Open Source Data Visualization Software - Page 6
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Data Visualization Software
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ImplicitDifferentiation.jl
Automatic differentiation of implicit functions
ImplicitDifferentiation.jl is a package for automatic differentiation of functions defined implicitly, i.e., forward mappings. Those for which automatic differentiation fails. Reasons can vary depending on your backend, but the most common include calls to external solvers, mutating operations or type restrictions. Those for which automatic differentiation is very slow. A common example is iterative procedures like fixed point equations or optimization algorithms. -
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InfiniteOpt.jl
An intuitive modeling interface for infinite-dimensional optimization
A JuMP extension for expressing and solving infinite-dimensional optimization problems. InfiniteOpt.jl provides a general mathematical abstraction to express and solve infinite-dimensional optimization problems (i.e., problems with decision functions). Such problems stem from areas such as space-time programming and stochastic programming. InfiniteOpt is meant to facilitate intuitive model definition, automatic transcription into solvable models, permit a wide range of user-defined extensions/behavior, and more. -
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IntervalRootFinding.jl
Find all roots of a function in a guaranteed way with Julia
This package provides guaranteed methods for finding roots of functions, i.e. solutions to the equation f(x) == 0 for a function f. To do so, it uses methods from interval analysis, using interval arithmetic from the IntervalArithmetic.jl package by the same authors. The basic function is roots. A standard Julia function and an interval is provided and the roots function return a list of intervals containing all roots of the function located in the starting interval. -
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JILL.py
A cross-platform installer for the Julia programming language
The enhanced Python fork of JILL, Julia Installer for Linux (and every other platform), Light. -
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Javis
Julia Animations and Visualizations
Javis: Julia Animations and Visualizations. Javis makes generating simple animations a breeze! Want to learn more? Check out our documentation for tutorials, our contributing guidelines, and the mission of Javis.jl. We have a live Zulip stream that you can join to discuss Javis with other Javis users. -
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LLVM.jl
Julia wrapper for the LLVM C API
A Julia wrapper for the LLVM C API. The LLVM.jl package is a Julia wrapper for the LLVM C API, and can be used to work with the LLVM compiler framework from Julia. You can use the package to work with LLVM code generated by Julia, to interoperate with the Julia compiler, or to create your own compiler. It is heavily used by the different GPU compilers for the Julia programming language. -
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LanguageServer.jl
An implementation of the Microsoft Language Server Protocol
This package implements the Microsoft Language Server Protocol for the Julia programming language. Text editors with a client for the Language Server Protocol are able to make use of the Julia Language Server for various code editing features. -
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LiveServer.jl
Simple development server with live-reload capability for Julia
This is a simple and lightweight development web-server written in Julia, based on HTTP.jl. It has live-reload capability, i.e. when modifying a file, every browser (tab) currently displaying the corresponding page is automatically refreshed. -
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MacroTools.jl
MacroTools provides a library of tools for working with Julia code
MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system and code-walking tools that let you do deep transformations of code in a few lines. See the docs for more info. -
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Mapbox GL JS
Interactive, thoroughly customizable maps in the browser
Mapbox GL JS is a JavaScript library that uses WebGL to render interactive maps from vector tiles and Mapbox styles. It is part of the Mapbox GL ecosystem, which includes Mapbox Mobile, a compatible renderer written in C++ with bindings for desktop and mobile platforms. Mapbox GL JS is part of the cross-platform Mapbox GL ecosystem, which also includes compatible native SDKs for applications on Android, iOS, macOS, Qt, and React Native. Mapbox provides building blocks to add location features like maps, search, and navigation into any experience you create. To get started with GL JS or any of our other building blocks, sign up for a Mapbox account. In addition to GL JS, this repository contains code, issues, and test fixtures that are common to both GL JS and the native SDKs. Mapbox GL JS v2 enables 3D mapping with elevated terrain, customizable skies and atmospheric lighting, a new camera, and performance enhancements. -
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Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy). Matplotlib is the brainchild of John Hunter (1968-2012), who, along with its many contributors, have put an immeasurable amount of time and effort into producing a piece of software utilized by thousands of scientists worldwide. Matplotlib is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. Matplotlib has support for visualizing information with a wide array of colors and colormaps. -
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MethodOfLines.jl
Automatic Finite Difference PDE solving with Julia SciML
MethodOfLines.jl is a Julia package for automated finite difference discretization of symbolically defined PDEs in N dimensions. It uses symbolic expressions for systems of partial differential equations as defined with ModelingToolkit.jl, and Interval from DomainSets.jl to define the space(time) over which the simulation runs. This project is under active development, therefore the interface is subject to change. The docs will be updated to reflect any changes, please check back for current usage information. -
