Showing 2673 open source projects for "antix-linux"

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  • 1
    Arrow Julia

    Arrow Julia

    Official Julia implementation of Apache Arrow

    This is a pure Julia implementation of the Apache Arrow data standard. This package provides Julia AbstractVector objects for referencing data that conforms to the Arrow standard. This allows users to seamlessly interface Arrow formatted data with a great deal of existing Julia code.
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  • 2
    MAT.jl

    MAT.jl

    Julia module for reading MATLAB files

    Julia module for reading MATLAB files. Read and write MATLAB files in Julia. This library can read MATLAB .mat files, both in the older v4/v5/v6/v7 format, as well as the newer v7.3 format.
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  • 3
    Krylov.jl

    Krylov.jl

    A Julia Basket of Hand-Picked Krylov Methods

    If you use Krylov.jl in your work, please cite it using the metadata given in CITATION.cff.
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  • 4
    FastGaussQuadrature.jl

    FastGaussQuadrature.jl

    Julia package for Gaussian quadrature

    A Julia package to compute n-point Gauss quadrature nodes and weights to 16-digit accuracy and in O(n) time. So far the package includes gausschebyshev(), gausslegendre(), gaussjacobi(), gaussradau(), gausslobatto(), gausslaguerre(), and gausshermite(). This package is heavily influenced by Chebfun.
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  • 5
    Oxygen.jl

    Oxygen.jl

    A breath of fresh air for programming web apps in Julia

    A breath of fresh air for programming web apps in Julia. Oxygen is a micro-framework built on top of the HTTP.jl library. Breathe easy knowing you can quickly spin up a web server with abstractions you're already familiar with.
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  • 6
    DFTK.jl

    DFTK.jl

    Density-functional toolkit

    The density-functional toolkit, DFTK for short, is a collection of Julia routines for experimentation with plane-wave density-functional theory (DFT). The unique feature of this code is its emphasis on simplicity and flexibility with the goal of facilitating algorithmic and numerical developments as well as interdisciplinary collaboration in solid-state research.
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  • 7
    Mixed-effects models in Julia

    Mixed-effects models in Julia

    A Julia package for fitting (statistical) mixed-effects models

    This package defines linear mixed models (LinearMixedModel) and generalized linear mixed models (GeneralizedLinearMixedModel). Users can use the abstraction for statistical model API to build, fit (fit/fit!), and query the fitted models. A mixed-effects model is a statistical model for a response variable as a function of one or more covariates. For a categorical covariate the coefficients associated with the levels of the covariate are sometimes called effects, as in "the effect of using...
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  • 8
    Parameters.jl

    Parameters.jl

    Types w/ default field values, keyword constructors, (un-)pack macros

    This is a package I use to handle numerical-model parameters, thus the name. However, it should be useful otherwise too.
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  • 9
    EllipsisNotation.jl

    EllipsisNotation.jl

    Julia-based implementation of ellipsis array indexing notation

    Julia-based implementation of ellipsis array indexing notation. This implements the notation .. for indexing arrays. It's similar to Python, in that it means "all the columns before (or after)". Note: .. slurps dimensions greedily, meaning that the first occurrence of .. in an index expression creates as many slices as possible. Other instances of .. afterward are treated simply as slices. Usually, you should only use one instance of .. in an indexing expression to avoid possible confusion.
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  • 10
    GeoInterface.jl

    GeoInterface.jl

    A Julia Protocol for Geospatial Data

    This Package describe a set of traits based on the Simple Features standard (SF) for geospatial vector data, including the SQL/MM extension with support for circular geometry. Using these traits, it should be easy to parse, serialize and use different geometries in the Julia ecosystem, without knowing the specifics of each individual package. In that regard it is similar to Tables.jl, but for geometries instead of tables.
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  • 11
    Bumper.jl

    Bumper.jl

    Bring Your Own Stack

    Bumper.jl is a package that aims to make working with bump allocators (also known as arena allocators) easier and safer. You can dynamically allocate memory to these bump allocators, and reset them at the end of a code block, just like Julia's stack. Allocating to a bump allocator with Bumper.jl can be just as efficient as stack allocation. Bumper.jl is still a young package, and may have bugs. Let me know if you find any.
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  • 12
    ExplainableAI.jl

