16 个仓库
Frameworks that combine high-level plotting APIs with browser-based interactive rendering engines.
Distinct from Graphics and Plotting: The candidates are either too broad (Graphics and Plotting) or too specific (Installation Frameworks), failing to capture the specific Python-to-Browser plotting paradigm.
Explore 16 awesome GitHub repositories matching scientific & mathematical computing · Interactive Plotting Frameworks. Refine with filters or upvote what's useful.
Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance graphics and data dashboards that render in web browsers. It serves as a tool for generating standalone HTML documents, embedded components for digital notebooks, and full-stack web applications powered by a Python backend. The project distinguishes itself through its ability to handle large or streaming datasets while maintaining smooth interactivity. It enables linked brushing across multiple views, allowing data selected in one plot to automatically highlight corresponding data i
Provides a framework for rendering high-performance graphics and streaming datasets in browsers via a Python backend.
pyecharts is a Python visualization library and wrapper for the Echarts JavaScript engine. It translates Python data and configurations into JSON specifications to generate interactive web-based charts and graphs. The library provides specialized capabilities for geographic data mapping using a comprehensive library of map assets to visualize spatial information. It also includes utilities to capture rasterized snapshots of rendered web visualizations for export as static image files. The tool supports rendering interactive plots directly within data science notebook environments and exporti
Combines a high-level Python API with a browser-based rendering engine for interactive data plotting.
TensorBoard is a visualization toolkit for tracking and analyzing machine learning model training progress and performance using TensorFlow event logs. It provides a monitoring dashboard for plotting scalar metrics, tensor distributions, and training curves, and includes specialized tools for visualizing neural network computational graphs and projecting high-dimensional embeddings. The project enables side-by-side comparison of multiple training runs to analyze the impact of hyperparameters on model outcomes. It also features a high-dimensional embedding projector and a graph visualizer for
Provides an interactive browser-based plotting interface for analyzing numerical training metrics over time.
VectorBT is a vectorized trading strategy backtesting framework that simulates thousands of strategy configurations in a single pass over historical price data. It operates as a parameter optimization engine, a portfolio performance analyzer, a technical indicator calculator, and a financial data fetcher, all built around a DataFrame-centric data model that uses NumPy broadcasting for signal alignment and compiled code acceleration for performance. The framework distinguishes itself through its ability to run large-scale parameter sweeps by constructing every combination of strategy parameter
Generates browser-ready charts and dashboards using Plotly for exploring backtest results.
ScottPlot is a cross-platform, high-performance charting library for .NET that renders interactive plots across desktop and web GUI frameworks including Windows Forms, WPF, MAUI, Avalonia, Blazor, and WinUI. It provides an optimized rendering engine capable of displaying millions of data points with interactive pan, zoom, and live data streaming, while also supporting image export to formats like PNG and SVG for file output, cloud applications, and notebooks. The library distinguishes itself through a comprehensive set of chart types including scatter, line, bar, pie, heatmap, financial, rada
Provides interactive charting for .NET with pan, zoom, and real-time exploration across desktop and web frameworks.
Provides zooming, panning, box selection, auto-fitting, and persistent query ranges for data exploration.
Orange3 is a visual data mining platform that provides an interactive canvas for building data analysis workflows without writing code. At its core, it offers a widget-based visual programming environment where users connect configurable components to perform data preprocessing, machine learning model training, statistical evaluation, and interactive visualization. The platform is built on NumPy-backed data tables with domain descriptors that define variable names, types, and roles, and includes a lazy SQL query proxy for working with database tables without loading all data into memory. The
Displays interactive plots and widgets that update in real-time as the data analysis workflow changes.
Live-Charts 是一个 .NET 数据可视化库,提供了一系列交互式图表、地图和仪表盘。它作为一个实时图表引擎和多格式图形库,旨在在 .NET 应用程序中渲染复杂数据集。 该库具有用于创建能够探索大型数据集的交互式数据仪表盘的工具。这由一个用于缩放、平移和利用多个坐标轴来导航数十万个数据点的系统所支持。 该可视化引擎支持多种格式,包括柱状图、折线图、热力图和地理地图。它包括用于实时数据监控和开发桌面仪表盘以跟踪实时指标和趋势的功能。
Acts as an interactive charting library for .NET, rendering diverse plot types across desktop and web GUI frameworks.
Shiny is a framework for building interactive web applications using R code, eliminating the need for HTML, CSS, or JavaScript. At its core, it provides a reactive programming model that automatically tracks data dependencies and re-executes only the parts of an application that depend on changed inputs. The framework handles server-side UI rendering and maintains persistent WebSocket connections between the browser and server for real-time updates without page reloads. The framework distinguishes itself through deep integration with the R ecosystem, including the ability to embed interactive
Responds to clicks, brushes, and hovers on plots to filter or highlight data elsewhere in the app.
