Showing 656 open source projects for "can="

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  • 1
    ClimateTools.jl

    ClimateTools.jl

    Climate science package for Julia

    ...To gain maximum performance, use (bash shell Linux/MacOSX) export JULIA_NUM_THREADS=n, where n is the number of threads. To get an idea of the number of threads you can use type (in Julia) Sys.THREADS. This is especially useful for bias correction.
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  • 2
    Wavelets.jl

    Wavelets.jl

    A Julia package for fast discrete wavelet transforms and utilities

    ...Filters are included for the following types: Haar, Daubechies, Coiflet, Symmlet, Battle-Lemarie, Beylkin, Vaidyanathan. 2nd generation wavelets by lifting (periodic and general type including orthogonal and biorthogonal). Included lifting schemes are currently only for Haar and Daubechies (under development). A new lifting scheme can be easily constructed by users. The current implementation of the lifting transforms is 2x faster than the filter transforms. Thresholding, best basis, and denoising functions, e.g. TI denoising by cycle spinning, best basis for WPT, noise estimation, and matching pursuit.
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  • 3
    FFTW.jl

    FFTW.jl

    Julia bindings to the FFTW library for fast Fourier transforms

    This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded for the current project, and other projects that wish to use MKL for FFTs should also set that same preference. Note further that MKL provides only a subset of the functionality provided by FFTW.
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  • 4
    HDF5.jl

    HDF5.jl

    Save and load data in the HDF5 file format from Julia

    ...In HDF5, a "group" is analogous to a directory, a "dataset" is like a file. HDF5 also uses "attributes" to associate metadata with a particular group or dataset. HDF5 uses ASCII names for these different objects, and objects can be accessed by Unix-like pathnames, e.g., "/sample1/tempsensor/firsttrial" for a top-level group "sample1", a subgroup "tempsensor", and a dataset "firsttrial". For simple types (scalars, strings, and arrays), HDF5 provides sufficient metadata to know how each item is to be interpreted. For example, HDF5 encodes that a given block of bytes is to be interpreted as an array of Int64, and represents them in a way that is compatible across different computing architectures. ...
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  • 5
    Mixed-effects models in Julia

    Mixed-effects models in Julia

    A Julia package for fitting (statistical) mixed-effects models

    This package defines linear mixed models (LinearMixedModel) and generalized linear mixed models (GeneralizedLinearMixedModel). Users can use the abstraction for statistical model API to build, fit (fit/fit!), and query the fitted models. A mixed-effects model is a statistical model for a response variable as a function of one or more covariates. For a categorical covariate the coefficients associated with the levels of the covariate are sometimes called effects, as in "the effect of using Treatment 1 versus the placebo". ...
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  • 6
    Luxor

    Luxor

    Simple drawings using vector graphics; Cairo "for tourists!"

    Luxor is a Julia package for drawing simple static 2D vector graphics. It provides basic drawing functions and utilities for working with shapes, polygons, clipping masks, PNG and SVG images, turtle graphics, and simple animations. The focus of Luxor is on simplicity and ease of use: it should be easier to use than plain Cairo.jl, with shorter names, fewer underscores, default contexts, and simplified functions. For more complex and sophisticated graphics in 2D and 3D, Makie.jl is the best...
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  • 7
    Optimization.jl

    Optimization.jl

    Mathematical Optimization in Julia

    ...It allows you to choose an Automatic Differentiation (AD) backend by simply passing an argument to indicate the package to use and automatically generates the efficient derivatives of the objective and constraints while giving you the flexibility to switch between different AD engines as per your problem. Additionally, Optimization.jl takes care of passing problem-specific information to solvers that can leverage it such as the sparsity pattern of the hessian or constraint jacobian and the expression graph.
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  • 8
    Makie

