Editing Scientific visualization (section)

== Applications ==
This section will give a series of examples how scientific visualization can be applied today.<ref>All examples both images and text here, unless another source is given, are from the [[Lawrence Livermore National Laboratory]] (LLNL), from the [http://www.llnl.gov/visit/gallery_02.html LLNL website], Retrieved 10–11 July 2008.</ref>

=== In the natural sciences ===
<gallery>
Image:Star formation.jpg|''Star formation''<ref>The data used to make this image were provided by Tom Abel Ph.D. and Matthew Turk of the Kavli Institute for Particle Astrophysics and Cosmology.</ref>
Image:Gravitywaves.JPG|''Gravitational waves''<ref>[http://www.anl.gov/Media_Center/logos20-2/globus01.htm BLACK-HOLE COLLISIONS] The Globus software creators Ian Foster, Carl Kesselman and Steve Tuecke. Publication Summer 2002.</ref>
Image:Massive Star Supernovae Explosions.jpg|''Massive Star Supernovae Explosions''
Image:Molecular rendering.jpg|''Molecular rendering''
</gallery>

''Star formation'': The featured plot is a Volume plot of the logarithm of gas/dust density in an Enzo star and galaxy simulation. Regions of high density are white while less dense regions are more blue and also more transparent.

''Gravitational waves'': Researchers used the Globus Toolkit to harness the power of multiple supercomputers to simulate the gravitational effects of black-hole collisions.

''Massive Star Supernovae Explosions'': In the image, three-Dimensional Radiation Hydrodynamics Calculations of Massive Star Supernovae Explosions The DJEHUTY stellar evolution code was used to calculate the explosion of SN 1987A model in three dimensions.

''Molecular rendering'': [[VisIt]]'s general plotting capabilities were used to create the molecular rendering shown in the featured visualization. The original data was taken from the Protein Data Bank and turned into a VTK file before rendering.

=== In [[geovisualization|geography]] and ecology ===
<gallery>
Image:Terrain rendering.jpg|''Terrain rendering''
Image:Climate visualization.jpg|''Climate visualization''<ref>Image courtesy of Forrest Hoffman and Jamison Daniel of Oak Ridge National Laboratory</ref>
Image:Atmospheric Anomaly in Times Square.jpg|''Atmospheric Anomaly in Times Square''
</gallery>

''[[Terrain rendering|Terrain visualization]]'': [[VisIt]] can read several file formats common in the field of [[Geographic Information Systems]] (GIS), allowing one to plot raster data such as terrain data in visualizations. The featured image shows a plot of a DEM dataset containing mountainous areas near Dunsmuir, CA. Elevation lines are added to the plot to help delineate changes in elevation.

''Tornado Simulation'': This image was created from data generated by a tornado simulation calculated on NCSA's IBM p690 computing cluster. High-definition television animations of the storm produced at NCSA were included in an episode of the PBS television series NOVA called "Hunt for the Supertwister." The tornado is shown by spheres that are colored according to pressure; orange and blue tubes represent the rising and falling airflow around the tornado.

''Climate visualization'': This visualization depicts the carbon dioxide from various sources that are advected individually as tracers in the atmosphere model. Carbon dioxide from the ocean is shown as plumes during February 1900.

''Atmospheric Anomaly in Times Square'' In the image the results from the SAMRAI simulation framework of an atmospheric anomaly in and around Times Square are visualized.

[[File:Tesseract.ogv|thumb|right|View of a 4D cube projected into 3D: orthogonal projection (left) and perspective projection (right).]]

=== In mathematics ===

{{main|Mathematical visualization}}

Scientific visualization of mathematical structures has been undertaken for purposes of building intuition and for aiding the forming of mental models.<ref>[[Andrew J. Hanson]], [[Tamara Munzner]], George Francis: ''Interactive methods for visualizable geometry'', Computer, vol.&nbsp;27, no.&nbsp;7, pp.&nbsp;73–83 ([https://ieeexplore.ieee.org/document/299415/ abstract])</ref>

[[File:Domain coloring x2-1 x-2-i x-2-i d x2+2+2i.xcf|120px|right|thumb|[[Domain coloring]] of 
{{math|''f''(''x'') {{=}} {{sfrac|(''x''<sup>2</sup>−1)(''x''−2−''i'')<sup>2</sup>|''x''<sup>2</sup>+2+2''i''}}}}]]