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NNlib.jl
Neural Network primitives with multiple backends
This package provides a library of functions useful for neural networks, such as softmax, sigmoid, batched multiplication, convolutions and pooling. Many of these are used by Flux.jl, which loads this package, but they may be used independently. -
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OptimalTransport.jl
Optimal transport algorithms for Julia
This package provides some Julia implementations of algorithms for computational optimal transport, including the Earth-Mover's (Wasserstein) distance, Sinkhorn algorithm for entropically regularized optimal transport as well as some variants or extensions. Notably, OptimalTransport.jl provides GPU acceleration through CUDA.jl and NNlibCUDA.jl. -
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PeriodicTable.jl
Periodic Table for Julians
A very simple package for accessing elements in the Periodic Table. PeriodicTable.jl provides a Julia interface to a small database of element properties for all of the elements in the periodic table. In particular PeriodicTable exports a global variable called elements, which is a collection of Element data structures. -
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SymbolicRegression.jl
Distributed High-Performance Symbolic Regression in Julia
SymbolicRegression.jl searches for symbolic expressions which optimize a particular objective. -
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Unitful.jl
Physical quantities with arbitrary units
Unitful is a Julia package for physical units. We want to support not only SI units but also any other unit system. We also want to minimize or in some cases eliminate the run-time penalty of units. There should be facilities for dimensional analysis. All of this should integrate easily with the usual mathematical operations and collections that are found in Julia base. -
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deck.gl
WebGL2 powered visualization framework
deck.gl is designed to simplify high-performance, WebGL-based visualization of large data sets. Users can quickly get impressive visual results with minimal effort by composing existing layers, or leveraging deck.gl's extensible architecture to address customer needs. deck.gl maps data (usually an array of JSON objects) into a stack of visual layers - e.g. icons, polygons, texts; and look at them with views: e.g. map, first-person, orthographic. deck.gl handles a number of challenges out of the box. Deck.gl is designed to be highly customizable. All layers come with flexible APIs to allow programmatic control of each aspect of the rendering. All core classes such are easily extendable by the users to address custom use cases. deck.gl is part of vis.gl, an OpenJS Foundation project. Read the contribution guidelines if you are interested in contributing. -
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jlpkg
A command line interface (CLI) for Pkg, Julia's package manager
A command line interface (CLI) to Pkg, Julia's package manager. -
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jlrs
Julia bindings for Rust
jlrs is a crate that provides access to most of the Julia C API, it can be used to embed Julia in Rust applications and to use functionality it provides when writing ccallable functions in Rust. Currently, this crate is only tested in combination with Julia 1.6 and 1.9, but also supports Julia 1.7, 1.8, and 1.10. Using the current stable version is highly recommended. The minimum supported Rust version is currently 1.65. Julia must be installed before jlrs can be used, jlrs is compatible with Julia 1.6 up to and including Julia 1.10. The JlrsCore package must also have been installed, if this is not the case it will automatically be added when jlrs is initialized by default. jlrs has not been tested with juliaup yet on Linux and macOS. -
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visual-explainer
Agent skill + prompt templates that generate rich HTML pages
visual-explainer is an AI-oriented agent skill that converts complex terminal or analytical output into polished, human-readable HTML reports designed for quick comprehension and sharing. The project includes prompt templates and automation logic that enable coding agents to generate visual summaries such as diff reviews, architecture overviews, plan audits, and structured data tables. Its primary goal is to bridge the readability gap between raw machine output and stakeholder-friendly documentation. By producing styled web pages instead of plain text logs, visual-explainer improves communication in engineering and AI workflows where clarity is critical. The tool is particularly useful in environments that rely on autonomous agents or CI pipelines that generate dense technical output. -
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EtherApe is a graphical network monitor modeled after etherman. Featuring Ethernet, IP, TCP, FDDI, Token Ring and wireless modes, it displays network activity graphically. Hosts and links change in size with traffic. Color coded protocols display.
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Euler Math Toolbox
Numerical and Symbolic Math Tool
Euler is a powerful all-in-one numerical software and includes Maxima for seamless symbolic computations. Euler supports Latex for math display, Povray for photo-realistic 3D scenes, Python, Matplotlib and C for scripting, and contains a full programming language. Features include libraries for numerical algorithms, optimization, plotting in 2D and 3D, graphics export, a complete help system, tutorials and examples. Euler runs in Windows natively, or in Linux via Wine. It is completely free of royalties. The source is licensed under GPL. -
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AppleAccelerate.jl
Julia interface to the macOS Accelerate framework
Julia interface to the macOS Accelerate framework. This provides a Julia interface to some of the macOS Accelerate frameworks. At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced accuracy.
