Showing 2243 open source projects for "arch-linux-gui"

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  • 1
    CSV

    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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    ClickVisual

    ClickVisual

    Log analytic and data visualize platform built on clickhouse

    ClickVisual is a lightweight browser-based logs analytics and logs search platform for ClickHouse.
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    LIBSVM.jl

    LIBSVM.jl

    LIBSVM bindings for Julia

    LIBSVM bindings for Julia. This is a Julia interface for LIBSVM and for the linear SVM model provided by LIBLINEAR. Supports all LIBSVM models: classification C-SVC, nu-SVC, regression: epsilon-SVR, nu-SVR and distribution estimation: one-class SVM. Model objects are represented by Julia-type SVM which gives you easy access to model features and can be saved e.g. as JLD file.
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  • 4
    ImplicitDifferentiation.jl

    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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    LatticeQCD.jl

    LatticeQCD.jl

    A native Julia code for lattice QCD with dynamical fermions in 4D

    This code enables you to perform lattice QCD calculations! A native Julia code for Lattice QCD.
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  • 6
    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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  • 7
    ggforce

    ggforce

    Accelerating ggplot2

    ggforce is an extension package for ggplot2 that introduces specialized statistical transforms, geoms, and layout utilities to enhance and complement the built-in ggplot2 offerings. It enables more advanced visualization techniques such as faceting enhancements, hulls, annotation marks, and novel layouts for network data and marked regions.
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  • 8
    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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  • 9
    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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  • 10
    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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  • 11
    Coluna.jl

    Coluna.jl

    Branch-and-Price-and-Cut in Julia

    Coluna is a branch-and-price-and-cut framework written in Julia. You write an original MIP that models your problem using the JuMP modeling language and our specific extension BlockDecomposition offers a syntax to specify the problem decomposition. Then, Coluna reformulates the original MIP and optimizes the reformulation using the algorithms you choose. Coluna aims to be very modular and tweakable so that you can define the behavior of your customized branch-and-price-and-cut algorithm.
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  • 12
    Metalhead.jl

    Metalhead.jl

    Computer vision models for Flux

    Metalhead.jl provides standard machine learning vision models for use with Flux.jl. The architectures in this package make use of pure Flux layers, and they represent the best practices for creating modules like residual blocks, inception blocks, etc. in Flux. Metalhead also provides some building blocks for more complex models in the Layers module.
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  • 13
    Graphs.jl

    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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  • 14
    ggstatsplot

    ggstatsplot

    Enhancing {ggplot2} plots with statistical analysis

    {ggstatsplot} is an extension of {ggplot2} package for creating graphics with details from statistical tests included in the information-rich plots themselves. In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. Bayesian hypothesis-testing. The central idea of {ggstatsplot} is simple: combine these...
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  • 15
    classic.tplx

    classic.tplx

    A more accurate representation of jupyter notebooks

    A more accurate representation of Jupyter notebooks when converting to pdfs. This template was designed to make converted Jupyter notebooks look (almost) identical to the actual notebook. If something doesn't exist in the original notebook then it doesn't belong in the conversion. As of nbconvert 5.5.0, the majority of these improvements have been merged into nbconvert's default template. Version 3.x of this package will continue to support nbconvert 5.5.0 and lower, whereas in the future...
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  • 16
    ImageInTerminal.jl

    ImageInTerminal.jl

    Julia package for displaying images in the terminal using ANSI colors

    ImageInTerminal is a drop-in package that once imported changes how a single Colorant and whole Colorant arrays (regular images) are displayed in the interactive REPL. The displayed images will be downscaled to fit into the size of your active terminal session. By default, this package will detect if your running terminal supports 24-bit colors (true colors). If it does, the image will be displayed in 24-bit colors, otherwise, it falls back to 8-bit (256 colors).
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  • 17
    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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  • 18
    Automa.jl

    Automa.jl

    A julia code generator for regular expressions

    Automa is a regex-to-Julia compiler. 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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  • 19
    CBinding.jl

    CBinding.jl

    Automatic C interfacing for Julia

    Use CBinding.jl to automatically create C library bindings with Julia at runtime. In order to support the fully automatic conversion and avoid name collisions, the names of C types or functions are mangled a bit to work in Julia. Therefore everything generated by CBinding.jl can be accessed with the c"..." string macro to indicate that it lives in C-land. As an example, the function func above is available in Julia as c"func". It is possible to store the generated bindings to more...
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  • 20
    Unitful.jl

    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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  • 21
    vim‑sneak

    vim‑sneak

    The missing motion for Vim

    vim‑sneak is a minimalist yet powerful navigation plugin for Vim, designed to jump to any location specified by two characters. It maintains compatibility with Vim's operators, macros, visual mode, repeat (.), and supports multibyte text. 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....
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  • 22
    JuliaSyntax

    JuliaSyntax

    A Julia frontend, written in Julia

    A Julia compiler frontend, written in Julia. Read the documentation for more information. JuliaSyntax.jl is used as the new default Julia parser in Julia 1.10. It's highly compatible with Julia's older femtoliter-based parser - It parses all of Base, the standard libraries and the General registry. Some minor differences remain where we've decided to fix bugs or strange behaviors in the reference parser. The AST and tree data structures are usable but their APIs will evolve as we try out...
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  • 23
    POMDPs

    POMDPs

    Interface for defining, solving, simulating Markov decision processes

    A Julia interface for defining, solving and simulating partially observable Markov decision processes and their fully observable counterparts. The POMDPs.jl package contains only the interface used for expressing and solving Markov decision processes (MDPs) and partially observable Markov decision processes (POMDPs). The POMDPTools package acts as a "standard library" for the POMDPs.jl interface, providing implementations of commonly-used components such as policies, belief updaters,...
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  • 24
    forecast

    forecast

    Forecasting Functions for Time Series and Linear Models

    The forecast package is a comprehensive R package for time series analysis and forecasting. It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual...
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  • 25
    ipychart

    ipychart

    The power of Chart.js with Python

    Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive, and modular and are displayed directly in the output of the cells of your jupyter notebook environment. Charts are fully interactive, you can hover it to display tooltips and select the information you want to see directly from the output cell of your notebook. All the types of charts present in Chart.js are exposed in ipychart. Even complex features such...
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