Search Results for "nvm-windows" - Page 8
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Showing 2241 open source projects for "nvm-windows"
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Enzyme.jl
Julia bindings for the Enzyme automatic differentiator
This is a package containing the Julia bindings for Enzyme. This is very much a work in progress and bug reports/discussion is greatly appreciated. Enzyme is a plugin that performs automatic differentiation (AD) of statically analyzable LLVM. It is highly-efficient and its ability perform AD on optimized code allows Enzyme to meet or exceed the performance of state-of-the-art AD tools. -
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OnlineStats.jl
Single-pass algorithms for statistics
OnlineStats does statistics and data visualization for big/streaming data via online algorithms. High-performance single-pass algorithms for statistics and data viz. Updated one observation at a time. Algorithms use O(1) memory. Algorithms use O(1) memory. -
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CUDA.jl
CUDA programming in Julia
High-performance GPU programming in a high-level language. JuliaGPU is a GitHub organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well-positioned to productively program hardware accelerators like GPUs without sacrificing performance. The latest development version of CUDA.jl requires Julia 1.8 or higher. If you are using an older version of Julia, you need to use a previous version of CUDA.jl. This will... -
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PySR
High-Performance Symbolic Regression in Python and Julia
PySR is an open-source tool for Symbolic Regression: a machine learning task where the goal is to find an interpretable symbolic expression that optimizes some objective. Over a period of several years, PySR has been engineered from the ground up to be (1) as high-performance as possible, (2) as configurable as possible, and (3) easy to use. PySR is developed alongside the Julia library SymbolicRegression.jl, which forms the powerful search engine of PySR. The details of these algorithms are... -
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Foxglove Studio
Robotics visualization and debugging
Foxglove Studio is an open-source visualization and debugging tool for robotics. Use customizable layouts to arrange interactive visualizations and quickly understand what your robot is doing. Use Foxglove Studio's rich interactive visualizations to analyze live connections and pre-recorded data. Experience the world as your robot does. Visualize images and point clouds, overlay bounding boxes, add classification labels and planned movements, and drill down into your data with plots or raw... -
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RuntimeGeneratedFunctions.jl
Functions generated at runtime without world-age issues or overhead
RuntimeGeneratedFunctions are functions generated at runtime without world-age issues and with the full performance of a standard Julia anonymous function. This builds functions in a way that avoids eval. For technical reasons, RuntimeGeneratedFunctions needs to cache the function expression in a global variable within some module. This is normally transparent to the user, but if the RuntimeGeneratedFunction is evaluated during module precompilation, the cache module must be explicitly set... -
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PhysicalConstants.jl
Collection of fundamental physical constants with uncertainties
PhysicalConstants.jl provides common physical constants. They are defined as instances of the new Constant type, which is a subtype of AbstractQuantity (from Unitful.jl package) and can also be turned into Measurement objects (from Measurements.jl package) at request. Constants are grouped into different submodules so that the user can choose different datasets as needed. Currently, 2014 and 2018 editions of CODATA recommended values of the fundamental physical constants are provided. -
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ReachabilityAnalysis.jl
Compute reachable states of dynamical systems
Reachability analysis is concerned with computing rigorous approximations of the set of states reachable by a dynamical system. In the scope of this package are systems modeled by continuous or hybrid dynamical systems, where the dynamics change with discrete events. Systems are modeled by ordinary differential equations (ODEs) or semi-discrete partial differential equations (PDEs), with uncertain initial states, uncertain parameters or non-deterministic inputs. -
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Stan.jl
Stan.jl illustrates the usage of the 'single method' packages
A collection of example Stan Language programs demonstrating all methods available in Stan's cmdstan executable (as an external program) from Julia. For most applications one of the "single method" packages, e.g. StanSample.jl, StanDiagnose.jl, etc., is a better choice for day-to-day use. To execute the most important method in Stan ("sample"), use StanSample.jl. Some Pluto notebook examples can be found in the repository. -
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PGFPlotsX.jl
Plots in Julia using the PGFPlots LaTeX package
PGFPlotsX is a Julia package to generate publication quality figures using the LaTeX library PGFPlots. It is similar in spirit to the package PGFPlots.jl but it tries to have a very close mapping to the PGFPlots API as well as minimize the number of dependencies. The fact that the syntax is similar to the TeX version means that examples from Stack Overflow and the PGFPlots manual can easily be incorporated in the Julia code. -
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Excalidraw MCP