Higher-dimensional objects can be visualized in form of projections (views) in lower dimensions. In particular, 4-dimensional objects are visualized by means of projection in three dimensions. The lower-dimensional projections of higher-dimensional objects can be used for purposes of virtual object manipulation, allowing 3D objects to be manipulated by operations performed in 2D,<ref>[[Andrew J. Hanson]]: ''Constrained 3D navigation with 2D controller'', Visualization '97., Proceedings, 24 October 1997, pp.&nbsp;175-182 ([https://ieeexplore.ieee.org/document/663876/ abstract])</ref> and 4D objects by interactions performed in 3D.<ref>Hui Zhang, [[Andrew J. Hanson]]: ''Shadow-Driven 4D Haptic Visualization'', IEEE Transactions on Visualization and Computer Graphics, vol.&nbsp;13, no.&nbsp;6, pp.&nbsp;1688-1695 ([https://ieeexplore.ieee.org/document/4376203/ abstract])</ref>

In [[complex analysis]], functions of the complex plane are inherently 4-dimensional, but there is no natural geometric projection into lower dimensional visual representations. Instead, colour vision is exploited to capture dimensional information using techniques such as [[domain coloring]].

=== In the formal sciences ===
<gallery>
Image:Curve plots.jpg|''Curve plots''
Image:Image annotations.jpg|''Image annotations''
Image:Scatter plot.jpg|''Scatter plot''
</gallery>

''Computer mapping of topographical surfaces'': Through computer mapping of topographical surfaces, mathematicians can test theories of how materials will change when stressed. The imaging is part of the work on the NSF-funded Electronic Visualization Laboratory at the University of Illinois at Chicago.

''Curve plots'': VisIt can plot curves from data read from files and it can be used to extract and plot curve data from higher-dimensional datasets using lineout operators or queries. The curves in the featured image correspond to elevation data along lines drawn on DEM data and were created with the feature lineout capability. Lineout allows you to interactively draw a line, which specifies a path for data extraction. The resulting data was then plotted as curves.

''Image annotations'': The featured plot shows Leaf Area Index (LAI), a measure of global vegetative matter, from a NetCDF dataset. The primary plot is the large plot at the bottom, which shows the LAI for the whole world. The plots on top are actually annotations that contain images generated earlier. Image annotations can be used to include material that enhances a visualization such as auxiliary plots, images of experimental data, project logos, etc.

''Scatter plot'': VisIt's Scatter plot allows visualizing multivariate data of up to four dimensions. The Scatter plot takes multiple scalar variables and uses them for different axes in phase space. The different variables are combined to form coordinates in the phase space and they are displayed using glyphs and colored using another scalar variable.

=== In the applied sciences ===
<gallery>
Image:Porsche 911 model imported from a NASTRAN bulk data file.jpg|''Porsche 911 model''
Image:YF-17 aircraft Plot.jpg|''YF-17 aircraft Plot''
Image:City rendering.jpg|''City rendering''
</gallery>

''Porsche 911 model'' (NASTRAN model): The featured plot contains a Mesh plot of a Porsche 911 model imported from a NASTRAN bulk data file. VisIt can read a limited subset of NASTRAN bulk data files, in general enough to import model geometry for visualization.

''YF-17 aircraft Plot'': The featured image displays plots of a CGNS dataset representing a YF-17 jet aircraft. The dataset consists of an unstructured grid with solution. The image was created by using a pseudocolor plot of the dataset's Mach variable, a Mesh plot of the grid, and Vector plot of a slice through the Velocity field.

''City rendering'': An ESRI shapefile containing a polygonal description of the building footprints was read in and then the polygons were resampled onto a rectilinear grid, which was extruded into the featured cityscape.

''Inbound traffic measured'': This image is a visualization study of inbound traffic measured in billions of bytes on the NSFNET T1 backbone for the month of September 1991. The traffic volume range is depicted from purple (zero bytes) to white (100 billion bytes). It represents data collected by Merit Network, Inc.<ref>Image by [[Donna Cox]] and Robert Patterson. [https://www.nsf.gov/news/mmg/media/images/nsfnet_h1.jpg The National Science Foundation] Press Release 08-112.</ref>