Analysis and Visualization with yt. Matthew Turk UIUC School of Information Sciences UIUC Astronomy
|
|
- Irma Nicholson
- 5 years ago
- Views:
Transcription
1 Analysis and Visualization with yt Matthew Turk UIUC School of Information Sciences UIUC Astronomy
2 yt-project.org hub.yt
3 Layers of Representation Bit
4 Layers of Representation Data Bit
5 Layers of Representation Model Data Bit
6 yt-project.org Volumetric analysis and visualization
7 Jill Naiman, AJ Christensen, Kalina Borkiewicz ytini.com
8 the yt project Python-based (C, Cython, etc) Community developed NumFOCUS FSA Code of Conduct Governance structure 100+ contributors Volumetric and non-spatial data Used in nearly 300 papers Grids, particles, octrees, and unstructured meshes Arbitrary geometric representations Minimize time to inquiry
9 Ingestion
10 Ingestion Representation
11 Ingestion Representation Analysis
12 Ingestion Representation Analysis Visualization
13 Community Ingestion Representation Analysis Visualization
14 Project Members Kenza Arraki Corentin Cadiou Brian Crosby Bili Dong Hilary Egan Nathan Goldbaum Cameron Hummels Suoqing Ji Allyson Julian Ben Keller Kacper Kowalik Sam Leitner Alex Lindsay Chris Malone Andrew Myers Jill Naiman Jeff Oishi Brian O'Shea Douglas Rudd Anthony Scopatz Sam Skillman Stephen Skory Britton Smith Casey Stark Matthew Turk John Wise Michael Zingale John ZuHone About 100 contributors...
15 D
16 yt D
17 Some Simulation
18 Layers of Representation Model Data Bit
19
20
21
22
23
24
25
26
27 ART ARTIO Athena Carpet Castro Chombo Eagle Enzo ExodusII FITS FLASH Gadget Gadget-FOF Gasoline GDF Maestro MOAB Nyx OWLS OWLS-Subfind PKDGrav PLUTO RAMSES Rockstar SDF Stream HTTP Stream Grids Stream Octree Stream Particles Stream Unstructured
28 ART ARTIO Athena Carpet Castro Chombo Eagle Enzo ExodusII FITS FLASH Gadget Gadget-FOF Gasoline GDF Maestro MOAB Nyx OWLS OWLS-Subfind PKDGrav PLUTO RAMSES Rockstar SDF Stream HTTP Stream Grids Stream Octree Stream Particles Stream Unstructured
29 ART ARTIO Athena Carpet Castro Chombo Eagle Enzo ExodusII FITS FLASH Gadget Gadget-FOF Gasoline GDF Maestro MOAB Nyx OWLS OWLS-Subfind PKDGrav PLUTO RAMSES Rockstar SDF Stream HTTP Stream Grids Stream Octree Stream Particles Stream Unstructured
30 ART ARTIO Athena Carpet Castro Chombo Eagle Enzo ExodusII FITS FLASH Gadget Gadget-FOF Gasoline GDF Maestro MOAB Nyx OWLS OWLS-Subfind PKDGrav PLUTO RAMSES Rockstar SDF Stream HTTP Stream Grids Stream Octree Stream Particles Stream Unstructured
31 ART ARTIO Athena Carpet Castro Chombo Eagle Enzo ExodusII FITS FLASH Gadget Gadget-FOF Gasoline GDF Maestro MOAB Nyx OWLS OWLS-Subfind PKDGrav PLUTO RAMSES Rockstar SDF Stream HTTP Stream Grids Stream Octree Stream Particles Stream Unstructured
32 Some Simulation
33 Some Selector Simulation
34 Selected
35 Selected D
36 Layers of Representation Model Data Bit
37 Low-Level Operations
38 Low-Level Operations
39 Low-Level Operations Chunk Chunk Chunk Chunk Chunk Chunk Chunk Chunk Chunk
40 Selected unk Chunk Chunk Chunk Chunk Chunk Chunk Chunk C
41 Low-Level Operations Chunk
42 Low-Level Operations Chunk
43 Low-Level Operations Chunk Chunk Chunk Chunk Chunk Chunk Chunk Chunk Chunk Chunk
44 Low-Level Operations Cells Chunk Chunk Chunk Particles Chunk Chunk Chunk Chunk Chunk Chunk Elements
45 Layers of Representation Model Data Bit
46 Data Representation Coordinate Handling Cartesian Cylindrical Spherical (geographic, tomographic) Symbolic Units Derived fields Dependency calculation Arithmetic and spatial
