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  • 1
    PhysicalConstants.jl

    PhysicalConstants.jl

    Collection of fundamental physical constants with uncertainties

    PhysicalConstants.jl provides common physical constants. They are defined as instances of the new Constant type, which is a subtype of AbstractQuantity (from Unitful.jl package) and can also be turned into Measurement objects (from Measurements.jl package) at request. Constants are grouped into different submodules so that the user can choose different datasets as needed. Currently, 2014 and 2018 editions of CODATA recommended values of the fundamental physical constants are provided.
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  • 2
    MultivariatePolynomials.jl

    MultivariatePolynomials.jl

    Multivariate polynomials interface

    ...It defines abstract types and an API for multivariate monomials, terms, and polynomials and gives default implementation for common operations on them using the API. On the one hand, This packages allows you to implement algorithms on multivariate polynomials that will be independant on the representation of the polynomial that will be chosen by the user. On the other hand, it allows the user to easily switch between different representations of polynomials to see which one is faster for the algorithm that he is using.
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  • 3
    ColorSchemes.jl

    ColorSchemes.jl

    colorschemes, colormaps, gradients, and palettes

    Color schemes, colormaps, gradients, and palettes. Choose ColorSchemes with care. Refer to Peter Kovesi's PerceptualColourMaps package, or to Fabio Crameri's Scientific Colour Maps for more information. If you want to make more advanced ColorSchemes, use linear-segment dictionaries or indexed lists, and use functions to generate color values, see the make_colorscheme() function in the ColorSchemeTools.jl package.
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  • 4
    Automa.jl

    Automa.jl

    A julia code generator for regular expressions

    ...By compiling regex to Julia code in the form of Expr objects, Automa provides facilities to create efficient and robust regex-based lexers, tokenizers and parsers using Julia's metaprogramming capabilities. You can view Automa as a regex engine that can insert arbitrary Julia code into its input-matching process, which will be executed when certain parts of the regex match an input.
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  • Stop Storing Third-Party Tokens in Your Database Icon
    Stop Storing Third-Party Tokens in Your Database

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  • 5
    FiniteDifferences.jl

    FiniteDifferences.jl

    High accuracy derivatives, estimated via numerical finite differences

    FiniteDifferences.jl estimates derivatives with finite differences. See also the Python package FDM. FiniteDiff.jl and FiniteDifferences.jl are similar libraries: both calculate approximate derivatives numerically. You should definitely use one or the other, rather than the legacy Calculus.jl finite differencing, or reimplementing it yourself. At some point in the future, they might merge, or one might depend on the other.
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  • 6
    ExponentialUtilities.jl

    ExponentialUtilities.jl

    Fast and differentiable implementations of matrix exponentials

    ExponentialUtilities is a package of utility functions for matrix functions of exponential type, including functionality for the matrix exponential and phi-functions. These methods are more numerically stable, generic (thus support a wider range of number types), and faster than the matrix exponentiation tools in Julia's Base. The tools are used by the exponential integrators in OrdinaryDiffEq. The package has no external dependencies, so it can also be used independently.
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  • 7
    Braket.jl

    Braket.jl

    Experimental Julia implementation of the Amazon Braket SDK

    Braket.jl is not an officially supported AWS product. This package is a Julia implementation of the Amazon Braket SDK allowing customers to access Quantum Hardware and Simulators. This is experimental software, and support may be discontinued in the future. For a fully supported SDK, please use the Python SDK. We may change, remove, or deprecate parts of the API when making new releases. Please review the CHANGELOG for information about changes in each release.
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  • 8
    CausalityTools.jl

    CausalityTools.jl

    Algorithms for detecting associations, dynamical influences

    ...Association measures from conventional statistics, information theory, and dynamical systems theory, for example, distance correlation, mutual information, transfer entropy, convergent cross mapping and a lot more. A dedicated API for independence testing, which comes with automatic compatibility with every measure-estimator combination you can think of. For example, we offer the generic SurrogateTest, which is fully compatible with TimeseriesSurrogates.jl, and the LocalPermutationTest for conditional independence testing.
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  • 9
    Compat.jl

    Compat.jl

    Compatibility across Julia versions

    ...In particular, in cases where it is impossible to write code that works with both the latest Julia master branch and older Julia versions, or impossible to write code that doesn't generate a deprecation warning in some Julia version, the Compat package provides a macro that lets you use the latest syntax in a backward-compatible way. This is primarily intended for use by other Julia packages, where it is important to maintain cross-version compatibility.
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  • 10
    GLFW.jl

    GLFW.jl

    Julia interface to GLFW, a multi-platform library for creating windows

    Julia interface to GLFW 3, a multi-platform library for creating windows with OpenGL or OpenGL ES contexts and receiving many kinds of input. GLFW has native support for Windows, OS X and many Unix-like systems using the X Window System, such as Linux and FreeBSD.
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  • 11
    LaTeXStrings.jl

    LaTeXStrings.jl

    convenient input and display of LaTeX equation strings for Julia

    This is a small package to make it easier to type LaTeX equations in string literals in the Julia language, written by Steven G. Johnson. With ordinary strings in Julia, to enter a string literal with embedded LaTeX equations you need to manually escape all backslashes and dollar signs: for example, $\alpha^2$ is written \$\\alpha^2\$. Also, even though IJulia is capable of displaying formatted LaTeX equations (via MathJax), an ordinary string will not exploit this.
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  • 12
    The NLopt module for Julia

