def prepare_for_run(self, add_member_prefix=True, specification_storage=None, specification_table=None, coefficients_storage=None,
coefficients_table=None, **kwargs):
if add_member_prefix:
specification_table, coefficients_table = \
self.group_member.add_member_prefix_to_table_names([specification_table, coefficients_table])
return RegressionModel.prepare_for_run(self, specification_storage=specification_storage, specification_table=specification_table,
coefficients_storage=coefficients_storage, coefficients_table=coefficients_table, **kwargs)
def prepare_for_run(self,
add_member_prefix=True,
specification_storage=None,
specification_table=None,
coefficients_storage=None,
coefficients_table=None,
**kwargs):
if add_member_prefix:
specification_table, coefficients_table = \
self.group_member.add_member_prefix_to_table_names([specification_table, coefficients_table])
return RegressionModel.prepare_for_run(
self,
specification_storage=specification_storage,
specification_table=specification_table,
coefficients_storage=coefficients_storage,
coefficients_table=coefficients_table,
**kwargs)
def prepare_for_run(self, *args, **kwargs):
spec, coef, dummy = RegressionModel.prepare_for_run(
self, *args, **kwargs)
return (spec, coef)
def prepare_for_run(self, dataset_pool,
create_proposal_set=True,
parcel_filter_for_new_development=None,
parcel_filter_for_redevelopment=None,
template_filter=None,
spec_replace_module_variable_pair=None,
proposed_units_variable="urbansim_parcel.development_project_proposal.units_proposed",
**kwargs):
"""create development project proposal dataset from parcels and development templates.
spec_replace_module_variable_pair is a tuple with two elements: module name, variable within the module
that contans a dictionary of model variables to be replaced in the specification.
"""
specification, coefficients, dummy = RegressionModel.prepare_for_run(self, **kwargs)
try:
existing_proposal_set_parent = dataset_pool.get_dataset('development_project_proposal')
#load proposals whose status_id are not of id_tentative or id_not_available
available_idx = where(logical_and(existing_proposal_set_parent.get_attribute("status_id") != DevelopmentProjectProposalDataset.id_tentative,
existing_proposal_set_parent.get_attribute("status_id") != DevelopmentProjectProposalDataset.id_not_available))[0]
existing_proposal_set = DatasetSubset(existing_proposal_set_parent, available_idx)
# Code updated by Hanyi Li, MAG 6/8/2010
# Replacing the cached 'development_project_proposal' dataset with
# the filtered dataset 'existing_proposal_set'
dataset_pool.replace_dataset(existing_proposal_set_parent.get_dataset_name(), existing_proposal_set)
except:
existing_proposal_set = None
parcels = dataset_pool.get_dataset('parcel')
templates = dataset_pool.get_dataset('development_template')
# It is important that during this method no variable flushing happens, since
# we create datasets of the same name for different purposes (new development and redevelopment)
# and flushing would mix them up
flush_variables_current = SessionConfiguration().get('flush_variables', False)
SessionConfiguration().put_data({'flush_variables': False})
# Code added by Jesse Ayers, MAG, 9/14/2009
# Getting an index of parcels that have actively developing projects (those on a velocity function)
# and making sure that new proposals are not generated for them
if existing_proposal_set:
parcels_with_proposals = existing_proposal_set.get_attribute('parcel_id')
parcels_with_proposals_idx = parcels.get_id_index(parcels_with_proposals)
if parcel_filter_for_new_development is not None:
if parcel_filter_for_new_development[parcel_filter_for_new_development.find('=')+1] == '=':
filter = 'flter = numpy.logical_and(parcel.number_of_agents(development_project_proposal) == 0, %s)' % parcel_filter_for_new_development
else:
parcel_filter_for_new_development = parcel_filter_for_new_development[parcel_filter_for_new_development.find('=')+1:].lstrip()
filter = 'flter = numpy.logical_and(parcel.number_of_agents(development_project_proposal) == 0, %s)' % parcel_filter_for_new_development
index1 = where(parcels.compute_variables(filter))[0]
else:
if parcel_filter_for_new_development is not None:
index1 = where(parcels.compute_variables(parcel_filter_for_new_development))[0]
else:
index1 = None
if template_filter is not None:
try:
index2 = where(templates.compute_variables(template_filter))[0]
except Exception, e:
logger.log_warning( "template_filter is set to %s, but there is an error when computing it: %s"
% (template_filter, e) )
index2 = None
def prepare_for_run(self, *args, **kwargs):
spec, coef, dummy = RegressionModel.prepare_for_run(self, *args, **kwargs)
return (spec, coef)
def prepare_for_run(
self,
dataset_pool,
create_proposal_set=True,
parcel_filter_for_new_development=None,
parcel_filter_for_redevelopment=None,
template_filter=None,
spec_replace_module_variable_pair=None,
proposed_units_variable="urbansim_parcel.development_project_proposal.units_proposed",
**kwargs):
"""create development project proposal dataset from parcels and development templates.
