def get_model(self, location_set,
sampler = "opus_core.samplers.weighted_sampler",
utilities = "opus_core.linear_utilities",
choices = "opus_core.random_choices",
probabilities = "opus_core.mnl_probabilities",
estimation = "opus_core.bhhh_mnl_estimation",
sample_proportion_locations = None,
sample_size_locations = 20,
estimation_size_agents = 1.0,
compute_capacity_flag = False,
filter = None,
submodel_string = "sector_id",
run_config = None, estimate_config=None, debuglevel=0):
run_config = merge_resources_if_not_None(run_config, [
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)])
run_config = merge_resources_with_defaults(run_config,
[("capacity_string", self.capacity_string_default)])
estimate_config = merge_resources_if_not_None(estimate_config, [
("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(estimate_config,
[("weights_for_estimation_string", self.estimation_weight_string_default)])
return AgentLocationChoiceModel(location_set, agent_name="job",
model_name="Employment Location Choice Model", \
short_name="ELCM", sampler=sampler, utilities=utilities,
probabilities=probabilities, choices=choices, filter=filter, submodel_string=submodel_string,
run_config=run_config, estimate_config=estimate_config,
debuglevel=debuglevel)
def __init__(self,
project_type,
location_set,
model_configuration,
sampler = "opus_core.samplers.weighted_sampler",
utilities = "opus_core.linear_utilities",
choices = "urbansim.first_agent_first_choices",
probabilities = "opus_core.mnl_probabilities",
estimation = "opus_core.bhhh_mnl_estimation",
sample_proportion_locations = None,
sample_size_locations = 30,
estimation_size_agents = 1.0,
compute_capacity_flag = True,
filter = "",
submodel_string = "size_category",
location_id_string = None,
run_config = None,
estimate_config=None,
debuglevel=0):
units = model_configuration['units']
developable_maximum_unit_variable_full_name = model_configuration['developable_maximum_unit_variable_full_name']
developable_minimum_unit_variable_full_name = model_configuration['developable_minimum_unit_variable_full_name']
default_capacity_attribute = "urbansim.gridcell.is_developable_for_%s" % units
default_filter = "urbansim.gridcell.developable_%s" % units
if filter == "":
filter = default_filter
run_config = merge_resources_if_not_None(run_config, [
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)])
run_config = merge_resources_with_defaults(run_config,
[("capacity_string", default_capacity_attribute)])
estimate_config = merge_resources_if_not_None(estimate_config, [
("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(estimate_config,
[("weights_for_estimation_string", self.estimation_weight_string_default)])
DevelopmentProjectLocationChoiceModel.__init__(self, location_set,
project_type=project_type,
units=units,
developable_maximum_unit_variable_full_name=developable_maximum_unit_variable_full_name,
developable_minimum_unit_variable_full_name=developable_minimum_unit_variable_full_name,
model_name="Regional Development Project %s Location Choice Model" % project_type,
sampler=sampler,
utilities=utilities,
probabilities=probabilities,
choices=choices,
filter=filter,
submodel_string=submodel_string,
location_id_string = location_id_string,
run_config=run_config,
estimate_config=estimate_config,
debuglevel=debuglevel)
def get_model(
self,
location_set,
sampler="opus_core.samplers.weighted_sampler",
utilities="opus_core.linear_utilities",
choices="opus_core.random_choices",
probabilities="opus_core.mnl_probabilities",
estimation="opus_core.bhhh_mnl_estimation",
sample_proportion_locations=None,
sample_size_locations=30,
estimation_size_agents=1.0,
compute_capacity_flag=True,
filter=None,
submodel_string=None,
location_id_string=None,
demand_string=None, # if not None, the aggregate demand for locations will be stored in this attribute
run_config=None,
estimate_config=None,
debuglevel=0,
dataset_pool=None):
run_config = merge_resources_if_not_None(
run_config,
[("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)])
run_config = merge_resources_with_defaults(
run_config,
[("capacity_string", self.capacity_string_default),
("number_of_agents_string", self.number_of_agents_string_default),
("number_of_units_string", self.number_of_units_string_default)])
if demand_string:
run_config["demand_string"] = demand_string
estimate_config = merge_resources_if_not_None(
estimate_config,
[("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(
estimate_config, [("weights_for_estimation_string",
self.estimation_weight_string_default)])
return AgentLocationChoiceModel(
location_set,
model_name="Household Location Choice Model",
short_name="HLCM",
sampler=sampler,
utilities=utilities,
probabilities=probabilities,
choices=choices,
filter=filter,
submodel_string=submodel_string,
location_id_string=location_id_string,
run_config=run_config,
estimate_config=estimate_config,
debuglevel=debuglevel,
dataset_pool=dataset_pool)
def get_model(self,
location_set,
sampler = "opus_core.samplers.weighted_sampler",
utilities = "opus_core.linear_utilities",
choices = "urbansim.first_agent_first_choices",
probabilities = "opus_core.mnl_probabilities",
estimation = "opus_core.bhhh_mnl_estimation",
sample_proportion_locations = None,
sample_size_locations = 30,
estimation_size_agents = 1.0,
