def hlcm_simulate(households, buildings, aggregations, settings, low_income):
fname = misc.config("hlcm.yaml")
print "\nAffordable housing HLCM:\n"
cfg = yaml.load(open(fname))
cfg["choosers_predict_filters"] = "income <= %d" % low_income
open(misc.config("hlcm_tmp.yaml"), "w").write(yaml.dump(cfg))
# low income into affordable units
utils.lcm_simulate("hlcm_tmp.yaml",
households,
buildings,
aggregations,
"building_id",
"residential_units",
"vacant_affordable_units",
settings.get("enable_supply_correction", None),
cast=True)
os.remove(misc.config("hlcm_tmp.yaml"))
print "\nMarket rate housing HLCM:\n"
# then everyone into market rate units
utils.lcm_simulate("hlcm.yaml",
households,
buildings,
aggregations,
"building_id",
"residential_units",
"vacant_market_rate_units",
settings.get("enable_supply_correction", None),
cast=True)
def hlcm_simulate(households, buildings, aggregations, settings, low_income):
fname = misc.config("hlcm.yaml")
print "\nAffordable housing HLCM:\n"
cfg = yaml.load(open(fname))
cfg["choosers_predict_filters"] = "income <= %d" % low_income
open(misc.config("hlcm_tmp.yaml"), "w").write(yaml.dump(cfg))
# low income into affordable units
utils.lcm_simulate("hlcm_tmp.yaml", households, buildings,
aggregations,
"building_id", "residential_units",
"vacant_affordable_units",
settings.get("enable_supply_correction", None))
os.remove(misc.config("hlcm_tmp.yaml"))
print "\nMarket rate housing HLCM:\n"
# then everyone into market rate units
utils.lcm_simulate("hlcm.yaml", households, buildings,
aggregations,
"building_id", "residential_units",
"vacant_market_rate_units",
settings.get("enable_supply_correction", None))
def elcm_simulate(jobs, buildings, aggregations, zones, elcm_config):
buildings.local["non_residential_rent"] = \
buildings.local.non_residential_rent.fillna(0)
return utils.lcm_simulate(
elcm_config, jobs, buildings, aggregations + [zones],
"building_id", "job_spaces",
"vacant_job_spaces", cast=True)
def elcm_simulate(jobs, buildings, aggregations):
buildings.local["non_residential_rent"] = \
buildings.local.non_residential_rent.fillna(0)
buildings.index.names = ["index"]
return utils.lcm_simulate("elcm.yaml",
orca.orca.DataFrameWrapper('jobs_for_sim',
jobs.to_frame().dropna(subset=['building_id'])),
buildings, aggregations,
"building_id", "job_spaces",
"vacant_job_spaces", cast=True)
def hlcm_simulate(households, buildings, aggregations, settings):
return utils.lcm_simulate(
"hlcm.yaml",
households,
buildings,
aggregations,
"building_id",
"residential_units",
"vacant_residential_units",
settings.get("enable_supply_correction", None),
)
def wplcm_simulate(persons, households, jobs):
# can only send in jobs that have a valid building_id, so remove unlocated jobs for now
jobs_df = jobs.to_frame()
jobs_df = jobs_df[jobs_df.building_id>0]
jobs_df.index.name = 'job_id'
orca.add_table('located_jobs', jobs_df)
located_jobs = orca.get_table('located_jobs')
res = utils.lcm_simulate("wplcmcoef.yaml", persons, located_jobs, None,
"job_id", "number_of_jobs", "vacant_jobs", cast=True)
orca.clear_cache()
def elcm_simulate(jobs, buildings, aggregations, elcm_config):
buildings.local["non_residential_rent"] = \
buildings.local.non_residential_rent.fillna(0)
return utils.lcm_simulate(elcm_config,
jobs,
buildings,
aggregations,
"building_id",
"job_spaces",
"vacant_job_spaces",
cast=True)
def hlcm_simulate(households, residential_units, aggregations,
settings, yaml_name, equilibration_name):
return utils.lcm_simulate(cfg=yaml_name,
choosers=households,
buildings=residential_units,
join_tbls=aggregations,
out_fname='unit_id',
supply_fname='num_units',
vacant_fname='vacant_units',
# enable_supply_correction=settings.get(
# equilibration_name, None),
cast=True)
def ual_hlcm_renter_simulate(households, residential_units, unit_aggregations,
ual_settings):
