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Introduction
Let me introduce a simple and efficient chart drawing and data visualization tool in C++: matplotlib-cpp. First, here are my system configurations and software version information.
- Windows 10 64-bit
- VS2015
- Python3.6.5
- OpenCV4.2Installing and Configuring Matplotlib-cpp
Using C++ to call Python’s matplotlib library for various data chart displays is the simplest C++ chart library. It supports usage on both Windows and Linux systems.
Download
git clone https://github.com/lava/matplotlib-cpp.gitThe directory structure is as follows:
Open WinBuild.cmd in the contrib folder and run this script to complete the compilation. However, before running, first open and modify the default parameters on lines 4-8 to match your software version and information. My modifications are as follows:
1REM ------Set Your Environment-------------------------------
2if NOT DEFINED MSVC_VERSION set MSVC_VERSION=14
3if NOT DEFINED CMAKE_CONFIG set CMAKE_CONFIG=Release
4if NOT DEFINED PYTHONHOME set PYTHONHOME=C:/Users/Administrator/AppData/Local/Programs/Python/Python36
5REM ---------------------------------------------------------Then run the following in the Windows command line:
After completing the compilation, you’re all set! Now you need to configure VS2015, which mainly consists of three steps:
– Configure Include Paths
– Configure Library Directories
– Configure Linker
Note:
Most importantly, set the corresponding Python home directory in the environment variables!
Using matplotlib-cpp
– Testing matplotlib-cpp
Create a test cpp file and add the following code:
1#include "matplotlibcpp.h"
2namespace plt = matplotlibcpp;
3int main() {
4 plt::plot({1,3,2,4});
5 plt::show();
6}The output will be as follows:
Using OpenCV + matplotlib-cpp Together
Displaying Images
Using plt::imshow supports displaying both grayscale and color images. The code to display an image is as follows:
1Mat src = imread("D:/images/test1.png");
2cvtColor(src, src, COLOR_BGR2RGB);
3const uchar* buff = src.ptr<uchar>(0);
4int h = src.rows;
5int w = src.cols;
6int channels = src.channels();
7plt::title("My Demo");
8plt::imshow(buff, h, w, channels);
9plt::show();Convert Image to HSV Color Space and Display Histogram for H Channel
Histogram Bar
Drawing Various Charts from Data
1// Prepare data.
2int n = 5000; // number of data points
3vector<double> x(n), y(n);
4for (int i = 0; i<n; ++i) {
5 double t = 2 * CV_PI*i / n;
6 x.at(i) = 16 * sin(t)*sin(t)*sin(t);
7 y.at(i) = 13 * cos(t) - 5 * cos(2 * t) - 2 * cos(3 * t) - cos(4 * t);
8}
9
10// plot() takes an arbitrary number of (x,y,format)-triples.
11// x must be iterable (that is, anything providing begin(x) and end(x)),
12// y must either be callable (providing operator() const) or iterable.
13plt::plot(x, y, "r-", x, [](double d) { return 12.5 + abs(sin(d)); }, "k-");
14
15
16// show plots
17plt::show();Displayed as follows:
3D Data Visualization
1std::vector<std::vector<double>> x, y, z;
2for (double i = -5; i <= 5; i += 0.25) {
3 std::vector<double> x_row, y_row, z_row;
4 for (double j = -5; j <= 5; j += 0.25) {
5 x_row.push_back(i);
6 y_row.push_back(j);
7 z_row.push_back(::std::sin(::std::hypot(i, j)));
8 }
9 x.push_back(x_row);
10 y.push_back(y_row);
11 z.push_back(z_row);
12}
13
14plt::plot_surface(x, y, z);
15plt::show();Displayed as follows:
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