    The NLopt module for Julia

    Package to call the NLopt nonlinear-optimization library from Julia

    This module provides a Julia-language interface to the free/open-source NLopt library for nonlinear optimization. NLopt provides a common interface for many different optimization algorithms.
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  • 13
    ReverseDiff

    ReverseDiff

    Reverse Mode Automatic Differentiation for Julia

    ReverseDiff is a fast and compile-able tape-based reverse mode automatic differentiation (AD) that implements methods to take gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really). While performance can vary depending on the functions you evaluate, the algorithms implemented by ReverseDiff generally outperform non-AD algorithms in both speed and accuracy.
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  • 14
    vim‑sneak

    vim‑sneak

    The missing motion for Vim

    ...It provides intuitive highlights that disappear once the jump is completed. Sneak has <Plug> mappings for f and t 1-character-sneak. These mappings do not invoke label-mode, even if you have it enabled. Highlights matches in the direction of your search. Input is always literal (don't need to escape special characters).
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  • 15
    Vulkan.jl

    Vulkan.jl

    Using Vulkan from Julia

    ...Because Vulkan is originally a C specification, interfacing with it requires some knowledge before correctly being used from Julia. This package acts as an abstraction layer, so that you don't need to know how to properly call a C library, while still retaining full functionality. The wrapper is generated directly from the Vulkan Specification.
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  • 16
    PlutoSliderServer.jl

    PlutoSliderServer.jl

    Web server to run just the `@bind` parts of a Pluto.jl notebook

    Web server to run just the @bind parts of a Pluto.jl notebook. PlutoSliderServer can run a notebook and generate the export HTML file. This will give you the same file as the export button inside Pluto (top right), but automatically, without opening a browser. One use case is to automatically create a GitHub Pages site from a repository with notebooks. For this, take a look at our template repository that used GitHub Actions and PlutoSliderServer to generate a website on every commit. ...
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  • 17
    JLD2

    JLD2

    HDF5-compatible file format in pure Julia

    ...JLD2 provides read-only support for files created with the JLD package. The save and load functions, provided by FileIO, provide a mechanism to read and write data from a JLD2 file. To use these functions, you may either write using FileIO or using JLD2. FileIO will determine the correct package automatically.
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  • 18
    DynamicalSystems.jl

    DynamicalSystems.jl

    Award winning software library for nonlinear dynamics timeseries

    DynamicalSystems.jl is an award-winning Julia software library for nonlinear dynamics and nonlinear time series analysis. To install DynamicalSystems.jl, run import Pkg; Pkg.add("DynamicalSystems"). To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl file. DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high-quality scientific software. All implemented algorithms provide a high-level scientific description of their functionality in their documentation string as well as references to scientific papers. ...
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  • 19
    PairPlots.jl

    PairPlots.jl

    Beautiful and flexible vizualizations of high dimensional data

    Beautiful and flexible visualizations of high-dimensional data. This package produces pair plots, otherwise known as corner plots or scatter plot matrices: grids of 1D and 2D histograms that allow you to visualize high-dimensional data. Pair plots are an excellent way to visualize the results of MCMC simulations, but are also a useful way to visualize correlations in general data tables. The default styles of this package roughly reproduce the output of the Python library corner.py for a single series and chainconsumer.py for multiple series. ...
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  • 20
    PDFIO.jl

    PDFIO.jl

    PDF Reader Library for Native Julia.

    ...PDF files are in existence for over three decades. Implementations of the PDF writers are not always to the specification or they may even vary significantly from vendor to vendor. Every time, you get a new PDF file there is a possibility that it may not work to the best interpretation of the specification. A script-based language makes it easier for the consumers to quickly modify the code and enhance to their specific needs.
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  • 21
    DynamicHMC

    DynamicHMC

    Implementation of robust dynamic Hamiltonian Monte Carlo methods

    Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent of coding a (log) posterior density in Julia. This approach allows the use of standard tools like profiling and benchmarking to optimize its performance.
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  • 22
    MPI.jl

    MPI.jl

    MPI wrappers for Julia

    ...As the main entry point for users, MPI.jl provides a high-level interface which loosely follows the MPI C API and is described in details in the following sections. The syntax should look familiar if you know MPI already, but some arguments may not be needed (e.g. the type or the number of elements of arrays, which are inferred automatically), others may be placed slightly differently, and others may be optional keyword arguments (e.g. for the index of the root process, or the source and destination of point-to-point communication functions).
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  • 23
    ChainRules.jl

    ChainRules.jl

    Forward and reverse mode automatic differentiation primitives

    The ChainRules package provides a variety of common utilities that can be used by downstream automatic differentiation (AD) tools to define and execute forward-, reverse--, and mixed-mode primitives. The core logic of ChainRules is implemented in ChainRulesCore.jl. To add ChainRules support to your package, by defining new rules or frules, you only need to depend on the very light-weight package ChainRulesCore.jl. This repository contains ChainRules.jl, which is what people actually use directly. ChainRules reexports all the ChainRulesCore functionality and has all the rules for the Julia standard library.
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  • 24
    ECharts

    ECharts

    A powerful, interactive charting and visualization library for browser

    ECharts is a free and open source charting and visualization library that gives you an easy way to add interactive, intuitive, custom charts to your commercial products, projects, presentations and more. It offers a rich set of features that includes rendering ability for ten-million-level data, Wechart and Powerpoint support, multi-dimension data analysis, and more. It also has a number of extensions for various applications.
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  • 25
    BetaML.jl

    BetaML.jl

    Beta Machine Learning Toolkit

    ...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. Thanks to its JIT compiler, Julia is indeed in the sweet spot where we can easily write models in a high-level language and still have them running efficiently.
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