Search Results for "julia" - Page 13
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Showing 405 open source projects for "julia"
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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. -
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Mousetrap.jl
Finally, a GUI Engine made for Julia
Mousetrap is a GUI library designed 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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ProximalOperators.jl
Proximal operators for nonsmooth optimization in Julia
Proximal operators for nonsmooth optimization in Julia. This package can be used to easily implement proximal algorithms for convex and nonconvex optimization problems such as ADMM, the alternating direction method of multipliers. With using ProximalOperators the package exports the prox and prox! methods to evaluate the proximal mapping of several functions. -
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Bootstrap.jl
Statistical bootstrapping library for Julia
Bootstrapping is a widely applicable technique for statistical estimation. -
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libCEED
CEED Library: Code for Efficient Extensible Discretizations
libCEED provides fast algebra for element-based discretizations, designed for performance portability, run-time flexibility, and clean embedding in higher-level libraries and applications. It offers a C99 interface as well as bindings for Fortran, Python, Julia, and Rust. While our focus is on high-order finite elements, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the user manual and API implementation portion of the documentation. One of the challenges with high-order methods is that a global sparse matrix is no longer a good representation of a high-order linear operator, both with respect to the FLOPs needed for its evaluation, as well as the memory transfer needed for a matvec. ... -
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IndexedTables.jl
Flexible tables with ordered indices
IndexedTables provides tabular data structures where some of the columns form a sorted index. It provides the backend to JuliaDB, but can be used on its own for efficient in-memory data processing and analytics. -
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Octo.jl
Octo.jl is an SQL Query DSL in Julia
Octo.jl is an SQL Query DSL in Julia. It also comes with a very useful tool called Repo. You could Repo.get, Repo.insert! Repo.update! Repo.delete! for many database drivers without hand-written SQL. -
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StatProfilerHTML.jl
Show Julia profiling data in an explorable HTML page
This module formats the output from Julia's Profile module into an html rendering of the source function lines and functions, allowing for interactive exploration of any bottlenecks that may exist in your code. -
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FastAI.jl
Repository of best practices for deep learning in Julia
FastAI.jl is a Julia library for training state-of-the-art deep learning models. From loading datasets and creating data preprocessing pipelines to training, FastAI.jl takes the boilerplate out of deep learning projects. It equips you with reusable components for every part of your project while remaining customizable at every layer. FastAI.jl comes with support for common computer vision and tabular data learning tasks, with more to come. -
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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. ... -
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AbstractFFTs.jl
A Julia framework for implementing FFTs
A general framework for fast Fourier transforms (FFTs) in Julia. This package is mainly not intended to be used directly. Instead, developers of packages that implement FFTs (such as FFTW.jl or FastTransforms.jl) extend the types/functions defined in AbstractFFTs. This allows multiple FFT packages to co-exist with the same underlying fft(x) and plan_fft(x) interface. -
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WhereTraits.jl
Traits for julia: dispatch on whatever you want using where syntax
...In addition, WhereTraits comes with a standardized way how to resolve ambiguities among traits, by defining an order among the traits with @traits_order. Under the hood @traits uses normal function dispatch to achieve the speed and flexibility, however, julia function dispatch can lead to ambiguities. With traits these can easily happen if someone defines @traits for the same standard dispatch but using different traits. -
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SciMLBenchmarks.jl
Benchmarks for scientific machine learning (SciML) software
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem. -
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DataVoyager.jl
Julia wrapper for the Voyager data exploration tool
This package provides Julia integration for the Voyager data exploration tool. DataVoyager.jl can be used for data exploration. It can help you visualize and understand any data that is in a tabular format. -
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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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DeepH-pack
Deep neural networks for density functional theory Hamiltonian
DeepH-pack is the official implementation of the DeepH (Deep Hamiltonian) method described in the paper Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation and in the Research Briefing. DeepH-pack supports DFT results made by ABACUS, OpenMX, FHI-aims or SIESTA and will support HONPAS. -
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Transducers.jl
Efficient transducers for Julia
...Transducers are introduced by Rich Hickey, the creator of the Clojure language. His Strange Loop talk is a great introduction to the idea of transducers. Transducers.jl is an implementation of the transducers in Julia. Aiming to satisfy the high-performance needs of Julia users, Transducers.jl uses a formulation that is pure and aiding type-stability. -
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Gaius.jl
Divide and Conquer Linear Algebra
Gaius.jl is a multi-threaded BLAS-like library using a divide-and-conquer strategy to parallelism, and built on top of the fantastic LoopVectorization.jl. Gaius spawns threads using Julia's depth-first parallel task runtime and so Gaius's routines may be fearlessly nested inside multi-threaded Julia programs. Gaius is not stable or well-tested. Only use it if you're adventurous. -
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ProxSDP.jl
Semidefinite programming optimization solver
ProxSDP is an open-source semidefinite programming (SDP) solver based on the paper "Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting". The main advantage of ProxSDP over other state-of-the-art solvers is the ability to exploit the low-rank structure inherent to several SDP problems. -
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ScikitLearn.jl
Julia implementation of the scikit-learn API
...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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Weave
Scientific reports/literate programming for Julia
Weave is a scientific report generator/literate programming tool for the Julia programming language. It resembles Pweave, knitr, R Markdown, and Sweave. You can write your documentation and code in an input document using Markdown, Noweb or ordinal Julia script syntax, and then use the weave function to execute code and generate an output document while capturing results and figures. Supports various output document formats: HTML, PDF, GitHub markdown, Jupyter Notebook, MultiMarkdown, Asciidoc and reStructuredText. -
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InteractiveDynamics.jl
Fast, general-purpose interactive applications for complex systems
Fast, general-purpose interactive applications for dynamical systems of all kinds, including ODEs, maps, billiards, and agent-based-models. -
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ACME.jl
Analog Circuit Modeling and Emulation for Julia
ACME is a Julia package for the simulation of electrical circuits, focusing on audio effect circuits. It allows one to programmatically describe a circuit in terms of elements and connections between them and then automatically derive a model for the circuit. The model can then be run on varying input data. -
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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 with... -
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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.
