Open Source Mac Data Visualization Software - Page 59

Data Visualization Software for Mac

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  • 1
    RayTracer.jl

    RayTracer.jl

    Differentiable RayTracing in Julia

    This package was written in the early days of Flux / Zygote. Both these packages have significantly improved over time. Unfortunately, the current state of this package of has not been updated to reflect those improvements. It also seems that it might be better to gradually transition to defining the adjoints directly using ChainRules. A Ray Tracer written completely in Julia. This allows us to leverage the AD capabilities provided by Zygote to differentiate through the Ray Tracer.
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  • 2
    This software system serves as both a DICOM image viewer as well as a diagramming tool for collaborating notes on the given image sets. This my Computer Science graduate thesis project at Loyola Marymount University.
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  • 3
    ReTest.jl

    ReTest.jl

    Testing framework for Julia

    ReTest is a testing framework for Julia allowing defining tests in source files, whose execution is deferred and triggered on demand. This is useful when one likes to have definitions of methods and corresponding tests close to each other. This is also useful for code that is not (yet) organized as a package, and where one doesn't want to maintain a separate set of files for tests. Filtering run testsets with a Regex, which is matched against the descriptions of testsets. This is useful for running only part of the test suite of a package. For example, if you made a change related to addition, and included "addition" in the description of the corresponding testsets, you can easily run only these tests.
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  • 4
    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 and bars to merge together. This is because to track changes in the dataset series, the library needs a key to be specified. If none is found, it can't tell the difference between the datasets while updating. Specify a different property to be used as a key by passing a datasetIdKey prop to your chart component.
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  • 5
    React Trend

    React Trend

    Simple, elegant spark lines

    Unfortunately, none of this project's authors have the time/enthusiasm to maintain this project right now. We recommend forking this project, or reading its source to learn how it's built). Graphing tools are often complex, abstract, and heavy. They require domain-specific knowledge and significant time investment. While building rich data visualizations for an analytics app, is a necessary cost. But what if you just need a sparkline that shows a trend? These are very simple and elegant visualizations, and they should not require a bloated graphing library to produce. React Trend is a concrete component that does 1 thing, and does it well, generate these trending graphs. By default, all properties not recognized by React Trend will be delegated to the SVG. The line inherits these properties if none of its own override them.
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  • 6
    React-Datasheet

    React-Datasheet

    Excel-like data grid (table) component for React

    This small component allows you to integrate an excel-like datasheet. By default, the spreadsheet handles keyboard navigation and copy-pasting of cells. This example computes expression underneath using mathjs. On an invalid expression, the cell changes color to show the error. Note that react-datasheet does not handle the validation nor the formula computation. Custom renderers allow you to add significant new capabilities to your sheets without requiring changes to react-datagrid itself. This example allows you to reorder both the columns and the rows using drag and drop. This is implemented by using custom components to render the main table (including a custom header) and each row. The drag handler for the rows is the gray cell at the beginning of each row. The "Rating" column also shows how to specify custom cell editing and viewing components.
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  • 7
    React-Vis

    React-Vis

    Data visualization components

    React-vis is a React visualization library. React-vis components are designed to work just like other React components. They have properties, children and callbacks. They can be composed. If you can work with React components, you can work with React-Vis. You can create complex charts with a minimum amount of code and sensible defaults, however, you can also customize every aspect of your chart. React-vis handles a great number of charts, from area charts to treemaps. React-vis was built to support the many internal tools at Uber. You can use react-vis directly on codepen (or equivalent). React-Vis charts are made of Series components, LineSeries, BarSeries and so on and so forth. Each of these Series components requires a data property, through which we pass an array of objects. These properties correspond to various visual characteristics of the corresponding marks. For example, x and y, which are required for most series types, affect the position of each mark.
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  • 8
    ReactiveMP.jl

    ReactiveMP.jl

    High-performance reactive message-passing based Bayesian engine

    ReactiveMP.jl is a Julia package that provides an efficient reactive message passing based Bayesian inference engine on a factor graph. The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called RxInfer. While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and real-time datasets.
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  • 9
    physicslib:- A library of rigid body physics routines and demos, designed for use in VR and entertainment applications. With tutorial style documentation intended to explain the concepts used in the code.
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  • 10
    The Real-time Network Grapher (RtNG) is a Java applet. RtNG plots a scrolling line-graph from a continuous feed of CSV-style data, where new data arrives periodically with a period 0.1s or greater. The data feed can be either a TCP port or a URL
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  • 11
    R.I.S.E. is a state of the art engine and framework for the simulation and realistic image synthesis of natural phenomenon based on physics, biology and chemistry.
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  • 12
    Reduce.jl

    Reduce.jl

    Symbolic parser for Julia language term rewriting using REDUCE algebra

    REDUCE is a portable general-purpose computer algebra system. It is a system for doing scalar, vector and matrix algebra by computer, which also supports arbitrary precision numerical approximation and interfaces to gnuplot to provide graphics. It can be used interactively for simple calculations (as illustrated in the screenshot below) but also provides a full programming language, with a syntax similar to other modern programming languages. REDUCE supports alternative user interfaces including Run-REDUCE, TeXmacs and GNU Emacs. REDUCE (and its complete source code) is available free of charge for most common computing systems, in some cases in more than one version for the same machine. The manual and other support documents and tutorials are also included in the distributions.
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  • 13
    Reexport.jl

    Reexport.jl

    Julia macro for re-exporting one module from another

    Maybe you have a module X that depends on module Y and you want using X to pull in all of the symbols from Y. Maybe you have an outer module A with an inner module B, and you want to export all of the symbols in B from A. It would be nice to have this functionality built into Julia, but we have yet to reach an agreement on what it should look like. This short macro is a stopgap we have a better solution.
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  • 14
    Registrator.jl

