Showing 8 open source projects for "numerical integration"

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  • 1
    QuadGK.jl

    QuadGK.jl

    adaptive 1d numerical Gauss–Kronrod integration in Julia

    This package provides support for one-dimensional numerical integration in Julia using adaptive Gauss-Kronrod quadrature. The code was originally part of Base Julia. It supports the integration of arbitrary numeric types, including arbitrary-precision (BigFloat), and even the integration of arbitrary normed vector spaces. The package provides three basic functions: quadgk, gauss, and kronrod. quadgk performs the integration, gauss computes Gaussian quadrature points and weights for integrating over the interval [a, b], and kronrod computes Kronrod points, weights, and embedded Gaussian quadrature weights for integrating over [-1, 1].
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  • 2
    Calculus.jl

    Calculus.jl

    Calculus functions in Julia

    The Calculus package provides tools for working with the basic calculus operations of differentiation and integration. You can use the Calculus package to produce approximate derivatives by several forms of finite differencing or to produce exact derivatives using symbolic differentiation. You can also compute definite integrals by different numerical methods.
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  • 3
    SymbolicNumericIntegration.jl

    SymbolicNumericIntegration.jl

    SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals

    SymbolicNumericIntegration.jl is a hybrid symbolic/numerical integration package that works on the Julia Symbolics expressions.
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  • 4
    Integrals.jl

    Integrals.jl

    A common interface for quadrature and numerical integration

    Integrals.jl is an instantiation of the SciML common IntegralProblem interface for the common numerical integration packages of Julia, including both those based upon quadrature as well as Monte-Carlo approaches. By using Integrals.jl, you get a single predictable interface where many of the arguments are standardized throughout the various integrator libraries. This can be useful for benchmarking or for library implementations since libraries that internally use a quadrature can easily accept an integration method as an argument.
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  • 5
    HCubature.jl

    HCubature.jl

    Pure-Julia multidimensional h-adaptive integration

    ...You can integrate real, complex, and matrix-valued integrands, for example. Note that HCubature assumes that your function f(x) can be computed at arbitrary points in the integration domain. (This is the ideal way to do numerical integration.) If you instead have f(x) precomputed at a fixed set of points, such as a Cartesian grid, you will need to use some other method (e.g. Trapz.jl for a multidimensional trapezoidal rule).
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  • 6
    Reduce.jl

    Reduce.jl

    Symbolic parser for Julia language term rewriting using REDUCE algebra

    REDUCE is a portable general-purpose computer algebra system. It is a system for doing scalar, vector and matrix algebra by computer, which also supports arbitrary precision numerical approximation and interfaces to gnuplot to provide graphics. It can be used interactively for simple calculations (as illustrated in the screenshot below) but also provides a full programming language, with a syntax similar to other modern programming languages. REDUCE supports alternative user interfaces...
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  • 7
    Measurements.jl

    Measurements.jl

    Error propagation calculator and library for physical measurements

    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. Physical measures are typically reported with an error, a quantification of the uncertainty of the accuracy of the measurement. Whenever you perform mathematical operations involving these quantities you have also to propagate the uncertainty, so that the resulting number will also have an attached error to quantify the confidence about its accuracy. ...
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  • 8
    JuliaCall for Seamless Integration of R
    Package JuliaCall is an R interface to Julia, which is a high-level, high-performance dynamic programming language for numerical computing. Below is an image for Mandelbrot set. JuliaCall brings more than 100 times speedup of the calculation.
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