Search Results for "visual-" - Page 2
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Showing 155 open source projects for "visual-"
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beautiful-mermaid
Render Mermaid diagrams as beautiful SVGs or ASCII art
beautiful-mermaid is a styling and rendering toolkit built to produce visually enhanced diagrams from Mermaid syntax, aiming to bridge the gap between simple technical diagrams and rich, presentation-ready visualizations, all while preserving the lightweight text-to-diagram workflow that Mermaid offers. Instead of plain, utilitarian shapes and lines, Beautiful Mermaid applies themes, typography enhancements, color palettes, and layout optimizations so diagrams look polished and professional... -
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Chokidar
Minimal and efficient cross-platform file watching library
...Same as with Node.js fs.watchFile. Therefore, Chokidar resolves these problems. Initially made for Brunch (an ultra-swift web app build tool), it is now used in Microsoft's Visual Studio Code, gulp, karma, PM2, browserify, webpack, BrowserSync, and many others. It has proven itself in production environments. Chokidar does still rely on the Node.js core fs module, but when using fs.watch and fs.watchFile for watching, it normalizes the events it receives, often checking for truth by getting file stats and/or dir contents. -
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PyVista
3D plotting and mesh analysis through a streamlined interface
...PyVista is a helper module for the Visualization Toolkit (VTK) that takes a different approach on interfacing with VTK through NumPy and direct array access. This package provides a Pythonic, well-documented interface exposing VTK’s powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets. This module can be used for scientific plotting for presentations and research papers as well as a supporting module for other mesh-dependent Python modules. Easily integrate with NumPy and create a variety of geometries and plot them. You could use any geometry to create your glyphs, or even plot the points directly. ... -
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ggforce
Accelerating ggplot2
ggforce is an extension package for ggplot2 that introduces specialized statistical transforms, geoms, and layout utilities to enhance and complement the built-in ggplot2 offerings. It enables more advanced visualization techniques such as faceting enhancements, hulls, annotation marks, and novel layouts for network data and marked regions. -
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Observable Plot
A concise API for exploratory data visualization
...In the spirit of show don’t tell, below is a scatterplot of the height and weight of Olympic athletes (sourced from Matt Riggott), constructed using a dot mark. We assign columns of data (such as weight) to visual properties (such as the dot’s x), and Plot infers the rest. You can configure much more, if needed, but Plot’s goal is to help you get a meaningful visualization quickly. Plot employs a layered grammar of graphics inspired by Vega-Lite, ggplot2, Wilkinson’s Grammar of Graphics, and Bertin’s Semiology of Graphics. Plot rejects a chart typology in favor of marks, scales, and transforms. ... -
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WordCloud.jl
Word cloud generator in julia
Word cloud (tag cloud or wordle) is a novelty visual representation of text data. The importance of each word is shown with its font size, position, or color. WordCloud.jl is the perfect tool for generating word clouds, offering several advantages. You have control over every aspect of generating a word cloud. You can customize the shape, color, angle, position, distribution, density, and spacing to align with your preferences and artistic style. -
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AI Data Science Team
An AI-powered data science team of agents
...It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. The project includes ready-to-use applications that showcase these agents in action, such as an exploratory data analysis copilot that generates reports, a pandas data analyst that combines wrangling and plotting, and SQL database agents that can query business databases and output results directly. -
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city-roads
Visualization of all roads within any city
...It typically fetches open map data (such as from OpenStreetMap) and then processes that data into geometry suited for rendering in the browser, allowing users to explore intricate road layouts at various scales. The visual style often abstracts away labels and extraneous map features to focus purely on the road network, giving a unique, aesthetic view of urban form and connectivity. Because road topology reflects historical, geographic, and planning decisions, the resulting images serve as both analytical tools and generative art. Developers can integrate it into web pages or interactive dashboards where geographic structure is central, and users can pan/zoom to compare different cities or neighborhoods. -
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Luigi
Python module that helps you build complex pipelines of batch jobs
Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more. The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop... -
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Simplio3D Visual Product Configurator
Web Based 3D Visual Product Configurator Software
With Simplio3D, you can easily create interactive and engaging 3D renderings to increase your sales. The newly developed platform is built on the basis of over 10 years of experience, one of the main goals being as friendly as possible to any user with any skill level. The platform takes e-commerce to another level, offering potential customers an interactive and engaging product experience. -
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Java 2D & 3D visual entity relationship design & modeling (ERD,SQL) for Oracle,MSSQL,Postgres,MySQL,...,Database change&dictionary management, Swing Data Binding, Apache FOP Renderer for dot matrix printers,Sparx Enterprise Architect Reports + more
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GLScene
GLScene Engine for Delphi & C++Builder VCL Windows 32/64
GLScene is an OpenGL based 3D library for Delphi, C++Builder and Lazarus. It provides visual components and objects allowing description and rendering 3D scenes in graphic applications. Update of newer versions of the trunk has been moved to https://github.com/glscene -
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qvge
Qt Visual Graph Editor
qvge is a multiplatform graph editor written in C++/Qt. Its main goal is to make possible visually edit two-dimensional graphs in a simple and intuitive way. Please note that qvge is not a replacement for such a software like Gephi, Graphvis, Dot, yEd, Dia and so on. It is neither a tool for "big data analysis" nor a math application. It is really just a simple graph editor :) -
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airda
airda(Air Data Agent
airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes. -
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FreeImage is a library project for developers who would like to support popular graphics image formats (PNG, JPEG, TIFF, BMP and others). Some highlights are: extremely simple in use, not limited to the local PC (unique FreeImageIO) and Plugin driven!
