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ggforce
Accelerating ggplot2
ggforce is an extension package for ggplot2 that introduces specialized statistical transforms, geoms, and layout utilities to enhance and complement the built-in ggplot2 offerings. It enables more advanced visualization techniques such as faceting enhancements, hulls, annotation marks, and novel layouts for network data and marked regions. -
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EvoTrees.jl
Boosted trees in Julia
A Julia implementation of boosted trees with CPU and GPU support. Efficient histogram-based algorithms with support for multiple loss functions, including various regressions, multi-classification and Gaussian max likelihood. -
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awesome-single-cell
Community-curated list of software packages and data resources
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc. List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Rapid, accurate and memory-frugal preprocessing of single-cell and single-nucleus RNA-seq data. Find bimodal, unimodal, and multimodal features in your data. Ascend is an R package comprised of fast, streamlined analysis functions optimized to... -
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FriendsDon'tLetFriends
Friends don't let friends make certain types of data visualization
Friends don't let friends make certain types of data visualization - What are they and why are they bad. -
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pydna
Clone with Python! Data structures for double stranded DNA
Clone with Python! Data structures for double stranded DNA & simulation of homologous recombination, Gibson assembly, cut & paste cloning. Planning genetic constructs with many parts and assembly steps, such as recombinant metabolic pathways, are often difficult to properly document as is evident from the poor state of documentation in the scientific literature. The pydna python package provide a human-readable formal description of cloning and genetic assembly strategies in Python which... -
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Coluna.jl
Branch-and-Price-and-Cut in Julia
Coluna is a branch-and-price-and-cut framework written in Julia. You write an original MIP that models your problem using the JuMP modeling language and our specific extension BlockDecomposition offers a syntax to specify the problem decomposition. Then, Coluna reformulates the original MIP and optimizes the reformulation using the algorithms you choose. Coluna aims to be very modular and tweakable so that you can define the behavior of your customized branch-and-price-and-cut algorithm. -
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Metalhead.jl
Computer vision models for Flux
Metalhead.jl provides standard machine learning vision models for use with Flux.jl. The architectures in this package make use of pure Flux layers, and they represent the best practices for creating modules like residual blocks, inception blocks, etc. in Flux. Metalhead also provides some building blocks for more complex models in the Layers module. -
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Graphs.jl
An optimized graphs package for the Julia programming language
The goal of Graphs.jl is to offer a performant platform for network and graph analysis in Julia, following the example of libraries such as NetworkX in Python. Offers a set of simple, concrete graph implementations – SimpleGraph (for undirected graphs) and SimpleDiGraph (for directed graphs), an API for the development of more sophisticated graph implementations under the AbstractGraph type, and a large collection of graph algorithms with the same requirements as this API. -
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Bayesian Optimization
Python implementation of global optimization with gaussian processes
This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic... -
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ggstatsplot
Enhancing {ggplot2} plots with statistical analysis
{ggstatsplot} is an extension of {ggplot2} package for creating graphics with details from statistical tests included in the information-rich plots themselves. In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. Bayesian hypothesis-testing. The central idea of {ggstatsplot} is simple: combine these... -
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classic.tplx
A more accurate representation of jupyter notebooks
A more accurate representation of Jupyter notebooks when converting to pdfs. This template was designed to make converted Jupyter notebooks look (almost) identical to the actual notebook. If something doesn't exist in the original notebook then it doesn't belong in the conversion. As of nbconvert 5.5.0, the majority of these improvements have been merged into nbconvert's default template. Version 3.x of this package will continue to support nbconvert 5.5.0 and lower, whereas in the future... -
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ImageInTerminal.jl
Julia package for displaying images in the terminal using ANSI colors
ImageInTerminal is a drop-in package that once imported changes how a single Colorant and whole Colorant arrays (regular images) are displayed in the interactive REPL. The displayed images will be downscaled to fit into the size of your active terminal session. By default, this package will detect if your running terminal supports 24-bit colors (true colors). If it does, the image will be displayed in 24-bit colors, otherwise, it falls back to 8-bit (256 colors). -
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ColorSchemes.jl
colorschemes, colormaps, gradients, and palettes
