def estimate_mu(self):
iout = -1
self.values_from_mr = {}
for quantity in self.observed_data.get_quantity_objects():
dataset_name = quantity.get_dataset_name()
variable = quantity.get_variable_name()
iout += 1
dimension_reduced = False
quantity_ids = quantity.get_dataset().get_id_attribute()
for i in range(self.number_of_runs):
ds = self._compute_variable_for_one_run(i, variable, dataset_name, self.get_calibration_year(), quantity)
if isinstance(ds, InteractionDataset):
ds = ds.get_flatten_dataset()
if i == 0: # first run
self.mu[iout] = zeros((self.y[iout].size, self.number_of_runs), dtype=float32)
ids = ds.get_id_attribute()
else:
if ds.size() > ids.shape[0]:
ds = DatasetSubset(ds, ds.get_id_index(ids))
dimension_reduced = True
scale = self.get_scales(ds, i+1, variable)
matching_index = ds.get_id_index(quantity_ids)
values = scale[matching_index] * ds.get_attribute(variable)[matching_index]
self.mu[iout][:,i] = try_transformation(values, quantity.get_transformation())
self.values_from_mr[variable.get_expression()] = self.mu[iout]
if dimension_reduced:
self.y[iout] = self.y[iout][quantity.get_dataset().get_id_index(ids)]
def run(self, in_storage, out_storage=None, business_dsname="business", zone_dsname=None):
dataset_pool = DatasetPool(storage=in_storage, package_order=['psrc_parcel', 'urbansim_parcel', 'urbansim', 'opus_core'] )
seed(1)
allbusinesses = dataset_pool.get_dataset(business_dsname)
parcels = dataset_pool.get_dataset('parcel')
buildings = dataset_pool.get_dataset('building')
parcels.compute_variables(["urbansim_parcel.parcel.residential_units", "number_of_buildings = parcel.number_of_agents(building)",
"non_residential_sqft = (parcel.aggregate(building.non_residential_sqft)).astype(int32)",
"number_of_res_buildings = parcel.aggregate(urbansim_parcel.building.is_residential)",
"number_of_nonres_buildings = parcel.aggregate(urbansim_parcel.building.is_non_residential)",
"number_of_mixed_use_buildings = parcel.aggregate(urbansim_parcel.building.is_generic_building_type_6)"
],
dataset_pool=dataset_pool)
restypes = [12, 4, 19, 11, 34, 10, 33]
reslutypes = [13,14,15,24]
is_valid_business = ones(allbusinesses.size(), dtype='bool8')
parcels_not_matched = logical_and(in1d(allbusinesses["parcel_id"], parcels.get_id_attribute(), invert=True), allbusinesses["parcel_id"] > 0)
if(parcels_not_matched.sum() > 0):
is_valid_business[where(parcels_not_matched)] = False
logger.log_warning(message="No parcel exists for %s businesses (%s jobs)" % (parcels_not_matched.sum(),
allbusinesses[self.number_of_jobs_attr][where(parcels_not_matched)].sum()))
zero_parcel = allbusinesses["parcel_id"]<=0
if zero_parcel.sum() > 0:
is_valid_business[where(zero_parcel)] = False
logger.log_warning(message="%s businesses (%s jobs) located on zero parcel_id" % (zero_parcel.sum(),
allbusinesses[self.number_of_jobs_attr][where(zero_parcel)].sum()))
zero_size = logical_and(is_valid_business, allbusinesses[self.number_of_jobs_attr].round() == 0)
if(sum(zero_size) > 0):
is_valid_business[where(zero_size)] = False
logger.log_warning(message="%s businesses are of size 0." % sum(zero_size))
businesses = DatasetSubset(allbusinesses, index=where(is_valid_business)[0])
parcels.add_attribute(name="number_of_workplaces", data=parcels.sum_dataset_over_ids(businesses, constant=1))
has_single_res_buildings = logical_and(parcels["number_of_buildings"] == 1, parcels["number_of_res_buildings"] == 1) # 1 (1 residential)
