Search Results for "python programming language"
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Showing 37 open source projects for "python programming language"
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
...Libraries from Python, R, C/Fortran, C++, and Java can also be used. -
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Julia VS Code
Julia extension for Visual Studio Code
This VS Code extension provides support for the Julia programming language. We build on Julia’s unique combination of ease-of-use and performance. Beginners and experts can build better software more quickly, and get to a result faster. With a completely live environment, Julia for VS Code aims to take the frustration and guesswork out of programming and put the fun back in. A hybrid “canvas programming” style combines the exploratory power of a notebook with the productivity and static analysis features of an IDE. ... -
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NetCDF.jl
NetCDF support for the julia programming language
NetCDF support for the Julia programming language, there is a high-level and a medium-level interface for writing and reading netcdf files. The dimensions "x1" and "t" of the variable are called "x1" and "t" in this example. If the dimensions do not exist yet in the file, they will be created. The dimension "x1" will be of length 10 and have the values 11..20, and the dimension "t" will have length 20 and the attribute "units" with the value "s". -
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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. -
Jscrambler: Pioneering Client-Side Protection PlatformJscrambler is the leader in Client-Side Protection and Compliance. We were the first to merge advanced polymorphic JavaScript obfuscation with fine-grained third-party tag protection in a unified Client-Side Protection and Compliance Platform. Our integrated solution ensures a robust defense against current and emerging client-side cyber threats, data leaks, and IP theft, empowering software development and digital teams to innovate securely. With Jscrambler, businesses adopt a unified, future-proof client-side security policy all while achieving compliance with emerging security standards including PCI DSS v4.0. Trusted by digital leaders worldwide, Jscrambler gives businesses the freedom to innovate securely.
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CUDA.jl
CUDA programming in Julia
High-performance GPU programming in a high-level language. JuliaGPU is a GitHub organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well-positioned to productively program hardware accelerators like GPUs without sacrificing performance. The latest development version of CUDA.jl requires Julia 1.8 or higher. -
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Circuitscape.jl
Algorithms from circuit theory to predict connectivity
...Its most common applications include modeling the movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. The new Circuitscape is built entirely in the Julia language, a new programming language for technical computing. Julia is built from the ground up to be fast. As such, this offers a number of advantages over the previous version. -
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TimeZones.jl
IANA time zone database access for the Julia programming language
IANA time zone database access for the Julia programming language. TimeZones.jl extends the Date/DateTime support for Julia to include a new time zone-aware TimeType: ZonedDateTime. -
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LLVM.jl
Julia wrapper for the LLVM C API
...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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Graphs.jl
An optimized graphs package for the Julia programming language
The goal of Graphs.jl is to offer a performant platform for network and graph analysis in Julia, following the example of libraries such as NetworkX in Python. Offers a set of simple, concrete graph implementations – SimpleGraph (for undirected graphs) and SimpleDiGraph (for directed graphs), an API for the development of more sophisticated graph implementations under the AbstractGraph type, and a large collection of graph algorithms with the same requirements as this API. -
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JuliaWorkshop
Intensive Julia workshop that takes you from zero to hero
This is an intensive workshop for the Julia language, composed out of three 2-hour segments. It targets people already familiar with programming, so that the established basics such as for-loops are skipped through quickly and efficiently. Nevertheless, it assumes only rudimentary programming familiarity and does explain concepts that go beyond the basics. The goal of the workshop is to take you from zero to hero (regarding Julia): even if you know nothing about Julia, by the end you should be able to use it like a pro. ... -
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BetaML.jl
Beta Machine Learning Toolkit
The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, Python, R and any other language with a Julia binding. All models are implemented entirely in Julia and are hosted in the repository itself (i.e. they are not wrapper to third-party models). If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its implementation. ... -
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Reduce.jl
Symbolic parser for Julia language term rewriting using REDUCE algebra
