#LargeVis This is the official implementation of the LargeVis model by the original authors, which is used to visualize large-scale and high-dimensional data (Tang, Liu, Zhang and Mei). It now supports visualizing both high-dimensional feature vectors and networks. The package also contains a…
Las características principales de lferry007/largevis son: C++ Visualization, C++ Visualization Tools, Scientific and System Tools.
Las alternativas de código abierto para lferry007/largevis incluyen: facontidavide/plotjuggler — PlotJuggler is an interactive time series visualization tool that loads, streams, and renders large datasets using… alandefreitas/matplotplusplus — This C++ data visualization library is a scientific plotting framework used to create 2D and 3D charts, network… lava/matplotlib-cpp — matplotlib-cpp is a header-only C++ library and wrapper that enables the creation of 2D and 3D visualizations by… ajstarks/svgo — Go Language Library for SVG generation. chenjiandongx/go-echarts — go-echarts is a Go library and wrapper for Apache ECharts used to create interactive data visualizations. It functions… gonum/plot — A repository for plotting and visualizing data.
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
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
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.
