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

This package provides an interface to line search algorithms implemented in Julia.

This package provides a wrapper for the libmount library from util-linux.

This package provides manually managed memory buffers backed by NTuples in Julia.

This package provides a math library with extended precision floats and complex types.

This package generates formatted output from timings made in different sections of a program.

This package has the purpose to print data in matrices in a human-readable format.

This package provides an alternative interface for dictionaries in Julia, for improved productivity and performance.

This package provides a pooled representation of arrays for purposes of compression when there are few unique elements.

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

This is a small package to make it easier to type LaTeX equations in string literals in the Julia language.

This package provides a fast, extensible progress bar for Julia. This can help users track the progress of long-running tasks.

OffsetArrays.jl provides Julia users with arrays that have arbitrary indices, similar to those found in some other programming languages like Fortran.

FoldingTrees implements a dynamic tree structure in which some nodes may be "folded," i.e., marked to avoid descent among that node's children. It also supports interactive text menus based on folding trees.

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.

SnoopCompile observes the Julia compiler, causing it to record the functions and argument types it's compiling. From these lists of methods, you can generate lists of precompile directives that may reduce the latency between loading packages.

This package provides a framework for implementing statically sized arrays in Julia, using the abstract type StaticArraySize,T,N <: AbstractArrayT,N. Subtypes of StaticArray will provide fast implementations of common array and linear algebra operations.

This package is intended to implement a "minimal" foundation for intervals upon which other packages might build. In particular, we encourage type-piracy for the reason that only one interval package can unambiguously define the .. and ± operators.

Measurements.jl is an error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration. The linear error propagation theory is employed to propagate the errors.

This package provides the @OptionalData macro and the corresponding OptData type which is a thin wrapper around a nullable value (of type UnionT, Nothing where T). It allows you to load and access globally available data at runtime in a type-stable way.

This package implements a trait-based framework for describing array layouts such as column major, row major, etc. that can be dispatched to appropriate BLAS or optimised Julia linear algebra routines. This supports a much wider class of matrix types than Julia's in-built StridedArray.

This package allows multiple FFT packages to co-exist with the same underlying fft(x) and plan_fft(x) interface. It is mainly not intended to be used directly. Instead, developers of packages that implement FFTs (such as FFTW.jl or FastTransforms.jl) extend the types/functions defined in AbstractFFTs.

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 introduces the type StructArray which is an AbstractArray whose elements are struct (for example NamedTuples, or ComplexF64, or a custom user defined struct). While a StructArray iterates structs, the layout is column based (meaning each field of the struct is stored in a separate Array).