Chapter 1 - Getting Started

Chapter 1 - Getting Started

This chapter introduces you to IRIS Explorer using five sample maps, each from a different scientific field. The examples cover:

Overview

You can create maps for all occasions, for example, to generate a 3D image of vortices around hydro-electric turbines, or to visualize carbon dioxide concentration as a function of geographic location. These activities involve a number of separate tasks such as reading the data into the map, colormapping a gradient, extracting a 2D slice of a 3D dataset and visualizing the result. The modules in the map carry out tasks like these.

The five maps presented here use authentic data to illustrate the workings of IRIS Explorer. Each map deals with a specific issue, and the modules provide ways of altering or enhancing the data so as to make its significance clear, and perhaps to elicit correlations that might otherwise have gone unnoticed.

The maps are complete. You need only launch, or open, the map in the Map Editor, and then try varying the parameters as suggested in each example. Chapter 2 explains how you set about creating your own maps. Table 1-1 defines some of the terms you will encounter when you start IRIS Explorer.

Term Meaning
Map Editor Work area for creating and modifying maps
Module Librarian Lists maps and modules available for use
Module Performs an algorithmic function on the data passing through it
Control Panel Gives the user access to the module functions
Widgets Dials, sliders, buttons, and text slots for changing parameters
Map A collection of modules that carry out a series of related operations on a dataset
Image A 2D array that can be viewed using the DisplayImg module
Geometric Object A collection of points, lines, polygons or other shapes that can be displayed by the Render module
Table 1-1 Some Components of IRIS Explorer

Launching a Map

You can open maps in two ways: when executing IRIS Explorer (through its command line) and from the Module Librarian in IRIS Explorer.

Opening Your First Map

If IRIS Explorer is not running, you can use the command line when you open a map for the first time, e.g. in UNIX use the command 
explorer -map /usr/explorer/maps/mapname.map

The mapname.map is the name of the map you want to open, for example, chemistry.map;. The name of each map shown in this chapter is given in the introduction to the map.

IRIS Explorer starts up and the map appears in the Map Editor. All the modules are selected (highlighted in white), and you can move the entire map by dragging on the title-bar of a single module.

Click on the background of the Map Editor to deselect the modules in the map before you experiment with individual modules. The highlighting disappears.

Opening Subsequent Maps

Once IRIS Explorer is running, you can use the Module Librarian to open a map. Follow these steps.

  1. To clear the Map Editor of modules, click on the Edit menu and select Destroy All.
  2. Go to the Module Librarian next to the Map Editor and use the vertical scroll bars to locate the maps, which are shown in blue.
  3. Select the map you want by placing the cursor on the map name and clicking the right mouse button, then selecting Launch from the pop-up menu.

    You can also hold down the left mouse button, drag the map over to the Map Editor and release the button.

When you release the mouse button, the map appears, module by module, on the screen. The menu bar displays a number in angle brackets, for example, <5>, which tells you initially how many modules are in the map; the number decreases as modules appear on screen, indicating how many modules remain to be launched.

Quitting IRIS Explorer

To quit IRIS Explorer, select Quit from the Admin menu in the Map Editor.

Opening Modules

You can expand the mini control panel (shown in Figure 1-1) of any module into the full-scale control panel by clicking on the square Maximize button at the right top corner of the control panel. When you do this, the parameter widgets and their values are displayed for easier manipulation.

Figure 1-1 Module Control Panel

Image Processing

This example illustrates how you can use IRIS Explorer modules to process an image. Please note that the Image Processing modules are not provided with all implementations of IRIS Explorer. The koreaContour map takes an aerial image of a region of the Korean landscape, renders it in 3D, and overlays a contour map showing altitudes. The resulting image is displayed on-screen. The map file is /usr/explorer/maps/koreaContour.map.

Opening the Image Map

To open the koreaContour map, displayed in Figure 1-2, type 

explorer -map koreaContour.map

The seven modules are connected to one another by blue wires. The modules on the left reads in the image file and altitude data, and the module on the far right displays the processed image. In between these are four modules that manipulate the image data.


Figure 1-2 Processing an Image

The seven modules in the map have the following functions:

Experimenting with the Image Map

Both the aerial image and the altitude data go through DisplaceLat (see Figure 1-3), which displaces the image data so that topographical features become 3D.


Figure 1-3 DisplaceLat Control Panel

The output of DisplaceLat<2> passes into Contour (see Figure 1-4), which creates a series of lines at varying heights above sea level just as in a topographic map. The scale factor for DisplaceLat<2> should be greater than that for DisplaceLat, to make the contour lines visible.


Figure 1-4 Contour Control Panel

To set the relationship between scale factors, the Scale parameter output port on DisplaceLat is wired to the Scale parameter input port on DisplaceLat<2>.

The result is shown in Render (see Figure 1-5). You can open the Render window by clicking on the Maximize button and rotate the object in the window.


Figure 1-5 The Contour Map in Render

For more information on using the Render menus to manipulate objects, see Visualizing Data in Chapter 3.