47 Fields Representation of state.
48 Fields Representation of state. Name Units Context Prescription
49 Fields Representation of state. Primitive
50 Fields Representation of state. Primitive Derived
51 Fields Arithmetic Operations E = mv2 2
52 Fields Arithmetic units="erg") def energy(field, data): E = 0.5 * (data["mass"] * data["velocity_magnitude"]**2) return E
53 Fields Spatial Operations div V = δv x + δv y + δv z δx δy δz
54 Fields Spatial units="1/s", validators=[validatespatial(1)]) def divergence(field, data): dx = data["index", "dx"] dy = data["index", "dy"] dz = data["index", "dz"] f = data["velocity_x"][sl_r,1:-1,1:-1]/ds f -= data["velocity_x"][sl_l,1:-1,1:-1]/ds f += data["velocity_y"][1:-1,sl_r,1:-1]/ds f -= data["velocity_y"][1:-1,sl_l,1:-1]/ds f += data["velocity_z"][1:-1,1:-1,sl_r]/ds f -= data["velocity_z"][1:-1,1:-1,sl_l ]/ds return f
55 Mid-Level Operations x =
56 Mid-Level Operations x = m s -1 m/s
57 Mid-Level Operations m x s -1 = m/s Symbolic manipulation and pragmatic ontologies
58 Semantically-meaningful Data x = m s -1 m/s Symbolic manipulation and pragmatic ontologies
59 Semantically-meaningful Data m x s -1 = m/s Symbolic manipulation and pragmatic ontologies
60
61 43 primitive fields 363 derived fields 35 distinct units 2.5 primitive fields per derived
62 High-Level Operations Chunk
63 High-Level Operations Chunk
64 High-Level Operations Chunk
65 High-Level Operations Chunk Chunk Chunk Chunk Chunk Chunk Chunk Chunk Chunk
66 Imaging and volume tools Volumetric segmentation Parallel Irregular resolution data Marching cubes Ray-tracing Radiative transfer Volume rendering Rasterization / pixelization Coordinate systems Discretization
67
68
69 Time Location
70 Time Location
71 Time Location
72 Time Location
73 Temperature Density Turk et al 2009
74
75 Disk Simulation
76 Simulation libyt Disk Analysis Hsi-Yu Schive
77 f(x,y,z) First Order Alex Lindsay, Andrew Myers
78 Second Order Alex Lindsay, Andrew Myers
79 Approximate Second Order Alex Lindsay, Andrew Myers
80 Approximate Second Order Alex Lindsay, Andrew Myers
81 Compressed bitmap indices
82 Compressed bitmap indices
83 Compressed bitmap indices Spatial Tree
84 Compressed bitmap indices Lang & Turk, 2016
85 Community Not the biggest, not the smallest, but active 375 on the users mailing list 115 on the dev mailing list Code Peer review Mentorship Continuous testing system
86 Community How can we increase diversity? How can we foster careers? How can we lower barriers?
87 What are our core values?
88 Technically Easy Socially Challenging Socially Easy Technically Challenging
89 Functional Detrimental Humanitarian Problematic
90 product versus project
91 product versus project
92 product versus project
93 product versus project the thing
94 product versus project the people
95 Thank you
96 Three Options: $ docker pull xarthisius/ythub-jupyter $ docker run --rm -ti -p 8888:8888 xarthisius/ythub-jupyter $ conda install -c conda-forge yt yt-project.org and click on Get yt
Volumes with yt. Matthew Turk Columbia University
Volumes with yt Matthew Turk Columbia University Exascale is made of people! - Mike Warren, 2014 Scientific Inquiry Analyzing Data Running Simulations Run Study 10% 90% 10% 90% Dekel s Law Data yt Data
More informationVisualization Challenges for Large Scale Astrophysical Simulation Data. Ultrascale Visualization Workshop
Visualization Challenges for Large Scale Astrophysical Simulation Data Ralf Kähler (KIPAC/SLAC) Tom Abel (KIPAC/Stanford) Marcelo Alvarez (CITA) Oliver Hahn (Stanford) Hans-Christian Hege (ZIB) Ji-hoon
More informationLecture notes: Object modeling
Lecture notes: Object modeling One of the classic problems in computer vision is to construct a model of an object from an image of the object. An object model has the following general principles: Compact
More informationIsosurface Rendering. CSC 7443: Scientific Information Visualization
Isosurface Rendering What is Isosurfacing? An isosurface is the 3D surface representing the locations of a constant scalar value within a volume A surface with the same scalar field value Isosurfaces form
More informationMODELLING-Representing space and time in a numerical model
MODELLING-Representing space and time in a numerical model Simulation parameters When setting up any simulation, whether computer-based or to be computed manually, it is important to identify the parameters
More informationPREPARING AN AMR LIBRARY FOR SUMMIT. Max Katz March 29, 2018