compute_capacity_flag = True,
filter = "randstad.gridcell.is_developable",
submodel_string = "development_type_id",
run_config = None,
estimate_config=None,
debuglevel=0):
default_capacity_string = "randstad.gridcell.is_developable"
run_config = merge_resources_if_not_None(run_config, [
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)
("filter", filter)])
run_config = merge_resources_with_defaults(run_config,
[("capacity_string", default_capacity_string),
("simulation_sampling_include_current_choice", False)])
estimate_config = merge_resources_if_not_None(estimate_config, [
("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(estimate_config,
[("weights_for_estimation_string", self.estimation_weight_string_default),
("simulation_sampling_include_current_choice", True)])
return LandUseDevelopmentLocationChoiceModel(location_set,
opus_package='randstad',
model_name="Landuse Development Location Choice Model",
sampler=sampler,
utilities=utilities,
probabilities=probabilities,
choices=choices,
filter=filter,
submodel_string=submodel_string,
run_config=run_config,
estimate_config=estimate_config,
debuglevel=debuglevel)
def get_model(self, location_set,
sampler = "opus_core.samplers.weighted_sampler",
utilities = "opus_core.linear_utilities",
choices = "opus_core.random_choices",
probabilities = "opus_core.mnl_probabilities",
estimation = "opus_core.bhhh_mnl_estimation",
sample_proportion_locations = None,
sample_size_locations = 30,
estimation_size_agents = 1.0,
compute_capacity_flag = True,
filter=None,
submodel_string = None, location_id_string = None,
demand_string = None, # if not None, the aggregate demand for locations will be stored in this attribute
run_config = None, estimate_config=None, debuglevel=0, dataset_pool=None):
run_config = merge_resources_if_not_None(run_config, [
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)])
run_config = merge_resources_with_defaults(run_config,
[("capacity_string", self.capacity_string_default),
("number_of_agents_string", self.number_of_agents_string_default),
("number_of_units_string", self.number_of_units_string_default)
])
if demand_string:
run_config["demand_string"] = demand_string
estimate_config = merge_resources_if_not_None(estimate_config, [
("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(estimate_config,
[("weights_for_estimation_string", self.estimation_weight_string_default)])
return AgentLocationChoiceModel(location_set,
model_name="Household Location Choice Model",
short_name="HLCM",
sampler=sampler,
utilities=utilities,
probabilities=probabilities,
choices=choices,
filter=filter,
submodel_string=submodel_string,
location_id_string=location_id_string,
run_config=run_config,
estimate_config=estimate_config,
debuglevel=debuglevel, dataset_pool=dataset_pool)
def get_model(self,
location_set,
sampler="opus_core.samplers.weighted_sampler",
utilities="opus_core.linear_utilities",
choices="opus_core.random_choices",
probabilities="opus_core.mnl_probabilities",
estimation="opus_core.bhhh_mnl_estimation",
sample_proportion_locations=None,
sample_size_locations=20,
estimation_size_agents=1.0,
compute_capacity_flag=False,
filter=None,
submodel_string="sector_id",
run_config=None,
estimate_config=None,
debuglevel=0):
run_config = merge_resources_if_not_None(
run_config,
[("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)])
run_config = merge_resources_with_defaults(
run_config, [("capacity_string", self.capacity_string_default)])
estimate_config = merge_resources_if_not_None(
estimate_config,
[("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(
estimate_config, [("weights_for_estimation_string",
self.estimation_weight_string_default)])
return AgentLocationChoiceModel(location_set, agent_name="job",
model_name="Employment Location Choice Model", \
short_name="ELCM", sampler=sampler, utilities=utilities,
probabilities=probabilities, choices=choices, filter=filter, submodel_string=submodel_string,
run_config=run_config, estimate_config=estimate_config,
debuglevel=debuglevel)
def __init__(
self,
group_member,
location_set,
agents_grouping_attribute='building.building_type_id',
sampler="opus_core.samplers.weighted_sampler",
utilities="opus_core.linear_utilities",
choices="urbansim.first_agent_first_choices",
probabilities="opus_core.mnl_probabilities",
estimation="opus_core.bhhh_mnl_estimation",
capacity_string="is_developable_for_buildings_UNITS",
estimation_weight_string=None,
developable_maximum_unit_variable="developable_maximum_buildings_UNITS",
developable_minimum_unit_variable="developable_minimum_UNITS", # None means don't consider any minimum. For default, set it to empty string
number_of_agents_string="buildings_SSS_space",
number_of_units_string="total_maximum_development_SSS",
sample_proportion_locations=None,
sample_size_locations=30,
estimation_size_agents=1.0,
compute_capacity_flag=True,
filter="developable_maximum_buildings_UNITS", # None doesn't use any filter
submodel_string="size_category_SSS", # Put here None, if no submodels should be used.
nrecords_per_chunk_for_estimation_sampling=1000, # put here None, if everything in 1 chunk
location_id_string=None,
run_config=None,
estimate_config=None,
debuglevel=0,
dataset_pool=None,
variable_package="urbansim"):
""" 'group_member' is of type ModelGroupMember.
