Editing Scientific visualization (section)

== Data visualization methods==
{{main|Data visualization}}

Criteria for classifications:
* dimension of the data
* method
** [[Texture advection| textura based methods]]
** geometry-based approaches such as arrow plots, streamlines, pathlines, timelines, streaklines, particle tracing, surface particles, stream arrows, stream tubes, stream balls, flow volumes and topological analysis



=== Two-dimensional data sets ===
Scientific visualization using computer graphics gained in popularity as graphics matured. Primary applications were scalar fields and vector fields from computer simulations and also measured data. The primary methods for visualizing two-dimensional (2D) scalar fields are color mapping and drawing [[contour line]]s. 2D vector fields are visualized using [[Glyph (data visualization)|glyphs]] and [[Streamlines, streaklines, and pathlines|streamlines]] or [[line integral convolution]] methods. 2D tensor fields are often resolved to a vector field by using one of the two eigenvectors to represent the tensor each point in the field and then visualized using vector field visualization methods.

=== Three-dimensional data sets ===
For 3D scalar fields the primary methods are [[volume rendering]] and [[isosurface]]s. Methods for visualizing vector fields include glyphs (graphical icons) such as arrows, [[Streamlines, streaklines, and pathlines|streamlines and streaklines]], particle tracing, [[line integral convolution]] (LIC) and topological methods. Later, visualization techniques such as hyperstreamlines<ref>{{cite journal|last=Delmarcelle|first=T|author2=Hesselink, L. |title=Visualizing second-order tensor fields with hyperstreamlines|journal=IEEE Computer Graphics and Applications |year=1993|volume=13|issue=4|pages=25–33|doi=10.1109/38.219447|hdl=2060/19950012873|s2cid=7698377|hdl-access=free}}</ref>  were developed to visualize 2D and 3D tensor fields.