(I hope I don't miss anything, no tests seem to fail and performance is increased significantly) but because `subelement_queue` initiated with the `traverse` all `element`'s subelements will be traversed inside `while` loop twice - once as a part of initial queue and another time when `element` is traversed inside the loop and all those elements added to the queue again.
Now we just initiate the `queue` with the `element` and it will be traversed inside the loop like any other element.
1) `do_not_delete` performs best when it's set
2) also_consider when `element` related elements go first, so there will be no need to traverse all other elements to see if they cover `element`'s inverses.
1) replaced walk with traverse(max_levels=1)
2) early return if there total_inverses == 0
3) early return if also_considered_inverses is enough to cover total_inverses
* feature_faster_unit_method > main: added constants
* feature_faster_unit_method > main: extended `file` class to dynamically save unit information
* feature_faster_unit_method > main: refactored `get_property_unit` method
1. split out case that returns the wrong type (dictionary of units) into its own method
2. cleaned up (but preserved) logic
3. refactored common part of all cases (the method which prioritises unit then value-entity then measure_class)
---------
Co-authored-by: raj-open <raj-open@users.noreply.github.com>
Co-authored-by: Dion Moult <dion@thinkmoult.com>
As it also has a third value "UNKNOWN" which has it's own meanig in IFC and therefore IfcLogical cannot be represented by simple booleans.
Example in Bonsai - https://i.imgur.com/xuPMcwA.png
Previously the code looked for additive facets (entity, instance)
anywhere in the query, and then only added the default basket once at
the beginning of the query. This change makes it look for additive
facets in order (that way you could start with a default selection, and
then later use an additive facet) and does it per facet list (so you can
omit the additive facet at the beginning of each list).
Andrej730