    Makie

    Interactive data visualizations and plotting in Julia

    Makie is an interactive data visualization and plotting ecosystem for the Julia programming language, available on Windows, Linux, and Mac. The backend packages GLMakie, WGLMakie, CairoMakie and RPRMakie add different functionalities: You can use Makie to interactively explore your data and create simple GUIs in native Windows or web browsers, export high-quality vector graphics or even raytrace with physically accurate lighting. Choose one or more backend packages: GLMakie (interactive OpenGL in native OS windows), WGLMakie (interactive WebGL in browsers, IDEs, notebooks), CairoMakie (static 2D vector graphics and images), and RPRMakie (raytracing). ...
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  • 9
    deck.gl

    deck.gl

    WebGL2 powered visualization framework

    deck.gl is designed to simplify high-performance, WebGL-based visualization of large data sets. Users can quickly get impressive visual results with minimal effort by composing existing layers, or leveraging deck.gl's extensible architecture to address customer needs. deck.gl maps data (usually an array of JSON objects) into a stack of visual layers - e.g. icons, polygons, texts; and look at them with views: e.g. map, first-person, orthographic. deck.gl handles a number of challenges out of the box. ...
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  • 10
    Charts.css

    Charts.css

    Open source CSS framework for data visualization

    ...Each component offers several CSS classes and CSS variables to customize your style. The key feature is the ability to customize everything using basic CSS. Frontend developers can target any HTML element and customize it. This philosophical guideline is what makes the framework so flexible, easy, and fun to use.
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  • 11
    ProbabilisticCircuits.jl

    ProbabilisticCircuits.jl

    Probabilistic Circuits from the Juice library

    This module provides a Julia implementation of Probabilistic Circuits (PCs), tools to learn structure and parameters of PCs from data, and tools to do tractable exact inference with them. Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units)....
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  • 12
    Reduce.jl

    Reduce.jl

    Symbolic parser for Julia language term rewriting using REDUCE algebra

    ...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 including Run-REDUCE, TeXmacs and GNU Emacs. REDUCE (and its complete source code) is available free of charge for most common computing systems, in some cases in more than one version for the same machine. ...
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  • 13
    ParallelStencil.jl

    ParallelStencil.jl

    Package for writing high-level code for parallel stencil computations

    ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C / HIP can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl or AMDGPU.jl GPU Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding GPU Array programming implementation; in absolute terms, it reached 70% of the theoretical upper performance bound of the used Nvidia P100 GPU, as defined by the effective throughput metric, T_eff. ...
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  • 14
    CxxWrap

    CxxWrap

    Package to make C++ libraries available in Julia

    This package aims to provide a Boost. Python-like wrapping for C++ types and functions to Julia. The idea is to write the code for the Julia wrapper in C++, and then use a one-liner on the Julia side to make the wrapped C++ library available there. The mechanism behind this package is that functions and types are registered in C++ code that is compiled into a dynamic library. This dynamic library is then loaded into Julia, where the Julia part of this package uses the data provided through a...
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  • 15
    ReinforcementLearning.jl

    ReinforcementLearning.jl

    A reinforcement learning package for Julia

    A collection of tools for doing reinforcement learning research in Julia. Provide elaborately designed components and interfaces to help users implement new algorithms. Make it easy for new users to run benchmark experiments, compare different algorithms, and evaluate and diagnose agents. Facilitate reproducibility from traditional tabular methods to modern deep reinforcement learning algorithms. Make it easy for new users to run benchmark experiments, compare different algorithms, and...
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  • 16
    Go Recipes

    Go Recipes

    Collection of handy tools for Go projects

    ...Use to find unexpected dependencies or visualize the project. Works best for a small number of packages, for large projects use grep to narrow down subgraph. Collect all the licenses or check if you can use the project for example in a proprietary or commercial environment. Tell Go compiler which versions of upstreams to include in your build. Tell all users of your module how to deal with versions of your module.
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  • 17
    LIBSVM.jl