parcels.add_attribute(data=has_single_res_buildings.astype("int32"), name="buildings_code")
has_mult_res_buildings = logical_and(parcels["number_of_buildings"] > 1, parcels["number_of_nonres_buildings"] == 0) # 2 (mult residential)
parcels.modify_attribute("buildings_code", data=2*ones(has_mult_res_buildings.sum()), index=where(has_mult_res_buildings))
has_single_nonres_buildings = logical_and(logical_and(parcels["number_of_buildings"] == 1, parcels["number_of_nonres_buildings"] == 1), parcels["number_of_mixed_use_buildings"] == 0) # 3 (1 non-res)
parcels.modify_attribute("buildings_code", data=3*ones(has_single_nonres_buildings.sum()), index=where(has_single_nonres_buildings))
has_mult_nonres_buildings = logical_and(logical_and(parcels["number_of_buildings"] > 1, parcels["number_of_res_buildings"] == 0), parcels["number_of_mixed_use_buildings"] == 0) # 4 (mult non-res)
parcels.modify_attribute("buildings_code", data=4*ones(has_mult_nonres_buildings.sum()), index=where(has_mult_nonres_buildings))
has_single_mixed_buildings = logical_and(parcels["number_of_buildings"] == 1, parcels["number_of_mixed_use_buildings"] == 1) # 5 (1 mixed-use)
parcels.modify_attribute("buildings_code", data=5*ones(has_single_mixed_buildings.sum()), index=where(has_single_mixed_buildings))
has_mult_mixed_buildings = logical_and(parcels["number_of_buildings"] > 1,
logical_or(logical_and(parcels["number_of_res_buildings"] > 0, parcels["number_of_nonres_buildings"] > 0),
logical_or(parcels["number_of_mixed_use_buildings"] > 1,
logical_and(parcels["number_of_res_buildings"] == 0,
parcels["number_of_mixed_use_buildings"] > 0)))) # 6
parcels.modify_attribute("buildings_code", data=6*ones(has_mult_mixed_buildings.sum()), index=where(has_mult_mixed_buildings))
has_no_building_res_lutype = logical_and(parcels["number_of_buildings"] == 0, in1d(parcels["land_use_type_id"], reslutypes)) # 7 (vacant with res LU type)
parcels.modify_attribute("buildings_code", data=7*ones(has_no_building_res_lutype.sum()), index=where(has_no_building_res_lutype))
has_no_building_nonres_lutype = logical_and(parcels["number_of_buildings"] == 0, in1d(parcels["land_use_type_id"], reslutypes)==0) # 8 (vacant with non-res LU type)
parcels.modify_attribute("buildings_code", data=8*ones(has_no_building_nonres_lutype.sum()), index=where(has_no_building_nonres_lutype))
business_sizes = businesses[self.number_of_jobs_attr].round().astype("int32")
business_location = {}
business_location1wrkpl = zeros(businesses.size(), dtype="int32")
business_location1wrkplres = zeros(businesses.size(), dtype="int32")
business_ids = businesses.get_id_attribute()
# sample one building for cases when sampling is required.
for ibusid in range(businesses.size()):
idx = where(buildings['parcel_id'] == businesses['parcel_id'][ibusid])[0]
bldgids = buildings['building_id'][idx]
business_location[business_ids[ibusid]] = bldgids
if bldgids.size == 1:
business_location1wrkpl[ibusid] = bldgids[0]
elif bldgids.size > 1:
business_location1wrkpl[ibusid] = bldgids[sample_noreplace(arange(bldgids.size), 1)]
if buildings['residential_units'][idx].sum() > 0:
# Residential buildings are sampled with probabilities proportional to residential units
business_location1wrkplres[ibusid] = bldgids[probsample_noreplace(arange(bldgids.size), 1, prob_array=buildings['residential_units'][idx])]
else:
business_location1wrkplres[ibusid] = business_location1wrkpl[ibusid]
home_based = zeros(business_sizes.sum(), dtype="bool8")
