomToFit(); // show plotter and make it a decent size plot.show(); plot.resize(600,600); plot.setWindowTitle("JKQTPColumnMathImage"); return app.exec(); }