PREPARING AN AMR LIBRARY FOR SUMMIT Max Katz March 29, 2018 CORAL: SIERRA AND SUMMIT NVIDIA Volta fueling supercomputers IBM Power 9 + NVIDIA Volta V100 Sierra (LLNL): 4 GPUs/node, ~4300 nodes Summit (ORNL):
More informationImplicit Surfaces & Solid Representations COS 426
Implicit Surfaces & Solid Representations COS 426 3D Object Representations Desirable properties of an object representation Easy to acquire Accurate Concise Intuitive editing Efficient editing Efficient
More informationEnzo-P / Cello. Formation of the First Galaxies. San Diego Supercomputer Center. Department of Physics and Astronomy
Enzo-P / Cello Formation of the First Galaxies James Bordner 1 Michael L. Norman 1 Brian O Shea 2 1 University of California, San Diego San Diego Supercomputer Center 2 Michigan State University Department
More informationComputer Graphics: Graphics Output Primitives Line Drawing Algorithms
Computer Graphics: Graphics Output Primitives Line Drawing Algorithms By: A. H. Abdul Hafez Abdul.hafez@hku.edu.tr, 1 Outlines 1. Basic concept of lines in OpenGL 2. Line Equation 3. DDA Algorithm 4. DDA
More informationParallel Algorithms: Adaptive Mesh Refinement (AMR) method and its implementation
Parallel Algorithms: Adaptive Mesh Refinement (AMR) method and its implementation Massimiliano Guarrasi m.guarrasi@cineca.it Super Computing Applications and Innovation Department AMR - Introduction Solving
More informationVolume Visualization
Volume Visualization Part 1 (out of 3) Overview: Volume Visualization Introduction to volume visualization On volume data Surface vs. volume rendering Overview: Techniques Simple methods Slicing, cuberille
More informationCosmology Simulations with Enzo
Cosmology Simulations with Enzo John Wise (Georgia Tech) Enzo Workshop 17 Oct 2013 Outline Introduction to unigrid cosmology simulations Introduction to nested grid cosmology simulations Using different
More informationGadget in yt. christopher erick moody
Gadget in yt First of all, hello, and thank you for giving me the opp to speak My name is chris moody and I m a grad student here at uc santa cruz and I ve been working with Joel for the last year and
More informationDirect Volume Rendering
Direct Volume Rendering CMPT 467/767 Visualization Torsten Möller Weiskopf/Machiraju/Möller Overview Volume rendering equation Compositing schemes Ray casting Acceleration techniques for ray casting Texture-based
More informationOverview of Traditional Surface Tracking Methods
Liquid Simulation With Mesh-Based Surface Tracking Overview of Traditional Surface Tracking Methods Matthias Müller Introduction Research lead of NVIDIA PhysX team PhysX GPU acc. Game physics engine www.nvidia.com\physx
More informationIntroduction to Mobile Robotics Techniques for 3D Mapping
Introduction to Mobile Robotics Techniques for 3D Mapping Wolfram Burgard, Michael Ruhnke, Bastian Steder 1 Why 3D Representations Robots live in the 3D world. 2D maps have been applied successfully for
More informationContours & Implicit Modelling 4
Brief Recap Contouring & Implicit Modelling Contouring Implicit Functions Visualisation Lecture 8 lecture 6 Marching Cubes lecture 3 visualisation of a Quadric toby.breckon@ed.ac.uk Computer Vision Lab.
More informationOverview of 3D Object Representations
Overview of 3D Object Representations Thomas Funkhouser Princeton University C0S 597D, Fall 2003 3D Object Representations What makes a good 3D object representation? Stanford and Hearn & Baker 1 3D Object
More informationarxiv: v1 [astro-ph.im] 15 Nov 2010
Draft version November 17, 2010 Preprint typeset using L A TEX style emulateapj v. 11/10/09 YT: A MULTI-CODE ANALYSIS TOOLKIT FOR ASTROPHYSICAL SIMULATION DATA Matthew J. Turk 1, Britton D. Smith 2, Jeffrey
More informationCS Rasterization. Junqiao Zhao 赵君峤
CS10101001 Rasterization Junqiao Zhao 赵君峤 Department of Computer Science and Technology College of Electronics and Information Engineering Tongji University Vector Graphics Algebraic equations describe
More informationRealistic Animation of Fluids
Realistic Animation of Fluids p. 1/2 Realistic Animation of Fluids Nick Foster and Dimitri Metaxas Realistic Animation of Fluids p. 2/2 Overview Problem Statement Previous Work Navier-Stokes Equations
More informationComputational Astrophysics 5 Higher-order and AMR schemes
Computational Astrophysics 5 Higher-order and AMR schemes Oscar Agertz Outline - The Godunov Method - Second-order scheme with MUSCL - Slope limiters and TVD schemes - Characteristics tracing and 2D slopes.
