Working with ParaView filters

ParaView filters (11 min)

Store your visualization workflow with a state file (2 min)

Side-by-side visualization (3 min)

Visualizing vectors (6 min)

Creating better streamlines (3 min)

Line integral convolution (LIC) (3 min)

Reading CSV data (6 min)

Word of caution

Many visualization filters, e.g. Clip and Slice, transform stuctured grid data into unstructured data. Since unstructured data can take several times as much memory, it is a good idea to monitor the memory footprint of your visualization workflow. If your current memory usage is already close to the physical memory of your computer (or the memory allocation of the cluster job running your pvserver), applying such a filter will either force your computer to swap making everything very slow, or your job on the cluster will get killed hence terminating your pvserver.

In ParaView it is easy to monitor your memory usage via View | Memory Inspector.

If you are running out of memory with a remote, distributed visualization (we will study this later), the best option is to ask for more CPU cores with a fixed --mem-per-cpu. Not only will this give you more total memory, it will also speed up your rendering and data reading, assuming that your file format supports parallel I/O.