This package provides bit twiddling convenience functions in Julia. These are useful for going to the next or previous mask size or for calculating corresponding shifts.

An IndirectArray is one that encodes data using a combination of an index and a value table. Each element is assigned its own index, which is used to retrieve the value from the value table. Among other uses, IndirectArrays can represent indexed images, sometimes called "colormap images" or "paletted images."

This package provides another JSON package for Julia, with a focus on speed and slick struct mapping.

TypedTables.jl provides two column-based storage containers: Table and FlexTable, both of which represent an array of NamedTuples. This package is designed to be lightweight, easy-to-use and fast, and presents a very minimal new interface to learn.

This minimalistic package serves as the foundation for other SIMD packages in Julia.

This package provides a simple and flexible IR format, expressive enough to work with both lowered and typed Julia code, as well as external IRs. It can be used with Julia metaprogramming tools such as Cassette.

This package provides support for decoding and encoding texts between multiple character encodings. It is currently based on the iconv interface, and supports all major platforms using GNU libiconv.

This package provides a wrapper around ImageMagick version 6. It was split off from Images.jl to make image I/O more modular.

This package defines the primitive types for nucleic acids and amino acids that are used ny otherBioJulia packages.

The Schur decomposition is the workhorse for eigensystem analysis of dense matrices. The diagonal eigen-decomposition of normal (especially Hermitian) matrices is an important special case, but for non-normal matrices the Schur form is often more useful.

ImageCore is the lowest-level component of the system of packages designed to support image processing and computer vision.

This package provides consistent and extensible functional programming infrastructures, and metaprogramming facilities.

The DualNumbers Julia package defines the Dual type to represent dual numbers, and supports standard mathematical operations on them. Conversions and promotions are defined to allow performing operations on combinations of dual numbers with predefined Julia numeric types.

This package contains the testset from Julia, packaged into a loadable module.

This package provides special mathematical functions, including Bessel, Hankel, Airy, error, Dawson, exponential (or sine and cosine) integrals, eta, zeta, digamma, inverse digamma, trigamma, and polygamma functions.

PDMats.jl supports efficient computation on positive definite matrices of various structures. In particular, it provides uniform interfaces to use positive definite matrices of various structures for writing generic algorithms, while ensuring that the most efficient implementation is used in actual computation.

This package provides a Julia wrapper for astronomical library ERFA.

This package enables the Markdown / MkDocs backend of Documenter.jl.

FuzzyCompletions provides fuzzy completions for a Julia runtime session.

CoordinateTransformations is a Julia package to manage simple or complex networks of coordinate system transformations. Transformations can be easily applied, inverted, composed, and differentiated (both with respect to the input coordinates and with respect to transformation parameters such as rotation angle). Transformations are designed to be light-weight and efficient enough for, e.g., real-time graphical applications, while support for both explicit and automatic differentiation makes it easy to perform optimization and therefore ideal for computer vision applications such as SLAM (simultaneous localization and mapping).

HTTP.jl is a Julia library for HTTP Messages, implementing both a client and a server.

FileIO aims to provide a common framework for detecting file formats and dispatching to appropriate readers/writers. The two core functions in this package are called load and save, and offer high-level support for formatted files (in contrast with Julia's low-level read and write).

This package provides a Julia interface defining a collection of types (without instances) for implementing conventions about the scientific interpretation of data. This package makes a distinction between the machine type and the scientific type of a Julia object. A machine type refers to the Julia type being used to represent the object, for instance Float64. The scientific type refers to how the object should be interpreted, for instance Continuous or Multiclass3.

Millboard.jl provides a library for getting data in a tablized format to arrange into rows and columns of cells.