Showing 50 open source projects for "bns-tools"

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  • 1
    MacroTools.jl

    MacroTools.jl

    MacroTools provides a library of tools for working with Julia code

    MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system and code-walking tools that let you do deep transformations of code in a few lines. See the docs for more info.
    Downloads: 6 This Week
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  • 2
    ChaosTools.jl

    ChaosTools.jl

    Tools for the exploration of chaos and nonlinear dynamics

    A Julia module that offers various tools for analyzing nonlinear dynamics and chaotic behavior. It can be used as a standalone package, or as part of DynamicalSystems.jl. All further information is provided in the documentation, which you can either find online or build locally by running the docs/make.jl file. ChaosTools.jl is the jack-of-all-trades package of the DynamicalSystems.jl library: methods that are not extensive enough to be a standalone package are added here.
    Downloads: 7 This Week
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  • 3
    MIRT.jl

    MIRT.jl

    MIRT: Michigan Image Reconstruction Toolbox (Julia version)

    MIRT.jl is a collection of Julia functions for performing image reconstruction and solving related inverse problems. It is very much still under construction, although there are already enough tools to solve useful problems like compressed sensing MRI reconstruction. Trying the demos is a good way to get started. The documentation is even more still under construction.
    Downloads: 7 This Week
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  • 4
    ExponentialUtilities.jl

    ExponentialUtilities.jl

    Fast and differentiable implementations of matrix exponentials

    ExponentialUtilities is a package of utility functions for matrix functions of exponential type, including functionality for the matrix exponential and phi-functions. These methods are more numerically stable, generic (thus support a wider range of number types), and faster than the matrix exponentiation tools in Julia's Base. The tools are used by the exponential integrators in OrdinaryDiffEq. The package has no external dependencies, so it can also be used independently.
    Downloads: 7 This Week
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  • 5
    GMT.jl

    GMT.jl

    Generic Mapping Tools Library Wrapper for Julia

    The Generic Mapping Tools, GMT, is an open source collection of tools for manipulating geographic and Cartesian data sets (including filtering, trend fitting, gridding, projecting, etc.) and producing PostScript illustrations ranging from simple x–y plots via contour maps to artificially illuminated surfaces and 3D perspective views. This link will take you to an impressive collection of figures made with GMT.
    Downloads: 5 This Week
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  • 6
    Clang.jl

    Clang.jl

    C binding generator and Julia interface to libclang

    ...The libclang API documentation provides background on the functionality available through libclang, and thus through the Julia wrapper. The repository also hosts related tools built on top of libclang functionality.
    Downloads: 11 This Week
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  • 7
    CImGui

    CImGui

    Julia wrapper for cimgui

    This package provides a Julia language wrapper for cimgui: a thin c-api wrapper programmatically generated for the excellent C++ immediate mode gui Dear ImGui. Dear ImGui is mainly for creating content creation tools and visualization / debug tools. You could browse Gallery to get an idea of its use cases.
    Downloads: 10 This Week
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  • 8
    InteractiveViz.jl

    InteractiveViz.jl

    Interactive visualization tools for Julia

    Julia already has a rich set of plotting tools in the form of the Plots and Makie ecosystems, and various backends for these. So why another plotting package? InteractiveViz is not a replacement for Plots or Makie, but rather a graphics pipeline system developed on top of Makie. It has a few objectives. To provide a simple API to visualize large or possibly infinite datasets (tens of millions of data points) easily.
    Downloads: 8 This Week
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  • 9
    DSGE.jl

    DSGE.jl

    Solve and estimate Dynamic Stochastic General Equilibrium models

    DSGE.jl is a Julia package developed by the Federal Reserve Bank of New York for estimating and analyzing dynamic stochastic general equilibrium (DSGE) models. It provides tools for Bayesian estimation, filtering, forecasting, and model comparison, supporting both academic research and policy applications. DSGE.jl includes pre-configured models used by central banks and offers extensibility for custom macroeconomic modeling.
    Downloads: 9 This Week
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  • 10
    FourierFlows.jl

    FourierFlows.jl

    Tools for building fast, hackable, pseudospectral equation solvers

    This software provides tools for partial differential equations on periodic domains using Fourier-based pseudospectral methods. A central intent of the software's design is also to provide a framework for writing new, fast solvers for new physical problems. The code is written in Julia.
    Downloads: 6 This Week
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  • 11
    Manopt.jl

    Manopt.jl

    Optimization on Manifolds in Julia

    ...A framework to implement arbitrary optimization algorithms on Riemannian Manifolds. Library of optimization algorithms on Riemannian manifolds. Easy-to-use interface for (debug) output and recording values during an algorithm run. Several tools to investigate the algorithms, gradients, and optimality criteria.
    Downloads: 7 This Week
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  • 12
    Enzyme.jl

    Enzyme.jl

    Julia bindings for the Enzyme automatic differentiator

    ...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.
    Downloads: 8 This Week
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  • 13
    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.
    Downloads: 7 This Week
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  • 14
    DataFrames.jl

