SciVisAgentBench-tasks / paraview /tornado /task_description.txt
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Load the Tornado vector field from "tornado/data/tornado_64x64x64_float32_scalar3.raw", the information about this dataset:
Tornado (Vector)
Data Scalar Type: float
Data Byte Order: Little Endian
Data Extent: 64x64x64
Number of Scalar Components: 3
Data loading is very important, make sure you correctly load the dataset according to their features.
Create a streamline visualization using a "Stream Tracer" filter with "Point Cloud" seed type. Set the seed center to [31.5, 31.5, 47.25], radius 12.6, and maximum streamline length to 512.0. Add a "Tube" filter (radius 0.25) on the stream tracer. Color the tubes by Velocity magnitude using the 'Cool to Warm (Diverging)' colormap. Also display the stream tracer directly with line width 5.0 and "Render Lines As Tubes" enabled.
Add a "Glyph" filter on the original data using Arrow glyph type. Orient arrows by the Velocity vector and scale by Velocity magnitude with a scale factor of 25.0. Set maximum number of sample points to 2500. Color glyphs by Velocity magnitude using the same colormap.
Add an "Outline" filter to display the dataset bounding box (black).
Use a white background (RGB: 1.0, 1.0, 1.0). Find an optimal view. Render at 1280x1280. Show both color bar and coordinate axes.
Save the visualization image as "tornado/results/{agent_mode}/tornado.png".
(Optional, but must save if use paraview) Save the paraview state as "tornado/results/{agent_mode}/tornado.pvsm".
(Optional, but must save if use pvpython script) Save the python script as "tornado/results/{agent_mode}/tornado.py".
(Optional, but must save if use VTK) Save the cxx code script as "tornado/results/{agent_mode}/tornado.cxx"
Do not save any other files, and always save the visualization image.