Saving assignments

[bsuwal]

A Score to get assignments

[wesg52]

Bump. In the python version I use

    districts = []
    plans = []
    for ix, partition in enumerate(chain):
        try:
            swap1, swap2 = list(partition.flows.keys())
            part1 = min(swap1, swap2)
            part2 = max(swap1, swap2)
            new_plan = plans[-1][:]
            new_plan[int(part1)] = len(districts)
            new_plan[int(part2)] = len(districts) + 1
            plans.append(new_plan)
            districts.append(list(partition.assignment.parts[part1]))
            districts.append(list(partition.assignment.parts[part2]))
        except: # First step in the chain
            districts = [list(part) for _, part in sorted(partition.assignment.parts.items())]
            plans.append(list(range(len(districts))))

[bsuwal]

hi @wesg52 , thanks for the bump! We will work on this asap. Feel free to let me know if you have any feedback on GerryChain meanwhile! (at [email protected])

[InnovativeInventor]

@wesg52 #121 should close this issue as the partition and score will be returned at each step when callilng the iterable version of recom_chain or flip_chain. E.g. this is what I'm doing right now (with the PR's changes applied):

using GerryChain

SHAPEFILE_PATH = "./PA_VTDs.json"
POPULATION_COL = "TOTPOP"
ASSIGNMENT_COL = "CD_2011"

# Initialize graph and partition
graph = BaseGraph(SHAPEFILE_PATH, POPULATION_COL)
partition = Partition(graph, ASSIGNMENT_COL)

# Define parameters of chain (number of steps and population constraint)
pop_constraint = PopulationConstraint(graph, partition, 0.02)
num_steps = 10000

# Run the chain
for (partition, _) in recom_chain_iter(graph, partition, pop_constraint, num_steps, [DistrictAggregate("presd", "PRES12D"),], progress_bar=false)
    for (i, district in enumerate(partition.assignments)
        println(district) # the district that node i is assigned to
    end
end
flush(stdout)