5.8 KiB
JKQtPlotter
Simple math image plot, showin a 1-channel OpenCV cv::Mat
This project (see ./examples/simpletest_imageplot_opencv/) simply creates a JKQtPlotter widget (as a new window) and adds a color-coded image plot of a mathematical function (here the Airy disk). The image is generated as an OpenCV cv::Mat image and then copied into a single column of the internal datasdtore (JKQTPMathImage could be directly used without the internal datastore).
To copy the data a special OpenCV Interface function JKQTPcopyCvMatToColumn() is used, that copies the data from a cv::Mat directly into a column.
The function JKQTPcopyCvMatToColumn() is available from the (non-default) header-only extension from jkqtplotter/jkqtpopencvinterface.h. This header provides facilities to interface JKQtPlotter with OPenCV.
The source code of the main application is (see jkqtplotter_simpletest_imageplot_opencv.cpp:
#include <QApplication>
#include <cmath>
#include "jkqtplotter/jkqtplotter.h"
#include "jkqtplotter/jkqtpgraphsimage.h"
#include "jkqtplotter/jkqtpopencvinterface.h"
#include <opencv/cv.h>
#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<double>(airydisk.cols)*dx;
const double h=static_cast<double>(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<airydisk.rows; iy++ ) {
x=-w/2.0;
for (int ix=0; ix<airydisk.cols; ix++ ) {
const double r=sqrt(x*x+y*y);
const double v=2.0*M_PI*NA*r/wavelength;
airydisk.at<double>(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();
}
The result looks like this:
See test/simpletest_imageplot for a detailed description of the other possibilities that the class JKQTPColumnMathImage (and also JKQTPMathImage) offer with respect to determining how an image is plottet.