Showing 2004 open source projects for "pnpm-linux"

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  • 1
    TimeZones.jl

    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.
    Downloads: 7 This Week
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  • 2
    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...
    Downloads: 8 This Week
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  • 3
    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.
    Downloads: 7 This Week
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  • 4
    FromFile.jl

    FromFile.jl

    Julia enhancement proposal (Julep) for implicit per file module

    This package exports a macro @from, which can be used to import objects from files. The hope is that you will never have to write include again. FromFile is a Julia Language package. To install FromFile, please open Julia's interactive session (known as REPL) and press ] key in the REPL to use the package mode.
    Downloads: 7 This Week
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  • 5
    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...
    Downloads: 8 This Week
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  • 6
    CompatHelper.jl

    CompatHelper.jl

    Automatically update the [compat] entries for your Julia dependencies

    CompatHelper.jl is a Julia package which keeps your Project.toml [compat] entries up to date.
    Downloads: 7 This Week
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  • 7
    PowerSimulationsDynamics.jl

    PowerSimulationsDynamics.jl

    Julia package to run Dynamic Power System simulations

    PowerSimulationsDynamics.jl is a Julia package for power system modeling and simulation of Power Systems dynamics.
    Downloads: 7 This Week
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  • 8
    MLJBase.jl

    MLJBase.jl

    Core functionality for the MLJ machine learning framework

    Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ.
    Downloads: 8 This Week
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  • 9
    Reduce.jl

    Reduce.jl

    Symbolic parser for Julia language term rewriting using REDUCE algebra

    REDUCE is a portable general-purpose computer algebra system. 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...
    Downloads: 9 This Week
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  • 10
    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...
    Downloads: 8 This Week
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  • 11
    Java Tablesaw

    Java Tablesaw

    Java dataframe and visualization library

    Tablesaw is a dataframe and visualization library that supports loading, cleaning, transforming, filtering, and summarizing data. If you work with data in Java, it may save you time and effort. Tablesaw also supports descriptive statistics and can be used to prepare data for working with machine learning libraries like Smile, Tribuo, H20.ai, DL4J. Import data from RDBMS, Excel, CSV, TSV, JSON, HTML, or Fixed Width text files, whether they are local or remote (http, S3, etc.) Tablesaw...
    Downloads: 9 This Week
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  • 12
    CategoricalArrays.jl

    CategoricalArrays.jl

    Arrays for working with categorical data

    This package provides tools for working with categorical variables, both with unordered (nominal variables) and ordered categories (ordinal variables), optionally with missing values.
    Downloads: 6 This Week
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  • 13
    Tables.jl

    Tables.jl

    An interface for tables in Julia

    The Tables.jl package provides simple, yet powerful interface functions for working with all kinds of tabular data.
    Downloads: 6 This Week
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  • 14
    Bayesian Optimization

    Bayesian Optimization

    Python implementation of global optimization with gaussian processes

    This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic...
    Downloads: 10 This Week
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  • 15
    visual-explainer

    visual-explainer

    Agent skill + prompt templates that generate rich HTML pages

    visual-explainer is an AI-oriented agent skill that converts complex terminal or analytical output into polished, human-readable HTML reports designed for quick comprehension and sharing. The project includes prompt templates and automation logic that enable coding agents to generate visual summaries such as diff reviews, architecture overviews, plan audits, and structured data tables. Its primary goal is to bridge the readability gap between raw machine output and stakeholder-friendly...
    Downloads: 8 This Week
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  • 16
    CondaPkg.jl

    CondaPkg.jl

    Add Conda dependencies to your Julia project

    Add Conda dependencies to your Julia project. This package is a lot like Pkg from the Julia standard library, except that it is for managing Conda packages. Conda dependencies are defined in CondaPkg.toml, which is analogous to Project.toml. CondaPkg will install these dependencies into a Conda environment specific to the current Julia project. Hence dependencies are isolated from other projects or environments. Functions like add, rm, status exist to edit the dependencies programmatically....
    Downloads: 8 This Week
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  • 17
    DiffOpt.jl

    DiffOpt.jl

    Differentiating convex optimization programs w.r.t. program parameters

    DiffOpt.jl is a package for differentiating convex optimization programs (JuMP.jl or MathOptInterface.jl models) with respect to program parameters. Note that this package does not contain any solver. This package has two major backends, available via the reverse_differentiate! and forward_differentiate! methods, to differentiate models (quadratic or conic) with optimal solutions. Differentiable optimization is a promising field of convex optimization and has many potential applications in...
    Downloads: 8 This Week
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  • 18
    BlockArrays.jl

    BlockArrays.jl

    BlockArrays for Julia

    A block array is a partition of an array into blocks or subarrays, see Wikipedia for a more extensive description. This package has two purposes. Firstly, it defines an interface for an AbstractBlockArray block arrays that can be shared among types representing different types of block arrays. The advantage to this is that it provides a consistent API for block arrays. Secondly, it also implements two different types of block arrays that follow the AbstractBlockArray interface. The type...
    Downloads: 8 This Week
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  • 19
    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.
    Downloads: 7 This Week
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  • 20
    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.
    Downloads: 7 This Week
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  • 21
    Bayesian Statistics

    Bayesian Statistics

    This repository holds slides and code for a full Bayesian statistics

    This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used...
    Downloads: 8 This Week
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  • 22
    luma.gl

    luma.gl

    High-performance Toolkit for WebGL-based data visualization

    luma.gl is a GPU toolkit for the Web-focused primarily on data visualization use cases. luma.gl aims to provide support for GPU programmers that need to work directly with shaders and want a low abstraction API that remains conceptually close to the WebGPU and WebGL APIs. Unlike other common WebGL APIs, the developer can choose to use the parts of luma.gl that support their use case and leave the others behind. While generic enough to be used for general 3D rendering, luma.gl's mandate is...
    Downloads: 8 This Week
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  • 23
    visx

    visx

    Visualization components

    visx a collection of expressive, low-level visualization primitives for React. At Airbnb, we made it a goal to unify our visualization stack across the company and in the process, we created a new project that brings together the power of D3 with the joy of React. visx is split into multiple packages. Start small and use only what you need. Bring your own state management, animation library, or CSS-in-JS solution. Odds are good your React app already has an opinion on how animation, theming,...
    Downloads: 9 This Week
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  • 24
    MIRT.jl

    MIRT.jl

    MIRT: Michigan Image Reconstruction Toolbox (Julia version)

    MIRT.jl is a collection of Julia functions for performing image reconstruction and solving related inverse problems. It is very much still under construction, although there are already enough tools to solve useful problems like compressed sensing MRI reconstruction. Trying the demos is a good way to get started. The documentation is even more still under construction.
    Downloads: 7 This Week
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  • 25
    Tulip.jl

    Tulip.jl

    Interior-point solver in pure Julia

    Tulip is an open-source interior-point solver for linear optimization, written in pure Julia. It implements the homogeneous primal-dual interior-point algorithm with multiple centrality corrections and therefore handles unbounded and infeasible problems. Tulip’s main feature is that its algorithmic framework is disentangled from linear algebra implementations. This allows to seamless integration of specialized routines for structured problems.
    Downloads: 7 This Week
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