More informationIndirect Volume Rendering
Indirect Volume Rendering Visualization Torsten Möller Weiskopf/Machiraju/Möller Overview Contour tracing Marching cubes Marching tetrahedra Optimization octree-based range query Weiskopf/Machiraju/Möller
More informationOverview of 3D Object Representations
Overview of 3D Object Representations Thomas Funkhouser Princeton University C0S 426, Fall 2000 Course Syllabus I. Image processing II. Rendering III. Modeling IV. Animation Image Processing (Rusty Coleman,
More informationTHE TANGENT PLANE 6.1 INTRODUCTION TO THE TANGENT PLANE CHAPTER 6:
CHAPTER 6: THE TANGENT PLANE 6.1 INTRODUCTION TO THE TANGENT PLANE The following diagram contains the graph of the function y = x 2 and the graph of its tangent line at the point (1, 1) With these graphs,
More information3D Modeling: Solid Models
CS 430/536 Computer Graphics I 3D Modeling: Solid Models Week 9, Lecture 18 David Breen, William Regli and Maxim Peysakhov Geometric and Intelligent Computing Laboratory Department of Computer Science
More information3D Modeling I. CG08b Lior Shapira Lecture 8. Based on: Thomas Funkhouser,Princeton University. Thomas Funkhouser 2000
3D Modeling I CG08b Lior Shapira Lecture 8 Based on: Thomas Funkhouser,Princeton University Course Syllabus I. Image processing II. Rendering III. Modeling IV. Animation Image Processing (Rusty Coleman,
More informationTHE TANGENT PLANE 6.1 INTRODUCTION TO THE TANGENT PLANE CHAPTER 6:
CHAPTER 6: THE TANGENT PLANE 6.1 INTRODUCTION TO THE TANGENT PLANE The following diagram contains the graph of the function y = x 2 and the graph of its tangent line at the point (1, 1) With these graphs,
More informationTópicos de Computação Gráfica Topics in Computer Graphics 10509: Doutoramento em Engenharia Informática. Chap. 2 Rasterization.
Tópicos de Computação Gráfica Topics in Computer Graphics 10509: Doutoramento em Engenharia Informática Chap. 2 Rasterization Rasterization Outline : Raster display technology. Basic concepts: pixel, resolution,
More informationWho has worked on a voxel engine before? Who wants to? My goal is to give the talk I wish I would have had before I started on our procedural engine.
1 Who has worked on a voxel engine before? Who wants to? My goal is to give the talk I wish I would have had before I started on our procedural engine. Three parts to this talk. A lot of content, so I
More informationCPSC GLOBAL ILLUMINATION
CPSC 314 21 GLOBAL ILLUMINATION Textbook: 20 UGRAD.CS.UBC.CA/~CS314 Mikhail Bessmeltsev ILLUMINATION MODELS/ALGORITHMS Local illumination - Fast Ignore real physics, approximate the look Interaction of
More information3D Reconstruction with Tango. Ivan Dryanovski, Google Inc.
3D Reconstruction with Tango Ivan Dryanovski, Google Inc. Contents Problem statement and motivation The Tango SDK 3D reconstruction - data structures & algorithms Applications Developer tools Problem formulation
More informationApplication of Two Rendering Techniques in the Visualization of 3D Geospatial Data
Available online at www.sciencedirect.com Procedia Environmental Sciences 12 (2012 ) 1432 1439 2011 International Conference on Environmental Science and Engineering (ICESE 2011) Application of Two Rendering
More informationEAT 233/3 GEOGRAPHIC INFORMATION SYSTEM (GIS)
EAT 233/3 GEOGRAPHIC INFORMATION SYSTEM (GIS) CO3: Ability to produce detail mapping using geographic information systems (GIS) BY : AYU WAZIRA AZHARI SPATIAL DATA & THE MODELLING Spatial Data in GIS Spatial
More informationScalar Algorithms: Contouring
Scalar Algorithms: Contouring Computer Animation and Visualisation Lecture tkomura@inf.ed.ac.uk Institute for Perception, Action & Behaviour School of Informatics Contouring Scaler Data Last Lecture...
More informationSurface Reconstruction. Gianpaolo Palma
Surface Reconstruction Gianpaolo Palma Surface reconstruction Input Point cloud With or without normals Examples: multi-view stereo, union of range scan vertices Range scans Each scan is a triangular mesh
More informationComputer Graphics and Visualization. What is computer graphics?
