Open Source Windows Data Visualization Software - Page 77
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Data Visualization Software for Windows
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SVG_plot
Plot data in SVG format using C++ library
The SVG_plot C++ library allows, with a few lines of C++ code, to add plotting of data, held in STL containers like vector and map, output as SVG files that can be viewed by all modern browsers. 1D, 2D and Boxplots can be produced, and there are a myriad of options to control appearance. The plots are very high quality and can be expanded without loss of quality (no pixelation!) but are tiny, (compared for a Microsoft Excel plot, for example) and are easily compressible, making them suitable for real-time transmission and update. The SVG_plot project was originally written by Jake Voytko in 2007 as a Boost-sponsored Google Summer of Code project in 2007. It has been maintained and enhanced since then in Boost Sandbox, but is judged unsuitable for a Boost Library, so now being made more widely available here. Version 2 adds representation of uncertainty estimates as numbers and zones. -
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SZARP is a full-featured, open source (GPL) SCADA system for Linux. Client programs are available for Linux and Windows.
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Sampler
Tool for shell commands execution, visualization and alerting
Sampler is a real-time monitoring dashboard that allows developers to track various metrics, system information, and custom data sources via a terminal interface. -
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SLFCEM stands for San Le's Free Comp. Electromagnetics. It is a package of scientific software and graphical user interfaces for use in computational electromagnetics. It is written in ANSI C and distributed under the terms of the GNU license.
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SLFCFD stands for San Le's Free Computational Fluid Dynamics. It is a package of scientific software and graphical user interfaces for use in computational fluid dynamics. It is written in ANSI C and distributed under the terms of the GNU license.
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SandDance
Visually explore, understand, and present your data
By using easy-to-understand views, SandDance helps you find insights about your data, which in turn help you tell stories supported by data, build cases based on evidence, test hypotheses, dig deeper into surface explanations, support decisions for purchases, or relate data into a wider, real world context. SandDance uses unit visualizations, which apply a one-to-one mapping between rows in your database and marks on the screen. Smooth animated transitions between views help you to maintain context as you interact with your data. This new version of SandDance has been rebuilt from scratch with the goal of being modular, extensible, and embeddable into your custom applications. We are open and driven by the community through contributions, feature requests, and discussion. SandDance was created by the Microsoft Research VIDA Group which explores novel technologies for visualization and immersive data analytics. -
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A GUI built using Python 2.3+, wxPython and PyOpenGL for the mathematical modeling and visualization of landscape and streamflow systems. This visualization tool uses the Channel-Hillslope Integrated Landscape Development (CHILD) model as its backend.
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SatMod-Lambda
Satellite constellation analysis software.
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SatelliteToolbox.jl
A toolbox for satellite analysis written in julia language
The SatelliteToolbox.jl contains a set of packages with functions to perform analysis and build simulations related to satellites. It is used on a daily basis on projects at the Brazilian National Institute for Space Research (INPE). -
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A plotting (chart) library for .NET. Provides the ability to create plots with a minimum of effort and also to customise them extensively where required.
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A basic ray tracer written in the Scala language. Features includes photon mapping and a frontend written in Groovy. Planed features are volumetric lighting and shadow photons.
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Scanmap3D
3D Network Traffic Visualisation
A java-based 3D Visualisation tool for analysing network traffic. Written with jMonkeyEngine. -
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Scenario Editor And Visualizer
Scenario Editing and Visualization tool for Scientific scenes
Software Assistive Systems supporting visualization, simulation with aid of virtual reality could possibly enhance the experience and thereby enhance the speed and characteristics of the learning process. For the inclusive systems this means to make the best use of all interfaces human beings are blessed with taken from visualization, touch, voice, smell and taste. The right blend between visualization, simulation and virtual reality could hold the key to a solution. With reduced costs and processing power available and availability of experimentation platforms could hold the key to an enchanting learning experience. The first step is an editing and visualization tool. Described in paper http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6629931&refinements%3D4278371973%26queryText%3DGlobal+Humanitarian+Technology+Conference%3A+South+Asia+Satellite+.LB.GHTC-SAS.RB.%2C+2013+IEEE#! -
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Scene Beans is an animation framework for Java2D. Scene Beans lets the programmer create animations by composing Java objects in a declarative style and hides the details of exactly how that animation is animated and rendered.
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Schedule Visualization
Tool to visualize and create time-triggered schedules as gant-chart.
The Schedule Visualization tool is based on Eclipse 4 RCP and uses Nebula Gantt charts to visualize schedules. The tool is linked to scheduling and schedule integration algorithms which allow to generate time-triggered schedules and visualizes the calculated schedules. The generated schedule might then be exported to a C header file to update the system schedule. It also supports an online mode using a network monitor to detect if nodes are offline and updates its status in the visualization, e.g., for fault-tolerant systems. The tool expects an XML-based description for the system specification and allows to export generated schedules as XML. -
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Schematic3d depicts analog circuits in three dimensional space. Third dimension for circuit element is added based on the voltage. It generates animation for transient simulation. (Values of voltages are taken from PSPICE software).
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The Scientific Visualization Artist Tools (SVAT) include converters from the Visualization Toolkit (VTK) to RenderMan Interface Bytestream (RIB) (ASCII and binary files supported), Blender to RenderMan, compilable RenderMan shaders and other utilities.
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SciChart
Interactive Swing based Charting library to display science data
This free charting library supporting in the initial version line plot and bar plots. Provides: Axis sharing independent rescaling and panning of axis and datasets. Basic tooltips Legend displayer component with ability to select the active dataset. It is designed upon the Model View Controller paradigm. This mean that the dataset related API is abstracted in a model. This model is used by the swing components. Display related functionality is limited to the swing components with no interaction with the model. -
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Urbigene contains SciFOAF and MyFOAFExplorer, two tools used to build a scientific FOAF network from NCBI pubmed and to browse it.
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SciML Style Guide for Julia
A style guide for stylish Julia developers
The SciML Style Guide is a style guide for the Julia programming language. It is used by the SciML Open Source Scientific Machine Learning Organization. As such, it is open to discussion with the community. If the standard for code contributions is that every PR needs to support every possible input type that anyone can think of, the barrier would be too high for newcomers. Instead, the principle is to be as correct as possible to begin with, and grow the generic support over time. All recommended functionality should be tested, and any known generality issues should be documented in an issue (and with a @test_broken test when possible). However, a function that is known to not be GPU-compatible is not grounds to block merging, rather it is encouraged for a follow-up PR to improve the general type support. -
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SciMLBenchmarks.jl
Benchmarks for scientific machine learning (SciML) software
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem. -
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SciMLTutorials.jl
Tutorials for doing scientific machine learning (SciML)
SciMLTutorials.jl holds PDFs, webpages, and interactive Jupyter notebooks showing how to utilize the software in the SciML Scientific Machine Learning ecosystem. This set of tutorials was made to complement the documentation and the devdocs by providing practical examples of the concepts. For more details, please consult the docs. To view the SciML Tutorials, go to tutorials.sciml.ai. By default, this will lead to the latest tagged version of the tutorials -
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An open source program that has the ability to graph data collected from scientific experiments. It will fit a variety of linear and non-linear regressions to data and will have the ability to save and print graphs.
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ScientificTypes.jl
An API for dispatching on the "scientific" type of data
This package makes a distinction between machine type and scientific type of a Julia object. The machine type refers to the Julia type being used to represent the object (for instance, Float64). The scientific type is one of the types defined in ScientificTypesBase.jl reflecting how the object should be interpreted (for instance, Continuous or Multiclass). -
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ScikitLearn.jl
Julia implementation of the scikit-learn API
The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework.