job_building_id = zeros(business_sizes.sum(), dtype="int32")
job_array_labels = business_ids.repeat(business_sizes)
job_assignment_case = zeros(business_sizes.sum(), dtype="int32")
processed_bindicator = zeros(businesses.size(), dtype="bool8")
business_codes = parcels.get_attribute_by_id("buildings_code", businesses["parcel_id"])
business_nworkplaces = parcels.get_attribute_by_id("number_of_workplaces", businesses["parcel_id"])
logger.log_status("Total number of jobs: %s" % home_based.size)
# 1. 1-2 worker business in 1 residential building
idx_sngl_wrk_1bld_fit = where(logical_and(business_sizes < 3, business_codes == 1))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_1bld_fit])
home_based[jidx] = True
job_building_id[jidx] = business_location1wrkpl[idx_sngl_wrk_1bld_fit].repeat(business_sizes[idx_sngl_wrk_1bld_fit])
job_assignment_case[jidx] = 1
processed_bindicator[idx_sngl_wrk_1bld_fit] = True
logger.log_status("1. %s jobs (%s businesses) set as home-based due to 1-2 worker x 1 residential building fit." % (
business_sizes[idx_sngl_wrk_1bld_fit].sum(), idx_sngl_wrk_1bld_fit.size))
# 2. 1-2 worker business in multiple residential buildings
idx_sngl_wrk_multbld_fit = where(logical_and(logical_and(processed_bindicator==0, business_sizes < 3), business_codes == 2))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_multbld_fit])
home_based[jidx] = True
job_building_id[jidx] = business_location1wrkplres[idx_sngl_wrk_multbld_fit].repeat(business_sizes[idx_sngl_wrk_multbld_fit])
job_assignment_case[jidx] = 2
processed_bindicator[idx_sngl_wrk_multbld_fit] = True
logger.log_status("2. %s jobs (%s businesses) set as home-based due to 1-2 worker x multiple residential buildings fit." % (
business_sizes[idx_sngl_wrk_multbld_fit].sum(), idx_sngl_wrk_multbld_fit.size))
# 3. 1-2 worker in single non-res building (not mixed-use)
idx_sngl_wrk_single_nonres_fit = where(logical_and(logical_and(processed_bindicator==0, business_sizes < 3), business_codes == 3))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_single_nonres_fit])
job_building_id[jidx] = business_location1wrkpl[idx_sngl_wrk_single_nonres_fit].repeat(business_sizes[idx_sngl_wrk_single_nonres_fit])
job_assignment_case[jidx] = 3
processed_bindicator[idx_sngl_wrk_single_nonres_fit] = True
logger.log_status("3. %s jobs (%s businesses) placed due to 1-2 worker x single non-res building fit." % (
business_sizes[idx_sngl_wrk_single_nonres_fit].sum(), idx_sngl_wrk_single_nonres_fit.size))
# 4. 1-2 worker in multiple non-res building (not mixed-use)
idx_sngl_wrk_mult_nonres_fit = where(logical_and(logical_and(processed_bindicator==0, business_sizes < 3), business_codes == 4))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_mult_nonres_fit])
job_building_id[jidx] = business_location1wrkpl[idx_sngl_wrk_mult_nonres_fit].repeat(business_sizes[idx_sngl_wrk_mult_nonres_fit])
job_assignment_case[jidx] = 4
processed_bindicator[idx_sngl_wrk_mult_nonres_fit] = True
logger.log_status("4. %s jobs (%s businesses) placed due to 1-2 worker x multiple non-res building fit." % (
business_sizes[idx_sngl_wrk_mult_nonres_fit].sum(), idx_sngl_wrk_mult_nonres_fit.size))
# 5. 1-2 worker in single mixed-use building
idx_sngl_wrk_smu_fit = where(logical_and(logical_and(processed_bindicator==0, business_sizes < 3), business_codes == 5))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_smu_fit])
job_building_id[jidx] = business_location1wrkpl[idx_sngl_wrk_smu_fit].repeat(business_sizes[idx_sngl_wrk_smu_fit])
