This package provides a minimal String type for Julia that allows for efficient string representation and transfer

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 provides information about the features of the host CPU in Julia.

The @unpack and @pack! macros work to unpack types, modules, and dictionaries.

This package provides string distances in Julia. Distances are defined for AbstractStrings, and any iterator that define length(). The package also defines Distance "modifiers" that can be applied to any distance.

ImageMetadata is a simple package providing utilities for working with images that have metadata attached. For example, you might want to associate an image with the date on which the picture was taken, or an MRI scan with patient data, or an astronomical image with sky coordinates and information about the detector used to acquire the image.

This package calculates approximate derivatives numerically using finite difference.

This module provides a Julia interface to GR, a framework for visualisation applications.

This package provides a method to ensure that arguments to a function conform to a specification.

This package provides the @muladd macro. It automatically converts expressions with multiplications and additions or subtractions to calls with muladd which then fuse via FMA when it would increase the performance of the code. The @muladd macro can be placed on code blocks and it will automatically find the appropriate expressions and nest muladd expressions when necessary. In mixed expressions summands without multiplication will be grouped together and evaluated first but otherwise the order of evaluation of multiplications and additions is not changed.

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.

The goal of RangeArrays is to provide efficient and convenient array data structures where the columns of the arrays are generated (on the fly) by Ranges.

This package provides a Julia interface to the Matplotlib plotting library from Python, and specifically to the matplotlib.pyplot module. PyPlot uses the Julia PyCall package to call Matplotlib directly from Julia with little or no overhead (arrays are passed without making a copy).

ArnoldiMethod.jl provides an iterative method to find a few approximate solutions to the eigenvalue problem in standard form with main goals:

• Having a native Julia implementation of the eigs function that performs as well as ARPACK. With native we mean that its implementation should be generic and support any number type. Currently the partialschur function does not depend on LAPACK, and removing the last remnants of direct calls to BLAS is in the pipeline.

• Removing the dependency of the Julia language on ARPACK. This goal was already achieved before the package was stable enough, since ARPACK moved to a separate repository Arpack.jl.

The VersionParsing package implements flexible parsing of version-number strings into Julia's built-in VersionNumber type, via the vparse(string) function. Unlike the VersionNumber(string) constructor, vparse(string) can handle version-number strings in a much wider range of formats than are encompassed by the semver standard. This is useful in order to support VersionNumber comparisons applied to "foreign" version numbers from external packages.

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.

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 a summary of available CPU features in Julia.

FixedPointNumbers.jl implements fixed-point number types for Julia. A fixed-point number represents a fractional, or non-integral, number. In contrast with the more widely known floating-point numbers, with fixed-point numbers the decimal point doesn't "float": fixed-point numbers are effectively integers that are interpreted as being scaled by a constant factor. Consequently, they have a fixed number of digits (bits) after the decimal (radix) point.

This package provides definitions for common functions that are useful for symbolic expression manipulation in Julia. Its purpose is to provide a shared interface between various symbolic programming packages, for example SymbolicUtils.jl, Symbolics.jl, and Metatheory.jl.

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.

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

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 a Julia wrapper for astronomical library ERFA.