mozilla/metrics-graphics
Metrics Graphics
metrics-graphics is a data visualization library and declarative graphics framework designed to create principled data graphics and layouts. It functions as a statistical graphics engine that maps raw data to geometric shapes and structured objects to render complex, data-driven layouts.
The toolkit specializes in rendering time-series data through line charts and scatterplots using a consistent layout system. It also provides capabilities for statistical distribution mapping, including the creation of rug plots to represent one-dimensional data density.
The system covers a broad surface of data visualization engineering, including custom chart layout design and declarative data visualization. It utilizes a compositional model to translate structured specifications into final pixels.
Features
- Time-Series Visualizers - Provides a comprehensive toolkit for rendering time-series data as line charts, scatterplots, and histograms.
- Statistical Plotting Libraries - Maps raw data to geometric shapes and statistical distributions like rug plots and histograms.
- Visualization Engines - Builds principled charts and layouts to represent complex datasets in a visual format.
- Data Visualization Libraries - Provides a library for creating principled data graphics and layouts optimized for concise representations of complex datasets.
- Geometric Data Mappings - Translates input arrays into geometric shapes like lines or rectangles based on defined mapping rules.
- Data-Driven Shape Generators - Builds complex visual layouts by mapping raw data arrays to geometric shapes and screen coordinates.
- Declarative Rendering - Separates visual properties from rendering implementation by translating structured object definitions into final pixels.
- Declarative Visualization Grammars - Defines visual properties through structured specifications that a rendering engine translates into pixels.
- Scale-Based Coordinate Mappings - Maps raw data values to screen coordinates using linear and logarithmic scales to ensure geometric accuracy.
- Chart Layout Components - Creates precise and consistent data graphics using a compositional system of nested elements and axis-relative positioning.
- Component Composition Patterns - Utilizes a compositional model that builds complex graphics by nesting small primitive elements into a hierarchical tree structure.
- Declarative Visualization Frameworks - Implements a compositional model that defines visual properties via structured objects to render complex data-driven layouts.
- Data-Driven Layouts - Develops precise layouts for data-driven graphics that follow a consistent design system.
- Rug Plots - Provides the capability to represent data point density along a specific axis using rug plots.
- Axis-Relative Positioning - Implements a system for calculating marker and label placements relative to data boundaries to maintain alignment across chart types.
- Hierarchical Layouts - Organizes nested graphical elements into a parent-child structure to coordinate scaling and positioning across the canvas.
- Statistical Distribution Visualizers - Visualizes data density and frequency through rug plots and histograms to understand dataset spread.
- Data Visualization - Library for concise, optimized data charts.
- Data Visualization - Concise and efficient D3-based charting library.
- Game Engines - Library for concise data graphics and layouts.