return utils.lcm_simulate(cfg='ual_hlcm_renter.yaml',
choosers=households,
buildings=residential_units,
join_tbls=unit_aggregations,
out_fname='unit_id',
supply_fname='num_units',
vacant_fname='vacant_units',
enable_supply_correction=ual_settings.get(
'rent_equilibration', None),
cast=True)
def hlcm_simulate(households, residential_units, aggregations,
settings, yaml_name, equilibration_name):
return utils.lcm_simulate(cfg=yaml_name,
choosers=households,
buildings=residential_units,
join_tbls=aggregations,
out_fname='unit_id',
supply_fname='num_units',
vacant_fname='vacant_units',
enable_supply_correction=settings.get(
equilibration_name, None),
cast=True)
def ual_hlcm_owner_simulate(households, residential_units, unit_aggregations,
ual_settings):
# Note that the submarket id (zone_id) needs to be in the table of alternatives,
# for supply/demand equilibration, and needs to NOT be in the choosers table, to
# avoid conflicting when the tables are joined
return utils.lcm_simulate(cfg='ual_hlcm_owner.yaml',
choosers=households,
buildings=residential_units,
join_tbls=unit_aggregations,
out_fname='unit_id',
supply_fname='num_units',
vacant_fname='vacant_units',
enable_supply_correction=ual_settings.get(
'price_equilibration', None),
cast=True)
def hlcm_simulate(households, buildings, persons, settings):
movers = households.to_frame()
movers = movers[movers.building_id == -1]
relocated = movers[movers.is_inmigrant < 1]
res = utils.lcm_simulate("hlcmcoef.yaml", households, buildings,
None, "building_id", "residential_units",
"vacant_residential_units", cast=True)
orca.clear_cache()
# Determine which relocated persons get disconnected from their job
if settings.get('remove_jobs_from_workers', False):
persons_df = persons.to_frame()
relocated_workers = persons_df.loc[(persons_df.employment_status > 0) &
(persons_df.household_id.isin
(relocated.index))]
relocated_workers['new_dist_to_work'] = network_distance_from_home_to_work(
relocated_workers.workplace_zone_id,
relocated_workers.household_zone_id)
relocated_workers['prev_dist_to_work'] = network_distance_from_home_to_work(
relocated_workers.workplace_zone_id,
relocated_workers.prev_household_zone_id)
# if new distance to work is greater than old, disconnect person from job
relocated_workers.job_id = np.where(relocated_workers.new_dist_to_work >
relocated_workers.prev_dist_to_work,
-1, relocated_workers.job_id)
persons.update_col_from_series("job_id", relocated_workers.job_id,
cast=True)
# Update is_inmigrant- I think this it is ok to do this now,
# but perhaps this should be part of a clean up step
# at the end of the sim year.
households.update_col_from_series("is_inmigrant", pd.Series(0,
index=households.index), cast=True)
orca.clear_cache()
return res
def elcm_simulate(jobs, buildings, parcels, zones, gridcells):
res = utils.lcm_simulate("elcmcoef.yaml", jobs, buildings,
[parcels, zones, gridcells],
"building_id", "job_spaces", "vacant_job_spaces",
cast=True)
orca.clear_cache()
def elcm_simulate(jobs, buildings, aggregations):
buildings.local["non_residential_price"] = \
buildings.local.non_residential_price.fillna(0)
return utils.lcm_simulate("elcm.yaml", jobs, buildings, aggregations,
"building_id", "job_spaces",
"vacant_job_spaces")
def elcm_simulate(jobs, buildings, aggregations):
return utils.lcm_simulate("elcm.yaml", jobs, buildings, aggregations,
"building_id", "job_spaces", "vacant_job_spaces")
def hlcm_simulate(households, buildings, aggregations, settings):
return utils.lcm_simulate("hlcm.yaml", households, buildings, aggregations,
"building_id", "residential_units",
"vacant_residential_units",
settings.get("enable_supply_correction", None))
def elcm_basic_simulate(jobs, buildings, aggregations):
return utils.lcm_simulate("elcm_basic.yaml", jobs, buildings, aggregations,
"building_id", "job_spaces",
"vacant_job_spaces")