Color schemes, colormaps, gradients, and palettes. Choose ColorSchemes with care. Refer to Peter Kovesi's PerceptualColourMaps package, or to Fabio Crameri's Scientific Colour Maps for more information. If you want to make more advanced ColorSchemes, use linear-segment dictionaries or indexed lists, and use functions to generate color values, see the make_colorscheme() function in the ColorSchemeTools.jl package. -
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Automa.jl
A julia code generator for regular expressions
Automa is a regex-to-Julia compiler. By compiling regex to Julia code in the form of Expr objects, Automa provides facilities to create efficient and robust regex-based lexers, tokenizers and parsers using Julia's metaprogramming capabilities. You can view Automa as a regex engine that can insert arbitrary Julia code into its input-matching process, which will be executed when certain parts of the regex match an input. -
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Query.jl
Query almost anything in julia
Query is a package for querying julia data sources. It can filter, project, join and group data from any iterable data source, including all the sources supported in IterableTables.jl. One can for example query any of the following data sources: any array, DataFrames, DataStreams (including CSV, Feather, SQLite, ODBC), DataTables, IndexedTables, TimeSeries, Temporal, TypedTables and DifferentialEquations (any DESolution). The package currently provides working implementations for in-memory... -
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CBinding.jl
Automatic C interfacing for Julia
Use CBinding.jl to automatically create C library bindings with Julia at runtime. In order to support the fully automatic conversion and avoid name collisions, the names of C types or functions are mangled a bit to work in Julia. Therefore everything generated by CBinding.jl can be accessed with the c"..." string macro to indicate that it lives in C-land. As an example, the function func above is available in Julia as c"func". It is possible to store the generated bindings to more... -
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Unitful.jl
Physical quantities with arbitrary units
Unitful is a Julia package for physical units. We want to support not only SI units but also any other unit system. We also want to minimize or in some cases eliminate the run-time penalty of units. There should be facilities for dimensional analysis. All of this should integrate easily with the usual mathematical operations and collections that are found in Julia base. -
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Mixed-effects models in Julia
A Julia package for fitting (statistical) mixed-effects models
This package defines linear mixed models (LinearMixedModel) and generalized linear mixed models (GeneralizedLinearMixedModel). Users can use the abstraction for statistical model API to build, fit (fit/fit!), and query the fitted models. A mixed-effects model is a statistical model for a response variable as a function of one or more covariates. For a categorical covariate the coefficients associated with the levels of the covariate are sometimes called effects, as in "the effect of using... -
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vim‑sneak
The missing motion for Vim
vim‑sneak is a minimalist yet powerful navigation plugin for Vim, designed to jump to any location specified by two characters. It maintains compatibility with Vim's operators, macros, visual mode, repeat (.), and supports multibyte text. It provides intuitive highlights that disappear once the jump is completed. Sneak has <Plug> mappings for f and t 1-character-sneak. These mappings do not invoke label-mode, even if you have it enabled. Highlights matches in the direction of your search.... -
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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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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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forecast
Forecasting Functions for Time Series and Linear Models
The forecast package is a comprehensive R package for time series analysis and forecasting. It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual... -
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ipychart
The power of Chart.js with Python
Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive, and modular and are displayed directly in the output of the cells of your jupyter notebook environment. Charts are fully interactive, you can hover it to display tooltips and select the information you want to see directly from the output cell of your notebook. All the types of charts present in Chart.js are exposed in ipychart. Even complex features such... -
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PairPlots.jl
Beautiful and flexible vizualizations of high dimensional data
Beautiful and flexible visualizations of high-dimensional data. This package produces pair plots, otherwise known as corner plots or scatter plot matrices: grids of 1D and 2D histograms that allow you to visualize high-dimensional data. Pair plots are an excellent way to visualize the results of MCMC simulations, but are also a useful way to visualize correlations in general data tables. The default styles of this package roughly reproduce the output of the Python library corner.py for a... -
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Kubernetes History Inspector
A log viewer for Kubernetes troubleshooting
The khi repository is a Google Cloud open-source project focused on infrastructure and system-level tooling, typically aimed at enabling advanced cloud-native workflows, observability, or orchestration in Kubernetes-based environments. It is designed to support engineers working with distributed systems by providing utilities and abstractions that simplify deployment, monitoring, or operational management. The project aligns with Google Cloud’s broader ecosystem of tools that help developers...
