We consider the problem of efficiently computing a discrete Morse complex on simplicial complexes of arbitrary dimension and very large size. Based on a common graph-based formalism, we analyze existing data structure...
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We consider the problem of efficiently computing a discrete Morse complex on simplicial complexes of arbitrary dimension and very large size. Based on a common graph-based formalism, we analyze existing data structures for simplicial complexes, and we define an efficient encoding for the discrete Morse gradient on the most compact of such representations. We theoretically compare methods based on reductions and coreductions for computing a discrete Morse gradient, proving that the combination of reductions and coreductions produces new mutually equivalent approaches. We design and implement a new algorithm for computing a discrete Morse complex on simplicial complexes. We show that our approach scales very well with the size and the dimension of the simplicial complex also through comparisons with the only existing public-domain algorithm for discrete Morse complex computation. We discuss applications to the computation of multi-parameter persistent homology and of extremum graphs for visualization of time-varying 3D scalar fields.
Particle based model simulations are widely used in scientificvisualization. In cosmology, particles are used to simulate the evolution of dark matter in the universe. Clusters of particles (that have special statist...
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Particle based model simulations are widely used in scientificvisualization. In cosmology, particles are used to simulate the evolution of dark matter in the universe. Clusters of particles (that have special statistical properties) are called halos. From a visualization point of view, halos are clusters of particles, each having a position, mass and velocity in three dimensional space, and they can be represented as point clouds that contain various structures of geometric interest such as filaments, membranes, satellite of points, clusters, and cluster of clusters. The thesis investigates methods for interacting with large scale data-sets represented as point clouds. The work mostly aims at the interactive visualization of cosmological simulation based on large particle systems. The study consists of three components: a) two human factors experiments into the perceptual factors that make it possible to see features in point clouds; b) the design and implementation of a user interface making it possible to rapidly navigate through and visualize features in the point cloud, c) software development and integration to support visualization.
The uPy Python extension module provides a uniform abstraction of the APIs of several 3D computer graphics programs (called hosts), including Blender, Maya, Cinema 4D, and DejaVu. A plug-in written with uPy can run in...
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The uPy Python extension module provides a uniform abstraction of the APIs of several 3D computer graphics programs (called hosts), including Blender, Maya, Cinema 4D, and DejaVu. A plug-in written with uPy can run in all uPy-supported hosts. Using uPy, researchers have created complex plug-ins for molecular and cellular modeling and visualization. uPy can simplify programming for many types of projects (not solely science applications) intended for multihost distribution. It's available at http://***. The first featured Web extra is a video that shows interactive analysis of a calcium dynamics simulation. YouTube URL: http://***/wvs-nWE6ypo. The second featured Web extra is a video that shows rotation of the HIV virus. YouTube URL: http://***/vEOybMaRoKc.
The self-organizing feature map (SOFM) has received great attention from researchers in a variety of areas such as engineering sciences, medicine, biology and economics. The topology of these maps is usually based on ...
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The self-organizing feature map (SOFM) has received great attention from researchers in a variety of areas such as engineering sciences, medicine, biology and economics. The topology of these maps is usually based on 1, 2, or 3 dimensions, forming a lattice. This article discusses various aspects of the spherical SOFMs along with examples illustrating its implementation on high-dimensional data. The main advantage of the spherical SOFM is the ability to visualize complex high-dimensional data by encapsulating physical measures of the data within the 3D attributes of its spherical lattice. The article presents the potential of the spherical SOFM to visualize nonlinear data using examples of two chaotic maps, Henon and Ikeda, with a fractal dimension of 1.2 and 1.7 respectively embedded in 2-5 dimensions.
We present a method for combining multiple point-based constraints in haptic programming environments. Instead of using a single proxy point for haptic feedback, the method maintains a separate proxy for each constrai...
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ISBN:
(纸本)1424402263
We present a method for combining multiple point-based constraints in haptic programming environments. Instead of using a single proxy point for haptic feedback, the method maintains a separate proxy for each constraint. The reaction force is computed by linking the proxies in a chain. Constraints are applied in sequential order, such that the proxy found in the current step becomes the probe for the next step in the chain. The advantage of the method over previous approaches is that the constraints are maintained precisely and the output is well-defined. We illustrate the method with examples from the domain of 3D scientific data visualization. Finally, we present the results of an experiment conducted to quantify the contribution of haptic guidance in two representative vector field exploration tasks.
The depiction of particle trajectories is an effective means for the visualization of fluid flows. However, standard visualization techniques suffer from a variety of weaknesses, ranging from ambiguous depth perceptio...
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The depiction of particle trajectories is an effective means for the visualization of fluid flows. However, standard visualization techniques suffer from a variety of weaknesses, ranging from ambiguous depth perception for simple line drawings to a high geometrical complexity and decreased interactivity for polygonal tubes. This paper addresses these problems by introducing a novel approach to pathline visualization, which we call Virtual Tubelets. It employs billboarding techniques in combination with suitable textures in order to create the illusion of solid tubes, thus efficiently and unambiguously depicting large amounts of particle trajectories at interactive frame rates. By choosing an appropriate orientation for the billboards, certain issues concerning immersive displays with multiple projection screens are resolved, which allows for an unrestricted use in virtual environments as well. Using modern graphics hardware with programmable vertex and pixel pipelines results in an additional speed-up of the rendering process and a further improvement of image quality. This creates a nearly perfect illusion of tubular geometry, including plausible intersections and consistent illumination with the rest of the scene. The efficiency of our approach is proven by comparing rendering speed and visual quality of Virtual Tubelets to that of conventional, polygonal tube renderings. (c) 2004 Elsevier Ltd. All rights reserved.
