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Implementation4.5. Implementation of SoBaseGrid85
Implementation4.5. Implementation of SoBaseGridSoStructuredGrid2D NodesSoStructuredGrid2D SoStructuredGrid → SoBaseGrid → SoNode → . . .SoCurvilinearGrid2D Each face contains of 4 vertices. The edges can be aligned in any angle.SoRectangularGrid2D Each face contains of 4 vertices. Each adjacent edge is orthogonal to each other.SoRegularSpacedRectangularGrid2D The spacing is constant for each principal direction. This is also known as Cartesiangrid [Wal95] (see figure 4.12a) on page 84).SoIrregularSpacedRectangularGrid2D Same as a Cartesian grid, but the spacing may differ for all faces per row and percolumn. (see figure 4.12b) on page 84).SoRadialGrid2DSoCylindricGrid2D This grid is the 2D shell of a cylinder in 3D (see figure 4.17 on page 90). Parametersare the radius and the height of the cylinder.SoRegularSpacedCylindricalGrid2D The spacing of the grid is constant like the SoRegularSpacedRectangularGrid2D(see figure 4.13 on page 89).SoIrregularSpacedCylindricalGrid2D The spacing of the grid is variable like the SoIrregularSpacedRectangularGrid2DSoPolarGrid2D Top surface of a cylinder in 3D. Identical to the polar coordinate system in 2D.The inner radius may be zero.SoRegularSpacedPolarGrid2D The radius increment is constant as well as the angular increment. (see figure4.14a) on page 89)SoIrregularSpacedPolarGrid2D The radius increment is variable and the angular increment is also variable. (seefigure 4.14b) on page 89)SoSphericalGrid2D Surface of a sphere with constant radius. Two variables are mapped to angularazimuth and angular altitude (see one layer in figure 4.18 on page 90).SoRegularSpacedSphericalGrid2D The angular azimuth increment and the angular altitude increment are constant.SoIrregularSpacedSphericalGrid2D The angular azimuth increment and the angular altitude increment are variable.86
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D I P L O M A R B E I TCash FlowA V
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KurzfassungDie Fusionierung von Vis
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3.7.2 Drawback of the Virtual Array
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Introductionis then executed using
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Related WorkAll of these frameworks
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Related Work2.1. Data Flow Models2.
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Related Work2.1. Data Flow Modelspu
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Related Work2.1. Data Flow ModelsTh
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Related Work2.2. Flow Visualization
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Page 43 and 44: Related Work2.2. Flow Visualization
Page 45 and 46: Chapter 3Software Design3.1 CashFlo
Page 47 and 48: Software Design3.1. CashFlow Visual
Page 49 and 50: Software Design3.2. Using the Scene
Page 51 and 52: Software Design3.3. Indirect Refere
Page 53 and 54: Software Design3.4. Using Virtual A
Page 55 and 56: Software Design3.4. Using Virtual A
Page 57 and 58: Software Design3.5. General CashFlo
Page 59 and 60: Software Design3.6. MultiData NodeT
Page 61 and 62: Software Design3.7. DataAccess Node
Page 67 and 68: Software Design3.8. Grid Nodealgori
Page 69 and 70: Software Design3.10. Render Nodes-
Page 71 and 72: Software Design3.12. User Interacti
Page 73 and 74: Chapter 4ImplementationFigure 4.1:
Page 75 and 76: Implementation4.1. Accessing Data4.
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Page 79 and 80: Implementation4.2. UML Inheritance
Page 81 and 82: Implementation4.3. SoMultiDataNode4
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Page 113 and 114: Results5.1. Combining MultiData Nod
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Page 117 and 118: Results5.2. CashFlow Scene Graph Ex
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Page 121 and 122: Results5.3. Curvilinear Grid Visual
Page 123 and 124: Results5.4. Streamlines in CashFlow
Page 125 and 126: Results5.5. Grid Iterator ExamplesF
Page 127 and 128: Results5.6. Example for Parameteriz
Page 129 and 130: Results5.7. Polygonal Surfaces & Te
Page 131 and 132: Appendix AField connection &TGS Mes
Page 133 and 134: DanksagungVielen Dank an meine Schw
Page 135 and 136: 2.35 Colored Flow field topology ex
Page 137 and 138: Bibliography[3D] Java 3D. Java 3D c
Page 139 and 140: [CEI94] CEI. http://www.ceintl.com/
Page 141 and 142: [EYSK94] David S. Ebert, Roni Yagel
Page 143 and 144: [HP97] Hans - Christian Hege and Ko
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[MAY] MAYA. MAYA c○ by ALIAS c○
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[RBHC91] B. Lucas R. B. Haber and N
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[Tog02] Together. Borland R○ Toge
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[WJSV92] G. D. Montanaro William J.
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network, 39OpenDX, 15sink, 13source
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flow field, 19transfer function, 6t
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