...It is a system for doing scalar, vector and matrix algebra by computer, which also supports arbitrary precision numerical approximation and interfaces to gnuplot to provide graphics. It can be used interactively for simple calculations (as illustrated in the screenshot below) but also provides a full programming language, with a syntax similar to other modern programming languages. REDUCE supports alternative user interfaces including Run-REDUCE, TeXmacs and GNU Emacs. REDUCE (and its complete source code) is available free of charge for most common computing systems, in some cases in more than one version for the same machine. The manual and other support documents and tutorials are also included in the distributions. -
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OpenCL.jl
OpenCL Julia bindings
Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
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InvertibleNetworks.jl
A Julia framework for invertible neural networks
Building blocks for invertible neural networks in the Julia programming language. -
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PolyChaos.jl
Julia package to construct orthogonal polynomials
PolyChaos is a collection of numerical routines for orthogonal polynomials written in the Julia programming language. Starting from some non-negative weight (aka an absolutely continuous nonnegative measure). -
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CSV
Utility library for working with CSV and other delimited files
Welcome to CSV.jl! A pure-Julia package for handling delimited text data, be it comma-delimited (csv), tab-delimited (tsv), or otherwise. A fast, flexible delimited file reader/writer for Julia. -
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Nemo.jl
Julia bindings for various mathematical libraries (including flint2)
Nemo is a computer algebra package for the Julia programming language. It aims to cover commutative algebra, number theory and group theory. Julia bindings for various mathematical libraries (including flint2) -
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NBInclude.jl
import code from IJulia Jupyter notebooks into Julia programs
NBInclude is a package for the Julia language that allows you to include and execute IJulia (Julia-language Jupyter) notebook files just as you would include an ordinary Julia file. The goal of this package is to make notebook files just as easy to incorporate into Julia programs as ordinary Julia (.jl) files, giving you the advantages of a notebook (integrated code, formatted text, equations, graphics, and other results) while retaining the modularity and re-usability of .jl files. -
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CounterfactualExplanations.jl
A package for Counterfactual Explanations and Algorithmic Recourse
...Both CE and AR are related tools for explainable artificial intelligence (XAI). While the package is written purely in Julia, it can be used to explain machine learning algorithms developed and trained in other popular programming languages like Python and R. See below for a short introduction and other resources or dive straight into the docs. -
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SciML Style Guide for Julia
A style guide for stylish Julia developers
The SciML Style Guide is a style guide for the Julia programming language. It is used by the SciML Open Source Scientific Machine Learning Organization. As such, it is open to discussion with the community. If the standard for code contributions is that every PR needs to support every possible input type that anyone can think of, the barrier would be too high for newcomers. Instead, the principle is to be as correct as possible to begin with, and grow the generic support over time. ... -
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JUDI.jl
Julia Devito inversion
...The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling operators can also be used as layers in (convolutional) neural networks to implement physics-augmented deep learning algorithms thanks to its implementation of ChainRules's rrule for the linear operators representing the discre wave equation. -
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. ... -
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Makie
Interactive data visualizations and plotting in Julia
Makie is an interactive data visualization and plotting ecosystem for the Julia programming language, available on Windows, Linux, and Mac. The backend packages GLMakie, WGLMakie, CairoMakie and RPRMakie add different functionalities: You can use Makie to interactively explore your data and create simple GUIs in native Windows or web browsers, export high-quality vector graphics or even raytrace with physically accurate lighting. -
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Measurements.jl
Error propagation calculator and library for physical measurements
Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration. Physical measures are typically reported with an error, a quantification of the uncertainty of the accuracy of the measurement. Whenever you perform mathematical operations involving these quantities you have also to propagate the uncertainty, so that the resulting number will also have... -
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Pkg Julia
Package manager for the Julia programming language
Unlike traditional package managers, which install and manage a single global set of packages, Pkg is designed around “environments”: independent sets of packages that can be local to an individual project or shared and selected by name. The exact set of packages and versions in an environment is captured in a manifest file which can be checked into a project repository and tracked in version control, significantly improving reproducibility of projects. If you’ve ever tried to run code you...
