Search Results for "offline library software"
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Showing 10 open source projects for "offline library software"
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1
renv
renv: Project environments for R
renv is an R dependency management toolkit that enables project-level library isolation and reproducibility. It tracks package versions in a lockfile and can restore exact library states across machines or over time, making R projects portable and consistent. -
2
plotly
An interactive graphing library for R
This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of... -
3
R Source
Read-only mirror of R source code
The wch/r-source repository is a read-only mirror of the official R language source code, maintained to reflect the upstream Subversion (SVN) R core development tree. This mirror provides public visibility into R’s internals—everything from the interpreter, base and recommended packages, documentation, and C/Fortran code under the hood. It is updated hourly to stay in sync with the upstream SVN. Although it mirrors the R source for browsing and reference, it is not the “canonical development... -
4
MetBrewer
Color palette package inspired by Metropolitan Museum of Art in NY
MetBrewer is an R package that provides color palettes inspired by artworks and collections in the Metropolitan Museum of Art (The Met). The idea is to draw on the rich visual heritage of fine art to generate palettes that are aesthetically pleasing and grounded in real-world artistic color usage. The palettes are curated, named after artworks or styles, and often include notes about colorblind-friendliness and contrast. The package supports both discrete and continuous palette types, with... -
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5
box
Write reusable, composable and modular R code
box is an R package providing a modular system / module loader for organizing reusable R code outside of full packages. It allows users to treat R scripts (files/folders) as modules — possibly nested — with explicit exports, imports, and scoping. The idea is to let users structure code in a more modular, composable way, without needing every reusable component to be a full CRAN-style package. It also provides a cleaner syntax for importing functions or modules (via box::use) that allows... -
6
QBPWCF
PHP library for not only web-based application in Fedora Linux
此專案的目的是要建立簡單、易用、參數說明完整且富有調整性的PHP元件庫，讓PHP程式設計開發者可以輕鬆地建立高度客製化的應用。 套用當代的術語而言，就是要作為LOW CODE平台的函式庫。 -
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R Packages (r-pkgs)
Building R packages
...The book teaches how to develop, document, test, and share R packages: the practices, tools, infrastructure, workflows, and best practices around package development in R. The repository contains the code, text, site content for building the book, examples, exercises, etc. It is not a software library to be loaded in R (except perhaps the examples), but a resource/guide/manual. The first edition is no longer available online. A second edition is under development and available. -
8
Scripting Language Bindings
A port of WFOPT to the several scripting languages
This project contains bindings for various scripting languages to the Wheefun Options Parsing Library. It is meant to provide parity with the C implementation so .NET languages can take advantage of WFOPT. For more information, please see the main page. -
9
osm4scala
Reading OpenStreetMap Pbf files.
Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files. -
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10
RStan
RStan, the R interface to Stan
RStan is the R interface to Stan, a C++ library for statistical modeling and high-performance statistical computation. It lets users specify models in the Stan modeling language (for Bayesian inference), compile them, and perform inference from R. Key inference approaches include full Bayesian inference via Hamiltonian Monte Carlo (specifically the No-U-Turn Sampler, NUTS), approximate Bayesian inference via variational methods, and optimization (penalized likelihood). RStan integrates with...
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