    DataFrames.jl

    In-memory tabular data in Julia

    ...It provides a familiar, flexible, and efficient interface for handling datasets, making it easy to load, manipulate, join, and analyze structured data. With syntax inspired by data frames in R and pandas in Python, it offers intuitive tools while taking advantage of Julia’s speed and type system. The package is actively maintained by the JuliaData community, with contributions from over 200 developers worldwide. It is widely used for data science, research, and production applications, supported by extensive documentation, tutorials, and a free Julia Academy course. ...
    Downloads: 7 This Week
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  • 15
    ChainRulesCore

    ChainRulesCore

    AD-backend agnostic system defining custom forward and reverse rules

    ...This will allow your package to be used with ChainRules.jl, which aims to provide a variety of common utilities that can be used by downstream automatic differentiation (AD) tools to define and execute forward-, reverse-, and mixed-mode primitives.
    Downloads: 10 This Week
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  • 16
    ClimateTools.jl

    ClimateTools.jl

    Climate science package for Julia

    Climate analysis tools in Julia. ClimateTools.jl is a collection of commonly-used tools in Climate science. Basics of climate field analysis are covered, with some forays into exploratory techniques associated with climate scenario design. The package is aimed to ease the typical steps of analysis of climate models outputs and gridded datasets (support for weather stations is a work-in-progress).
    Downloads: 8 This Week
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  • 17
    DynamicHMC

    DynamicHMC

    Implementation of robust dynamic Hamiltonian Monte Carlo methods

    ...Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent of coding a (log) posterior density in Julia. This approach allows the use of standard tools like profiling and benchmarking to optimize its performance.
    Downloads: 5 This Week
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  • 18
    Gridap.jl

    Gridap.jl

    Grid-based approximation of partial differential equations in Julia

    ...It also provides methods for time integration. Gridap is extensible and modular. One can implement new FE spaces, new reference elements, use external mesh generators, linear solvers, post-processing tools, etc. See, e.g., the list of available Gridap plugins.
    Downloads: 6 This Week
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  • 19
    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). ...
    Downloads: 6 This Week
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  • 20
    CategoricalArrays.jl

    CategoricalArrays.jl

    Arrays for working with categorical data

    This package provides tools for working with categorical variables, both with unordered (nominal variables) and ordered categories (ordinal variables), optionally with missing values.
    Downloads: 5 This Week
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  • 21
    FileTrees.jl

    FileTrees.jl

    Parallel file processing made easy

    ...Read a directory structure as a Julia data structure, (lazy-)load the files, apply map and reduce operations on the data while not exceeding available memory if possible. Make up a file tree in memory, create some data to go with each file (in parallel), write the tree to disk (in parallel). FileTrees is a set of tools to lazy-load, process and save file trees. Built-in parallelism allows you to max out all threads and processes that Julia is running with. Files and subtrees in a file tree can have any value attached to them, you can map and reduce over these values, or combine them by merging or collapsing trees or subtrees. When computing lazy trees, these values are held in distributed memory and operated on in parallel.
    Downloads: 6 This Week
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  • 22
    EzXML.jl

    EzXML.jl

    XML/HTML handling tools for primates

    EzXML.jl is a package to handle XML/HTML documents for primates. This package depends on libxml2, which will be automatically installed as an artifact via XML2_jll.jl if you use Julia 1.3 or later. Currently, Windows, Linux, macOS, and FreeBSD are now supported.
    Downloads: 5 This Week
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  • 23
    Revise.jl

    Revise.jl

    Automatically update function definitions in a running Julia session

    Revise.jl is a Julia package that automatically updates functions, types, and modules in a running Julia session when their source code changes. It significantly improves the development workflow by removing the need to restart the REPL or re-include files after edits. Revise is ideal for iterative coding, package development, and interactive exploration, enabling a fast and fluid programming experience.
    Downloads: 7 This Week
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  • 24
    PowerSystems.jl

    PowerSystems.jl

    Data structures in Julia to enable power systems analysis

    The PowerSystems.jl package provides a rigorous data model using Julia structures to enable power systems analysis and modeling. In addition to stand-alone system analysis tools and data model building, the PowerSystems.jl package is used as the foundational data container for the PowerSimulations.jl and PowerSimulationsDynamics.jl packages. PowerSystems.jl supports a limited number of data file formats for parsing.
    Downloads: 7 This Week
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  • 25
    Functors.jl

    Functors.jl

    Parameterise all the things

    Functors.jl provides tools to express a powerful design pattern for dealing with large/ nested structures, as in machine learning and optimization. For large machine learning models, it can be cumbersome or inefficient to work with parameters as one big, flat vector, and structs help manage complexity; but it is also desirable to easily operate over all parameters at once, e.g. for changing precision or applying an optimizer update step.
    Downloads: 8 This Week
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