Showing 738 open source projects for "c source code"

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  • 1
    Pkg Julia

    Pkg Julia

    Package manager for the Julia programming language

    Unlike traditional package managers, which install and manage a single global set of packages, Pkg is designed around “environments”: independent sets of packages that can be local to an individual project or shared and selected by name. The exact set of packages and versions in an environment is captured in a manifest file which can be checked into a project repository and tracked in version control, significantly improving reproducibility of projects. If you’ve ever tried to run code you...
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  • 2
    Sweetviz

    Sweetviz

    Visualize and compare datasets, target values and associations

    Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks.
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  • 3
    QuantumClifford.jl

    QuantumClifford.jl

    Clifford circuits, graph states, and other quantum Stabilizer tools

    A Julia package for working with quantum stabilizer states and Clifford circuits that act on them. Graphs states are also supported. The package is already very fast for the majority of common operations, but there are still many low-hanging fruits performance-wise. See the detailed suggested readings & references page for background on the various algorithms.
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  • 4
    Enzyme.jl

    Enzyme.jl

    Julia bindings for the Enzyme automatic differentiator

    This is a package containing the Julia bindings for Enzyme. This is very much a work in progress and bug reports/discussion is greatly appreciated. Enzyme is a plugin that performs automatic differentiation (AD) of statically analyzable LLVM. It is highly-efficient and its ability perform AD on optimized code allows Enzyme to meet or exceed the performance of state-of-the-art AD tools.
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  • 5
    LinearSolve.jl

    LinearSolve.jl

    High-Performance Unified Interface for Linear Solvers in Julia

    LinearSolve.jl is a unified interface for the linear solving packages of Julia. It interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. Performance is key: the current methods are made to be highly performant on scalar and statically sized small problems,...
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  • 6
    Vizzu

    Vizzu

    Library for animated data visualizations and data stories

    Vizzu is a free, open-source Javascript/C++ library utilizing a generic dataviz engine that generates many types of charts and seamlessly animates between them. It can be used to create static charts but more importantly, it is designed for building animated data stories and interactive explorers as Vizzu enables showing different perspectives of the data that the viewers can easily follow due to the animation.
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  • 7
    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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  • 8
    DynamicalSystems.jl

    DynamicalSystems.jl

    Award winning software library for nonlinear dynamics timeseries

    DynamicalSystems.jl is an award-winning Julia software library for nonlinear dynamics and nonlinear time series analysis. To install DynamicalSystems.jl, run import Pkg; Pkg.add("DynamicalSystems"). To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl file. DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high-quality scientific software. All implemented algorithms...
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  • 9
    city-roads

    city-roads

    Visualization of all roads within any city

    city-roads is a data visualization and mapping project that renders street networks of cities as vector paths, offering an interactive, zoomable experience that highlights how cities are stitched together by their road infrastructure. It typically fetches open map data (such as from OpenStreetMap) and then processes that data into geometry suited for rendering in the browser, allowing users to explore intricate road layouts at various scales. The visual style often abstracts away labels and...
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  • 10
    EAGO.jl

    EAGO.jl

    A development environment for robust and global optimization

    EAGO is an open-source development environment for robust and global optimization in Julia. EAGO is a deterministic global optimizer designed to address a wide variety of optimization problems, emphasizing nonlinear programs (NLPs), by propagating McCormick relaxations along the factorable structure of each expression in the NLP. Most operators supported by modern automatic differentiation (AD) packages (e.g., +, sin, cosh) are supported by EAGO and a number of utilities for sanitizing native Julia code and generating relaxations on a wide variety of user-defined functions have been included. ...
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  • 11
    JUDI.jl

    JUDI.jl

    Julia Devito inversion

    JUDI is a framework for large-scale seismic modeling and inversion and is designed to enable rapid translations of algorithms to fast and efficient code that scales to industry-size 3D problems. The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling...
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  • 12
    NCDatasets.jl

    NCDatasets.jl

    Load and create NetCDF files in Julia

    NCDatasets allows one to read and create netCDF files. NetCDF data set and attribute list behave like Julia dictionaries and variables like Julia arrays. This package implements the CommonDataModel.jl interface, which means that the datasets can be accessed in the same way as GRIB files opened with GRIBDatasets.jl.
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  • 13
    MPI.jl