job_assignment_case[jidx] = 5
processed_bindicator[idx_sngl_wrk_smu_fit] = True
logger.log_status("5. %s jobs (%s businesses) in 1-2 worker x single mixed-use building." % (
business_sizes[idx_sngl_wrk_smu_fit].sum(), idx_sngl_wrk_smu_fit.size))
# 6. 1-2 worker in multiple mixed-type buildings
idx_sngl_wrk_mmu_fit = where(logical_and(logical_and(processed_bindicator==0, business_sizes < 3), business_codes == 6))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_mmu_fit])
job_building_id[jidx] = business_location1wrkpl[idx_sngl_wrk_mmu_fit].repeat(business_sizes[idx_sngl_wrk_mmu_fit])
bldtype = buildings.get_attribute_by_id("building_type_id", business_location1wrkpl[idx_sngl_wrk_mmu_fit])
is_bldtype_res = in1d(bldtype, restypes)
home_based[in1d(job_array_labels, business_ids[idx_sngl_wrk_mmu_fit][where(is_bldtype_res)])] = True
job_assignment_case[jidx] = 6
processed_bindicator[idx_sngl_wrk_mmu_fit] = True
logger.log_status("6. %s jobs (%s businesses) in 1-2 worker x multiple mixed-type buildings. %s jobs classified as home-based." % (
business_sizes[idx_sngl_wrk_mmu_fit].sum(), idx_sngl_wrk_mmu_fit.size, business_sizes[idx_sngl_wrk_mmu_fit][where(is_bldtype_res)].sum()))
# 7. 1-2 worker business in residential parcel with no building
idx_sngl_wrk_vacant_res = where(logical_and(logical_and(processed_bindicator==0, business_sizes < 3), business_codes == 7))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_vacant_res])
job_assignment_case[jidx] = 7
home_based[jidx] = True
processed_bindicator[idx_sngl_wrk_vacant_res] = True
logger.log_status("7. %s jobs (%s businesses of size 1-2) could not be placed due to non-existing buildings in parcels with residential LU type." % (
business_sizes[idx_sngl_wrk_vacant_res].sum(), idx_sngl_wrk_vacant_res.size))
# 8. 3+ workers of governmental workplaces in 1+ residential building
ind_bussiness_case8 = logical_and(logical_and(processed_bindicator==0, logical_and(business_sizes > 2, in1d(businesses['sector_id'], [18,19]))), in1d(business_codes, [1,2]))
idx_wrk_fit = where(ind_bussiness_case8)[0]
jidx = in1d(job_array_labels, business_ids[idx_wrk_fit])
job_assignment_case[jidx] = 8
processed_bindicator[idx_wrk_fit] = True
logger.log_status("8. %s governmental jobs (%s businesses of size 3+) could not be placed due to residing in residential buildings only." % (
business_sizes[idx_wrk_fit].sum(), idx_wrk_fit.size))
# 9. 3-30 workers in single residential building. Make two of them home based.
idx_sngl_wrk_fit = where(logical_and(logical_and(processed_bindicator==0, logical_and(business_sizes > 2, business_sizes <= 30)), business_codes == 1))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_fit])
job_building_id[jidx] = business_location1wrkpl[idx_sngl_wrk_fit].repeat(business_sizes[idx_sngl_wrk_fit])
bsizeminus2 = vstack((2*ones(idx_sngl_wrk_fit.size), business_sizes[idx_sngl_wrk_fit]-2)).ravel("F").astype("int32") # interweaving 2 and remaining business size
hbidx = tile(array([True, False]), bsizeminus2.size/2).repeat(bsizeminus2) # set the first two jobs of every business to True, others to False
home_based[(where(jidx)[0])[hbidx]] = True
job_assignment_case[jidx] = 9
processed_bindicator[idx_sngl_wrk_fit] = True
logger.log_status("9. %s jobs (%s businesses) in 3-30 worker x single residential building. %s jobs assigned as home-based." % (
business_sizes[idx_sngl_wrk_fit].sum(), idx_sngl_wrk_fit.size, hbidx.sum()))
