Search Results for "using" - Page 4
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Showing 103 open source projects for "using"
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InteractiveErrors.jl
Interactive error messages for the Julia REPL
Interactive error messages for the Julia REPL. Just start using your REPL normally. Once you hit an error you'll be presented with an interactive tree representing your stacktrace which you can explore. To turn interactive errors off and return to using normal stack traces call toggle(). Call toggle() again to turn it back on. Press up and down arrows to move through the stacktrace. Press space to fold or unfold the currently selected line. -
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Bayesian Julia
Bayesian Statistics using Julia and Turing
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 for making predictions about future events. Bayesian statistics is a departure from... -
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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
...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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WhereTraits.jl
Traits for julia: dispatch on whatever you want using where syntax
...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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ClimateTools.jl
Climate science package for Julia
Climate analysis tools in Julia. ClimateTools.jl is a collection of commonly-used tools in Climate science. Basics of climate field analysis are covered, with some forays into exploratory techniques associated with climate scenario design. The package is aimed to ease the typical steps of analysis of climate models outputs and gridded datasets (support for weather stations is a work-in-progress). Climate indices and bias correction functions are coded to leverage the use of multiple threads.... -
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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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Transducers.jl
Efficient transducers for Julia
Transducers are transformations of "sequence" of input that can be composed very efficiently. The interface used by transducers naturally describes a wide range of processes that is expressible as a succession of steps. Furthermore, transducers can be defined without specifying the details of the input and output (collections, streams, channels, etc.) and therefore achieves a full reusability. Transducers are introduced by Rich Hickey, the creator of the Clojure language. His Strange Loop... -
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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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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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DiffEqOperators.jl
Linear operators for discretizations of differential equations
...The cases of 1, 2, and 3 dimensions with an evenly spaced grid are optimized with a convolution routine from NNlib.jl. Care is taken to give efficiency by avoiding unnecessary allocations, using purpose-built stencil compilers, allowing GPUs and parallelism, etc. Any operator can be concretized as an Array, a BandedMatrix or a sparse matrix. -
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Memento.jl
A flexible logging library for Julia
Memento is a flexible hierarchical logging library for Julia. -
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JuliaCall for Seamless Integration of R
Embed Julia in R
Package JuliaCall is an R interface to Julia, which is a high-level, high-performance dynamic programming language for numerical computing. Below is an image for Mandelbrot set. JuliaCall brings more than 100 times speedup of the calculation. -
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Soss
Probabilistic programming via source rewriting
...Soss and DynamicPPL are both maturing and becoming more complete, so the above will change over time. It's also worth noting that we (the Turing team and I) hope to move toward a natural way of using these systems together to arrive at the best of both. -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
...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 sequence of operations for which the parameters can (but need not) be random variables, as the following code snippet demonstrates. -
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OpticSim.jl
Optical Simulation software
OpticSim.jl is a Julia package for geometric optics (ray tracing) simulation and optimization of complex optical systems developed by the Microsoft Research Interactive Media Group and the Microsoft Hardware Architecture Incubation Team (HART). 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... -
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Julia Data Science
Book on Julia for Data Science
This is an open source and open access book on how to do Data Science using Julia. Our target audience are researchers from all fields of applied sciences. Of course, we hope to be useful for industry too. You can navigate through the pages of the ebook by using the arrow keys (left/right) on your keyboard. -
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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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TimeseriesPrediction.jl
Prediction of timeseries using methods of nonlinear dynamics
Repository for predicting time series using methods from nonlinear dynamics and time series analysis. It uses DelayEmbeddings. -
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RigidBodyDynamics.jl
Julia implementation of various rigid body dynamics
RigidBodyDynamics.jl is a rigid body dynamics library in pure Julia. It aims to be user friendly and performant, but also generic in the sense that the algorithms can be called with inputs of any (suitable) scalar types. This means that if fast numeric dynamics evaluations are required, a user can supply Float64 or Float32 inputs. However, if symbolic quantities are desired for analysis purposes, they can be obtained by calling the algorithms with e.g. SymPy.Sym inputs. If gradients are... -
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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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RayTracer.jl
Differentiable RayTracing in Julia
...Unfortunately, the current state of this package of has not been updated to reflect those improvements. It also seems that it might be better to gradually transition to defining the adjoints directly using ChainRules. A Ray Tracer written completely in Julia. This allows us to leverage the AD capabilities provided by Zygote to differentiate through the Ray Tracer. -
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ArgCheck.jl
Package for checking function arguments
Package for checking function arguments. @argcheck code is as fast as @assert or a hand written if. That being said it is possible to erase argchecks, much like one can erase bounds checking using @inbounds. This feature is currently experimental. It may be silently changed or removed without increasing the major ArgCheck version number. -
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CUDAnative.jl
Julia support for native CUDA programming
...It is built on the CUDA toolkit and aims to be as full-featured and offer the same performance as CUDA C. The toolchain is mature, has been under development since 2014, and can easily be installed on any current version of Julia using the integrated package manager. -
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JuliaFEM.jl
The JuliaFEM software library is a framework
The JuliaFEM software library is a framework that allows for the distributed processing of large Finite Element Models across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. The JuliaFEM software library is a framework that allows for the distributed processing of large Finite Element Models across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. ...
