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README.md
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README.md
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# ImPlot
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ImPlot is an immediate mode, GPU accelerated plotting library for [Dear ImGui](https://github.com/ocornut/imgui). It aims to provide a first-class API that ImGui fans will love. ImPlot is well suited for visualizing program data in real-time or creating interactive plots, 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.
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ImPlot is an immediate mode, GPU accelerated plotting library for [Dear ImGui](https://github.com/ocornut/imgui). It aims to provide a first-class API that ImGui fans will love. ImPlot is well suited for visualizing program data in real-time or creating interactive plots, 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.
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<img src="https://raw.githubusercontent.com/wiki/epezent/implot/screenshots3/controls.gif" width="270"> <img src="https://raw.githubusercontent.com/wiki/epezent/implot/screenshots3/dnd.gif" width="270"> <img src="https://raw.githubusercontent.com/wiki/epezent/implot/screenshots3/pie.gif" width="270">
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@ -29,7 +29,7 @@ ImPlot is an immediate mode, GPU accelerated plotting library for [Dear ImGui](h
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- and more likely to come
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- mix/match multiple plot items on a single plot
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- configurable axes ranges and scaling (linear/log)
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- time formatted x-axes
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- time formatted x-axes (US formatted or ISO 8601)
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- reversible and lockable axes
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- up to three independent y-axes
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- controls for zooming, panning, box selection, and auto-fitting data
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- several plot styling options: 10 marker types, adjustable marker sizes, line weights, outline colors, fill colors, etc.
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- 10 built-in and user definable colormaps
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- optional plot titles, axis labels, and grid labels
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- optional legend with toggle buttons to quickly show/hide items
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- optional and configurable legends with toggle buttons to quickly show/hide plot items
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- default styling based on current ImGui theme, but most elements can be customized independently
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- customizable data getters and data striding (just like ImGui:PlotLine)
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- accepts data as float, double, and 8, 16, 32, and 64-bit signed/unsigned integral types
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## Usage
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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!
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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()`, `PlotScatter()`, etc). Finally, wrap things up with a call to `ImPlot::EndPlot()`. That's it!
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```cpp
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int bar_data[11] = ...;
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## Integration
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0) Set up an [ImGui](https://github.com/ocornut/imgui) environment if you don't already have one.
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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).
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0) Set up an [ImGui](https://github.com/ocornut/imgui) environment if you don't already have one.
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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).
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2) Create and destroy an `ImPlotContext` wherever you do so for your `ImGuiContext`:
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```cpp
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ImGui::DestroyContext();
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```
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You should be good to go!
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You should be good to go!
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If you want to test ImPlot quickly, consider trying [mahi-gui](https://github.com/mahilab/mahi-gui), which bundles ImGui, ImPlot, and several other packages for you.
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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), OR...
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2) Enable 32-bit indices by uncommenting `#define ImDrawIdx unsigned int` in your ImGui `imconfig.h` file.
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- By default, no anti-aliasing is done on line plots for performance gains. If you use 4x MSAA, then you likely won't even notice. However, you can enable software AA per-plot with the `ImPlotFlags_AntiAliased` flag, or globally with `ImPlot::GetStyle().AntiAliasedLines = true;`.
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- Like ImGui, it is recommended that you compile and link ImPlot as a *static* library or directly as a part of your sources. However, if you are compiling ImPlot and ImGui as separate DLLs, make sure you set the current *ImGui* context with `ImPlot::SetImGuiContext(ImGuiContext* ctx)`. This ensures that global ImGui variables are correctly shared across the DLL boundary.
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## FAQ
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A: If you're looking to generate publication quality plots and/or export plots to a file, ImPlot is NOT the library for you. ImPlot is geared toward plotting application data at realtime speeds. ImPlot does its best to create pretty plots (indeed, there are quite a few styling options available), but it will always favor function over form.
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**Q: Where is the documentation?**
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A: The API is thoroughly commented in `implot.h`, and the demo in `implot_demo.cpp` should be more than enough to get you started.
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**Q: Is ImPlot suitable for plotting large datasets?**
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A: Yes, within reason. You can plot tens to hundreds of thousands of points without issue, but don't expect millions to be a buttery smooth experience. However, you can downsample extremely large datasets by telling ImPlot to stride your data at larger intervals if needed.
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A: Yes, within reason. You can plot tens to hundreds of thousands of points without issue, but don't expect millions to be a buttery smooth experience. That said, you can always downsample extremely large datasets by telling ImPlot to stride your data at larger intervals if needed.
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**Q: Can plot styles be modified?**
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A: Yes. Plot colors, palettes, and various styling variables can be pushed/popped or modified permanently on startup. Three default styles are available, as well as an automatic style that attempts to match you ImGui style.
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A: Yes. Data colormaps and various styling colors and variables can be pushed/popped or modified permanently on startup. Three default styles are available, as well as an automatic style that attempts to match you ImGui style.
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**Q: Does ImPlot support logarithmic scaling or time formatting?**
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**Q: Does ImPlot support multiple y-axes? x-axes?**
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A: Yes. Up to three y-axes can be enabled. Multiple x-axes are not supported.
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A: Yes. Up to three y-axes can be enabled. Multiple x-axes are not supported.
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**Q: Does ImPlot support [insert plot type]?**
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**Q: What data types can I plot?**
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A: ImPlot plotting functions accept most scalar types:
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`float`, `double`, `int8`, `uint8`, `int16`, `uint16`, `int32`, `uint32`, `int64`, `uint64`.
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A: ImPlot plotting functions accept most scalar types:
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`float`, `double`, `int8`, `uint8`, `int16`, `uint16`, `int32`, `uint32`, `int64`, `uint64`. Arrays of custom structs or classes (e.g. `Vector2f` or similar) are easily passed to ImPlot functions using the built in striding features (see `implot.h` for documentation).
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**Q: Can ImPlot be used with other languages/bindings?**
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A: Yes, you can use the generated 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).
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A: Yes, you can use the generated 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).
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