spec_replace_module_variable_pair is a tuple with two elements: module name, variable within the module
that contans a dictionary of model variables to be replaced in the specification.
"""
specification, coefficients, dummy = RegressionModel.prepare_for_run(
self, **kwargs)
try:
existing_proposal_set_parent = dataset_pool.get_dataset(
'development_project_proposal')
#load proposals whose status_id are not of id_tentative or id_not_available
available_idx = where(
logical_and(
existing_proposal_set_parent.get_attribute("status_id") !=
DevelopmentProjectProposalDataset.id_tentative,
existing_proposal_set_parent.get_attribute("status_id") !=
DevelopmentProjectProposalDataset.id_not_available))[0]
existing_proposal_set = DatasetSubset(existing_proposal_set_parent,
available_idx)
# Code updated by Hanyi Li, MAG 6/8/2010
# Replacing the cached 'development_project_proposal' dataset with
# the filtered dataset 'existing_proposal_set'
dataset_pool.replace_dataset(
existing_proposal_set_parent.get_dataset_name(),
existing_proposal_set)
except:
existing_proposal_set = None
parcels = dataset_pool.get_dataset('parcel')
templates = dataset_pool.get_dataset('development_template')
# It is important that during this method no variable flushing happens, since
# we create datasets of the same name for different purposes (new development and redevelopment)
# and flushing would mix them up
flush_variables_current = SessionConfiguration().get(
'flush_variables', False)
SessionConfiguration().put_data({'flush_variables': False})
# Code added by Jesse Ayers, MAG, 9/14/2009
# Getting an index of parcels that have actively developing projects (those on a velocity function)
# and making sure that new proposals are not generated for them
if existing_proposal_set:
parcels_with_proposals = existing_proposal_set.get_attribute(
'parcel_id')
parcels_with_proposals_idx = parcels.get_id_index(
parcels_with_proposals)
if parcel_filter_for_new_development is not None:
if parcel_filter_for_new_development[
parcel_filter_for_new_development.find('=') +
1] == '=':
filter = 'flter = numpy.logical_and(parcel.number_of_agents(development_project_proposal) == 0, %s)' % parcel_filter_for_new_development
else:
parcel_filter_for_new_development = parcel_filter_for_new_development[
parcel_filter_for_new_development.find('=') +
1:].lstrip()
filter = 'flter = numpy.logical_and(parcel.number_of_agents(development_project_proposal) == 0, %s)' % parcel_filter_for_new_development
index1 = where(parcels.compute_variables(filter))[0]
else:
if parcel_filter_for_new_development is not None:
index1 = where(
parcels.compute_variables(
parcel_filter_for_new_development))[0]
else:
index1 = None
if template_filter is not None:
try:
index2 = where(templates.compute_variables(template_filter))[0]
except Exception, e:
logger.log_warning(
"template_filter is set to %s, but there is an error when computing it: %s"
% (template_filter, e))
index2 = None
