Showing 2061 open source projects for "data visualization, research"

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  • 1
    Metal.jl

    Metal.jl

    Metal programming in Julia

    With Metal.jl it's possible to program GPUs on macOS using the Metal programming framework. The package is a work in progress. There are bugs, functionality is missing, and performance hasn't been optimized. Expect to have to make changes to this package if you want to use it. PRs are very welcome. These requirements are fairly strict, and are due to our limited development resources (manpower, hardware). Technically, they can be relaxed. If you are interested in contributing to this, see...
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  • 2
    SciMLBase.jl

    SciMLBase.jl

    The Base interface of the SciML ecosystem

    SciMLBase.jl is the core interface definition of the SciML ecosystem. It is a low-dependency library made to be depended on by the downstream libraries to supply the common interface and allow for the interexchange of mathematical problems. The SciML common interface ties together the numerical solvers of the Julia package ecosystem into a single unified interface. It is designed for maximal efficiency and parallelism, while incorporating essential features for large-scale scientific machine...
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  • 3
    IntervalRootFinding.jl

    IntervalRootFinding.jl

    Find all roots of a function in a guaranteed way with Julia

    This package provides guaranteed methods for finding roots of functions, i.e. solutions to the equation f(x) == 0 for a function f. To do so, it uses methods from interval analysis, using interval arithmetic from the IntervalArithmetic.jl package by the same authors. The basic function is roots. A standard Julia function and an interval is provided and the roots function return a list of intervals containing all roots of the function located in the starting interval.
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  • 4
    DataFramesMeta.jl

    DataFramesMeta.jl

    Metaprogramming tools for DataFrames

    Metaprogramming tools for DataFrames.jl objects to provide more convenient syntax. DataFrames.jl has the functions select, transform, and combine, as well as the in-place select! and transform! for manipulating data frames. DataFramesMeta.jl provides the macros @select, @transform, @combine, @select!, and @transform! to mirror these functions with more convenient syntax. Inspired by dplyr in R and LINQ in C#.
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  • 5
    Vue Clock Visualizer

    Vue Clock Visualizer

    Simple clock component written in Vue

    Simple clock component is written in Vue.
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  • 6
    awesome-single-cell

    awesome-single-cell

    Community-curated list of software packages and data resources

    Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc. List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Rapid, accurate and memory-frugal preprocessing of single-cell and single-nucleus RNA-seq data. Find bimodal, unimodal, and multimodal features in your data. Ascend is an R package comprised of fast, streamlined analysis functions optimized to...
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  • 7
    TimeZones.jl

    TimeZones.jl

    IANA time zone database access for the Julia programming language

    IANA time zone database access for the Julia programming language. TimeZones.jl extends the Date/DateTime support for Julia to include a new time zone-aware TimeType: ZonedDateTime.
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  • 8
    FrankWolfe.jl

    FrankWolfe.jl

    Julia implementation for various Frank-Wolfe and Conditional Gradient

    This package is a toolbox for Frank-Wolfe and conditional gradient algorithms. Frank-Wolfe algorithms were designed to solve optimization problems where f is a differentiable convex function and C is a convex and compact set. They are especially useful when we know how to optimize a linear function over C in an efficient way.
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  • 9
    OptimalTransport.jl

    OptimalTransport.jl

    Optimal transport algorithms for Julia

    This package provides some Julia implementations of algorithms for computational optimal transport, including the Earth-Mover's (Wasserstein) distance, Sinkhorn algorithm for entropically regularized optimal transport as well as some variants or extensions. Notably, OptimalTransport.jl provides GPU acceleration through CUDA.jl and NNlibCUDA.jl.
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  • 10
    ProbNumDiffEq.jl

    ProbNumDiffEq.jl

    Probabilistic Numerical Differential Equation solvers via Bayesian fil

    ProbNumDiffEq.jl provides probabilistic numerical ODE solvers to the DifferentialEquations.jl ecosystem. The implemented ODE filters solve differential equations via Bayesian filtering and smoothing. The filters compute not just a single point estimate of the true solution, but a posterior distribution that contains an estimate of its numerical approximation error.
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  • 11
    ImplicitDifferentiation.jl

    ImplicitDifferentiation.jl

    Automatic differentiation of implicit functions

    ImplicitDifferentiation.jl is a package for automatic differentiation of functions defined implicitly, i.e., forward mappings. Those for which automatic differentiation fails. Reasons can vary depending on your backend, but the most common include calls to external solvers, mutating operations or type restrictions. Those for which automatic differentiation is very slow. A common example is iterative procedures like fixed point equations or optimization algorithms.
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  • 12
    JavaCall.jl

