Various special functions based on log and exp moved from StatsFuns.jl into a separate package, to minimize dependencies. These functions only use native Julia code, so there is no need to depend on librmath or similar libraries.

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).

CommonSolve.jl provides solve, init, solve!, and step! commands. By using the same definition, solver libraries from other completely different ecosystems can extend the functions and thus not clash with SciML if both ecosystems export the solve command.

This small package supports the representation of images as AxisArrays to endow the axes with "meaning," and makes programming with such arrays easy via traits.

This package provides a function extrapolate that extrapolates a given function f(x) to f(x0), evaluating f only at a geometric sequence of points > x0 (or optionally < x0). The key algorithm is Richardson extrapolation using a Neville–Aitken tableau, which adaptively increases the degree of an extrapolation polynomial until convergence is achieved to a desired tolerance (or convergence stalls due to e.g. floating-point errors). This allows one to obtain f(x0) to high-order accuracy, assuming that f(x0+h) has a Taylor series or some other power series in h.

This package provides zlib codecs for TranscodingStreams.jl.

This package provides tools for working with categorical variables, both with unordered (nominal variables) and ordered categories (ordinal variables), optionally with missing values.

The is package provides a variety of common utilities that can be used by downstream automatic differentiation (AD) tools to define and execute forward-, reverse-, and mixed-mode primitives.

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

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 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 provides reader/writer for delimited text data, as comma-delimited (csv), tab-delimited (tsv), or otherwise.

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.

SoftGlobalScope is a package for the Julia language that simplifies the variable scoping rules for code in global scope. It is intended for interactive shells to make it easier to work interactively with Julia, especially for beginners.

This package is for calculating derivatives, gradients, Jacobians, Hessians, etc. numerically. This library is for maximizing speed while giving a usable interface to end users in a way that specializes on array types and sparsity.

This package only contains and exports a single function realdot(x, y). It computes real(LinearAlgebra.dot(x, y)) while avoiding computing the imaginary part of LinearAlgebra.dot(x, y) if possible. The real dot product is useful when one treats complex numbers as embedded in a real vector space.

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.

This package supports representing banded matrices by only the entries on the bands.

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

This package provides a namespace for data-related generic function definitions to solve the optional dependency problem; packages wishing to share and/or extend functions can avoid depending directly on each other by moving the function definition to StatsAPI.jl and each package taking a dependency on it.

This package provides a wide array of functions for dealing with color. This includes conversion between colorspaces, measuring distance between colors, simulating color blindness, parsing colors, and generating color scales for graphics.

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

PositiveFactorizations is a package for computing a positive definite matrix decomposition (factorization) from an arbitrary symmetric input. The motivating application is optimization (Newton or quasi-Newton methods), in which the canonical search direction -H/g (H being the Hessian and g the gradient) may not be a descent direction if H is not positive definite.

This package provides the StructTypes.StructType trait for Julia types to declare the kind of "struct" they are, providing serialization/deserialization packages patterns and strategies to automatically construct objects.