# 10. 3-30 workers in multiple residential buildings. Make two of them home based.
idx_sngl_wrk_fit = where(logical_and(logical_and(processed_bindicator==0, logical_and(business_sizes > 2, business_sizes <= 30)), business_codes == 2))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrk_fit])
job_assignment_case[jidx] = 10
processed_bindicator[idx_sngl_wrk_fit] = True
# sample buildings to businesses by parcels
bpcls = unique(businesses["parcel_id"][idx_sngl_wrk_fit])
for ipcl in range(bpcls.size):
bidx = where(buildings['parcel_id'] == bpcls[ipcl])[0]
bldgids = buildings['building_id'][bidx]
bussids = intersect1d(business_ids[businesses["parcel_id"] == bpcls[ipcl]], business_ids[idx_sngl_wrk_fit])
# multiply by units for sampling prop. to units rather than buildings
bldgids = bldgids.repeat(maximum(1, buildings['residential_units'][bidx].astype('int32')))
if bldgids.size < bussids.size:
bldarray = bldgids.repeat(1+ceil((bussids.size - bldgids.size)/float(bldgids.size)) )
else:
bldarray = bldgids
shuffle(bldarray) # randomly reorder in-place
for ib in range(bussids.size):
jidx = where(job_array_labels == bussids[ib])[0]
job_building_id[jidx] = bldarray[ib]
home_based[jidx[0:2]] = True
logger.log_status("10. %s jobs (%s businesses) in 3-30 worker x multiple residential building. %s jobs assigned as home-based." % (
business_sizes[idx_sngl_wrk_fit].sum(), idx_sngl_wrk_fit.size, idx_sngl_wrk_fit.size*2))
# 11. single workplace, 3+ workers in single non-res or mixed-use building (11.)
idx_sngl_wrkplace_2plus_workers = where(logical_and(logical_and(logical_and(processed_bindicator==0, business_sizes > 2),
logical_or(business_codes==3, business_codes==5)),
business_nworkplaces==1))[0]
which_labels = where(in1d(job_array_labels, business_ids[idx_sngl_wrkplace_2plus_workers]))[0]
job_building_id[which_labels] = business_location1wrkpl[idx_sngl_wrkplace_2plus_workers].repeat(business_sizes[idx_sngl_wrkplace_2plus_workers])
job_assignment_case[which_labels] = 11
processed_bindicator[idx_sngl_wrkplace_2plus_workers] = True
logger.log_status("11. %s jobs (%s businesses) could be placed due to single workplace x 3+ workers x single non-res/mixed-use building fit." % (
business_sizes[idx_sngl_wrkplace_2plus_workers].sum(), idx_sngl_wrkplace_2plus_workers.size))
# 12. single workplace, 3+ workers in multiple mixed-type building
idx_sngl_wrkplace_2plus_workers = where(logical_and(logical_and(logical_and(processed_bindicator==0, business_sizes > 2),
logical_or(business_codes==4, business_codes==6)),
business_nworkplaces==1))[0]
jidx = in1d(job_array_labels, business_ids[idx_sngl_wrkplace_2plus_workers])
job_building_id[jidx] = business_location1wrkpl[idx_sngl_wrkplace_2plus_workers].repeat(business_sizes[idx_sngl_wrkplace_2plus_workers])
job_assignment_case[jidx] = 12
processed_bindicator[idx_sngl_wrkplace_2plus_workers] = True
logger.log_status("12. %s jobs (%s businesses) could be placed due to single workplace x 3+ workers x multiple non-res/mixed building fit." % (
business_sizes[idx_sngl_wrkplace_2plus_workers].sum(), idx_sngl_wrkplace_2plus_workers.size))
# 13. multiple workplaces, 3+ workers in single non-res or mixed building
idx_mult_wrkplace_2plus_workers = where(logical_and(logical_and(logical_and(processed_bindicator==0, business_sizes > 2),
logical_or(business_codes==3, business_codes==5)),
business_nworkplaces > 1))[0]