Numerical Mathematics

This example illustrates how to use IRIS Explorer modules to read in a short program script describing a mathematical function and visualize the data in the Render window. The mathematical function describes diffusive heat flow. It is a finite difference (footnote) stencil for solving problems in parabolic differential heat conduction.

The form of the equation in this example is dimensionless; it serves as a normalized thermal model. A map using a specific form of such an equation with actual data can be used, for example, to test the conductivity of steel.

Opening the Heat-flux Map

To open the heat-flux map (see Figure 1-6), type 

explorer -map heat-flux.map

Figure 1-6 Map for a Heat Flux

The map contains six modules, which have these functions:

A lattice is an IRIS Explorer data type, which is used to store an ordered array of data. For more information, see Understanding IRIS Explorer Data Types in Chapter 2.

Experimenting with the Heat-flux Map

LatFunction reads in a short program written in the Shape language, which is described in detail in "Chapter 10"of the IRIS Explorer Module Writer's Guide. It is a C-like language that has capabilities for operating on whole lattices with a single statement. The program is saved in a file called heat-flux in /usr/explorer/maps and can be run as often you choose.

The data passes from LatFunction to Displacelat, which displaces the 2D data into a 3D array to show the heat source as a peak and the heat sink as a trough. You can change the degree to which the peaks project from the surface by turning the dial on Displacelat. This causes the data to be displaced out of the plane to a greater or lesser degree.

GenerateColormap colormaps the heat-flux data according to temperature value. You can change the colors associated with each temperature value by using the option menus on the control panel. Refer to Creating Colormaps in Chapter 3 for more information.

LatToGeom uses the heat-flux and colormap data (which are both IRIS Explorer lattices) to create geometry for display in Render (see Figure 1-7). Render can only display geometry, and all lattice data must be converted first.


Figure 1-7 Visualization of the Flux Peaks

Once the data is displayed in Render, you can change the background color of the window by selecting Edit Background Color from the Viewing menu. When the Background Color Picker appears:

Molecular Chemistry

This example illustrates how you can use IRIS Explorer modules to construct a 3D model of a complex organic molecule and then calculate the optimal radius and likely path for a probe atom investigating the target molecule.

Opening the Chemistry Map

To open the chemistry map (see Figure 1-8), type: 

explorer -map chemistry.map

Figure 1-8 Visualizing a NutraSweet Molecule

The map takes configuration data for a NutraSweet molecule and creates a ball-and stick representation of it and a dot surface that shows the region that is accessible by a probe atom.

The map contains seven modules:

Experimenting with the Chemistry Map

The molecular configuration data is read in by ReadPDB. The input file is in the Brookhaven Protein DataBase (PDB) format, a commonly used format for saving descriptions of proteins, including atom positions and properties, and bond locations.

BallStick (see Figure 1-9) receives the data in pyramid form and generates sphere-and-cylinder geometry. (The pyramid is an IRIS Explorer data type.) The radius of each sphere is calculated according to the van der Waals' radius of the corresponding atom.


Figure 1-9 BallStick Control Panel

The molecule data also passes into AtomicSurf (see Figure 1-10). It uses the van der Waals' radius of each atom and adds a solvent probe radius to it. The surface points in this solvation layer represent the positions in which a solvent probe would be in contact with the target molecule.


Figure 1-10 AtomicSurf Control Panel

GenerateColormap creates a default colormap for the molecule based on atomic number. The domain is set at a minimum of 0 and a maximum of 16 to accommodate the atoms, which are hydrogen, carbon, oxygen, and nitrogen.

It also colormaps the dots in the solvent-accessible surface according to the parent atom of each dot. This provides you with information about which atoms a given probe will touch as it traverse the surface of the molecule.

You can use the capacities of Render to look at the NutraSweet molecule in great detail (see Figure 1-11). You can:


Figure 1-11 The Molecule in Render

For more information on using Render, read Visualizing Data in Chapter 3.

You can use FileList to select another chemistry molecule to examine.

Atmospheric Physics

This example illustrates how you can use IRIS Explorer modules to visualize atmospheric data. Intense storms can produce tornadoes, high winds, and hail, and it is possible to simulate these storms by integrating a set of mathematical flow equations. These equations can, for example, predict values for the wind speed and direction, air temperature, humidity, pressure, and water content every 5 to 10 seconds on a lattice of grid points 500 to 1000 meters apart.

The data in the example map is taken from a simulation of a single severe storm made by the storm group at the University of Illinois (footnote) . The map shows an isosurface of rain density and a volume rendering of air buoyancy. An isosurface is a surface which passes through all points in a 3-D dataset where the data has a particular value. The data is in the form of a uniform lattice.

Opening the Volume Map

To open the volume map (see Figure 1-12), type: 

explorer -map volume.map

Figure 1-12 Simulating an Evolving Storm

The map contains eight modules:

For volume rendering techniques to display the volume as shown in this map, you require alpha blending hardware. Some workstations do not have this hardware, but they can display the volume adequately if the Splat type on VolumeToGeom is set to Point (see Experimenting with the Volume Map below).