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seaborn
Statistical data visualization in Python
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps you explore and understand your data. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API lets you focus on what the different elements of... -
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InstaGraph
Converts text input or URL into knowledge graph and displays
InstaGraph is a Flask application that converts text input or a URL into a visual knowledge graph. It uses an LLM to identify entities, relationships, labels, and node types from the provided content. The generated graph is displayed visually, helping users understand relationships that may be harder to see in plain text. The project includes Graphviz-based visualization logic and supports updating an existing graph through follow-up instructions. -
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Rawgraphs app
A web interface to create custom vector-based visualizations
Inspired by and built on top of open-source projects. RAWGraphs is open to the community for contributions. Almost 30 visual models to visualize quantities, hierarchies, and time series and find insights in your data. Even though RAWGraphs is a web app, the data you insert will be processed only by your web browser. Save your project, or export it as a vector or raster image. Edit it within your favorite software. RAWGraphs is an open source data visualization framework built with the goal of making the visual representation of complex data easy for everyone. ... -
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SolexaQA is a software to calculate quality statistics and visual representations of data quality for second-generation sequencing data.
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NBi
NBi is a testing framework (add-on to NUnit)
...The main goal of this framework is to let users create tests with a declarative approach based on an Xml syntax. By the means of NBi, you don't need to develop C# code to specify your tests! Either, you don't need Visual Studio to compile your test suite. Just create an Xml file and let the framework interpret it and play your tests. The framework is designed as an add-on of NUnit but with the possibility to port it easily to other testing frameworks. -
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High Dynamic Range Visual Difference Predictor (HDR VDP) is a perceptual metric that can predict whether differences between two images are visible to the human observer or not.
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Orchest
Build data pipelines, the easy way
Code, run and monitor your data pipelines all from your browser! From idea to scheduled pipeline in hours, not days. Interactively build your data science pipelines in our visual pipeline editor. Versioned as a JSON file. Run scripts or Jupyter notebooks as steps in a pipeline. Python, R, Julia, JavaScript, and Bash are supported. Parameterize your pipelines and run them periodically on a cron schedule. Easily install language or system packages. Built on top of regular Docker container images. Creation of multiple instances with up to 8 vCPU & 32 GiB memory. ... -
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missingno
Missing data visualization module for Python
Messy datasets? Missing values? missingno provides a small toolset of flexible and easy-to-use missing data visualizations and utilities that allows you to get a quick visual summary of the completeness (or lack thereof) of your dataset. Just pip install missingno to get started. This quickstart uses a sample of the NYPD Motor Vehicle Collisions Dataset dataset. The msno.matrix nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion. At a glance, date, time, the distribution of injuries, and the contribution factor of the first vehicle appear to be completely populated, while geographic information seems mostly complete, but spottier. ... -
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Tree Visualisation with Visual Cues
Tree Visualisation with Visual Cues
This project extends a previous work on node link tree visualisation and interaction by providing visual clues on hidden structures. We adopt DOITree from Prefuse package (https://github.com/prefuse/Prefuse), a multi-focal tree layout algorithm, for exploring large hierarchical structures. Related publications: https://www.sciencedirect.com/science/article/pii/S1045926X1630009X https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6902871 -
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SnappyData
Memory optimized analytics database, based on Apache Spark
...One common use case for SnappyData is to provide analytics at interactive speeds over large volumes of data with minimal or no pre-processing of the dataset. For instance, there is no need to often pre-aggregate/reduce or generate cubes over your large data sets for ad-hoc visual analytics. This is made possible by smartly managing data in memory, dynamically generating code using vectorization optimizations, and maximizing the potential of modern multi-core CPUs. SnappyData enables complex processing on large data sets in sub-second timeframes.