CSCI 120 Computer Graphics and Visualization Shiaofen Fang Department of Computer and Information Science Indiana University Purdue University Indianapolis What is computer graphics? Computer graphics
More informationShape Representation Basic problem We make pictures of things How do we describe those things? Many of those things are shapes Other things include
Shape Representation Basic problem We make pictures of things How do we describe those things? Many of those things are shapes Other things include motion, behavior Graphics is a form of simulation and
More informationContents. What is yt? Installing yt Using yt > yt from the command line. yt with the ipython notebook. scripting yt. yt s Cookbook
YT An introduction Contents What is yt? Installing yt Using yt > yt from the command line yt with the ipython notebook scripting yt yt s Cookbook What is yt? simulation data yt images plots Enzo Flash
More informationVisualization Computer Graphics I Lecture 20
15-462 Computer Graphics I Lecture 20 Visualization Height Fields and Contours Scalar Fields Volume Rendering Vector Fields [Angel Ch. 12] November 20, 2003 Doug James Carnegie Mellon University http://www.cs.cmu.edu/~djames/15-462/fall03
More informationCSG obj. oper3. obj1 obj2 obj3. obj5. obj4
Solid Modeling Solid: Boundary + Interior Volume occupied by geometry Solid representation schemes Constructive Solid Geometry (CSG) Boundary representations (B-reps) Space-partition representations Operations
More informationScalar Visualization
Scalar Visualization Visualizing scalar data Popular scalar visualization techniques Color mapping Contouring Height plots outline Recap of Chap 4: Visualization Pipeline 1. Data Importing 2. Data Filtering
More informationarxiv: v2 [cs.gr] 1 Nov 2018
DRAFT VERSION NOVEMBER 5, 2018 Preprint typeset using LATEX style emulateapj v. 12/16/11 CINEMATIC VISUALIZATION OF MULTIRESOLUTION DATA: YTINI FOR ADAPTIVE MESH REFINEMENT IN HOUDINI KALINA BORKIEWICZ
More informationComputer Graphics. Bing-Yu Chen National Taiwan University The University of Tokyo
Computer Graphics Bing-Yu Chen National Taiwan University The University of Tokyo Hidden-Surface Removal Back-Face Culling The Depth-Sort Algorithm Binary Space-Partitioning Trees The z-buffer Algorithm
More informationRay Tracing Acceleration Data Structures
Ray Tracing Acceleration Data Structures Sumair Ahmed October 29, 2009 Ray Tracing is very time-consuming because of the ray-object intersection calculations. With the brute force method, each ray has
More informationGeographic Surfaces. David Tenenbaum EEOS 383 UMass Boston
Geographic Surfaces Up to this point, we have talked about spatial data models that operate in two dimensions How about the rd dimension? Surface the continuous variation in space of a third dimension
More informationUsing GADGET-2 for cosmological simulations - Background -
Using GADGET-2 for cosmological simulations - Background - 3 Phases of Running a Cosmological Simulation I. Generate Initial Conditions II. Run Simulation Performing a numerical integral III.Analysis Halo
More informationParticle-Based Volume Rendering of Unstructured Volume Data
Particle-Based Volume Rendering of Unstructured Volume Data Takuma KAWAMURA 1)*) Jorji NONAKA 3) Naohisa SAKAMOTO 2),3) Koji KOYAMADA 2) 1) Graduate School of Engineering, Kyoto University 2) Center for
More informationComputer Graphics. Bing-Yu Chen National Taiwan University
Computer Graphics Bing-Yu Chen National Taiwan University Visible-Surface Determination Back-Face Culling The Depth-Sort Algorithm Binary Space-Partitioning Trees The z-buffer Algorithm Scan-Line Algorithm
More informationVisualization. Images are used to aid in understanding of data. Height Fields and Contours Scalar Fields Volume Rendering Vector Fields [chapter 26]
Visualization Images are used to aid in understanding of data Height Fields and Contours Scalar Fields Volume Rendering Vector Fields [chapter 26] Tumor SCI, Utah Scientific Visualization Visualize large
More informationL1 - Introduction. Contents. Introduction of CAD/CAM system Components of CAD/CAM systems Basic concepts of graphics programming
L1 - Introduction Contents Introduction of CAD/CAM system Components of CAD/CAM systems Basic concepts of graphics programming 1 Definitions Computer-Aided Design (CAD) The technology concerned with the
More informationAdaptive Refinement Tree (ART) code. N-Body: Parallelization using OpenMP and MPI
Adaptive Refinement Tree (ART) code N-Body: Parallelization using OpenMP and MPI 1 Family of codes N-body: OpenMp N-body: MPI+OpenMP N-body+hydro+cooling+SF: OpenMP N-body+hydro+cooling+SF: MPI 2 History:
More informationVolume Visualization. Volume Data. Volume Data. Tutorials Applied Visualizaton Summer Term 2009 Part VII - 3D Scalar Fields