    JavaCall.jl

    Call Java from Julia

    Call Java programs from Julia. Julia 1.3.0 through Julia 1.6.2 are tested and guaranteed to work on Linux, macOS, and Windows via continuous integration. Julia 1.6.2 and newer should work on Linux and Windows. The JULIA_COPY_STACKS environment variable should be set to 1 on macOS and Linux, but not Windows.
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  • 13
    LatticeQCD.jl

    LatticeQCD.jl

    A native Julia code for lattice QCD with dynamical fermions in 4D

    This code enables you to perform lattice QCD calculations! A native Julia code for Lattice QCD.
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  • 14
    FromFile.jl

    FromFile.jl

    Julia enhancement proposal (Julep) for implicit per file module

    This package exports a macro @from, which can be used to import objects from files. The hope is that you will never have to write include again. FromFile is a Julia Language package. To install FromFile, please open Julia's interactive session (known as REPL) and press ] key in the REPL to use the package mode.
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  • 15
    CompatHelper.jl

    CompatHelper.jl

    Automatically update the [compat] entries for your Julia dependencies

    CompatHelper.jl is a Julia package which keeps your Project.toml [compat] entries up to date.
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  • 16
    LinearOperators.jl

    LinearOperators.jl

    Linear Operators for Julia

    Operators behave like matrices (with some exceptions - see below) but are defined by their effect when applied to a vector. They can be transposed, conjugated, or combined with other operators cheaply. The costly operation is deferred until multiplied with a vector.
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  • 17
    PowerSimulationsDynamics.jl

    PowerSimulationsDynamics.jl

    Julia package to run Dynamic Power System simulations

    PowerSimulationsDynamics.jl is a Julia package for power system modeling and simulation of Power Systems dynamics.
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  • 18
    VoronoiFVM.jl

    VoronoiFVM.jl

    Solution of nonlinear multiphysics partial differential equations

    Solver for coupled nonlinear partial differential equations (elliptic-parabolic conservation laws) based on the Voronoi finite volume method. It uses automatic differentiation via ForwardDiff.jl and DiffResults.jl to evaluate user functions along with their jacobians and calculate derivatives of solutions with respect to their parameters.
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  • 19
    CausalInference.jl

    CausalInference.jl

    Causal inference, graphical models and structure learning in Julia

    Julia package for causal inference and analysis, graphical models and structure learning. This package contains code for the PC algorithm and the extended FCI algorithm, the score based greedy equivalence search (GES) algorithm, the Bayesian Causal Zig-Zag sampler and a function suite for adjustment set search.
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  • 20
    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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  • 21
    MAT.jl

    MAT.jl

    Julia module for reading MATLAB files

    Julia module for reading MATLAB files. Read and write MATLAB files in Julia. This library can read MATLAB .mat files, both in the older v4/v5/v6/v7 format, as well as the newer v7.3 format.
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  • 22
    FastGaussQuadrature.jl

    FastGaussQuadrature.jl

    Julia package for Gaussian quadrature

    A Julia package to compute n-point Gauss quadrature nodes and weights to 16-digit accuracy and in O(n) time. So far the package includes gausschebyshev(), gausslegendre(), gaussjacobi(), gaussradau(), gausslobatto(), gausslaguerre(), and gausshermite(). This package is heavily influenced by Chebfun.
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  • 23
    Oxygen.jl

    Oxygen.jl

    A breath of fresh air for programming web apps in Julia

    A breath of fresh air for programming web apps in Julia. Oxygen is a micro-framework built on top of the HTTP.jl library. Breathe easy knowing you can quickly spin up a web server with abstractions you're already familiar with.
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  • 24
    Parameters.jl

    Parameters.jl

    Types w/ default field values, keyword constructors, (un-)pack macros

    This is a package I use to handle numerical-model parameters, thus the name. However, it should be useful otherwise too.
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  • 25
    JuliaConnectoR

    JuliaConnectoR

    A functionally oriented interface for calling Julia from R

    This R-package provides a functionally oriented interface between R and Julia. The goal is to call functions from Julia packages directly as R functions. Julia functions imported via the JuliaConnectoR can accept and return R variables. It is also possible to pass R functions as arguments in place of Julia functions, which allows callbacks from Julia to R. From a technical perspective, R data structures are serialized with an optimized custom streaming format, sent to a (local) Julia TCP...
    Downloads: 1 This Week
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