424,514 research outputs found
Mayavi: 3D visualization of scientific data
International audienceMayavi is an open-source, general-purpose, 3D scientific visualization package. It seeks to provide easy and interactive tools for data visualization that fit with the scientific user's workflow. For this purpose, Mayavi provides several entry points: a full-blown interactive application; a Python library with both a MATLAB-like interface focused on easy scripting and a feature-rich object hierarchy; widgets associated with these objects for assembling in a domain-specific application, and plugins that work with a general purpose application-building framework. In this article, we present an overview of the various features of Mayavi, we then provide insight on the design and engineering decisions made in implementing Mayavi, and finally discuss a few novel applications
Virtual Reality Visualization by CAVE with VFIVE and VTK
The CAVE-type virtual reality (VR) system was introduced for scientific
visualization of large scale data in the plasma simulation community about a
decade ago. Since then, we have been developing a VR visualization software,
VFIVE, for general CAVE systems. Recently, we have integrated an open source
visualization library, the Visualization Toolkit (VTK), into VFIVE. Various
visualization methods of VTK can be incorporated and used interactively in
VFIVE.Comment: 3 pages, 3 figures, submitted to J. Plasma Physcs (special issue for
19th ICNSP
Reading Responses To Journal Articles, Computational Emulation Of Published Research
Students responded to sets of journal articles in computational optics and imaging every week. Articles investigated scientific questions, visualization of scientific data, ethical questions, and international collaborative projects (such as the Event Horizon Telescope). Students also completed labs to gain proficiency in computational tools
A New role of ontologies and advanced scientific visualization in big data analytics
Accessing and contextual semantic searching structured, semi-structured and unstructured information resources and their ontology based analysis in a uniform way across text-free Big Data query implementation is a main feature of approach under discussion. To increase the semantic power of query results’ analysis the ontology based implementation of multiplatform adaptive tools of scientific visualization are demonstrated. The ontologies are used not for integration of heterogeneous resources in traditional way but for parallel analysis of recourses and its related ontologies to achieve the effect of a virtual integration
Correlative visualization techniques for multidimensional data
Critical to the understanding of data is the ability to provide pictorial or visual representation of those data, particularly in support of correlative data analysis. Despite the advancement of visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are other computer science domains outside of computer graphics that are required to make visualization effective such as data management. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformation, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and Earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in data visualization system
GPU-Based Volume Rendering of Noisy Multi-Spectral Astronomical Data
Traditional analysis techniques may not be sufficient for astronomers to make
the best use of the data sets that current and future instruments, such as the
Square Kilometre Array and its Pathfinders, will produce. By utilizing the
incredible pattern-recognition ability of the human mind, scientific
visualization provides an excellent opportunity for astronomers to gain
valuable new insight and understanding of their data, particularly when used
interactively in 3D. The goal of our work is to establish the feasibility of a
real-time 3D monitoring system for data going into the Australian SKA
Pathfinder archive.
Based on CUDA, an increasingly popular development tool, our work utilizes
the massively parallel architecture of modern graphics processing units (GPUs)
to provide astronomers with an interactive 3D volume rendering for
multi-spectral data sets. Unlike other approaches, we are targeting real time
interactive visualization of datasets larger than GPU memory while giving
special attention to data with low signal to noise ratio - two critical aspects
for astronomy that are missing from most existing scientific visualization
software packages. Our framework enables the astronomer to interact with the
geometrical representation of the data, and to control the volume rendering
process to generate a better representation of their datasets.Comment: 4 pages, 1 figure, to appear in the proceedings of ADASS XIX, Oct 4-8
2009, Sapporo, Japan (ASP Conf. Series
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