Tutorials Applied Visualizaton Summer Term 2009 Part VII - 3D Scalar Fields 3D Scalar Fields Essential information in the interior Can not be described by geometric representation Fire, clouds, gaseous
More informationComputer Science 426 Midterm 3/11/04, 1:30PM-2:50PM
NAME: Login name: Computer Science 46 Midterm 3//4, :3PM-:5PM This test is 5 questions, of equal weight. Do all of your work on these pages (use the back for scratch space), giving the answer in the space
More informationContours & Implicit Modelling 1
Contouring & Implicit Modelling Visualisation Lecture 8 Institute for Perception, Action & Behaviour School of Informatics Contours & Implicit Modelling 1 Brief Recap Contouring Implicit Functions lecture
More informationVolume visualization. Volume visualization. Volume visualization methods. Sources of volume visualization. Sources of volume visualization
Volume visualization Volume visualization Volumes are special cases of scalar data: regular 3D grids of scalars, typically interpreted as density values. Each data value is assumed to describe a cubic
More informationRay Tracing with Spatial Hierarchies. Jeff Mahovsky & Brian Wyvill CSC 305
Ray Tracing with Spatial Hierarchies Jeff Mahovsky & Brian Wyvill CSC 305 Ray Tracing Flexible, accurate, high-quality rendering Slow Simplest ray tracer: Test every ray against every object in the scene
More informationThe Level Set Method. Lecture Notes, MIT J / 2.097J / 6.339J Numerical Methods for Partial Differential Equations
The Level Set Method Lecture Notes, MIT 16.920J / 2.097J / 6.339J Numerical Methods for Partial Differential Equations Per-Olof Persson persson@mit.edu March 7, 2005 1 Evolving Curves and Surfaces Evolving
More informationAbout Phoenix FD PLUGIN FOR 3DS MAX AND MAYA. SIMULATING AND RENDERING BOTH LIQUIDS AND FIRE/SMOKE. USED IN MOVIES, GAMES AND COMMERCIALS.
About Phoenix FD PLUGIN FOR 3DS MAX AND MAYA. SIMULATING AND RENDERING BOTH LIQUIDS AND FIRE/SMOKE. USED IN MOVIES, GAMES AND COMMERCIALS. Phoenix FD core SIMULATION & RENDERING. SIMULATION CORE - GRID-BASED
More informationData Representation in Visualisation
Data Representation in Visualisation Visualisation Lecture 4 Taku Komura Institute for Perception, Action & Behaviour School of Informatics Taku Komura Data Representation 1 Data Representation We have
More informationAREPO: a moving-mesh code for cosmological hydrodynamical simulations
AREPO: a moving-mesh code for cosmological hydrodynamical simulations E pur si muove: Galiliean-invariant cosmological hydrodynamical simulations on a moving mesh Springel, 2010 arxiv:0901.4107 Rubens
More information1. Interpreting the Results: Visualization 1
1. Interpreting the Results: Visualization 1 visual/graphical/optical representation of large sets of data: data from experiments or measurements: satellite images, tomography in medicine, microsopy,...
More informationCGT 581 G Fluids. Overview. Some terms. Some terms
CGT 581 G Fluids Bedřich Beneš, Ph.D. Purdue University Department of Computer Graphics Technology Overview Some terms Incompressible Navier-Stokes Boundary conditions Lagrange vs. Euler Eulerian approaches
More informationThe meshfree computation of stationary electric current densities in complex shaped conductors using 3D boundary element methods
Boundary Elements and Other Mesh Reduction Methods XXXVII 121 The meshfree computation of stationary electric current densities in complex shaped conductors using 3D boundary element methods A. Buchau
More informationVisualization Tools for Adaptive Mesh Refinement Data
Visualization Tools for Adaptive Mesh Refinement Data Gunther H. Weber 1, Vincent E. Beckner 1, Hank Childs 2, Terry J. Ligocki 1, Mark C. Miller 2, Brian Van Straalen 1 and E. Wes Bethel 1 1 Lawrence
More informationParallel Programming for Graphics
Beyond Programmable Shading Course ACM SIGGRAPH 2010 Parallel Programming for Graphics Aaron Lefohn Advanced Rendering Technology (ART) Intel What s In This Talk? Overview of parallel programming models
More informationSolid Modelling. Graphics Systems / Computer Graphics and Interfaces COLLEGE OF ENGINEERING UNIVERSITY OF PORTO
Solid Modelling Graphics Systems / Computer Graphics and Interfaces 1 Solid Modelling In 2D, one set 2D line segments or curves does not necessarily form a closed area. In 3D, a collection of surfaces
More informationProgramming Fundamentals
Programming Fundamentals Lecture 03 Introduction to Löve 2D Edirlei Soares de Lima Computer Graphics Concepts What is a pixel? In digital imaging, a pixel is a single
More informationSolid Modeling. Thomas Funkhouser Princeton University C0S 426, Fall Represent solid interiors of objects
Solid Modeling Thomas Funkhouser Princeton University C0S 426, Fall 2000 Solid Modeling Represent solid interiors of objects Surface may not be described explicitly Visible Human (National Library of Medicine)
More informationGeometric Representations. Stelian Coros
