This package provides several functions to manipulate strings with ANSI escape sequences.

This package provides a multivariate polynomials implementation of commutative and non-commutative variables.

This package defines functionality to calculate volume element changes for functions that perform a change of variables (like coordinate transformations).

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 implements OrderedDicts and OrderedSets, which are similar to containers in base Julia. However, during iteration the Ordered* containers return items in the order in which they were added to the collection.

This package provides tools for transcoding data streams which are:

• fast: small overhead and specialized methods

• consistent: basic I/O operations work as expected

• generic: support any I/O objects like files, buffers, pipes, etc.

• extensible: easy definition for new codec to transcode data

This package provides a wrapper for the libXrender library.

This package provides a wrapper for the libxkbfile library.

This package provides a wrapper for the libxcursor library.

ANSIColoredPrinters.jl converts a text qualified by ANSI escape codes to another format.

This package allows a few "forward" definitions for the DataValues.jl package that other packages can utilize for integration without having to take direct dependencies.

This package provides a collection of useful extensions for Julia's built-in docsystem. These are features that are not yet mature enough to be considered for inclusion in Base, or that have sufficiently niche use cases that including them with the default Julia installation is not seen as valuable enough at this time.

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.

This package exports following operations over bit vectors with extremely fast speed while keeping extra memory usage small:

• getindex(bv::IndexableBitVectors, i::Integer): i-th element of bv

• rank(b::Bool, bv::AbstractIndexableBitVector, i::Integer): the number of occurrences of bit b in bv[1:i]

• select(b::Bool, bv::AbstractIndexableBitVector, i::Integer): the index of i-th occurrence of b in bv.

and other shortcuts or types.

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.

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 package provides a wrapper for the libxinerama library.

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

This package provides a wrapper for the xcb-util-wm library.

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

The purpose of this package is partly to extend linear algebra functionality in base to cover generic element types, e.g. BigFloat and Quaternion, and partly to be a place to experiment with fast linear algebra routines written in Julia (except for optimized BLAS).

This package enables the Julia compiler to generate efficient code when running test cases. Test cases are typically run with flags that prevent efficient code generation. This package detects those flags and instead spawns a separate Julia process without the flags in which to run the test cases.

This package provides a wrapper for the wayland-protocols library.

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.