    MPI.jl

    MPI wrappers for Julia

    This is a basic Julia wrapper for the portable message-passing system Message Passing Interface (MPI). Inspiration is taken from mpi4py, although we generally follow the C and not the C++ MPI API. (The C++ MPI API is deprecated.) MPI is based on a single program, multiple data (SPMD) model, where multiple processes are launched running independent programs, which then communicate as necessary via messages. As the main entry point for users, MPI.jl provides a high-level interface which loosely follows the MPI C API and is described in details in the following sections. ...
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  • 14
    SymEngine.jl

    SymEngine.jl

    Julia wrappers of SymEngine

    Julia Wrappers for SymEngine, a fast symbolic manipulation library, written in C++.
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  • 15
    JuliaWorkshop

    JuliaWorkshop

    Intensive Julia workshop that takes you from zero to hero

    This is an intensive workshop for the Julia language, composed out of three 2-hour segments. It targets people already familiar with programming, so that the established basics such as for-loops are skipped through quickly and efficiently. Nevertheless, it assumes only rudimentary programming familiarity and does explain concepts that go beyond the basics. The goal of the workshop is to take you from zero to hero (regarding Julia): even if you know nothing about Julia, by the end you should...
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  • 16
    DynamicHMC

    DynamicHMC

    Implementation of robust dynamic Hamiltonian Monte Carlo methods

    Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent...
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  • 17
    GDAL.jl

    GDAL.jl

    Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library

    Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly.
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  • 18
    HiGHS.jl

    HiGHS.jl

    Julia wrapper for the HiGHS solver

    HiGHS.jl is a wrapper for the HiGHS solver.
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  • 19
    Clustering.jl

    Clustering.jl

    A Julia package for data clustering

    Methods for data clustering and evaluation of clustering quality.
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  • 20
    errsole.js

    errsole.js

    Collect, Store, and Visualize Logs with a Single Module

    Errsole is an open-source logger for Node.js. It has a built-in web dashboard to view, filter, and search your app logs.
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  • 21
    Mapbox GL JS

    Mapbox GL JS

    Interactive, thoroughly customizable maps in the browser

    ...To get started with GL JS or any of our other building blocks, sign up for a Mapbox account. In addition to GL JS, this repository contains code, issues, and test fixtures that are common to both GL JS and the native SDKs. Mapbox GL JS v2 enables 3D mapping with elevated terrain, customizable skies and atmospheric lighting, a new camera, and performance enhancements.
    Downloads: 1 This Week
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  • 22
    Digital Earth Australia notebooks

    Digital Earth Australia notebooks

    Repository for Digital Earth Australia Jupyter Notebooks

    The knowledge hub brings together information about Digital Earth Australia’s products and services, allowing you to utilize our free and open-source satellite imagery archive. Browse our catalog of data products to find supporting information and ways to access the data. The Digital Earth Australia notebooks and tools repository (dea-notebooks) hosts Jupyter Notebooks, Python scripts and workflows for analyzing Digital Earth Australia (DEA) satellite data and derived products. This...
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  • 23
    plotly

    plotly

    An interactive graphing library for R

    This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of...
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  • 24
    AAChartKit

    AAChartKit

    Modern declarative data visualization chart framework

    AAChartKit is an elegant and friendly (user-friendly && enviroment-friendly) chart framework for iOS, based on the open source Highcharts JS libraries. AAChartKit is extremely powerful, easy to configure and a pleasure to use. Currently AAChartKit includes support for the following chart types: column chart, bar chart, area chart, area spline chart, line chart, spline chart, radar chart, polar chart, pie chart, bubble chart, pyramid chart, funnel chart, column range and area range chart....
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  • 25
    LossFunctions.jl

    LossFunctions.jl

    Julia package of loss functions for machine learning

    This package represents a community effort to centralize the definition and implementation of loss functions in Julia. As such, it is a part of the JuliaML ecosystem. The sole purpose of this package is to provide an efficient and extensible implementation of various loss functions used throughout Machine Learning (ML). It is thus intended to serve as a special purpose back-end for other ML libraries that require losses to accomplish their tasks. To that end we provide a considerable amount...
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