Experimenting with the Volume Map

This map uses both surface rendering (the isosurface) and volume rendering (the haze) in one visualization to show the relationship between a number of variables which have been calculated in 3-D space during the modelling of the evolution of the storm.

IsosurfaceLat (see Figure 1-13) calculates an isosurface from the density data and outputs it as geometry. The threshold value is the density value for which an isosurface is created.


Figure 1-13 IsosurfaceLat Control Panel
VolumeToGeom volume-renders the buoyancy data as a hazy cloud surrounding the isosurface. The entities that make up the cloud are called splats, small planar shapes that simulate fuzzy blobs on screen.

Rendering splats can may take a long time. You can set and adjust an error tolerance to get a balance between rendering time and splat quality.

ReadLat<3> reads the colormap settings for the volume rendering of the water buoyancy data into GenerateColormap. The current setting for the colormap shows buoyant air, containing little water, in red and the saturated air in blue.

Once the data is in Render, you can analyze it in detail. Figure 1-14 displays the reflectivity from the storm (footnote) . The blue-white surface encloses the area containing most of the large drops and hail. Several light sources illuminate the surface. You can see the overhang, observed by weather radar in many severe storms, at mid-level where the reflectivity surface comes out toward the viewer.


Figure 1-14 Storm Data in Render

Above the storm, there is a region of many colors volumetrically rendered from the buoyancy, a quantity used in the equations for vertical velocity. It represents the instantaneous effects of temperature, moisture, and water mixed with ice on the velocity acceleration, and is large at and above the top of the storm.

A wavy appearance is evident, indicating the presence of strong gravity waves. Yellow/green indicates relatively high buoyancy, blue indicates relatively low buoyancy. The effect is roughly similar to throwing a rock into a pond, but here it is the storm growing into the upper atmosphere.

You can change the opacity values on the colormap to affect the look of the volume rendering (see Chapter 3, Creating Colormaps).

Computational Fluid Dynamics

This example illustrates how you can use IRIS Explorer modules to study the dynamics of air flow over the nose of an aeroplane. The cfd map shows variations in air density surrounding the surface of the aeroplane.

The map generates an air flow field around the plane, extracts 2D slices of the volume, and colormaps them by density value, thus providing a means of examining different areas of the field.

The CFD group at Silicon Graphics created the plane from a model aeroplane by a digitized 3D scanning process, and the air flow data was generated from NASA's fluid dynamics program, ARC3D (footnote) .

Opening the Cfd Map

To open the cfd map (see Figure 1-17), type: 

explorer -map cfd.map

The map contains nine modules:

Experimenting with the Cfd Map

OrthoSlice (see Figure 1-15) operates on the air density data to produce a curvilinear grid depicting the density field around the plane. The slice number is 3 and this index increases in a direction normal to the plane's surface. For J = 1, the grid actually lies along the surface of the plane.

Figure 1-15 OrthoSlice Control Panel
ProbeLat and IsosurfaceLat complement each other. IsosurfaceLat generates an isosurface from the air density data. This tells you how all the air of a given density is distributed around the plane. You can change the threshold (the value at which the isosurface is calculated) by turning the dial on the control panel. ProbeLat (see Figure 1-16) probes the curvilinear flow field along an arbitrary axis. The slice shows all density values in that region, colormapped by value.

Figure 1-16 ProbeLat Control Panel
You can control the area of the slice by turning the Clip Size dial on the control panel. You can also change the form the probe takes, by selecting a type from the Probe Type option menu. In Figure 1-17, the selected probe type is a paddle.

Figure 1-17 Different Levels of Air Density
The axis along which the plane is cut is controlled by TransformGen. You can slice in any direction you choose by using the widgets on the TransformGen control panel to set a different axis. You can alter the orientation of the probe by using the mouse to move the object in TransformGen's window.

GenerateColormap colormaps the grid produced by OrthoSlice according to its air density values. It is a scalar field, with one value at every point. The domain in GenerateColormap is set to a density minimum of about 0.7 and maximum of 1.1. This colormap is also used to color the probe surface according to air density values.

PyrToGeom and LatToGeom convert pyramid and lattice data respectively to geometry which can be displayed by Render.

Once the data is displayed in Render (see Figure 1-18), you can enhance the visualized data by using the Render menus. For example, click on the background of the Render window to bring up the Render pop-up menu. Select the Draw Style option, and then select wireframe from the cascading menu. To return all the surfaces to their original state, bring up the menu again and select the as is option.


Figure 1-18 The Rendered Flow Field
The grid, isosurface, and probe surface are separate objects, which can be separately treated in Render. For example, you could make the probe surface transparent, which would reveal the features behind it.
Last modified: Mon Oct 13 11:04:05 1997
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© NAG Ltd. Oxford, UK, 1997