a_AND_b = region_A.and(region_B) #common overlapa_XOR_b = region_A.xor(region_B) #differenceexact_region = a_AND_b.not_interacting(a_XOR_b) #when a_AND/XOR_b don't interact and a_AND_b is not an empt
There is a specific issue with extracting devices that may make devices appear on the wrong hierarchy level. Here is one related discussion: https://www.klayout.de/forum/discussion/comment/11290#Comme
for the idea!$ [python3] fishfinder.py option & argument : comment on option if any default value --------------------------------------------------------------+--------
I noticed something about reading/writing files and dbu value changes. I don't think it makes a difference in the output, but it wasn't the behavior I expected. I'm sure this is related to floating po
For hierarchical data, a scripted approach is better suited, like the one described here: https://www.klayout.de/forum/discussion/comment/10834#Comment_10834
of the layout. This handles all the #complicated work of finding shapes in the current cell and #all child cells. reg.insert(layout.begin_shapes(cell, layer_indexes[idx]))
of the layout. This handles all the #complicated work of finding shapes in the current cell. reg.insert(layout.begin_shapes(cell,layer_indexes[idx])) total_area += reg.area(
Usually maintaining the hierarchy helps. Simply adding two layers can be done cell wise (Layout#copy_layer does this in case you stay inside the same layout object). Deep mode may be an option. The ke