4 个仓库
High-performance libraries and tools for C++ data plotting.
Explore 4 awesome GitHub repositories matching part of an awesome list · C++ Visualization. Refine with filters or upvote what's useful.
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
Qt5-based application for plotting time-series data.
这个 C++ 数据可视化库是一个科学绘图框架,用于创建 2D 和 3D 图表、网络图和地理地图。它作为一个多后端图形库运行,将高级绘图逻辑与低级渲染引擎解耦,以支持各种输出后端。 该项目以其双接口 API 脱颖而出,既提供用于快速原型的全局函数接口,也提供用于精确控制的面向对象接口。它具有一个用于管理平铺网格和子图的基于组件的布局引擎,以及一个允许在不清除坐标轴的情况下叠加多个数据系列的层级绘图状态。 该库涵盖了广泛的可视化功能,包括数学函数绘图、向量场,以及通过热力图和平行坐标进行的多维数据分析。它包括用于地理数据可视化的专用工具(如地理气泡图和地理密度图),以及用于渲染有向和无向图网络的工具。通用功能包括坐标轴管理、带有色图的美学样式,以及高质量图形的导出。 该项目利用 CMake 进行构建自动化和依赖检索,以促进在不同操作系统上的安装。
Provides a high-performance C++ library for creating 2D and 3D scientific charts, plots, and graphs.
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.
Enables high-performance 2D and 3D data plotting directly within C++ applications.
#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…
Implementation for visualizing large-scale, high-dimensional data.