# cut the cells and triangulate (crinkle=0), or keep complete cells # side kept : 0 to keep the inside, 1 to keep the outside # rotation around the three axes (in degrees) # side kept : 0 to keep the side in the Normal direc., 1 for other side # list of distances to the origin : to create several parallel planes # triangulate : will create a triangle mesh on the slice # crinkle : 0=cut cells and create new polygons, 1=keep full cells The dataset ‘data’ used in the examples is an unstructured grid containing two variables :ĭata = pvs.LegacyVTKReader(FileNames=) The following filters should work for structured and unstructured grids, even in multiblocks. Note that each ParaView filter works with only some types of data. NEVER do that (unless you really know what you are doing).įor the sake of generality, the dataset used for the examples is nammed ‘data’ and its type is not precised. In this case ParaView will use the current active source as input. NB : it is possible to avoid the declaration of the filter input. It is time-consuming, since it forces ParaView to perform all the operations of the filter and return an output. Updating the filter corresponds to pressing the “Apply” button in the filter Properties panel of the GUI. My_filter = pvs.FilterName(Input=my_data) import the paraview.simple module (here renammed 'pvs') This article may be extended later.Īpplying a filter to an object of the pipeline always requires 4 simple steps : This is rather a selection of filters that (in my scope of CFD engineer) cover the most common use of ParaView. Here I will illustrate how to call some ParaView filters in python scripts.There are far too many filtes in ParaView for even thinking about a complete description. Another article about this python API will come – one day, soon. ParaView offers a great python API that provides incredible scripting possibilities. This is the first of many articles about ParaView scripting with python.
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