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models.py
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models.py
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import random
import orca
import dataset
import utils
import variables
@orca.injectable()
def year(iter_var):
return iter_var
@orca.step('rsh_estimate')
def rsh_estimate(buildings, zones):
return utils.hedonic_estimate("rsh.yaml", buildings, zones)
@orca.step('rsh_simulate')
def rsh_simulate(buildings, zones):
return utils.hedonic_simulate("rsh.yaml", buildings, zones,
"residential_sales_price")
@orca.step('nrh_estimate')
def nrh_estimate(buildings, zones):
return utils.hedonic_estimate("nrh.yaml", buildings, zones)
@orca.step('nrh_simulate')
def nrh_simulate(buildings, zones):
return utils.hedonic_simulate("nrh.yaml", buildings, zones,
"non_residential_rent")
@orca.step('hlcm_estimate')
def hlcm_estimate(households, buildings, zones):
return utils.lcm_estimate("hlcm.yaml", households, "building_id",
buildings, zones)
@orca.step('hlcm_simulate')
def hlcm_simulate(households, buildings, zones):
return utils.lcm_simulate("hlcm.yaml", households, buildings, zones,
"building_id", "residential_units",
"vacant_residential_units")
@orca.step('elcm_estimate')
def elcm_estimate(jobs, buildings, zones):
return utils.lcm_estimate("elcm.yaml", jobs, "building_id",
buildings, zones)
@orca.step('elcm_simulate')
def elcm_simulate(jobs, buildings, zones):
return utils.lcm_simulate("elcm.yaml", jobs, buildings, zones,
"building_id", "job_spaces", "vacant_job_spaces")
@orca.step('households_relocation')
def households_relocation(households):
return utils.simple_relocation(households, .05, "building_id")
@orca.step('jobs_relocation')
def jobs_relocation(jobs):
return utils.simple_relocation(jobs, .05, "building_id")
@orca.step('households_transition')
def households_transition(households):
return utils.simple_transition(households, .05, "building_id")
@orca.step('jobs_transition')
def jobs_transition(jobs):
return utils.simple_transition(jobs, .05, "building_id")
@orca.step('feasibility')
def feasibility(parcels):
utils.run_feasibility(parcels,
variables.parcel_average_price,
variables.parcel_is_allowed,
residential_to_yearly=True)
def random_type(form):
form_to_btype = orca.get_injectable("form_to_btype")
return random.choice(form_to_btype[form])
def add_extra_columns(df):
for col in ["residential_sales_price", "non_residential_rent"]:
df[col] = 0
return df
@orca.step('residential_developer')
def residential_developer(feasibility, households, buildings, parcels, year):
utils.run_developer("residential",
households,
buildings,
"residential_units",
parcels.parcel_size,
parcels.ave_unit_size,
parcels.total_units,
feasibility,
year=year,
target_vacancy=.15,
form_to_btype_callback=random_type,
add_more_columns_callback=add_extra_columns,
bldg_sqft_per_job=400.0)
@orca.step('non_residential_developer')
def non_residential_developer(feasibility, jobs, buildings, parcels, year):
utils.run_developer(["office", "retail", "industrial"],
jobs,
buildings,
"job_spaces",
parcels.parcel_size,
parcels.ave_unit_size,
parcels.total_job_spaces,
feasibility,
year=year,
target_vacancy=.15,
form_to_btype_callback=random_type,
add_more_columns_callback=add_extra_columns,
residential=False,
bldg_sqft_per_job=400.0)