Open Source Mac Data Visualization Software - Page 63

Soss is a library for probabilistic programming. Soss and DynamicPPL are both maturing and becoming more complete, so the above will change over time. It's also worth noting that we (the Turing team and I) hope to move toward a natural way of using these systems together to arrive at the best of both.

A Enclosure+Connection technique for layout and navigation of Hierarchical Information. The layout uses "angular" enclosure partitioning approach where the child nodes are located around their parent. The program was written in Java Applet. Related Publications: https://ieeexplore.ieee.org/abstract/document/1173152 https://journals.sagepub.com/doi/abs/10.1057/palgrave.ivs.9500031

Now maintained at github.com/spacepy/spacepy Space Science library for Python - contains superposed epoch classes, drift shell tracing, access to magnetic field models, streamline tracing, bootstrap confidence limits, time and coordinate conversions, etc.

A Julia interface to Apache Spark. Spark.jl provides an interface to Apache Spark™ platform, including SQL / DataFrame and Structured Streaming. It closely follows the PySpark API, making it easy to translate existing Python code to Julia. Spark.jl supports multiple cluster types (in client mode), and can be considered as an analog to PySpark or RSpark within the Julia ecosystem. It supports running within on-premise installations, as well as hosted instances such as Amazon EMR and Azure HDInsight.

Develop a basic understanding of the behavior of polar spherical coordinates through selected examples. Provide sample files for diverse mathematics engines

Spin3D - OpenGL Visualization Tool for high dimensional data.

Implementation of a bidirectional bridge between Sun SPOTs and virtual Spaughts in SecondLife using XML-RPC between Java (spot-side) and C# (libsecondlife on SL-side).

Tensegrity simulator

Spy is a Mac OS X menu extra displaying inportant info about your computer (CPU, Network, Disk and Memory usage)

SpyGlass is a modular and extensible visualization framework for wireless sensor networks.

Codes related to answers by Royi Avital on StackExchange Network.

The Stage Lighting Synth lets you create stage lighting shows with real-life lighting fixtures controlled via DMX. It is a visual graph editor for creating and controlling stage lighting shows in realtime, and is incredibly easy to extend.

A collection of example Stan Language programs demonstrating all methods available in Stan's cmdstan executable (as an external program) from Julia. For most applications one of the "single method" packages, e.g. StanSample.jl, StanDiagnose.jl, etc., is a better choice for day-to-day use. To execute the most important method in Stan ("sample"), use StanSample.jl. Some Pluto notebook examples can be found in the repository.

StarMap 3D: the project aims to offer a fast and easy consultation of stellar systems

Welcome to the documentation for Starlight.jl, a greedy application framework for greedy developers. Its primary use case is video games, but the power of Julia, SDL2, Vulkan, and the Bullet Physics SDK can be leveraged to make just about anything you want. With a focus on flexibility and code quality, Starlight aims to be such a framework. It includes a suite of components and integrations that make it particuarly well-suited for video games, so it is not a stretch to call it a "game engine". However, Starlight is most fundamentally a scripting layer for SDL, Vulkan, and Bullet (via the Telescope backend), meaning it can be used for any application that needs high-performance rendering and physics. Furthermore, there are plans to allow selective enabling of different subsystems, meaning it could be used for GUI apps or pure physics simulation or anything else you can imagine.

StatCvs-XML provides statistics about cvs usage based on the cvs log. It extends the StatCvs project with fancy 3D charts, advanced report generation and customization features. It also features a plugin for seamless integration with Apache Maven.

The aim of this project is to automate and simplify the linking / merging / importing of country data from various sources, such as UNESCO, WHO, World Bank, IMF, etc. Project website: www.statsilk.com

This module formats the output from Julia's Profile module into an html rendering of the source function lines and functions, allowing for interactive exploration of any bottlenecks that may exist in your code.

StateGL++ is an abstraction layer hiding OpenGL implementation details such as stack depths and attribute settings and allowing pushing and popping of lights and materials. With StateGL you don't have to worry about GL_MAX_*STACK_DEPTH.

StateVis is a package that allows states (or groups) to create a browsable database of their Landsat holdings.

The Stats Jam project is an extension to Mediawiki that allows users to embed database queries and visualisations into their wiki pages.

StatsBase.jl is a Julia package that provides basic support for statistics. Particularly, it implements a variety of statistics-related functions, such as scalar statistics, high-order moment computation, counting, ranking, covariances, sampling, and empirical density estimation.

This is a convenience meta-package that allows loading essential packages for statistics in one command.

StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can contain people as nodes and friendships between them as links, with data like a person’s age and the date a friendship was established. StellarGraph supports the analysis of many kinds of graphs. StellarGraph is built on TensorFlow 2 and its Keras high-level API, as well as Pandas and NumPy. It is thus user-friendly, modular and extensible. It interoperates smoothly with code that builds on these, such as the standard Keras layers and scikit-learn.

A software to implement the existing stereo matching algorithms in computer vision, including the easiest SSD, and the newest algorithms.