14 مستودعات
Methodologies for creating high-quality scientific 2D and 3D graphical representations.
Distinct from Plotting and Visualization: Focuses on the workflow and quality of publication-ready plots, which is broader than specific 2D histogram visualizers.
Explore 14 awesome GitHub repositories matching graphics & multimedia · Data Plotting Workflows. Refine with filters or upvote what's useful.
This project is a collection of interactive Python notebooks and educational resources designed for mastering data science, machine learning, and numerical computing. It provides a series of practical guides and tutorials covering deep learning, big data processing, and statistical analysis. The repository features specialized instructional suites for implementing classical machine learning algorithms, building deep learning model architectures, and managing AWS cloud infrastructure. It includes dedicated notebooks for data visualization and numerical computing exercises. The project covers
Provides a workflow for creating publication-quality 2D and 3D plots and maps using matplotlib.
FriendsDontLetFriends is a scientific data visualization guide and framework designed to help users create accurate plots while avoiding common data representation mistakes. It provides a collection of scripts and guidelines for selecting distribution plots, color scales, and layouts that accurately represent complex experimental data. The project distinguishes itself through specialized toolkits for revealing hidden patterns in large datasets. It includes systems for heatmap optimization via dimension reordering and outlier management, as well as spatial layout algorithms to improve the inte
Implements a methodology for selecting appropriate distribution plots and color scales for complex scientific data.
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.
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
Export the current chart to a PNG file at a specified size for sharing or storage.
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.
Saves the current plot view as a raster image file for sharing or embedding in reports.
Provides a constructor for creating 2D plots with configurable axes and styling.
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
Generates publication-quality figures featuring error bars, logarithmic scales, and contour plots.
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.
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.
Briefer هي منصة دفاتر بيانات تفاعلية وأداة لوحة تحكم ذكاء الأعمال تُستخدم لتحليل البيانات والتقارير التعاونية. توفر بيئة معتمدة على الحاويات لبناء تقارير تجمع بين SQL، وPython، وMarkdown مع تصورات أصلية. تتميز المنصة بمساعد كود مدمج يستخدم نماذج لغة كبيرة لتوليد مقتطفات SQL و Python من مطالبات اللغة الطبيعية. وهي مصممة كتطبيق بيانات Kubernetes، حيث يتم النشر عبر Helm charts لإدارة بيئات الحوسبة المعزولة وضمان موارد منفصلة لكل صفحة من خلال العزل القائم على الـ pod. يغطي النظام نطاقاً واسعاً من القدرات بما في ذلك اتصال قاعدة البيانات الخارجية، والتحرير المشترك في الوقت الفعلي، وتسليم التقارير المؤتمتة عبر الجدولة. تتكامل مع OpenID Connect لتوفير الهوية وتوفر تحكماً في الوصول قائماً على الأدوار، وإدارة آمنة للاعتمادات، وتخزين مؤقت للاستعلام قائم على النتائج. يتم نشر التطبيق وتوسيع نطاقه عبر مجموعات Kubernetes باستخدام Helm charts مدارة.
Saves data plots and visualizations generated by code or blocks as PNG image files.
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.
MNE-Python is an open-source Python library for processing, visualizing, and analyzing human neurophysiological data, including MEG, EEG, sEEG, ECoG, and NIRS recordings. It provides a comprehensive framework for loading data from over 30 proprietary file formats into a common hierarchical FIF data structure, and represents all time-series data as NumPy arrays for seamless integration with the scientific Python ecosystem. The library is built around object-oriented data containers that encapsulate raw, epoched, evoked, and source data with built-in preprocessing and visualization methods. The
Provides specialized butterfly-style evoked response plotting with channel-type grouping and global field power overlay.
Makie.jl is a high-performance Julia data visualization library and hardware-accelerated plotting engine used to create interactive 2D and 3D visualizations. It functions as a reactive visualization framework where plots update automatically via observables and compute graphs, and as a vector graphics generator for high-resolution academic output. The system is distinguished by its backend-agnostic rendering pipeline, which supports OpenGL, WebGL, and ray-traced scenes. It employs a grammar-of-graphics approach to map variables to aesthetic attributes and utilizes a hierarchical scene graph t
Generates high-performance 2D and 3D plots including lines and surfaces to visualize complex datasets.