![]() ffmpeg (optional), for making live screencasts.GLFW (mandatory) (support for alternative window backends will be considered).The GPU code of most 2D visuals in Datoviz comes directly from Glumpy. Glumpy, developed by Nicolas Rougier, provides efficient implementations of high-quality 2D visuals on the GPU, using algorithms from the antigrain geometry library. The current strategy is to rebuild VisPy on top of Datoviz, pygfx (a WebGPU-based library developed by Almar Klein), and other backends. In 2021, VisPy received another CZI grant for building VisPy 2.0, a completely redesigned library leveraging newer GPU technology such as Vulkan and WebGPU. In 2020, VisPy received a 1-year funding from the Chan Zuckerberg Initiative (CZI) to improve the documentation and knowledge base. The current version of VisPy suffers from the limitations of OpenGL, a 30-year-old technology. David Hoese and some of the original VisPy developers are currently maintaining the library. There is today a community of users and projects based on VisPy ( napari). We joined forces to create a single library unifying all of our approaches. VisPy is a Python scientific visualization library created in 2013 by Luke Campagnola (developer of pyqtgraph), Almar Klein (developer of visvis), Nicolas Rougier (developer of glumpy), and myself (Cyrille Rossant, developer of galry). ![]() ![]() late 2022?: redesigned internal architecture for multithreading and distributed environments (still a work-in-progress)ĭatoviz borrows heavily ideas and code from other projects.: new experimental release v0.1.0-alpha.1 with bug fixes and minor improvements.: first experimental release v0.1.0-alpha.0 with precompiled pip wheels for Linux, Windows, macOS.: first public experimental release (manual compilation required).2020: multiple cycles of prototyping and refactoring.late 2019: first experiments with using Vulkan for scientific visualization.Distributed architecture (integration in the web browser, Jupyter.).Bindings in other languages (Julia, R, MATLAB, Rust.).Further data transformations: logarithmic, polar, basic Earth coordinate systems for geographical data.More visuals: arrows, triangulations, planar straight-line graphs (PSLG), histograms, areas, graphs, fake 3D spheres.Continuous integration and continuous building.Offscreen rendering and CPU emulation via swiftshader.Builtin creencasts and video recording with ffmpeg (optional dependency).Custom visuals, with custom shaders and/or custom data transformations.GUIs integrated via the Dear ImGUI C++ library (Qt or other backends not required).High-level interactivity: pan & zoom, mouse arcball, first-person cameras.~150 colormaps included (from matplotlib, colorcet, MATLAB).Mixing 2D and 3D plots seamlessly in the same window.High-quality antialiased 2D visuals: markers, paths, lines (contributions by Nicolas P.1000 signals with 30K points each (30M vertices): 200 FPS. ![]() ![]()
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