jidx = in1d(job_array_labels, business_ids[idx_mult_wrkplace_2plus_workers])
job_building_id[jidx] = business_location1wrkpl[idx_mult_wrkplace_2plus_workers].repeat(business_sizes[idx_mult_wrkplace_2plus_workers])
job_assignment_case[jidx] = 13
processed_bindicator[idx_mult_wrkplace_2plus_workers] = True
logger.log_status("13. %s jobs (%s businesses) could be placed due to multiple workplaces x 3+ workers x single non-res/mixed building fit." % (
business_sizes[idx_mult_wrkplace_2plus_workers].sum(), idx_mult_wrkplace_2plus_workers.size))
# 14. multiple workplaces, 3+ workers in multiple non-res or mixed building
idx_mult_wrkplace_2plus_workers = where(logical_and(logical_and(logical_and(processed_bindicator==0, business_sizes > 2),
logical_or(business_codes==4, business_codes==6)),
business_nworkplaces > 1))[0]
processed_bindicator[idx_mult_wrkplace_2plus_workers] = True
# sample buildings to businesses by parcels
bpcls = unique(businesses["parcel_id"][idx_mult_wrkplace_2plus_workers])
#hbasedsum = home_based.sum()
for ipcl in range(bpcls.size):
bldgids = buildings['building_id'][buildings['parcel_id'] == bpcls[ipcl]]
bussids = intersect1d(business_ids[businesses["parcel_id"] == bpcls[ipcl]], business_ids[idx_mult_wrkplace_2plus_workers])
if bldgids.size < bussids.size:
bldarray = bldgids.repeat(1+ceil((bussids.size - bldgids.size)/float(bldgids.size)))
else:
bldarray = bldgids
shuffle(bldarray) # randomly reorder in-place
is_res = in1d(bldarray, restypes)
for ib in range(bussids.size):
jidx = where(job_array_labels == bussids[ib])
job_building_id[jidx] = bldarray[ib]
#home_based[jidx] = is_res
job_assignment_case[jidx] = 14
logger.log_status("14. %s jobs (%s businesses) could be placed due to multiple workplaces x 3+ workers x multiple non-res/mixed building fit." % (
business_sizes[idx_mult_wrkplace_2plus_workers].sum(), idx_mult_wrkplace_2plus_workers.size))
# 15. 3+ workers in residential parcel with no building
idx_wrk_vacant_res = where(logical_and(logical_and(processed_bindicator==0, business_sizes > 2), business_codes == 7))[0]
jidx = in1d(job_array_labels, business_ids[idx_wrk_vacant_res])
job_assignment_case[jidx] = 15
processed_bindicator[idx_wrk_vacant_res] = True
logger.log_status("15. %s jobs (%s businesses of 3+ workers) could not be placed due to non-existing buildings in parcels with residential LU type." % (
business_sizes[idx_wrk_vacant_res].sum(), idx_wrk_vacant_res.size))
# 16. nonresidential parcel with no building
idx_wrk_vacant_nonres = where(logical_and(processed_bindicator==0, business_codes == 8))[0]
jidx = in1d(job_array_labels, business_ids[idx_wrk_vacant_nonres])
job_assignment_case[jidx] = 16
processed_bindicator[idx_wrk_vacant_nonres] = True
logger.log_status("16. %s jobs (%s businesses) could not be placed due to non-existing buildings in parcels with non-esidential LU type." % (
business_sizes[idx_wrk_vacant_nonres].sum(), idx_wrk_vacant_nonres.size))
# 17. 31+ workers in single residential building. Do not place - will go into ELCM.
idx_wrk_fit = where(logical_and(logical_and(processed_bindicator==0, business_sizes > 30), business_codes == 1))[0]
jidx = in1d(job_array_labels, business_ids[idx_wrk_fit])
job_assignment_case[jidx] = 17
processed_bindicator[idx_wrk_fit] = True
logger.log_status("17. %s jobs (%s businesses) in 31+ workers x single residential building." % (
business_sizes[idx_wrk_fit].sum(), idx_wrk_fit.size))
