Open sgreenbury opened 4 days ago
This is particularly useful if we are running on a big study area. The workzone assignment optimization problem might not be feasible at a high resolution (OA level) for a city like London. Running the problem at a lower resolution (MSOA level) would significantly reduce the number of variables.
One question to answer before implementing: Under what scenario would it be insufficient to run the entire pipeline at a lower resolution (e.g. MSOA level)?
In terms of steps, it would require some edits to
3.2.2_assign_primary_zone_work.py
:Edit possible_zones_work before it is used here. The zones all match the boundary_geography resolution. If boundary_geography is OA, we should replace each possible_zones to it's parent MSOA and use that as possible_zones_work
After the assignment, each activity is mapped to an MSOA. If the boundary_geography is OA, we need to sample oan OA from the chosen MSOAs. This should be done before this step
Originally posted by @Hussein-Mahfouz in https://github.com/Urban-Analytics-Technology-Platform/acbm/issues/52#issuecomment-2396454928