Showing 2388 open source projects for "x-windows"

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  • 1
    HDF5.jl

    HDF5.jl

    Save and load data in the HDF5 file format from Julia

    HDF5 stands for Hierarchical Data Format v5 and is closely modeled on file systems. 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...
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  • 2
    Convex.jl

    Convex.jl

    A Julia package for disciplined convex programming

    Convex.jl is a Julia package for Disciplined Convex Programming (DCP). Convex.jl makes it easy to describe optimization problems in a natural, mathematical syntax, and to solve those problems using a variety of different (commercial and open-source) solvers. Convex.jl works by transforming the problem—which possibly has nonsmooth, nonlinear constructions like the nuclear norm, the log determinant, and so forth—into a linear optimization problem subject to conic constraints. This...
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  • 3
    Optimization.jl

    Optimization.jl

    Mathematical Optimization in Julia

    Optimization.jl provides the easiest way to create an optimization problem and solve it. It enables rapid prototyping and experimentation with minimal syntax overhead by providing a uniform interface to >25 optimization libraries, hence 100+ optimization solvers encompassing almost all classes of optimization algorithms such as global, mixed-integer, non-convex, second-order local, constrained, etc. It allows you to choose an Automatic Differentiation (AD) backend by simply passing an...
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  • 4
    Gridap.jl

    Gridap.jl

    Grid-based approximation of partial differential equations in Julia

    Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can...
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    BertViz

    BertViz

    BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

    BertViz is an interactive tool for visualizing attention in Transformer language models such as BERT, GPT2, or T5. It can be run inside a Jupyter or Colab notebook through a simple Python API that supports most Huggingface models. BertViz extends the Tensor2Tensor visualization tool by Llion Jones, providing multiple views that each offer a unique lens into the attention mechanism. The head view visualizes attention for one or more attention heads in the same layer. It is based on the...
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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. Create a placeholder element that will contain the rendered chart. The Vizzu...
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  • 7
    HyperTools

    HyperTools

    A Python toolbox for gaining geometric insights

    HyperTools is a library for visualizing and manipulating high-dimensional data in Python. It is built on top of matplotlib (for plotting), seaborn (for plot styling), and scikit-learn (for data manipulation). Functions for plotting high-dimensional datasets in 2/3D. Static and animated plots. Simple API for customizing plot styles. Set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more. Support for lists of Numpy arrays, Pandas dataframes,...
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  • 8
    gganimate

    gganimate

    A Grammar of Animated Graphics

    gganimate extends the grammar of graphics as implemented by ggplot2 to include the description of animation. It does this by providing a range of new grammar classes that can be added to the plot object in order to customize how it should change with time. Here we take a simple boxplot of fuel consumption as a function of cylinders and let it transition between the number of gears available in the cars. As this is a discrete split (gear being best described as an ordered factor) we use...
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  • 9
    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. Shows how a target value (e.g. "Survived" in the Titanic...
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  • 10
    React Chart.js

    React Chart.js

    React components for Chart.js, the most popular charting library

    React components for Chart.js, the most popular charting library. With v4, this library introduces a number of breaking changes. In order to improve performance, offer new features, and improve maintainability, it was necessary to break backwards compatibility, but we aimed to do so only when worth the benefit. You will find that any event which causes the chart to re-render, such as hover tooltips, etc., will cause the first dataset to be copied over to other datasets, causing your lines...
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  • 11
    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...
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  • 12
    Charts.css