# 18. 31+ workers in multiple residential buildings.
idx_wrk_fit = where(logical_and(logical_and(processed_bindicator==0, business_sizes > 30), business_codes == 2))[0]
jidx = in1d(job_array_labels, business_ids[idx_wrk_fit])
job_assignment_case[jidx] = 18
processed_bindicator[idx_wrk_fit] = True
logger.log_status("18. %s jobs (%s businesses) in 31+ workers x multiple residential building." % (
business_sizes[idx_wrk_fit].sum(), idx_wrk_fit.size))
# jobs in messy buildings
idx_messy_fit = where(logical_and(logical_and(processed_bindicator==0, business_sizes > 0), business_codes == 0))[0]
processed_bindicator[idx_messy_fit] = True
logger.log_status("%s jobs (%s businesses) could not be placed due to messy buildings." % (
business_sizes[idx_messy_fit].sum(), idx_messy_fit.size))
# build new buildings for jobs in cases 7, 8, 15 and 16
jidx_no_bld = where(in1d(job_assignment_case, [7,8,15,16]))[0]
bus = unique(job_array_labels[jidx_no_bld])
bsidx = businesses.get_id_index(bus)
# first create buildings for single workplaces per parcel
single_workplace_idx = where(business_nworkplaces[bsidx] == 1)[0]
newbld_parcel_id = businesses['parcel_id'][bsidx][single_workplace_idx]
newbld_bt = sector2building_type(businesses['sector_id'][bsidx][single_workplace_idx])
newbids = arange(buildings.get_id_attribute().max()+1, buildings.get_id_attribute().max()+single_workplace_idx.size+1)
bbldid = zeros(bsidx.size, dtype='int32')
bbldid[single_workplace_idx] = newbids
# for parcels with multiple workplaces select the largest business to determine its building type
mult_bsidx = bsidx[where(business_nworkplaces[bsidx] > 1)[0]]
empty_parcels = businesses['parcel_id'][mult_bsidx]
uempty_parcels = unique(empty_parcels)
bsize_on_empty_pcl = ndmax(business_sizes[mult_bsidx], labels=empty_parcels, index=uempty_parcels)
newbld2_sec = zeros(uempty_parcels.size, dtype='int32')
newbids2 = arange(newbids.max()+1, newbids.max()+uempty_parcels.size+1)
for ipcl in range(uempty_parcels.size):
newbld2_sec[ipcl] = businesses['sector_id'][mult_bsidx][logical_and(businesses['parcel_id'][mult_bsidx] == uempty_parcels[ipcl],
business_sizes[mult_bsidx]==bsize_on_empty_pcl[ipcl])][0]
this_bidx = where(businesses['parcel_id'][bsidx] == uempty_parcels[ipcl])
bbldid[this_bidx] = newbids2[ipcl]
newbld_parcel_id = concatenate((newbld_parcel_id, uempty_parcels))
newbld_bt = concatenate((newbld_bt, sector2building_type(newbld2_sec)))
newbldgs = {'building_id': concatenate((newbids, newbids2)),
'parcel_id': newbld_parcel_id,
'building_type_id': newbld_bt,
}
buildings.add_elements(newbldgs, require_all_attributes=False)
jidx = where(in1d(job_array_labels, business_ids[bsidx]))[0]
job_building_id[jidx] = bbldid.repeat(business_sizes[bsidx])
logger.log_status("Build %s new buildings to accommodate %s jobs (out of which %s are governmental) from cases 7, 15, 16." % (
newbld_parcel_id.size, jidx.size, business_sizes[bsidx][where(in1d(businesses['sector_id'][bsidx], [18,19]))].sum()))
logger.log_status("Assigned %s (%s percent) home-based jobs." % (home_based.sum(), round(home_based.sum()/(home_based.size/100.),2)))
logger.log_status("Finished %s percent (%s) jobs (%s businesses) processed. %s jobs (%s businesses) remain to be processed." % \
(round(business_sizes[processed_bindicator].sum()/(home_based.size/100.),2),
business_sizes[processed_bindicator].sum(), processed_bindicator.sum(),
business_sizes[logical_not(processed_bindicator)].sum(), business_sizes[logical_not(processed_bindicator)].size))
logger.start_block("Storing jobs data.")
# create job dataset
job_data = {"job_id": (arange(job_building_id.size)+1).astype("int32"),
"home_based_status" : home_based,
"building_id": job_building_id,
"business_id": job_array_labels.astype("int32"),
"sector_id": businesses['sector_id'].repeat(business_sizes).astype("int32"),
"parcel_id": businesses['parcel_id'].repeat(business_sizes).astype("int32"),
"assignment_case": job_assignment_case}
# join with zones
if zone_dsname is not None:
zones = dataset_pool.get_dataset(zone_dsname)
idname = zones.get_id_name()[0]
#jpcls = buildings.get_attribute_by_id('parcel_id', job_building_id)
job_data[idname] = parcels.get_attribute_by_id(idname, job_data["parcel_id"])
dictstorage = StorageFactory().get_storage('dict_storage')
dictstorage.write_table(table_name="jobs", table_data=job_data)
jobs = Dataset(in_storage=dictstorage, in_table_name="jobs", dataset_name="job", id_name="job_id")
if out_storage is not None:
jobs.write_dataset(out_storage=out_storage, out_table_name="jobs")
buildings.write_dataset(out_storage=out_storage, attributes=AttributeType.PRIMARY)
logger.end_block()
return jobs
