Showing 2050 open source projects for "qt data visualization"

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  • 1
    CoordinateTransformations.jl

    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...
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  • 2
    Coluna.jl

    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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  • 3
    InfiniteOpt.jl

    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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  • 4
    Metalhead.jl

    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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  • 5
    Graphs.jl

    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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  • 6
    ApproxFun.jl

    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...
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  • 7
    Oceananigans.jl

    Oceananigans.jl

    Julia software for fast, friendly, flexible fluid dynamics on CPUs

    Oceananigans is a fast, friendly, flexible software package for finite volume simulations of the nonhydrostatic and hydrostatic Boussinesq equations on CPUs and GPUs. It runs on GPUs (wow, fast!), though we believe Oceananigans makes the biggest waves with its ultra-flexible user interface that makes simple simulations easy, and complex, creative simulations possible.
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  • 8
    Pluto.jl

    Pluto.jl

    Simple reactive notebooks for Julia plutojl.org

    We are on a mission to make scientific computing more accessible and fun. Writing a notebook is not just about writing the final document, Pluto empowers the experiments and discoveries that are essential to getting there.
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  • 9
    Kubernetes History Inspector

    Kubernetes History Inspector

    A log viewer for Kubernetes troubleshooting

    The khi repository is a Google Cloud open-source project focused on infrastructure and system-level tooling, typically aimed at enabling advanced cloud-native workflows, observability, or orchestration in Kubernetes-based environments. It is designed to support engineers working with distributed systems by providing utilities and abstractions that simplify deployment, monitoring, or operational management. The project aligns with Google Cloud’s broader ecosystem of tools that help developers...
    Downloads: 4 This Week
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  • 10
    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). Climate indices and bias correction functions are coded to leverage the use of multiple threads....
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  • 11
    ImplicitGlobalGrid.jl

    ImplicitGlobalGrid.jl

    Distributed parallelization of stencil-based GPU and CPU applications

    ImplicitGlobalGrid is an outcome of a collaboration of the Swiss National Supercomputing Centre, ETH Zurich (Dr. Samuel Omlin) with Stanford University (Dr. Ludovic Räss) and the Swiss Geocomputing Centre (Prof. Yuri Podladchikov). It renders the distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid almost trivial and enables close to ideal weak scaling of real-world applications on thousands of GPUs [1, 2, 3]. ImplicitGlobalGrid relies on the...
    Downloads: 0 This Week
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  • 12
    Wavelets.jl

    Wavelets.jl

    A Julia package for fast discrete wavelet transforms and utilities

    A Julia package for fast wavelet transforms (1-D, 2-D, 3-D, by filtering or lifting). The package includes discrete wavelet transforms, column-wise discrete wavelet transforms, and wavelet packet transforms. 1st generation wavelets using filter banks (periodic and orthogonal). 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...
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  • 13
    Matplotlib

    Matplotlib

    matplotlib: plotting with Python

    Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a...
    Downloads: 7 This Week
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  • 14
    ConformalPrediction.jl

    ConformalPrediction.jl

    Predictive Uncertainty Quantification through Conformal Prediction

    ConformalPrediction.jl is a package for Predictive Uncertainty Quantification (UQ) through Conformal Prediction (CP) in Julia. It is designed to work with supervised models trained in MLJ (Blaom et al. 2020). Conformal Prediction is easy-to-understand, easy-to-use and model-agnostic and it works under minimal distributional assumptions. Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates through repeated sampling or the use...
    Downloads: 0 This Week
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  • 15
    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.
    Downloads: 0 This Week
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  • 16
    PairPlots.jl

    PairPlots.jl

    Beautiful and flexible vizualizations of high dimensional data

    Beautiful and flexible visualizations of high-dimensional data. This package produces pair plots, otherwise known as corner plots or scatter plot matrices: grids of 1D and 2D histograms that allow you to visualize high-dimensional data. Pair plots are an excellent way to visualize the results of MCMC simulations, but are also a useful way to visualize correlations in general data tables. The default styles of this package roughly reproduce the output of the Python library corner.py for a...
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  • 17
    FileTrees.jl

    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...
    Downloads: 4 This Week
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  • 18
    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: 0 This Week
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  • 19
    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....
    Downloads: 0 This Week
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  • 20
    PlutoSliderServer.jl

    PlutoSliderServer.jl

    Web server to run just the `@bind` parts of a Pluto.jl notebook

    Web server to run just the @bind parts of a Pluto.jl notebook. PlutoSliderServer can run a notebook and generate the export HTML file. This will give you the same file as the export button inside Pluto (top right), but automatically, without opening a browser. One use case is to automatically create a GitHub Pages site from a repository with notebooks. For this, take a look at our template repository that used GitHub Actions and PlutoSliderServer to generate a website on every commit. Many...
    Downloads: 1 This Week
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  • 21
    Fermi.jl

    Fermi.jl

    Fermi quantum chemistry program

    Fermi.jl is a quantum chemistry framework written in pure Julia. This code is developed at the Center for Computational Quantum Chemistry at the University of Georgia under the supervision of Dr. Justin M. Turney and Prof. Henry F. Schaefer. This work is supported by the U.S. National Science Foundation under grant number CHE-1661604. Fermi focuses on post Hartree--Fock methods. Currently, only restricted references are supported. This is intended as a research code with an ever growing...
    Downloads: 1 This Week
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  • 22
    GemGIS

    GemGIS

    Spatial data processing for geomodeling

    GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model-building process. Postprocessing of model results will allow export...
    Downloads: 0 This Week
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  • 23
    SQLPad

    SQLPad

    Web-based SQL editor run in your own private cloud

    A web app for writing and running SQL queries and visualizing the results. Supports Postgres, MySQL, SQL Server, ClickHouse, Crate, Vertica, Trino, Presto, SAP HANA, Cassandra, Snowflake, Google BigQuery, SQLite, TiDB, and many more via ODBC. The docker image runs on port 3000 and uses /var/lib/sqlpad for the embedded database directory. latest tag is continuously built from latest commit in repo. Only use that if you want to live on the edge, otherwise use specific version tags to ensure...
    Downloads: 3 This Week
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  • 24
    CausalityTools.jl

    CausalityTools.jl

    Algorithms for detecting associations, dynamical influences

    CausalityTools.jl is a package for quantifying associations and dynamical coupling between datasets, independence testing, and causal inference. Association measures from conventional statistics, information theory, and dynamical systems theory, for example, distance correlation, mutual information, transfer entropy, convergent cross mapping and a lot more. A dedicated API for independence testing, which comes with automatic compatibility with every measure-estimator combination you can...
    Downloads: 0 This Week
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  • 25
    ComponentArrays.jl

    ComponentArrays.jl

    Arrays with arbitrarily nested named components

    The main export of this package is the ComponentArray type. "Components" of ComponentArrays are really just array blocks that can be accessed through a named index. This will create a new ComponentArray whose data is a view into the original, allowing for standalone models to be composed together by simple function composition. In essence, ComponentArrays allow you to do the things you would usually need a modeling language for, but without actually needing a modeling language. The main...
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