    Registrator.jl

    Julia package registration bot

    Registrator is a GitHub app that automates the creation of registration pull requests for your Julia packages to the General registry.
    Downloads: 0 This Week
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  • 15
    ReinforcementLearning.jl

    ReinforcementLearning.jl

    A reinforcement learning package for Julia

    A collection of tools for doing reinforcement learning research in Julia. Provide elaborately designed components and interfaces to help users implement new algorithms. Make it easy for new users to run benchmark experiments, compare different algorithms, and evaluate and diagnose agents. Facilitate reproducibility from traditional tabular methods to modern deep reinforcement learning algorithms. Make it easy for new users to run benchmark experiments, compare different algorithms, and evaluate and diagnose agents. Facilitate reproducibility from traditional tabular methods to modern deep reinforcement learning algorithms. Provide elaborately designed components and interfaces to help users implement new algorithms. A number of built-in environments and third-party environment wrappers are provided to evaluate algorithms in various scenarios.
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  • 16
    ReinforcementLearningAnIntroduction.jl

    ReinforcementLearningAnIntroduction.jl

    Julia code for the book Reinforcement Learning An Introduction

    This project provides the Julia code to generate figures in the book Reinforcement Learning: An Introduction(2nd). One of our main goals is to help users understand the basic concepts of reinforcement learning from an engineer's perspective. Once you have grasped how different components are organized, you're ready to explore a wide variety of modern deep reinforcement learning algorithms in ReinforcementLearningZoo.jl.
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  • 17
    Relations RCP is a personal wiki style application for knowledge creation and management. Its use is the visualization of terms and concepts and the relations governing these items. Relations is implemented as Eclipse RCP application.
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  • 18
    Remotery

    Remotery

    Single C file, Realtime CPU/GPU Profiler with Remote Web Viewer

    Remotery is a real-time CPU/GPU profiler implemented as a single C file, providing developers with immediate insights into the performance of their applications. It features a remote web-based viewer that runs in browsers like Chrome, Firefox, and Safari, allowing for cross-platform performance analysis. Remotery supports profiling multiple threads and GPU contexts, offering a comprehensive view of an application's performance characteristics.
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  • 19
    RenderTools

    RenderTools

    A cross-platform OpenGL based lightweight scenegraph library

    RenderTools is an OpenGL based scenegraph library in C++ for Windows, OSX and IOS supporting OpenGL|ES1.1, ES2.0, OpenGL1.5 and up to the latest version (currently 4.2). It allows the developer to easily (de)serialize a scenegraph to-and-from xml, create renderbuffers, framebuffers, samplers, vertexbuffers etc. and cross-reference those items. RenderTools allows you to completely specify an application, its resources, viewcontrollers and its renderpasses in one single xml. GraphNodes such as RelationalNode, RenderNode, and TransformNode can be used to create a complex hierarchy for rendering. Both update and render calls can selectively include or exclude specific components such as geometric details or lighting or texturing.
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  • 20
    ReplMaker.jl

    ReplMaker.jl

    Simple API for building repl modes in Julia

    The idea behind ReplMaker.jl is to make a tool for building (domain-specific) languages in Julia. Suppose you've invented some language called MyLang and you've implemented a parser that turns MyLang code into Julia code which is then supposed to be executed by the Julia runtime. With ReplMaker.jl, you can simply hook your parser into the package and ReplMaker will then create a REPL mode where end users just type MyLang code and have it executed automatically. My hope is for this to be useful to someone who implements a full language or DSL in Julia that uses syntax not supported by Julia's parser and doesn't want to deal with the headache of making their own REPL mode.
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  • 21
    ReservoirComputing.jl

    ReservoirComputing.jl

    Reservoir computing utilities for scientific machine learning (SciML)

    ReservoirComputing.jl provides an efficient, modular and easy-to-use implementation of Reservoir Computing models such as Echo State Networks (ESNs). For information on using this package please refer to the stable documentation. Use the in-development documentation to take a look at not-yet-released features.
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  • 22
    ResultTypes.jl

    ResultTypes.jl

    A Result type for Julia—it's like Nullables for Exceptions

    ResultTypes provides a Result type that can hold either a value or an error. This allows us to return a value or an error in a type-stable manner without throwing an exception.
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  • 23
    ResumableFunctions.jl

    ResumableFunctions.jl

    C# style generators a.k.a. semi-coroutines for Julia

    C# has a convenient way to create iterators using the yield return statement. The package ResumableFunctions provides the same functionality for the Julia language by introducing the @resumable and the @yield macros. These macros can be used to replace the Task switching functions produce and consume which were deprecated in Julia v0.6. Channels are the preferred way for inter-task communication in Julia v0.6+, but their performance is subpar for iterator applications.
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  • 24
    ReverseDiff

    ReverseDiff

    Reverse Mode Automatic Differentiation for Julia

    ReverseDiff is a fast and compile-able tape-based reverse mode automatic differentiation (AD) that implements methods to take gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really). While performance can vary depending on the functions you evaluate, the algorithms implemented by ReverseDiff generally outperform non-AD algorithms in both speed and accuracy.
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  • 25
    RevoGrid

    RevoGrid

    Powerful virtual data grid smartsheet with advanced customization

    Support Millions of cells and thousands of columns easy and efficiently for fast data rendering. Easy to use. For large organizations managing massive datasets. Performance and scalability to handle even the most complex data tables. Rapid prototyping with intuitive and extendable codebase. Agility to build robust data-driven applications in no time. Quickly build elegant and efficient data grids. Lightweight yet powerful architecture lets you easily scale as your needs grow.
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