ImPlot is an immediate mode plotting widget for [Dear ImGui](https://github.com/ocornut/imgui). It aims to provide a first-class API that will make ImGui users feel right at home. ImPlot is well suited for visualizing program data in real-time and requires minimal code to integrate. Just like ImGui, it does not burden the end user with GUI state management, avoids STL containers and C++ headers, and has no external dependencies except for ImGui itself.
The API is used just like any other ImGui `BeginX`/`EndX` pair. First, start a new plot with `ImPlot::BeginPlot()`. Next, plot as many items as you want with the provided `PlotX` functions (e.g. `PlotLine()`, `PlotBars()`, `PlotErrorBars()`, etc). Finally, wrap things up with a call to `ImPlot::EndPlot()`. That's it!
1) Add `implot.h`, `implot_internal.h`, `implot.cpp`, `implot_items.cpp` and optionally `implot_demo.cpp` to your sources. Alternatively, you can get ImPlot using [vcpkg](https://github.com/microsoft/vcpkg/tree/master/ports/implot).
Of course, this assumes you already have an ImGui-ready environment. If not, consider trying [mahi-gui](https://github.com/mahilab/mahi-gui), which bundles ImGui, ImPlot, and several other packages for you.
1) Handle the `ImGuiBackendFlags_RendererHasVtxOffset` flag in your renderer when using 16-bit indices (the official OpenGL3 renderer supports this) and use an ImGui version with patch [imgui@f6120f8](https://github.com/ocornut/imgui/commit/f6120f8e16eefcdb37b63974e6915a3dd35414be).
2) Enable 32-bit indices by uncommenting `#define ImDrawIdx unsigned int` in your `imconfig.h` file.
- By default, no anti-aliasing is done on line plots for performance reasons. If you use 4x MSAA, then you likely won't even notice. However, you can re-enable AA with the `ImPlotFlags_AntiAliased` flag.
An online version of the demo is hosted [here](https://traineq.org/implot_demo/src/implot_demo.html). You can view the plots and the source code that generated them. Note that this demo may not always be up to date and is not as performant as a desktop implemention, but it should give you a general taste of what's possible with ImPlot. Special thanks to [pthom](https://github.com/pthom) for creating and hosting this!
A: ImGui is an incredibly powerful tool for rapid prototyping and development, but provides only limited mechanisms for data visualization. Two dimensional plots are ubiquitous and useful to almost any application. Being able to visualize your data in real-time will give you insight and better understanding of your application.
A: Yes, within reason. You can plot tens to hundreds of thousands of points without issue, but don't expect plotting over a million to be a buttery smooth experience. We do our best to keep it fast and avoid memory allocations.
A: Maybe. Check the demo, gallery, or [Announcements](https://github.com/epezent/implot/issues/48) to see if your desired plot type is shown. If not, consider submitting an issue or better yet, a PR!
A: Not currently. Use your OS's screen capturing mechanisms if you need to capture a plot. ImPlot is not suitable for rendering publication quality plots; it is only intended to be used as a visualization tool. Post-process your data with MATLAB and matplotlib for these purposes.
A: Yes, you can use the C binding, [cimplot](https://github.com/cimgui/cimplot) with most high level languages. [DearPyGui](https://github.com/hoffstadt/DearPyGui) provides a Python wrapper, among other things. A Rust binding, [implot-rs](https://github.com/4bb4/implot-rs), is currently in the works. An example using Emscripten can be found [here](https://github.com/pthom/implot_demo).