Showing 83 open source projects for "one-wire"

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  • Build Securely on Azure with Proven Frameworks Icon
    Build Securely on Azure with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

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  • 1
    InteractiveViz.jl

    InteractiveViz.jl

    Interactive visualization tools for Julia

    Julia already has a rich set of plotting tools in the form of the Plots and Makie ecosystems, and various backends for these. So why another plotting package? InteractiveViz is not a replacement for Plots or Makie, but rather a graphics pipeline system developed on top of Makie. It has a few objectives. To provide a simple API to visualize large or possibly infinite datasets (tens of millions of data points) easily. To enable interactivity, and be responsive even with large amounts of data....
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  • 2
    LossFunctions.jl

    LossFunctions.jl

    Julia package of loss functions for machine learning

    This package represents a community effort to centralize the definition and implementation of loss functions in Julia. As such, it is a part of the JuliaML ecosystem. The sole purpose of this package is to provide an efficient and extensible implementation of various loss functions used throughout Machine Learning (ML). It is thus intended to serve as a special purpose back-end for other ML libraries that require losses to accomplish their tasks. To that end we provide a considerable amount...
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  • 3
    SciML Style Guide for Julia

    SciML Style Guide for Julia

    A style guide for stylish Julia developers

    The SciML Style Guide is a style guide for the Julia programming language. It is used by the SciML Open Source Scientific Machine Learning Organization. As such, it is open to discussion with the community. If the standard for code contributions is that every PR needs to support every possible input type that anyone can think of, the barrier would be too high for newcomers. Instead, the principle is to be as correct as possible to begin with, and grow the generic support over time. All...
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  • 4
    GMT.jl

    GMT.jl

    Generic Mapping Tools Library Wrapper for Julia

    ... to the command line version and yet to provide all the facilities of the Julia language. In this sense, all GMT options are put in a single text string that is passed, plus the data itself when it applies, to the gmt() command. However, we also acknowledge that not every one is comfortable with the GMT syntax. This syntax is needed to accommodate the immense pool of options that let you control all details of a figure but that also makes it harder to read/master.
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  • Free and Open Source HR Software Icon
    Free and Open Source HR Software

    OrangeHRM provides a world-class HRIS experience and offers everything you and your team need to be that HR hero you know that you are.

    Give your HR team the tools they need to streamline administrative tasks, support employees, and make informed decisions with the OrangeHRM free and open source HR software.
  • 5
    Roots.jl

    Roots.jl

    Root finding functions for Julia

    This package contains simple routines for finding roots, or zeros, of scalar functions of a single real variable using floating-point math. The find_zero function provides the primary interface. The basic call is find_zero(f, x0, [M], [p]; kws...) where, typically, f is a function, x0 a starting point or bracketing interval, M is used to adjust the default algorithms used, and p can be used to pass in parameters. Bisection-like algorithms. For functions where a bracketing interval is known (one...
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  • 6
    HDF5.jl

    HDF5.jl

    Save and load data in the HDF5 file format from Julia

    ..., strings, and arrays), HDF5 provides sufficient metadata to know how each item is to be interpreted. For example, HDF5 encodes that a given block of bytes is to be interpreted as an array of Int64, and represents them in a way that is compatible across different computing architectures. However, to preserve Julia objects, one generally needs additional type information to be supplied, which is easy to provide using attributes.
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  • 7
    CxxWrap

    CxxWrap

    Package to make C++ libraries available in Julia

    This package aims to provide a Boost. Python-like wrapping for C++ types and functions to Julia. The idea is to write the code for the Julia wrapper in C++, and then use a one-liner on the Julia side to make the wrapped C++ library available there. The mechanism behind this package is that functions and types are registered in C++ code that is compiled into a dynamic library. This dynamic library is then loaded into Julia, where the Julia part of this package uses the data provided through a C...
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  • 8
    OrdinaryDiffEq.jl

    OrdinaryDiffEq.jl

    High performance ordinary differential equation (ODE)

    ... for high-precision and HPC applications. At the same time, it wraps the classic C/Fortran methods, making it easy to switch over to them whenever necessary. Solving differential equations with different methods from different languages and packages can be done by changing one line of code, allowing for easy benchmarking to ensure you are using the fastest method possible.
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  • 9
    Makie

    Makie

    Interactive data visualizations and plotting in Julia

    Makie is an interactive data visualization and plotting ecosystem for the Julia programming language, available on Windows, Linux, and Mac. The backend packages GLMakie, WGLMakie, CairoMakie and RPRMakie add different functionalities: You can use Makie to interactively explore your data and create simple GUIs in native Windows or web browsers, export high-quality vector graphics or even raytrace with physically accurate lighting. Choose one or more backend packages: GLMakie (interactive OpenGL...
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  • High-performance Open Source API Gateway Icon
    High-performance Open Source API Gateway

    KrakenD is a stateless, distributed, high-performance API Gateway that helps you effortlessly adopt microservices

    KrakenD is a high-performance API Gateway optimized for resource efficiency, capable of managing 70,000 requests per second on a single instance. The stateless architecture allows for straightforward, linear scalability, eliminating the need for complex coordination or database maintenance.
  • 10
    Kinetic.jl