    Charts.css

    Open source CSS framework for data visualization

    Charts.css is a modern CSS framework. It uses CSS utility classes to style HTML elements as charts. No dependencies. 72kb file size. Less than 6kb gzipped file size! Visualization helps end-users understand data. Charts.css help frontend developers turn data into beautiful charts and graphs using simple CSS classes. The data is structured using semantic HTML tags and styled using CSS classes which change the visual representation displayed to the end-user. The framework offers developers...
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  • 13
    vue-chartjs

    vue-chartjs

    Vue.js wrapper for Chart.js

    vue-chartjs is a wrapper for Chart.js in vue. You can easily create reusable chart components. You can use vue-chartjs directly in the browser without any build setup. Like in this codepen. For this case, please use the vue-chartjs.min.js which is the minified version. You also need to add the Chart.js CDN script. Chart.js does not update or re-render the chart if new data is passed. However, you can simply implement this on your own or use one of the two mixins which are included. The...
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  • 14
    nw_wrld

    nw_wrld

    nw_wrld is an event-driven sequencer for triggering visuals

    nw_wrld is a procedurally generated world-building engine tailored for game developers and interactive storytellers who want to craft rich, random yet coherent environments without hand-crafting every detail. It uses noise functions and modular terrain algorithms to generate expansive maps, diverse biomes, and layered features like rivers, mountain ranges, forests, and resource nodes. The system is designed to be extensible, letting developers plug in new generation rules or tweak parameters...
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  • 15
    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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  • 16
    pprof

    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...
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  • 17
    see

    see

    Visualisation toolbox for beautiful and publication-ready figures

    see is an R package that serves as the visualization component of the easystats ecosystem, providing plotting utilities to produce publication-ready visualizations of statistical model parameters, diagnostics, predictions, and performance metrics. It works in conjunction with other easystats packages (such as parameters, performance, modelbased, bayestestR, etc.) to convert model outputs or summary objects into visual forms (dot-and-whisker plots, diagnostic plots, residual plots, etc.). It...
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  • 18
    ggrepel

    ggrepel

    epel overlapping text labels away from each other in your ggplot2

    ggrepel is an R package that provides “smart” repulsion for text and label geoms in ggplot2. When placing text labels on a plot (e.g. labeling points), the labels can often overlap; ggrepel ensures labels don’t overlap (or overlap less) by repelling labels / pushing them away, adding connecting lines or nudges, etc. It improves the readability of plots, especially when many labels are present. Support for point and segment geoms (so labels can be connected by lines when moved). Supports both...
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  • 19
    Data Formulator

    Data Formulator

    Create rich visualizations with AI

    To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals. To achieve this, analysts need not only proficiency in data transformation and visualization tools but also efforts to manage the branching history consisting of many different versions of data and charts. Recent LLM-powered AI systems have greatly improved visualization authoring experiences, for example by mitigating manual data...
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  • 20
    Chromatone

    Chromatone

    Chromatone is a digital garden of visual music theory

    Cards and short overviews on the physics and physiology of vision and hearing and their intersection at visual music research, exploration, practice, and self-expression. Useful tools to have in the pocket like a pack of interactive cards to learn and use in everyday music practice. These are open source web experiments with different aspects of sound and color. Chromatone is an open source research and design project to explore, develop and implement the scientific way of visual music...
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  • 21
    nb-clean

    nb-clean

    Clean Jupyter notebooks of outputs, metadata, and empty cells

    nb-clean cleans Jupyter notebooks of cell execution counts, metadata, outputs, and (optionally) empty cells, preparing them for committing to version control. It provides both a Git filter and pre-commit hook to automatically clean notebooks before they're staged, and can also be used with other version control systems, as a command line tool, and as a Python library. It can determine if a notebook is clean or not, which can be used as a check in your continuous integration pipelines....
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  • 22
    WordCloud.jl

    WordCloud.jl

    Word cloud generator in julia

    Word cloud (tag cloud or wordle) is a novelty visual representation of text data. The importance of each word is shown with its font size, position, or color. WordCloud.jl is the perfect tool for generating word clouds, offering several advantages. You have control over every aspect of generating a word cloud. You can customize the shape, color, angle, position, distribution, density, and spacing to align with your preferences and artistic style. This visualization solution guarantees...
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  • 23
    NonlinearSolve.jl

    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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  • 24
    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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  • 25
    NeuralOperators.jl

    NeuralOperators.jl

    DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia

    Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function...
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