ScrollableGraphView 是一个 Swift 数据可视化库和 iOS 绘图框架,用于将离散数值数据集渲染为交互式图表。它提供了一个可滚动的用户界面组件,使用具有可配置布局和样式的坐标系来可视化数据点。 该框架的特点是其自适应图表缩放,当用户滚动时,它会自动调整垂直轴以适应可见数据点。它支持实时数据渲染,允许图表视图随着底层数据集通过动画过渡发生变化而即时更新。 该库涵盖了多种图表类型,包括折线图、柱状图和点图,并支持多数据集绘图以在单个图表上显示多个数据系列。其他功能包括 X 轴数据点标注、自定义图表样式,以及使用参考线标记来突出显示特定阈值或基准值。
Serves as a comprehensive framework for displaying multiple data series on a single coordinate system with configurable layouts for iOS.
LiveCharts2 是一个 .NET 数据可视化库和跨平台图表工具包。它提供了一系列交互式图表、地图和仪表盘,旨在跨各种 .NET 用户界面框架和操作系统表示复杂数据集。 该项目实施了一种跨框架 UI 图表方法,使用在不同 .NET UI 技术栈中保持一致的单个 API。这允许创建响应式视觉表示和交互式仪表板,以响应用户输入和状态变化。 该工具包涵盖了实时数据映射和动态数据图表的渲染。它利用抽象层将图表 API 转换为框架特定的绘图命令,从而实现跨不同设备的视觉效果显示。
Provides an interactive plotting library for .NET that renders diverse chart types across desktop and web GUI frameworks.
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。
Generates dynamic visualizations that allow users to explore and interact with data in real-time.
statsforecast 是一个高性能统计时间序列预测库,旨在生成点预测和预测区间。它作为一个分布式时间序列框架,利用基于 C 的预测引擎和自动模型选择器来识别并拟合数据集中每个唯一序列的最佳统计模型。该系统还包括一个时间序列异常检测器,通过将观测值与概率预测区间进行比较来识别异常数据点。 该项目的特色在于其处理数百万个独立序列的大规模并行预测的能力。它通过分布式计算框架、多核并行执行和加速核心 ARIMA 及指数平滑逻辑的编译 C 内核来实现这一点。该系统进一步利用长格式数据布局和惰性求值数据流水线来优化大规模处理,以减少内存开销。 该库提供了一套全面的模型,包括 AutoARIMA、用于间歇性或季节性需求的各种指数平滑方法、Theta 分解以及用于金融风险的 GARCH 波动率建模。它涵盖了更广泛的功能领域,例如带有外生变量的多元预测、时间序列分解以及通过历史交叉验证和滑动窗口分析进行模型评估。 该库与 Polars 等高性能数据结构集成,并提供将保存的模型作为 REST 端点提供服务以进行网络可访问预测的实用程序。
Renders time series predictions and uncertainty intervals as interactive plots for performance analysis.
PyQtGraph is a scientific plotting and graphics framework built for PyQt and PySide applications, providing fast, interactive 2D and 3D visualizations with GPU-accelerated rendering. It serves as both a real-time signal monitoring system for streaming time-series data and a toolkit for constructing interactive data dashboards with dockable panels, parameter trees, and custom widgets. The library also includes a node-based visual flowchart tool for building data processing pipelines and a scientific graphics export system that saves plots as PNG, SVG, or CSV and converts items to Matplotlib for
Provides ready-made GUI components for plotting, image viewing, parameter editing, and data exploration.
PyVista is a scientific 3D plotting framework and visualization library that provides a Python interface for rendering and analyzing spatial datasets using a VTK backend. It functions as a volumetric rendering engine and a 3D mesh analysis tool for computing geometric properties and performing boolean operations on surface and volumetric meshes. The project is distinguished by its ability to operate as a headless 3D renderer, generating high-quality renders and animations on remote servers without a physical display. It also features a lazy-accessor extension mechanism that allows the registr
Provides interactive widgets like sliders and boxes to manipulate filters and data views in real time.
bqplot is an interactive data visualization library for IPython and Jupyter notebooks that utilizes a grammar of graphics. It functions as a tool for creating 2D charts and maps with real-time updates and bidirectional communication between the kernel and frontend. The library is distinguished by its ability to act as a geographic data visualization tool, rendering choropleth maps and spatial data via GeoJSON and custom projections. It also serves as a financial charting tool for producing OHLC and candle bar charts, and as an interactive dashboard framework for combining plotting widgets wit
Combines high-level plotting APIs with browser-based rendering to create reactive data applications in notebooks.