Geometric Representations Stelian Coros Geometric Representations Languages for describing shape Boundary representations Polygonal meshes Subdivision surfaces Implicit surfaces Volumetric models Parametric
More informationComputer Graphics Ray Casting. Matthias Teschner
Computer Graphics Ray Casting Matthias Teschner Outline Context Implicit surfaces Parametric surfaces Combined objects Triangles Axis-aligned boxes Iso-surfaces in grids Summary University of Freiburg
More informationRasterization. Rasterization (scan conversion) Digital Differential Analyzer (DDA) Rasterizing a line. Digital Differential Analyzer (DDA)
CSCI 420 Computer Graphics Lecture 14 Rasterization Jernej Barbic University of Southern California Scan Conversion Antialiasing [Angel Ch. 6] Rasterization (scan conversion) Final step in pipeline: rasterization
More information3D Object Representation. Michael Kazhdan ( /657)
3D Object Representation Michael Kazhdan (601.457/657) 3D Objects How can this object be represented in a computer? 3D Objects This one? H&B Figure 10.46 3D Objects This one? H&B Figure 9.9 3D Objects
More information11/1/13. Visualization. Scientific Visualization. Types of Data. Height Field. Contour Curves. Meshes
CSCI 420 Computer Graphics Lecture 26 Visualization Height Fields and Contours Scalar Fields Volume Rendering Vector Fields [Angel Ch. 2.11] Jernej Barbic University of Southern California Scientific Visualization
More informationVisualization. CSCI 420 Computer Graphics Lecture 26
CSCI 420 Computer Graphics Lecture 26 Visualization Height Fields and Contours Scalar Fields Volume Rendering Vector Fields [Angel Ch. 11] Jernej Barbic University of Southern California 1 Scientific Visualization
More information3D Representation and Solid Modeling
MCS 585/480 Computer Graphics I 3D Representation and Solid Modeling Week 8, Lecture 16 William Regli and Maxim Peysakhov Geometric and Intelligent Computing Laboratory Department of Computer Science Drexel
More information9. Three Dimensional Object Representations
9. Three Dimensional Object Representations Methods: Polygon and Quadric surfaces: For simple Euclidean objects Spline surfaces and construction: For curved surfaces Procedural methods: Eg. Fractals, Particle
More informationCSI31 Introduction to Computer Programming I. Dr. Sharon Persinger Fall
CSI31 Introduction to Computer Programming I Dr. Sharon Persinger Fall 2018 1 Overview Basic definitions: Computer Computer science Algorithm Programming language What is a computer? A modern computer
More informationPart I: Theoretical Background and Integration-Based Methods
Large Vector Field Visualization: Theory and Practice Part I: Theoretical Background and Integration-Based Methods Christoph Garth Overview Foundations Time-Varying Vector Fields Numerical Integration
More informationHexahedral Mesh Generation for Volumetric Image Data
Hexahedral Mesh Generation for Volumetric Image Data Jason Shepherd University of Utah March 27, 2006 Outline Hexahedral Constraints Topology Boundary Quality Zhang et al. papers Smoothing/Quality Existing
More informationSoft Shadow Volumes for Ray Tracing Samuli Laine, Timo Aila, Ulf Assarsson, Jaakko Lethinen, Tomas Akenine-Möller presented by Manuel Lang
Soft Shadow Volumes for Ray Tracing Samuli Laine, Timo Aila, Ulf Assarsson, Jaakko Lethinen, Tomas Akenine-Möller presented by Manuel Lang 1 Outline of this presentation Introduction to Soft-Shadows Soft-Shadows
More information- Volume Rendering -
Computer Graphics - Volume Rendering - Pascal Grittmann Using pictures from: Monte Carlo Methods for Physically Based Volume Rendering; SIGGRAPH 2018 Course; Jan Novák, Iliyan Georgiev, Johannes Hanika,
More informationGIS Data Models. 4/9/ GIS Data Models
GIS Data Models 1 Conceptual models of the real world The real world can be described using two conceptually different models: 1. As discrete objects, possible to represent as points, lines or polygons.
More informationInteractive Isosurface Ray Tracing of Large Octree Volumes
Interactive Isosurface Ray Tracing of Large Octree Volumes Aaron Knoll, Ingo Wald, Steven Parker, and Charles Hansen Scientific Computing and Imaging Institute University of Utah 2006 IEEE Symposium on
More information3D Deep Learning on Geometric Forms. Hao Su
3D Deep Learning on Geometric Forms Hao Su Many 3D representations are available Candidates: multi-view images depth map volumetric polygonal mesh point cloud primitive-based CAD models 3D representation
More informationRepresenting Geography
Data models and axioms Chapters 3 and 7 Representing Geography Road map Representing the real world Conceptual models: objects vs fields Implementation models: vector vs raster Vector topological model
More informationSolid Modeling. Michael Kazhdan ( /657) HB , FvDFH 12.1, 12.2, 12.6, 12.7 Marching Cubes, Lorensen et al.
