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Scalar Visualization

Scalar Visualization. Outline. Visualizing scalar data A number of the most popular scalar visualization techniques Color mapping Contouring Height plots. Color mapping Design of effective colormaps Contouring in 2D and 3D Height plots. Visualization Pipeline. 1. Data Importing

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Scalar Visualization

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  1. Scalar Visualization

  2. Outline • Visualizing scalar data • A number of the most popular scalar visualization techniques • Color mapping • Contouring • Height plots • Color mapping • Design of effective colormaps • Contouring in 2D and 3D • Height plots

  3. Visualization Pipeline 1. Data Importing 2. Data Filtering 3. Data Mapping 4. Date Rendering

  4. Scalar Function

  5. Color Mapping • color look-up table • Associate a specific color with every scalar value • The geometry of Dv is the same as D

  6. Luminance Colormap • Use grayscale to represent scalar value • Most scientific data (through measurement, observation, or simulation) are intrinsically grayscale, not color Luminance Colormap Legend

  7. Rainbow Colormap • Red: high value; Blue: low value • A commonly used colormap Luminance Map Rainbow Colormap

  8. Rainbow Colormap • Construction • f<dx: R=0, G=0, B=1 • f=2: R=0, G=1, B=1 • f=3: R=0, G=1, B=0 • f=4: R=1, G=1, B=0 • f>6-dx: R=1, G=0, B=0

  9. Rainbow Colormap Implementation void c(float f, float & R, float & G, float &B) { const float dx=0.8 f=(f<0) ? 0: (f>1)? 1 : f //clamp f in [0,1] g=(6-2*dx)*f+dx //scale f to [dx, 6-dx] R=max(0, (3-fabs(g-4)-fabs(g-5))/2); G=max(0,(4-fabs(g-2)-fabs(g-4))/2); B=max(0,(3-fabs(g-1)-fabs(g-2))/2); }

  10. Colormap: Designing Issues • Choose right color map for correct perception • Grayscale: good in most cases • Rainbow: e.g., temperature map • Rainbow + white: e.g., landscape • Blue: sea, lowest • Green: fields • Brown: mountains • White: mountain peaks, highest

  11. Rainbow Colormap http://atmoz.org/img/weatherchannel_national_temps.png

  12. Exp: Earth map http://www.oera.net/How2/PlanetTexs/EarthMap_2500x1250.jpg

  13. Exp: Sun in green-white colormap

  14. Exp: Coronal loop http://media.skyandtelescope.com/images/SPD+on+CME+image+5+--+TRACE.gif

  15. Color Banding Effect Caused by a small number of colors in a look-up table

  16. Contouring • A contour line C is defined as all points p in a dataset D that have the same scalar value, or isovalue s(p)=x • A contour line is also called an isoline • In 3-D dataset, a contour is a 2-D surface, called isosurface

  17. Contouring Cartograph

  18. Contouring One contour at s=0.11 S > 0.11 S < 0.11 Contouring and Color Banding

  19. Contouring Contouring and Colormapping: Show (1) the smooth variation and (2) the specific values 7 contour lines

  20. Properties of Contours • Indicating specific values of interest • In the height-plot, a contour line corresponds with the interaction of the graph with a horizontal plane of s value

  21. Properties of Contours • The tangent to a contour line is the direction of the function’s minimal (zero) variation • The perpendicular to a contour line is the direction of the function’s maximum variation: the gradient Contour lines Gradient vector

  22. Constructing Contours V=0.48 Finding line segments within cells

  23. Constructing Contours • For each cell, and then for each edge, test whether the isoline value v is between the attribute values of the two edge end points (vi, vj) • If yes, the isoline intersects the edge at a point q, which uses linear interpolation • For each cell, at least two points, and at most as many points as cell edges • Use line segments to connect these edge-intersection points within a cell • A contour line is a polyline.

  24. Constructing Contours V=0.37: 4 intersection points in a cell -> Contour ambiguity

  25. Implementation: Marching Squares • Determining the topological state of the current cell with respect to the isovalue v • Inside state (1): vertex attribute value is less than isovalue • Outside state (0): vertex attribute value is larger than isovalue • A quad cell: (S3S2S1S0), 24=16 possible states • (0001): first vertex inside, other vertices outside • Use optimized code for the topological state to construct independent line segments for each cell • Merge the coincident end points of line segments originating from neighboring grid cells that share an edge

  26. Implementation: Marching Squares Topological State of a Quad Cell

  27. Implementation: Marching Cube Topological State of a hex Cell Marching cube generates a set of polygons for each contoured cell: triangle, quad, pentagon, and hexagon

  28. Contours in 3-D • In 3-D scalar dataset, a contour at a value is an isosurface Isosurface for a value corresponding to the skin tissue of an MRI scan 1283 voxels

  29. Contours in 3-D Two nested isosurface: the outer isosurface is transparent

  30. Height Plots • The height plot operation is to “warp” the data domain surface along the surface normal, with a factor proportional to the scalar value

  31. Height Plots Height plot over a planar 2-D surface

  32. Height Plots Height plot over a nonplanar 2-D surface

  33. Vector Visulization • Divergence and Vorticity • Vector Glyphs • Vector Color Coding • Displacement Plots • Stream Objects • Texture-Based Vector Visualization • Simplified Representation of Vector Fields

  34. Vector Function

  35. Vector versus Scalar

  36. Example in 2-D

  37. Gradient of a Scalar

  38. Gradient of a Scalar

  39. Divergence of a Vector

  40. Divergence of a Vector • Divergence computes the flux that the vector field transports through the imaginary boundary Γ, as Γ0 • Divergence of a vector is a scalar • A positive divergence point is called source, because it indicates that mass would spread from the point (in fluid flow) • A negative divergence point is called sink, because it indicates that mass would get sucked into the point (in fluid flow) • A zero divergence denotes that mass is transported without compression or expansion.

  41. Divergence of a Vector

  42. Divergence of a Vector

  43. Vorticity of a Vector

  44. Vorticity of a Vector • Vorticity computes the rotation flux around a point • Vorticity of a vector is a vector • The magnitude of vorticity expresses the speed of angular rotation • The direction of vorticity indicates direction perpendicular to the plane of rotation • Vorticity signals the presence of vortices in vector field

  45. Vorticity of a Vector Color: Glyph:

  46. Vector Glyph • Vector glyph mapping technique associates a vector glyph (or icon) with the sampling points of the vector dataset • The magnitude and direction of the vector attribute is indicated by the various properties of the glyph: location, direction, orientation, size and color

  47. Vector Glyph Line glyph, or hedgehog glyph Sub-sampled by a factor of 8 (32 X 32) Original (256 X 256) Velocity Field of a 2D Magnetohydrodynamic Simulation

  48. Vector Glyph Line glyph, or hedgehog glyph Sub-sampled by a factor of 4 (64 X 64) Original (256 X 256) Velocity Field of a 2D Magnetohydrodynamic Simulation

  49. Vector Glyph Sub-sampled by a factor of 2 (128 X 128) Original (256 X 256) Problem with a dense Representation using glyph: (1) clutter (2) miss-representation

  50. Vector Glyph Random Sub-sampling Is better

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