Showing 343 open source projects for "documentation"

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  • 1
    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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  • 2
    AppleAccelerate.jl

    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...
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  • 3
    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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  • 4
    GDAL.jl

    GDAL.jl

    Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library

    Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly.
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  • 5
    JUDI.jl

    JUDI.jl

    Julia Devito inversion

    JUDI is a framework for large-scale seismic modeling and inversion and is designed to enable rapid translations of algorithms to fast and efficient code that scales to industry-size 3D problems. 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...
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  • 6
    ReTest.jl

    ReTest.jl

    Testing framework for Julia

    ReTest is a testing framework for Julia allowing defining tests in source files, whose execution is deferred and triggered on demand. This is useful when one likes to have definitions of methods and corresponding tests close to each other. This is also useful for code that is not (yet) organized as a package, and where one doesn't want to maintain a separate set of files for tests. Filtering run testsets with a Regex, which is matched against the descriptions of testsets. This is useful for...
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  • 7
    ConformalPrediction.jl

    ConformalPrediction.jl

    Predictive Uncertainty Quantification through Conformal Prediction

    ConformalPrediction.jl is a package for Predictive Uncertainty Quantification (UQ) through Conformal Prediction (CP) in Julia. It is designed to work with supervised models trained in MLJ (Blaom et al. 2020). Conformal Prediction is easy-to-understand, easy-to-use and model-agnostic and it works under minimal distributional assumptions. Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates through repeated sampling or the use...
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  • 8
    CausalityTools.jl

    CausalityTools.jl

    Algorithms for detecting associations, dynamical influences

    CausalityTools.jl is a package for quantifying associations and dynamical coupling between datasets, independence testing, and causal inference. 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...
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  • 9
    Compat.jl

    Compat.jl

    Compatibility across Julia versions

    The Compat package is designed to ease interoperability between older and newer versions of the Julia language. 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...
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  • 10
    SimpleTraits.jl

    SimpleTraits.jl

    Simple Traits for Julia

    This package provides a macro-based implementation of traits, using Tim Holy's trait trick. The main idea behind traits is to group types outside the type-hierarchy and to make dispatch work with that grouping. The difference to Union-types is that types can be added to a trait after the creation of the trait, whereas Union types are fixed after creation. The cool thing about Tim's trick is that there is no performance impact compared to using ordinary dispatch. For a bit of background and a...
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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
    ComponentArrays.jl

    ComponentArrays.jl

    Arrays with arbitrarily nested named components

    The main export of this package is the ComponentArray type. "Components" of ComponentArrays are really just array blocks that can be accessed through a named index. This will create a new ComponentArray whose data is a view into the original, allowing for standalone models to be composed together by simple function composition. In essence, ComponentArrays allow you to do the things you would usually need a modeling language for, but without actually needing a modeling language. The main...
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  • 13
    Literate

    Literate

    Simple package for literate programming in Julia

    Literate is a package for Literate Programming. The main purpose is to facilitate writing Julia examples/tutorials that can be included in your package documentation. Literate can generate markdown pages (for e.g. Documenter.jl), and Jupyter notebooks, from the same source file. There is also an option to "clean" the source from all metadata, and produce a pure Julia script. Using a single source file for multiple purposes reduces maintenance, and makes sure your different output formats are synced with each other.
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  • 14
    Data Formulator

    Data Formulator

    Create rich visualizations with AI

    To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals. To achieve this, analysts need not only proficiency in data transformation and visualization tools but also efforts to manage the branching history consisting of many different versions of data and charts. Recent LLM-powered AI systems have greatly improved visualization authoring experiences, for example by mitigating manual data...
    Downloads: 1 This Week
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  • 15
    WordCloud.jl

    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. This visualization solution guarantees...
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  • 16
    ParallelStencil.jl

    ParallelStencil.jl

    Package for writing high-level code for parallel stencil computations

    ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C / HIP can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl or AMDGPU.jl GPU Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding GPU Array...
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  • 17
    leafmap

    leafmap

    A Python package for interactive mapping and geospatial analysis

    A Python package for geospatial analysis and interactive mapping in a Jupyter environment. Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed specifically to work with Google Earth Engine (GEE). However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It...
    Downloads: 3 This Week
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  • 18
    The ARCHModels Package for Julia

    The ARCHModels Package for Julia

    A Julia package for estimating ARMA-GARCH models

    ARCH (Autoregressive Conditional Heteroskedasticity) models are a class of models designed to capture a feature of financial returns data known as volatility clustering, i.e., the fact that large (in absolute value) returns tend to cluster together, such as during periods of financial turmoil, which then alternate with relatively calmer periods. This package provides efficient routines for simulating, estimating, and testing a variety of GARCH models. ARCH (Autoregressive Conditional...
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  • 19
    Tokenize.jl

    Tokenize.jl

    Tokenization for Julia source code

    Tokenize is a Julia package that serves a similar purpose and API as the tokenize module in Python but for Julia. This is to take a string or buffer containing Julia code, perform lexical analysis and return a stream of tokens.
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  • 20
    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. Many...
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  • 21
    Fermi.jl

    Fermi.jl

    Fermi quantum chemistry program

    Fermi.jl is a quantum chemistry framework written in pure Julia. This code is developed at the Center for Computational Quantum Chemistry at the University of Georgia under the supervision of Dr. Justin M. Turney and Prof. Henry F. Schaefer. This work is supported by the U.S. National Science Foundation under grant number CHE-1661604. Fermi focuses on post Hartree--Fock methods. Currently, only restricted references are supported. This is intended as a research code with an ever growing...
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  • 22
    Rotations.jl

    Rotations.jl

    Julia implementations for different rotation parameterizations

    3D rotations made easy in Julia. This package implements various 3D rotation parameterizations and defines conversions between them. At their heart, each rotation parameterization is a 3×3 unitary (orthogonal) matrix (based on the StaticArrays.jl package), and acts to rotate a 3-vector about the origin through matrix-vector multiplication. While the RotMatrix type is a dense representation of a 3×3 matrix, we also have sparse (or computed, rather) representations such as quaternions,...
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  • 23
    QuadGK.jl

    QuadGK.jl

    adaptive 1d numerical Gauss–Kronrod integration in Julia

    This package provides support for one-dimensional numerical integration in Julia using adaptive Gauss-Kronrod quadrature. The code was originally part of Base Julia. It supports the integration of arbitrary numeric types, including arbitrary-precision (BigFloat), and even the integration of arbitrary normed vector spaces. The package provides three basic functions: quadgk, gauss, and kronrod. quadgk performs the integration, gauss computes Gaussian quadrature points and weights for...
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  • 24
    Books.jl

    Books.jl

    Create books with Julia

    In a nutshell, this package is meant to generate books (or reports or dashboards) with embedded Julia output. Via Pandoc, the package can live serve a website and build various outputs including a website and PDF. For many standard output types, such as DataFrames and plots, the package can run your code and will automatically handle proper embedding in the output documents, and also try to guess suitable captions and labels. Also, it is possible to work via the live server, which shows...
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  • 25
    gramm

    gramm

    Gramm is a complete data visualization toolbox for Matlab

    Gramm is a MATLAB toolbox that enables the rapid creation of complex, publication-quality figures. Its design philosophy focuses on a declarative approach, where users specify the desired end result, as opposed to the traditional imperative method involving for loops, if/else statements, etc. The MATLAB implementation of gramm is inspired by the "grammar of graphics" principles (Wilkinson 1999) and the ggplot2 library for R by Hadley Wickham. As a reference to this inspiration, gramm stands...
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