Solid Modeling Michael Kazhdan (601.457/657) HB 10.15 10.17, 10.22 FvDFH 12.1, 12.2, 12.6, 12.7 Marching Cubes, Lorensen et al. 1987 Announcement OpenGL review session: When: Today @ 9:00 PM Where: Malone
More informationDATA MODELS IN GIS. Prachi Misra Sahoo I.A.S.R.I., New Delhi
DATA MODELS IN GIS Prachi Misra Sahoo I.A.S.R.I., New Delhi -110012 1. Introduction GIS depicts the real world through models involving geometry, attributes, relations, and data quality. Here the realization
More informationRenderer Implementation: Basics and Clipping. Overview. Preliminaries. David Carr Virtual Environments, Fundamentals Spring 2005
INSTITUTIONEN FÖR SYSTEMTEKNIK LULEÅ TEKNISKA UNIVERSITET Renderer Implementation: Basics and Clipping David Carr Virtual Environments, Fundamentals Spring 2005 Feb-28-05 SMM009, Basics and Clipping 1
More informationHomework 1: Implicit Surfaces, Collision Detection, & Volumetric Data Structures. Loop Subdivision. Loop Subdivision. Questions/Comments?
Homework 1: Questions/Comments? Implicit Surfaces,, & Volumetric Data Structures Loop Subdivision Shirley, Fundamentals of Computer Graphics Loop Subdivision SIGGRAPH 2000 course notes Subdivision for
More informationVolume Visualization. Part 1 (out of 3) Volume Data. Where do the data come from? 3D Data Space How are volume data organized?
Volume Data Volume Visualization Part 1 (out of 3) Where do the data come from? Medical Application Computed Tomographie (CT) Magnetic Resonance Imaging (MR) Materials testing Industrial-CT Simulation
More informationHybrid Rendering for Collaborative, Immersive Virtual Environments
Hybrid Rendering for Collaborative, Immersive Virtual Environments Stephan Würmlin wuermlin@inf.ethz.ch Outline! Rendering techniques GBR, IBR and HR! From images to models! Novel view generation! Putting
More informationImage Acquisition + Histograms
Image Processing - Lesson 1 Image Acquisition + Histograms Image Characteristics Image Acquisition Image Digitization Sampling Quantization Histograms Histogram Equalization What is an Image? An image
More informationImage-Space-Parallel Direct Volume Rendering on a Cluster of PCs
Image-Space-Parallel Direct Volume Rendering on a Cluster of PCs B. Barla Cambazoglu and Cevdet Aykanat Bilkent University, Department of Computer Engineering, 06800, Ankara, Turkey {berkant,aykanat}@cs.bilkent.edu.tr
More informationReview of Cartographic Data Types and Data Models
Review of Cartographic Data Types and Data Models GIS Data Models Raster Versus Vector in GIS Analysis Fundamental element used to represent spatial features: Raster: pixel or grid cell. Vector: x,y coordinate
More information8 Special Models for Animation. Chapter 8. Special Models for Animation. Department of Computer Science and Engineering 8-1
Special Models for Animation 8-1 L-Systems 8-2 L-Systems Branching Structures Botany Display geometric substitution turtle graphics Animating plants, animals 8-3 Plant examples http://algorithmicbotany.org/papers/#abop
More informationWhat is visualization? Why is it important?
What is visualization? Why is it important? What does visualization do? What is the difference between scientific data and information data Visualization Pipeline Visualization Pipeline Overview Data acquisition
More informationPoint Cloud Filtering using Ray Casting by Eric Jensen 2012 The Basic Methodology
Point Cloud Filtering using Ray Casting by Eric Jensen 01 The Basic Methodology Ray tracing in standard graphics study is a method of following the path of a photon from the light source to the camera,
More informationGPU-based Distributed Behavior Models with CUDA
GPU-based Distributed Behavior Models with CUDA Courtesy: YouTube, ISIS Lab, Universita degli Studi di Salerno Bradly Alicea Introduction Flocking: Reynolds boids algorithm. * models simple local behaviors
More information- Volume Rendering -
Computer Graphics - Volume Rendering - Pascal Grittmann, Jaroslav Křivánek Using pictures from: Monte Carlo Methods for Physically Based Volume Rendering; SIGGRAPH 2018 Course; Jan Novák, Iliyan Georgiev,
More information