7 repositorios
Constructs a plot instance with configurable axes, data series, labels, and visual styling for two-dimensional data visualization.
Distinct from Data Plotting Workflows: Distinct from Data Plotting Workflows: focuses on the programmatic construction of plot instances, not the workflow of creating publication-ready plots.
Explore 7 awesome GitHub repositories matching graphics & multimedia · 2D Plot Constructors. Refine with filters or upvote what's useful.
Smile is a comprehensive JVM machine learning library and statistical computing toolkit. It provides a suite of algorithms for classification, regression, and clustering, implemented natively for Java, Scala, and Kotlin. The project also functions as a deep learning framework, a natural language processing library, and an inference engine for large language models. The library distinguishes itself through GPU acceleration via LibTorch bindings and support for the ONNX model interchange format. It includes specialized capabilities for large language model inference, featuring Byte-Pair Encodin
Generates interactive 2D and 3D scatter plots and histograms for scientific data exploration.
Flot is an interactive charting library for jQuery that renders line, bar, pie, and time-series plots with zooming and panning. It provides interactive plots for engineering and scientific data with customizable axes, scales, and series styles, and supports real-time data updates. The library is built as a jQuery plugin with a canvas-based rendering pipeline and a plugin extension system that allows third-party code to add new chart types, interactions, and data transformations. The library distinguishes itself through a broad range of specialized chart types, including candlestick, bubble, r
Creates interactive line, scatter, and image plots for scientific and engineering data.
Provides a constructor for creating 2D plots with configurable axes and styling.
matplotlib-cpp es una biblioteca C++ de solo cabecera y wrapper que permite la creación de visualizaciones 2D y 3D llamando a funciones de Matplotlib directamente desde código C++. Sirve como una interfaz de trazado para generar gráficos de líneas, barras y superficies utilizando un backend basado en Python. La biblioteca está diseñada como una integración ligera que proporciona capacidades de trazado sin requerir un proceso de compilación complejo o binarios compilados. Cubre una gama de capacidades de visualización, incluyendo renderizado de datos multidimensionales, trazado de campos vectoriales y la disposición de múltiples subgráficos. El kit de herramientas también admite la producción de animaciones dinámicas y la exportación de las visualizaciones generadas como archivos de imagen.
Provides programmatic construction of 2D and 3D charts, including line, surface, and quiver plots.
Plotters is a data visualization library for the Rust programming language used to create 2D and 3D charts, plots, and mathematical visualizations. It functions as a multi-backend rendering engine and coordinate mapping framework that translates raw data values into pixel coordinates through customizable chart contexts. The library distinguishes itself through its ability to export graphics to multiple formats, including SVG, BitMap, and HTML5 canvas. It provides specific capabilities for 3D graphics plotting, featuring adjustable camera viewpoints and projection matrices to manage spatial da
Provides programmatic construction of 2D plots with configurable axes, data series, and labels.
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
Creates interactive line, scatter, and image plots for real-time exploration of scientific and engineering data.
bqplot is an interactive data visualization library for Jupyter notebooks. It implements a grammar of graphics model, allowing users to build complex 2D charts by combining marks, scales, and axes. The library distinguishes itself with specialized toolkits for financial charting, such as OHLC candlesticks and time-series analysis, and geographic data visualization, including choropleths and custom map projections for TopoJSON and GeoJSON data. It enables deep interaction through tools like lasso selection, rectangular brushing, and the ability to manually manipulate plot points or line data.
Programmatically constructs interactive 2D plots using a grammar of marks, scales, and axes.