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Back to lferry007/largevis

Open-source alternatives to LargeVis

6 open-source projects similar to lferry007/largevis, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best LargeVis alternative.

  • facontidavide/plotjugglerfacontidavide avatar

    facontidavide/PlotJuggler

    5,957View on GitHub↗

    PlotJuggler is an interactive time series visualization tool that loads, streams, and renders large datasets using hardware-accelerated OpenGL graphics. It functions as a multi-format data loader, supporting file formats such as CSV, ULog, and ROS bags, and also serves as a live data stream viewer that subscribes to real-time sources via MQTT, WebSockets, ZeroMQ, and UDP. The tool distinguishes itself through a plugin-based extensibility platform that allows users to add custom data sources, file formats, and processing capabilities. It includes a Lua scripting engine for creating custom data

    C++
    View on GitHub↗5,957
  • alandefreitas/matplotplusplusalandefreitas avatar

    alandefreitas/matplotplusplus

    4,894View on GitHub↗

    This C++ data visualization library is a scientific plotting framework used to create 2D and 3D charts, network graphs, and geographic maps. It operates as a multi-backend graphics library, decoupling high-level plotting logic from low-level rendering engines to support various output backends. The project distinguishes itself with a dual-interface API, providing both a global functional interface for rapid prototyping and an object-oriented interface for precise control. It features a component-based layout engine for managing tiled grids and subplots, alongside a layered plot state that all

    C++charting-librarychartscontour-plots
    View on GitHub↗4,894
  • lava/matplotlib-cpplava avatar

    lava/matplotlib-cpp

    4,760View on GitHub↗

    matplotlib-cpp is a header-only C++ library and wrapper that enables the creation of 2D and 3D visualizations by calling Matplotlib functions directly from C++ code. It serves as a plotting interface for generating line plots, bar graphs, and surface charts using a Python-based backend. The library is designed as a lightweight integration that provides plotting capabilities without requiring a complex build process or compiled binaries. It covers a range of visualization capabilities, including multi-dimensional data rendering, vector field plotting, and the arrangement of multiple subplots.

    C++
    View on GitHub↗4,760

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  • ajstarks/svgoajstarks avatar

    ajstarks/svgo

    2,247View on GitHub↗

    Go Language Library for SVG generation

    Go
    View on GitHub↗2,247
  • chenjiandongx/go-echartschenjiandongx avatar

    chenjiandongx/go-echarts

    7,626View on GitHub↗

    go-echarts is a Go library and wrapper for Apache ECharts used to create interactive data visualizations. It functions as a generator that produces the configurations and HTML files necessary to render complex datasets as visual charts and graphs in a web browser. The library includes specialized tools for geographic data visualization, allowing spatial information and distributed datasets to be mapped using coordinates and regional boundaries. The project supports exporting visualizations as standalone HTML files for static use or serving them through an HTTP server for web-based dashboardi

    Go
    View on GitHub↗7,626
  • gonum/plotgonum avatar

    gonum/plot

    2,957View on GitHub↗

    A repository for plotting and visualizing data

    Go
    View on GitHub↗2,957