The depiction of particle trajectories is an effective means for the visualization of fluid flows. However, standard visualization techniques suffer from a variety of weaknesses, ranging from ambiguous depth perceptio...
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The depiction of particle trajectories is an effective means for the visualization of fluid flows. However, standard visualization techniques suffer from a variety of weaknesses, ranging from ambiguous depth perception for simple line drawings to a high geometrical complexity and decreased interactivity for polygonal tubes. This paper addresses these problems by introducing a novel approach to pathline visualization, which we call Virtual Tubelets. It employs billboarding techniques in combination with suitable textures in order to create the illusion of solid tubes, thus efficiently and unambiguously depicting large amounts of particle trajectories at interactive frame rates. By choosing an appropriate orientation for the billboards, certain issues concerning immersive displays with multiple projection screens are resolved, which allows for an unrestricted use in virtual environments as well. Using modern graphics hardware with programmable vertex and pixel pipelines results in an additional speed-up of the rendering process and a further improvement of image quality. This creates a nearly perfect illusion of tubular geometry, including plausible intersections and consistent illumination with the rest of the scene. The efficiency of our approach is proven by comparing rendering speed and visual quality of Virtual Tubelets to that of conventional, polygonal tube renderings. (c) 2004 Elsevier Ltd. All rights reserved.
In this article we explore techniques to detect and visualize features in data from molecular dynamics (MD) simulations. Although the techniques proposed are general, we focus on silicon (Si) atomic systems. The first...
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ISBN:
(纸本)0780387880
In this article we explore techniques to detect and visualize features in data from molecular dynamics (MD) simulations. Although the techniques proposed are general, we focus on silicon (Si) atomic systems. The first set of methods use 3D location of atoms. Defects are detected and categorized using local operators and statistical modeling. Our second set of exploratory techniques employ electron density data. This data is visualized to glean the defects. We describe techniques to automatically detect the salient iso-values for iso-surface extraction and designing transfer functions. We compare and contrast the results obtained from both sources of data. Essentially, we find that the methods of defect (feature) detection are at least as robust as those based on the exploration of electron density for Si systems.
scientific data visualization requires a variety of mathematical techniques to transform multivariate data sets into simple graphical objects, or glyphs, that provide scientists and engineers with a clearer understand...
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scientific data visualization requires a variety of mathematical techniques to transform multivariate data sets into simple graphical objects, or glyphs, that provide scientists and engineers with a clearer understanding of the underlying system behaviour. The spherical self-organizing feature map (SOFM) described in this paper exploits an unsupervised clustering algorithm to map randomly organized N-dimensional data into a lower three-dimensional (3D) space for visual pattern analysis. Each node on the spherical lattice corresponds to a cluster of input vectors that lie in close spatial proximity within the original feature space, and neighbouring nodes on the lattice represent cluster centres with a high degree of vector similarity. Simple metrics are used to extract associations between the cluster units and the input vectors assigned to them. These are then graphically displayed on the spherical SOFM as either surface elevations or colourized facets. The resulting colourized graphical objects are displayed and manipulated within 3D immersive virtual reality (IVR) environments for interactive data analysis. The ability of the proposed algorithm to transform arbitrarily arranged numeric strings into unique, reproducible shapes is illustrated using chaotic data generated by the Lozi, Henon, Rossler, and Lorenz attractor functions under varying initial conditions. Implementation of the basic datavisualization technique is further demonstrated using the more common Wisconsin breast cancer data and multispectral satellite data. (C) 2003 Elsevier Ltd. All rights reserved.
Structure in 4-D data is visualized with a new modeling algorithm called SBP. The SBP vector fusion algorithm makes 3-D display space models of data having any dimensionality that is input in matrix form. SBP maps poi...
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ISBN:
(纸本)0819448095
Structure in 4-D data is visualized with a new modeling algorithm called SBP. The SBP vector fusion algorithm makes 3-D display space models of data having any dimensionality that is input in matrix form. SBP maps points on complete manifolds in 4-D to 3-D to visualize any 4-D data. Starting with familiar shapes in 2-D data, 3-D models are constructed to demonstrate how SBP works. Then 3-D data is modeled in 3-D display space. Finally 4-D data are modeled in 3-D display space. The 3-D display space models are points mapped from collections of points on 4-D manifolds. Two types of SBP models are discussed: the latitude/longitude collection and the helical collection. SBP also maps points on complete manifolds of n-D data to 3-D display space models. The objective of this work is to present what 4-D spheres and tori look like when visualized from 4-D data using the SBP algorithm. This demonstrates the SBP. algorithm as a new and useful tool for visualizing and understanding 4-D data, and by implication, n-D geometry. Future uses for SBP could be modeling and studying protein structure and space-time structure in general relativity and string theory.
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