| Task: |
|
|
| Load the solar plume dataset from "solar-plume/data/solar-plume_126x126x512_float32_scalar3.raw", the information about this dataset: |
| solar-plume (Vector) |
| Data Scalar Type: float |
| Data Byte Order: little Endian |
| Data Extent: 126x126x512 |
| Number of Scalar Components: 3 |
| Data loading is very important, make sure you correctly load the dataset according to their features. |
|
|
| Add a “stream tracer” filter under the solar plume data to display streamline, set the "Seed type" to "Point Cloud" and set the center of point cloud to 3D position [50, 50, 320] with a radius 30, then hide the point cloud sphere. |
|
|
| Add a "tube" filter under the "stream tracer" filter to enhance the streamline visualization. Set the radius to 0.5. In the pipeline browser panel, hide everything except the "tube" filter. |
|
|
|
|
| Please think step by step and make sure to fulfill all the visualization goals mentioned above. |
|
|
| Set the viewpoint parameters as: [62.51, -984.78, 255.45] to position; [62.51, 62.46, 255.45] to focal point; [0, 0, 1] to camera up direction. |
|
|
| Use a white background. Find an optimal view. Render at 1280x1280. Do not show a color bar or coordinate axes. |
|
|
| Save the visualization image as "solar-plume/results/{agent_mode}/solar-plume.png". |
| (Optional, but must save if use paraview) Save the paraview state as "solar-plume/results/{agent_mode}/solar-plume.pvsm". |
| (Optional, but must save if use pvpython script) Save the python script as "solar-plume/results/{agent_mode}/solar-plume.py". |
| (Optional, but must save if use VTK) Save the cxx code script as "solar-plume/results/{agent_mode}/solar-plume.cxx" |
| Do not save any other files, and always save the visualization image. |
|
|