Fast and streamable Excalidraw MCP App
Excalidraw-MCP is an open-source Model Context Protocol (MCP) application and server that connects the visual power of Excalidraw’s hand-drawn diagram editor with AI-driven workflows, enabling agents like Claude, ChatGPT, VS Code, and other MCP-compatible hosts to generate and manipulate diagrams programmatically. Rather than being just a static whiteboard, Excalidraw-MCP serves diagrams in real time using an MCP backend and streams interactive visual output back to the client, letting AI... -
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FEniCS.jl
A scientific machine learning (SciML) wrapper for the FEniCS
FEniCS.jl is a wrapper for the FEniCS library for finite element discretizations of PDEs. This wrapper includes three parts. Installation and direct access to FEniCS via a Conda installation. Alternatively one may use their current FEniCS installation. A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of FEniCS itself. Interfaces have been provided for the main functions and their... -
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ArgParse.jl
Package for parsing command-line arguments to Julia programs
ArgParse.jl is a package for parsing command-line arguments to Julia programs. -
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GDAL.jl
Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library
Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly. -
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Bukdu.jl
Bukdu is a web development framework for Julia
Bukdu.jl is a web development framework for Julia. -
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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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Registrator.jl
Julia package registration bot
Registrator is a GitHub app that automates the creation of registration pull requests for your Julia packages to the General registry. -
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Optim.jl
Optimization functions for Julia
Univariate and multivariate optimization in Julia. Optim.jl is part of the JuliaNLSolvers family. Optim.jl is a package for univariate and multivariate optimization of functions. -
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Kibana
Your window into the Elastic Stack
Kibana is a analytics and search dashboard for Elasticsearch that allows you to visualize Elasticsearch data and efficiently navigate the Elastic Stack. With Kibana you can visualize and shape your data simply and intuitively, share visualizations for greater collaboration, organize dashboards and visualizations, and so much more. -
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Coverage.jl
Take Julia code coverage and memory allocation results, do useful thin
Julia can track how many times, if any, each line of your code is run. This is useful for measuring how much of your code base your tests actually test, and can reveal the parts of your code that are not tested and might be hiding a bug. You can use Coverage.jl to summarize the results of this tracking or to send them to a service like Coveralls.io or Codecov.io. Julia can track how much memory is allocated by each line of your code. This can reveal problems like type instability, or... -
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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... -
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JuliaSyntax
A Julia frontend, written in Julia
A Julia compiler frontend, written in Julia. Read the documentation for more information. JuliaSyntax.jl is used as the new default Julia parser in Julia 1.10. It's highly compatible with Julia's older femtoliter-based parser - It parses all of Base, the standard libraries and the General registry. Some minor differences remain where we've decided to fix bugs or strange behaviors in the reference parser. The AST and tree data structures are usable but their APIs will evolve as we try out... -
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Tullio.jl
Tullio is a very flexible einsum macro
Tullio is a very flexible einsum macro. It understands many array operations written in index notation -- not just matrix multiplication and permutations, but also convolutions, stencils, scatter/gather, and broadcasting. Used by itself the macro writes ordinary nested loops much like Einsum.@einsum. One difference is that it can parse more expressions, and infer ranges for their indices. Another is that it will use multi-threading (via Threads.@spawn) and recursive tiling, on large enough arrays. -
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esquisse
RStudio add-in to make plots interactively with ggplot2
The purpose of this add-in is to let you explore your data quickly to extract the information they hold. You can create visualization with {ggplot2}, filter data with {dplyr} and retrieve generated code. This addin allows you to interactively explore your data by visualizing it with the ggplot2 package. It allows you to draw bar plots, curves, scatter plots, histograms, boxplot and sf objects, then export the graph or retrieve the code to reproduce the graph. This addin allows you to... -
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Delta
A viewer for git and diff output
Code evolves, and we all spend time studying diffs. Delta aims to make this both efficient and enjoyable: it allows you to make extensive changes to the layout and styling of diffs, as well as allowing you to stay arbitrarily close to the default git/diff output. Language syntax highlighting with color themes. Within-line highlights based on a Levenshtein edit inference algorithm. Git style strings (foreground color, background color, font attributes) are supported for >20 stylable elements....