    LIBSVM.jl

    LIBSVM bindings for Julia

    ...Supports all LIBSVM models: classification C-SVC, nu-SVC, regression: epsilon-SVR, nu-SVR and distribution estimation: one-class SVM. Model objects are represented by Julia-type SVM which gives you easy access to model features and can be saved e.g. as JLD file.
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  • 18
    Excalidraw MCP

    Excalidraw MCP

    Fast and streamable Excalidraw MCP App

    ...Its design supports fast, streamable rendering with smooth viewport control and optional fullscreen editing so that diagrams feel live and fluid as they evolve. Users can deploy it locally or via services like Vercel, then configure their MCP host to point at the Excalidraw-MCP endpoint, so prompts like “draw an architecture diagram” yield immediate visual results within chat.
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  • 19
    visx

    visx

    Visualization components

    ...As you start using visualization primitives, you’ll end up building your own charting library that’s optimized for your use case. You’re in control. And most importantly, it’s just React. If you know React, you can make visualizations. It’s all the same standard APIs and familiar patterns. visx should feel at home in any React codebase.
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  • 20
    ArgParse.jl

    ArgParse.jl

    Package for parsing command-line arguments to Julia programs

    ArgParse.jl is a package for parsing command-line arguments to Julia programs.
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  • 21
    Comonicon

    Comonicon

    Your best CLI generator in JuliaLang

    Roger's magic book for command line interfaces.
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  • 22
    Maxima -- GPL CAS based on DOE-MACSYMA

    Maxima -- GPL CAS based on DOE-MACSYMA

    Computer Algebra System written in Common Lisp

    ...Executables can be downloaded for Windows, Mac, Linux, and Android; source code is also available. An active community maintains and extends the system. Website: https://maxima.sourceforge.io Additional add-on packages for Maxima can be found at: https://github.com/maxima-project-on-github/maxima-packages
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    Downloads: 3,808 This Week
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  • 23
    Jmol

    Jmol

    An interactive viewer for three-dimensional chemical structures.

    ...Jmol/JSmol is a molecular viewer for 3D chemical structures that runs in four independent modes: an HTML5-only web application utilizing jQuery, a Java applet, a stand-alone Java program (Jmol.jar), and a "headless" server-side component (JmolData.jar). Jmol can read many file types, including PDB, CIF, SDF, MOL, PyMOL PSE files, and Spartan files, as well as output from Gaussian, GAMESS, MOPAC, VASP, CRYSTAL, CASTEP, QuantumEspresso, VMD, and many other quantum chemistry programs. Files can be transferred directly from several databases, including RCSB, EDS, NCI, PubChem, and MaterialsProject. ...
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    Downloads: 727 This Week
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  • 24
    JLD.jl

    JLD.jl

    Saving and loading julia variables while preserving native types

    ...By comparison with "plain" HDF5, JLD files automatically add attributes and naming conventions to preserve type information for each object. For lossless storage of arbitrary Julia objects, the only other complete solution appears to be Julia's serializer, which can be accessed via the serialize and deserialize commands. However, because the serializer is also used for inter-process communication, long-term backward compatibility is currently uncertain. (The JLDArchives repository exists to test the compatibility of older JLD file formats.) If you choose to save data using the serializer, please use the file extension .jls to distinguish the files from .jld files.
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  • 25
    Viking GPS data editor and analyzer

    Viking GPS data editor and analyzer

    Viking is a free/open source program to manage GPS data

    Viking is a free/open source program to manage GPS data. You can import, plot and create tracks, routes and waypoints, show OSM, Bing Aerial and other maps, geotag images, create routes using OSRM, see real-time GPS position (not in Windows), make maps using Mapnik (not in Windows), control items, etc. It is written in mostly in C (with some C++) & the GTK+3 toolkit. Viking is currently dual managed - with a corresponding Github presence at: https://github.com/viking-gps/viking Where you may find it easier to view the code and raise issues there too.
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    Downloads: 286 This Week
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