Adding information on how many times an activity functions as an input exchange to another activitiy is very run time intensive. Creating the for loop is quickly done. However, to reduce run time it would probably make sense to get the counts for a sector seperately from generating the lca tables and adding them subeseuqntly to the lca tables. My approach was to add these statistics post lca table generation which conqsequently would run the loop multiple times (for each table) for one activtiy. I was also considering to add this part of code to the bw2analyzer function compare_activities_by_grouped_leaves but this would likely entail multiple runs for one activity.
Approach to consider: Include loop in activity dictionary generated by sector_filter.process_yaml_files.
Added a function that creates a dictionary for each activitiy in sector_filter.py. --> def activities_are_exchanges_stats(activity_dict, database_name)
Adding information on how many times an activity functions as an input exchange to another activitiy is very run time intensive. Creating the for loop is quickly done. However, to reduce run time it would probably make sense to get the counts for a sector seperately from generating the lca tables and adding them subeseuqntly to the lca tables. My approach was to add these statistics post lca table generation which conqsequently would run the loop multiple times (for each table) for one activtiy. I was also considering to add this part of code to the bw2analyzer function compare_activities_by_grouped_leaves but this would likely entail multiple runs for one activity.
Approach to consider: Include loop in activity dictionary generated by sector_filter.process_yaml_files.