Showing 38 open source projects for "tools"

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    FinEtools.jl

    FinEtools.jl

    Finite Element tools in Julia

    FinEtools is a package for basic operations on finite element meshes: Construction, modification, selection, and evaluation of quantities defined on a mesh. Utilities are provided for maintaining mesh-based data (fields), for defining normals and loads, for working with physical units and coordinate systems, and for integrating over finite element meshes.
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  • 2
    The Julia Programming Language

    The Julia Programming Language

    High-level, high-performance dynamic language for technical computing

    ...Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. Libraries from Python, R, C/Fortran, C++, and Java can also be used.
    Downloads: 1 This Week
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  • 3
    Metal.jl

    Metal.jl

    Metal programming in Julia

    With Metal.jl it's possible to program GPUs on macOS using the Metal programming framework. The package is a work in progress. There are bugs, functionality is missing, and performance hasn't been optimized. Expect to have to make changes to this package if you want to use it. PRs are very welcome. These requirements are fairly strict, and are due to our limited development resources (manpower, hardware). Technically, they can be relaxed. If you are interested in contributing to this, see...
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  • 4
    StaticTools.jl

    StaticTools.jl

    Enabling StaticCompiler.jl-based compilation of (some) Julia code

    Tools to enable StaticCompiler.jl-based static compilation of Julia code (or more accurately, a subset of Julia which we might call "unsafe Julia") to standalone native binaries by avoiding GC allocations and llvmcall-ing all the things. This package currently requires Julia 1.8 or greater for best results (if in doubt, check which versions are passing CI).
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  • 5
    ChainRules.jl

    ChainRules.jl

    Forward and reverse mode automatic differentiation primitives

    The ChainRules package provides a variety of common utilities that can be used by downstream automatic differentiation (AD) tools to define and execute forward-, reverse--, and mixed-mode primitives. The core logic of ChainRules is implemented in ChainRulesCore.jl. To add ChainRules support to your package, by defining new rules or frules, you only need to depend on the very light-weight package ChainRulesCore.jl. This repository contains ChainRules.jl, which is what people actually use directly. ...
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  • 6
    ReinforcementLearning.jl

    ReinforcementLearning.jl

    A reinforcement learning package for Julia

    A collection of tools for doing reinforcement learning research in Julia. Provide elaborately designed components and interfaces to help users implement new algorithms. Make it easy for new users to run benchmark experiments, compare different algorithms, and evaluate and diagnose agents. Facilitate reproducibility from traditional tabular methods to modern deep reinforcement learning algorithms.
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  • 7
    ProbabilisticCircuits.jl

    ProbabilisticCircuits.jl

    Probabilistic Circuits from the Juice library

    This module provides a Julia implementation of Probabilistic Circuits (PCs), tools to learn structure and parameters of PCs from data, and tools to do tractable exact inference with them. Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units). ...
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  • 8
    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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  • 9
    Mousetrap.jl

    Mousetrap.jl

    Finally, a GUI Engine made for Julia

    ...It fully wraps GTK4 (which is written in C), vastly simplifying its interface to improve ease of use without sacrificing flexibility. It aims to give developers of all skill levels the tools to start creating complex GUI applications with little time and effort while taking full advantage of Julia's idiosyncrasies.
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  • 10
    MeasureTheory.jl

    MeasureTheory.jl

    "Distributions" that might not add to one.

    Probabilistic programming and statistical computing are vibrant areas in the development of the Julia programming language, but the underlying infrastructure dramatically predates recent developments. The goal of MeasureTheory.jl is to provide Julia with the right vocabulary and tools for these tasks. In this package we introduce well-chosen foundational primitives centered around the notion of measure, density and conditional probability with powerful combinators and transforms intended to power and unify work on probabilistic programming and statistical computing within Julia. Check out our JuliaCon 2021 article detailing our ideas for and with this package.
    Downloads: 0 This Week
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  • 11
    ScikitLearn.jl

    ScikitLearn.jl

    Julia implementation of the scikit-learn API

    The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework.
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  • 12
    MessyTimeSeries.jl

    MessyTimeSeries.jl

    A Julia implementation of basic tools for time series analysis

    A Julia implementation of basic tools for time series analysis compatible with incomplete data. Advanced estimation and validation algorithms are included in MessyTimeSeriesOptim.
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  • 13
    OpticSim.jl

    OpticSim.jl

    Optical Simulation software

    ...It is designed to allow optical engineers to create optical systems procedurally and then to simulate and optimize them. Unlike Zemax, Code V, or other interactive optical design systems OpticSim.jl has limited support for interactivity, primarily in the tools for visualizing optical systems. A large variety of surface types are supported, and these can be composed into complex 3D objects through the use of constructive solid geometry (CSG). A complete catalog of optical materials is provided through the complementary GlassCat submodule. This software provides extensive control over the modelling, simulation, visualization and optimization of optical systems. ...
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