    Kinetic.jl

    Universal modeling and simulation of fluid mechanics upon ML

    Kinetic is a computational fluid dynamics toolbox written in Julia. It aims to furnish efficient modeling and simulation methodologies for fluid dynamics, augmented by the power of machine learning. Based on differentiable programming, mechanical and neural network models are fused and solved in a unified framework. Simultaneous 1-3 dimensional numerical simulations can be performed on CPUs and GPUs.
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  • 11
    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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  • 12
    DiffEqOperators.jl

    DiffEqOperators.jl

    Linear operators for discretizations of differential equations

    DiffEqOperators.jl is a package for finite difference discretization of partial differential equations. It allows building lazy operators for high order non-uniform finite differences in an arbitrary number of dimensions, including vector calculus operators. For the operators, both centered and upwind operators are provided, for domains of any dimension, arbitrarily spaced grids, and for any order of accuracy. The cases of 1, 2, and 3 dimensions with an evenly spaced grid are optimized...
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  • 13
    AugmentedGaussianProcesses.jl

    AugmentedGaussianProcesses.jl

    Gaussian Process package based on data augmentation, and sparsity

    AugmentedGaussianProcesses.jl is a Julia package in development for Data Augmented Sparse Gaussian Processes. It contains a collection of models for different gaussian and non-gaussian likelihoods, which are transformed via data augmentation into conditionally conjugate likelihood allowing for extremely fast inference via block coordinate updates. There are also more options to use more traditional variational inference via quadrature or Monte Carlo integration.
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  • 14
    Augmentor.jl

    Augmentor.jl

    A fast image augmentation library in Julia for machine learning

    A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a...
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  • 15
    Geodesy.jl

    Geodesy.jl

    Work with points defined in various coordinate systems

    Geodesy is a Julia package for working with points in various world and local coordinate systems. The primary feature of Geodesy is to define and perform coordinate transformations in a convenient and safe framework, leveraging the CoordinateTransformations package. Transformations are accurate and efficient and implemented in native Julia code (with many functions being ported from Charles Karney's GeographicLib C++ library), and some common geodetic datums are provided for convenience.
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  • 16

    riscordbot

    Discordbot which will keep track of Risk: Global Domination Matches.

    This discordbot will be available to all servers who are hosting Risk tournaments, so there is an easy and centralised way to track statistics for players, scores, tournament settings, and much more data that will be nicely output into a userfriendly environment (being plaintext data structured to be viewed in discord-chat, twitch-chat or via a nice designed website.)
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  • 17
    Semagrams.jl

    Semagrams.jl

    A graphical editor for graph-like structures

    A graphical editor for graph-like structures based on Catlab. Legacy version built with typescript is in the legacy branch, and will not receive updates; new version with scala is now in the main branch. The core of Semagrams is just a library; in order to make it do things, one needs to create an "app" that uses it. Currently, the only app that is being developed is a Petri net editor, though this will soon change. In order to run the Petri net editor standalone, install Mill and npm...
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  • 18
    ReinforcementLearningAnIntroduction.jl

    ReinforcementLearningAnIntroduction.jl

    Julia code for the book Reinforcement Learning An Introduction

    This project provides the Julia code to generate figures in the book Reinforcement Learning: An Introduction(2nd). One of our main goals is to help users understand the basic concepts of reinforcement learning from an engineer's perspective. Once you have grasped how different components are organized, you're ready to explore a wide variety of modern deep reinforcement learning algorithms in ReinforcementLearningZoo.jl.
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  • 19
    Reexport.jl

    Reexport.jl

    Julia macro for re-exporting one module from another

    Maybe you have a module X that depends on module Y and you want using X to pull in all of the symbols from Y. Maybe you have an outer module A with an inner module B, and you want to export all of the symbols in B from A. It would be nice to have this functionality built into Julia, but we have yet to reach an agreement on what it should look like. This short macro is a stopgap we have a better solution.
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  • 20
    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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  • 21
    Temporal.jl

    Temporal.jl

    Time series implementation for the Julia language

    This package provides a flexible & efficient time series class, TS, for the Julia programming language. While still early in development, the overarching goal is for the class to be able to slice & dice data with the rapid prototyping speed of R's xts and Python's pandas packages, while retaining the performance one expects from Julia. See the documentation for a more in-depth look at the package and some of the pain points it may solve when doing technical research with time series data.
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  • 22
    StatsKit.jl

    StatsKit.jl

    Convenience meta-package to load essential packages for statistics

    This is a convenience meta-package that allows loading essential packages for statistics in one command.
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  • 23
    MLDataUtils.jl

    MLDataUtils.jl

    Utility package for generating, loading, and processing ML datasets

    This package is designed to be the end-user facing front-end to all the data related functionality that is spread out across the JuliaML ecosystem. Most of the following sub-categories are covered by a single back-end package that is specialized on that specific problem. Consequently, if one of the following topics is of special interest to you, make sure to check out the corresponding documentation of that package.
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  • 24
    Bridge.jl

    Bridge.jl

    A statistical toolbox for diffusion processes

    Statistics and stochastic calculus for Markov processes in continuous time, include univariate and multivariate stochastic processes such as stochastic differential equations or diffusions (SDE's) or Levy processes.
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  • 25
    BayesianOptimization.jl

    BayesianOptimization.jl

    Bayesian optimization for Julia

    Bayesian optimization for Julia.
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