    ExplainableAI.jl

    Explainable AI in Julia

    This package implements interpretability methods for black box models, with a focus on local explanations and attribution maps in input space. It is similar to Captum and Zennit for PyTorch and iNNvestigate for Keras models. Most of the implemented methods only require the model to be differentiable with Zygote. Layerwise Relevance Propagation (LRP) is implemented for use with Flux.jl models.
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  • 13
    InferOpt.jl

    InferOpt.jl

    Combinatorial optimization layers for machine learning pipelines

    InferOpt.jl is a toolbox for using combinatorial optimization algorithms within machine learning pipelines. It allows you to create differentiable layers from optimization oracles that do not have meaningful derivatives. Typical examples include mixed integer linear programs or graph algorithms.
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  • 14
    MultilayerGraphs.jl

    MultilayerGraphs.jl

    Julia package for the creation and analysis of multilayer graphs

    MultilayerGraphs.jl is a Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs. A multilayer graph is a graph consisting of multiple standard subgraphs called layers which can be interconnected through bipartite graphs called interlayers composed of the vertex sets of two different layers and the edges between them. The vertices in each layer represent a single set of nodes, although not all nodes have to be represented in...
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  • 15
    NetCDF.jl

    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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  • 16
    Polyhedra

    Polyhedra

    Polyhedral Computation Interface

    Polyhedra provides an unified interface for Polyhedral Computation Libraries such as CDDLib.jl. This manipulation notably includes the transformation from (resp. to) an inequality representation of a polyhedron to (resp. from) its generator representation (convex hull of points + conic hull of rays) and projection/elimination of a variable with e.g. Fourier-Motzkin.
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  • 17
    Rocket.jl

    Rocket.jl

    Functional reactive programming extensions library for Julia

    Rocket.jl is a Julia package for reactive programming using Observables, to make it easier to work with asynchronous data. Rocket.jl has been designed with a focus on performance and modularity.
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  • 18
    EvoTrees.jl

    EvoTrees.jl

    Boosted trees in Julia

    A Julia implementation of boosted trees with CPU and GPU support. Efficient histogram-based algorithms with support for multiple loss functions, including various regressions, multi-classification and Gaussian max likelihood.
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  • 19
    BAT.jl

    BAT.jl

    A Bayesian Analysis Toolkit in Julia

    Welcome to BAT, a Bayesian analysis toolkit in Julia. BAT.jl offers a variety of posterior sampling, mode estimation and integration algorithms, supplemented by plotting recipes and I/O functionality. BAT.jl originated as a rewrite/redesign of BAT, the Bayesian Analysis Toolkit in C++. BAT.jl now offer a different set of functionality and a wider variety of algorithms than its C++ predecessor.
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  • 20
    Clang.jl

    Clang.jl

    C binding generator and Julia interface to libclang

    This package provides a Julia language wrapper for libclang: the stable, C-exported interface to the LLVM Clang compiler. The libclang API documentation provides background on the functionality available through libclang, and thus through the Julia wrapper. The repository also hosts related tools built on top of libclang functionality.
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  • 21
    CImGui

    CImGui

    Julia wrapper for cimgui

    This package provides a Julia language wrapper for cimgui: a thin c-api wrapper programmatically generated for the excellent C++ immediate mode gui Dear ImGui. Dear ImGui is mainly for creating content creation tools and visualization / debug tools. You could browse Gallery to get an idea of its use cases.
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  • 22
    Compose.jl

    Compose.jl

    Declarative vector graphics

    Compose is a vector graphics library for Julia. It forms the basis for the statistical graphics system Gadfly. Compose is a declarative vector graphics system written in Julia. It's designed to simplify the creation of complex graphics and serves as the basis of the Gadfly data visualization package.
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  • 23
    OpenCL.jl

    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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  • 24
    FriendsDon'tLetFriends

    FriendsDon'tLetFriends

    Friends don't let friends make certain types of data visualization

    Friends don't let friends make certain types of data visualization - What are they and why are they bad.
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  • 25
    pydna

    pydna

    Clone with Python! Data structures for double stranded DNA

    Clone with Python! Data structures for double stranded DNA & simulation of homologous recombination, Gibson assembly, cut & paste cloning. Planning genetic constructs with many parts and assembly steps, such as recombinant metabolic pathways, are often difficult to properly document as is evident from the poor state of documentation in the scientific literature. The pydna python package provide a human-readable formal description of cloning and genetic assembly strategies in Python which...
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