Search Results for "sandbox:/mnt/data/project_plan.pod" - Page 12
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Showing 2565 open source projects for "sandbox:/mnt/data/project_plan.pod"
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GMT.jl
Generic Mapping Tools Library Wrapper for Julia
...In this sense, all GMT options are put in a single text string that is passed, plus the data itself when it applies, to the gmt() command. However, we also acknowledge that not every one is comfortable with the GMT syntax. This syntax is needed to accommodate the immense pool of options that let you control all details of a figure but that also makes it harder to read/master. -
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XLSX.jl
Excel file reader and writer for the Julia language
XLSX.jl is a Julia package to read and write Excel spreadsheet files. Internally, an Excel XLSX file is just a Zip file with a set of XML files inside. The formats for these XML files are described in the Standard ECMA-376. This package follows the EMCA-376 to parse and generate XLSX files. -
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OpenCL.jl
OpenCL Julia bindings
Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
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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... -
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ScottPlot
Interactive Plotting Library for .NET
...ScottPlot does not require a GUI so it can be used to create plots in cloud applications. The images below are regenerated hourly using Azure Functions to update star metrics from the GitHub API and download count from the NuGet API. The data is plotted with ScottPlot and saved as an image file in blob storage. -
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FileTrees.jl
Parallel file processing made easy
Easy everyday parallelism with a file tree abstraction. 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. ... -
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Coverage.jl
Take Julia code coverage and memory allocation results, do useful thin
Julia can track how many times, if any, each line of your code is run. This is useful for measuring how much of your code base your tests actually test, and can reveal the parts of your code that are not tested and might be hiding a bug. You can use Coverage.jl to summarize the results of this tracking or to send them to a service like Coveralls.io or Codecov.io. Julia can track how much memory is allocated by each line of your code. This can reveal problems like type instability, or... -
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JuliaSyntax
A Julia frontend, written in Julia
...It's highly compatible with Julia's older femtoliter-based parser - It parses all of Base, the standard libraries and the General registry. Some minor differences remain where we've decided to fix bugs or strange behaviors in the reference parser. The AST and tree data structures are usable but their APIs will evolve as we try out various use cases. Parsing to the standard Expr AST is always possible and will be stable. The intention is to extend this library over time to cover more of the Julia compiler front end. -
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NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers
Fast implementations of root-finding algorithms in Julia that satisfy the SciML common interface. For information on using the package, see the stable documentation. Use the in-development documentation for the version of the documentation that contains the unreleased features. NonlinearSolve.jl is a unified interface for the nonlinear solving packages of Julia. The package includes its own high-performance nonlinear solvers which include the ability to swap out to fast direct and iterative... -
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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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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. -
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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. -
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Parquet.jl
Julia implementation of Parquet columnar file format reader
A parquet file or dataset can be loaded using the read_parquet function. A parquet dataset is a directory with multiple parquet files, each of which is a partition belonging to the dataset. -
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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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MethodOfLines.jl
Automatic Finite Difference PDE solving with Julia SciML
MethodOfLines.jl is a Julia package for automated finite difference discretization of symbolically defined PDEs in N dimensions. It uses symbolic expressions for systems of partial differential equations as defined with ModelingToolkit.jl, and Interval from DomainSets.jl to define the space(time) over which the simulation runs. This project is under active development, therefore the interface is subject to change. The docs will be updated to reflect any changes, please check back for current... -
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Conda.jl
https://github.com/JuliaPy/Conda.jl
This package allows one to use conda as a cross-platform binary provider for Julia for other Julia packages, especially to install binaries that have complicated dependencies like Python. conda is a package manager that started as the binary package manager for the Anaconda Python distribution, but it also provides arbitrary packages. Instead of the full Anaconda distribution, Conda.jl uses the miniconda Python environment, which only includes conda and its dependencies. -
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CoordinateTransformations.jl
A fresh approach to coordinate transformations
CoordinateTransformations is a Julia package to manage simple or complex networks of coordinate system transformations. Transformations can be easily applied, inverted, composed, and differentiated (both with respect to the input coordinates and with respect to transformation parameters such as rotation angle). Transformations are designed to be light-weight and efficient enough for, e.g., real-time graphical applications, while support for both explicit and automatic differentiation makes... -
18
Coluna.jl
Branch-and-Price-and-Cut in Julia
Coluna is a branch-and-price-and-cut framework written in Julia. You write an original MIP that models your problem using the JuMP modeling language and our specific extension BlockDecomposition offers a syntax to specify the problem decomposition. Then, Coluna reformulates the original MIP and optimizes the reformulation using the algorithms you choose. Coluna aims to be very modular and tweakable so that you can define the behavior of your customized branch-and-price-and-cut algorithm. -
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InfiniteOpt.jl
An intuitive modeling interface for infinite-dimensional optimization
A JuMP extension for expressing and solving infinite-dimensional optimization problems. InfiniteOpt.jl provides a general mathematical abstraction to express and solve infinite-dimensional optimization problems (i.e., problems with decision functions). Such problems stem from areas such as space-time programming and stochastic programming. InfiniteOpt is meant to facilitate intuitive model definition, automatic transcription into solvable models, permit a wide range of user-defined... -
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Metalhead.jl
Computer vision models for Flux
Metalhead.jl provides standard machine learning vision models for use with Flux.jl. The architectures in this package make use of pure Flux layers, and they represent the best practices for creating modules like residual blocks, inception blocks, etc. in Flux. Metalhead also provides some building blocks for more complex models in the Layers module. -
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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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Graphs.jl
An optimized graphs package for the Julia programming language
The goal of Graphs.jl is to offer a performant platform for network and graph analysis in Julia, following the example of libraries such as NetworkX in Python. Offers a set of simple, concrete graph implementations – SimpleGraph (for undirected graphs) and SimpleDiGraph (for directed graphs), an API for the development of more sophisticated graph implementations under the AbstractGraph type, and a large collection of graph algorithms with the same requirements as this API. -
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ApproxFun.jl
Julia package for function approximation
ApproxFun is a package for approximating functions. It is in a similar vein to the Matlab package Chebfun and the Mathematica package RHPackage. The ApproxFun Documentation contains detailed information, or read on for a brief overview of the package. The documentation contains examples of usage, such as solving ordinary and partial differential equations. The ApproxFun Examples repo contains many examples of using this package, in Jupyter notebooks and Julia scripts. Note that this is... -
24
Finch.jl
Sparse tensors in Julia and more
Finch is a cutting-edge Julia-to-Julia compiler specially designed for optimizing loop nests over sparse or structured multidimensional arrays. Finch empowers users to write conventional for loops which are transformed behind-the-scenes into fast sparse code. -
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pprof
pprof is a tool for visualization and analysis of profiling data
pprof is a profiling visualization and analysis tool that ingests profiles in the profile.proto format and generates human-readable and graph-based reports. It supports multiple profile types (CPU, heap, allocations, contention, etc.) and can present data as text tables, call graphs (via Graphviz/dot), flame graphs, and interactive web UIs. The tool helps developers find hot paths, quantify resource usage, and compare profiles across runs to validate performance changes. It is widely used in Go but also has bindings and exporters for other ecosystems, and the repository includes a Go package for reading and writing profiles programmatically. ...
