This package provides the @cse macro, which performs common subexpression elimination.

This package is designed to help in testing ChainRulesCore.frule and ChainRulesCore.rrule methods. The main entry points are ChainRulesTestUtils.frule_test, ChainRulesTestUtils.rrule_test, and ChainRulesTestUtils.test_scalar. Currently this is done via testing the rules against numerical differentiation (using FiniteDifferences.jl).

ChainRulesTestUtils.jl is separated from ChainRulesCore.jl so that it can be a test-only dependency, allowing it to have potentially heavy dependencies, while keeping ChainRulesCore.jl as light-weight as possible.

LightGraphs offers both (a) a set of simple, concrete graph implementations -- Graph (for undirected graphs) and DiGraph (for directed graphs), and (b) an API for the development of more sophisticated graph implementations under the AbstractGraph type.

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 package provides these irrational constants:

• twoπ = 2π

• fourπ = 4π

• halfπ = π / 2

• quartπ = π / 4

• invπ = 1 / π

• twoinvπ = 2 / π

• fourinvπ = 4 / π

• inv2π = 1 / (2π)

• inv4π = 1 / (4π)

• sqrt2 = √2

• sqrt3 = √3

• sqrtπ = √π

• sqrt2π = √2π

• sqrt4π = √4π

• sqrthalfπ = √(π / 2)

• invsqrt2 = 1 / √2

• invsqrtπ = 1 / √π

• invsqrt2π = 1 / √2π

• loghalf = log(1 / 2)

• logtwo = log(2)

• logten = log(10)

• logπ = log(π)

• log2π = log(2π)

• log4π = log(4π)

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

This package provides a set of tools for working with tabular data in Julia. Its design and functionality are similar to those of Pandas from Python or data.frame, data.table and dplyr from R, making it a great general purpose data science tool, especially for those coming to Julia from R or Python.

This package contains utilities for setting up documentation generation with Documenter.jl.

This package make loading packages faster, maybe. It supports specifying glue code in packages which will load automatically when another package is loaded, so that explicit dependencies (and long load times) can be avoided.

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.

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).

Showoff provides an interface for consistently formatting an array of n things, e.g. numbers, dates, unitful values. It's used in Gadfly, Plots and Makie to label axes and keys.

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

Crayons is a package that makes it simple to write strings in different colors and styles to terminals. It supports the 16 system colors, both the 256 color and 24 bit true color extensions, and the different text styles available to terminals.

This package implements image show methods suitable for graphical platforms such as IJulia. It is intended to provide convenient inline presentation of greyscale or color images.

This package provides Julia implementation for reading and writing FITS files, based on the cfitsio library.

This package implements methods to take derivatives, gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really) using forward mode automatic differentiation (AD).

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).

This package provides an implementation of an associative container mapping (K,V) pairs via the type IntervalTreeK, V. The type K may be any ordered type.

This package provides an implementation of shifted arrays for Julia.

MutableArithmetics is a Julia package which allows:

• mutable types to implement mutable arithmetics

• algorithms that could exploit mutable arithmetics to exploit them while still being completely generic

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

This package contains types with default field values, keyword constructors and (un-)pack macros. Keyword functions can be slow in Julia, however, the normal positional constructor is also provided and could be used in performance critical code.

The purpose of this package is to allow Julia function calls to be temporarily overloaded for the purpose of testing.