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This is a twin package to ImageCore with functions that are used among many of the packages in JuliaImages. The main purpose of this package is to reduce unnecessary compilation overhead from external dependencies.
This package provides Data types and methods for common operations with biological sequences, including DNA, RNA, and amino acid sequences.
This package determines tabular file formats based on file extensions. It is intended to be the base both for TableIO.jl and for the Pluto.jl tabular data import functionality.
AxisAlgorithms is a collection of filtering and linear algebra algorithms for multidimensional arrays. For algorithms that would typically apply along the columns of a matrix, you can instead pick an arbitrary axis (dimension).
This Julia package provides the adapt(T, x) function acts like convert(T, x), but without the restriction of returning a T. This allows you to "convert" wrapper types like Adjoint to be GPU compatible without throwing away the wrapper.
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.
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 @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.
FuzzyCompletions provides fuzzy completions for a Julia runtime session.
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 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.
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 support for image resizing, image rotation, and other spatial transformations of arrays.
This package contains the underlying query operators that are exposed to users in Query.jl.
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).
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.
This package provides tools for working with categorical variables, both with unordered (nominal variables) and ordered categories (ordinal variables), optionally with missing values.
Common functional iterator patterns (formerly Iterators.jl).
The purpose of this package is to provide test problems for JuliaNLSolvers packages.
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.
A Julia package to contain non-standard matrix factorizations. At the moment it implements the QL, RQ, and UL factorizations, a combined Cholesky factorization with inverse, and polar decompositions. In the future it may include other factorizations such as the LQ factorization.
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.
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 provides a parser for Julia code.