Aqua.jl, provides functions to run a few automatable checks for Julia packages.

A block array is a partition of an array into blocks or subarrays. This package has two purposes. Firstly, it defines an interface for an AbstractBlockArray block arrays that can be shared among types representing different types of block arrays. The advantage to this is that it provides a consistent API for block arrays. Secondly, it also implements two different type of block arrays that follow the AbstractBlockArray interface. The type BlockArray stores each block contiguously while the type PseudoBlockArray stores the full matrix contiguously. This means that BlockArray supports fast non copying extraction and insertion of blocks while PseudoBlockArray supports fast access to the full matrix to use in in for example a linear solver.

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

This package provides tools to express a design pattern for dealing with large/ nested structures, as in machine learning and optimisation. For large machine learning models it can be cumbersome or inefficient to work with parameters as one big, flat vector, and structs help in managing complexity; but it is also desirable to easily operate over all parameters at once, e.g. for changing precision or applying an optimiser update step.

This package provides Data types and methods for common operations with biological sequences, including DNA, RNA, and amino acid sequences.

This package provides support for image resizing, image rotation, and other spatial transformations of arrays.

This package provides a C-compatible enum for Julia.

This package provides SentinelArrayT that wraps an AbstractArray of type T, and accepts a sentinel and value argument.

This package provides a type stable and efficient wrapper of arbitrary functions.

This package provides a macro-based implementation of traits. 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.

This package provides definitions for most of the primary types and functions in StaticArrays.jl. This enables downstream packages to implement new methods on these types without depending on the entirety of StaticArrays.jl.

AxisAlgorithms is a collection of filtering and linear algebra algorithms for multidimensional arrays. For algorithms that would typically apply along the columns of a matrix, you can instead pick an arbitrary axis (dimension).

This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease-of-use, broad algorithmic support, and exceptional performance.

This package just exports one type: the InvertedIndex, or Not for short. It can wrap any supported index type and may be used as an index into any AbstractArray subtype, including OffsetArrays.

The aim of this package is to provide users with a set of small generic routines useful above all in astronomical and astrophysical context, written in Julia.

This minimalistic package serves as the foundation for working with colors in Julia. It defines basic color types and their constructors, and sets up traits and show methods to make them easier to work with.

This is a twin package to ImageCore with functions that are used among many of the packages in JuliaImages. The main purpose of this package is to reduce unnecessary compilation overhead from external dependencies.

This package implements "lazy" in-place elementwise transformations of arrays for the Julia programming language. Explicitly, it provides a "view" M of an array A so that M[i] = f(A[i]) for a specified (but arbitrary) function f, without ever having to compute M explicitly (in the sense of allocating storage for M). The name of the package comes from the fact that M == map(f, A).

Parsers.jl is a collection of type parsers and utilities for Julia.

ReferenceTests.jl is a Julia package that adds a couple of additional macros to your testing toolbox. In particular, it focuses on functionality for testing values against reference files, which in turn the package can help create and update if need be.

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."

The Preferences package provides an integrated way for packages to store configuration switches to persistent TOML files, and use those pieces of information at both run time and compile time in Julia. This enables the user to modify the behavior of a package, and have that choice reflected in everything from run time algorithm choice to code generation at compile time.

This package provides a functionality of files download with cURL, wget or HTTP.jl backends.

This package defines the Bijection data type. A Bijection data structure behaves similar to a Dict, however it prevents assigning the same value to two different keys.