"""
group_member_name = group_member.get_member_name()
units = group_member.get_attribute_value("units")[0]
if capacity_string:
capacity_string = re.sub("UNITS", units, capacity_string)
capacity_string = re.sub("SSS", group_member_name, capacity_string)
if filter:
filter = re.sub("UNITS", units, filter)
filter = re.sub("SSS", group_member_name, filter)
if developable_maximum_unit_variable:
developable_maximum_unit_variable = re.sub(
"UNITS", units, developable_maximum_unit_variable)
developable_maximum_unit_variable = re.sub(
"SSS", group_member_name, developable_maximum_unit_variable)
if developable_minimum_unit_variable == "":
developable_minimum_unit_variable = "developable_minimum_%s" % units
elif developable_minimum_unit_variable:
developable_minimum_unit_variable = re.sub(
"UNITS", units, developable_minimum_unit_variable)
developable_minimum_unit_variable = re.sub(
"SSS", group_member_name, developable_minimum_unit_variable)
if submodel_string:
submodel_string = re.sub("UNITS", units, submodel_string)
submodel_string = re.sub("SSS", group_member_name, submodel_string)
if number_of_agents_string:
number_of_agents_string = re.sub('UNITS', units,
number_of_agents_string)
number_of_agents_string = re.sub('SSS', group_member_name,
number_of_agents_string)
if number_of_units_string:
number_of_units_string = re.sub('UNITS', units,
number_of_units_string)
number_of_units_string = re.sub('SSS', group_member_name,
number_of_units_string)
# create full names from (possibly) short names
tmpdict = Resources({
"filter": filter,
"max": developable_maximum_unit_variable,
"min": developable_minimum_unit_variable
})
self.add_prefix_to_variable_names(["filter", "max", "min"],
location_set,
variable_package,
resources=tmpdict)
filter = tmpdict["filter"]
if tmpdict["max"]:
self.developable_maximum_unit_variable = VariableName(
tmpdict["max"])
else:
self.developable_maximum_unit_variable = None
if tmpdict["min"]:
self.developable_minimum_unit_variable = VariableName(
tmpdict["min"])
else:
self.developable_minimum_unit_variable = None
self.project_type = group_member_name
self.units = units
run_config = merge_resources_with_defaults(run_config, [
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag),
("capacity_string", capacity_string),
("agent_units_string", "urbansim.building.building_size"),
("number_of_agents_string", number_of_agents_string),
("number_of_units_string", number_of_units_string),
])
estimate_config = merge_resources_with_defaults(
estimate_config,
[("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents),
("weights_for_estimation_string", estimation_weight_string),
("capacity_string", capacity_string),
("compute_capacity_flag", compute_capacity_flag)])
if nrecords_per_chunk_for_estimation_sampling:
estimate_config[
"chunk_specification_for_estimation"] = ChunkSpecification({
"records_per_chunk":
nrecords_per_chunk_for_estimation_sampling
})
AgentLocationChoiceModelMember.__init__(
self,
group_member,
location_set,
agents_grouping_attribute,
model_name="Building Location Choice Model",
short_name="BLCM",
sampler=sampler,
utilities=utilities,
probabilities=probabilities,
choices=choices,
filter=filter,
submodel_string=submodel_string,
location_id_string=location_id_string,
run_config=run_config,
estimate_config=estimate_config,
debuglevel=debuglevel,
dataset_pool=dataset_pool,
variable_package=variable_package)
def get_model(self,
project_type,
location_set,
sampler = "opus_core.samplers.weighted_sampler",
utilities = "opus_core.linear_utilities",
choices = "urbansim.first_agent_first_choices",
probabilities = "opus_core.mnl_probabilities",
estimation = "opus_core.bhhh_mnl_estimation",
sample_proportion_locations = None,
sample_size_locations = 30,
estimation_size_agents = 1.0,
compute_capacity_flag = True,
filter = "",
submodel_string = "size_category",
model_configuration = None,
location_id_string = None,
run_config = None,
estimate_config = None,
debuglevel = 0,
units = '',
developable_maximum_unit_variable_full_name = '',
developable_minimum_unit_variable_full_name = '',
residential = False):
if model_configuration is not None:
units = model_configuration['units']
developable_maximum_unit_variable_full_name = model_configuration['developable_maximum_unit_variable_full_name']
developable_minimum_unit_variable_full_name = model_configuration['developable_minimum_unit_variable_full_name']
default_capacity_attribute = "urbansim.gridcell.is_developable_for_%s" % units
default_filter = "urbansim.gridcell.developable_%s" % units
if filter == "":
filter = default_filter
run_config = merge_resources_if_not_None(run_config, [
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)])
run_config = merge_resources_with_defaults(run_config,
[("capacity_string", default_capacity_attribute)])
estimate_config = merge_resources_if_not_None(estimate_config, [
("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(estimate_config,
[("weights_for_estimation_string", self.estimation_weight_string_default)])
return DevelopmentProjectLocationChoiceModel(location_set,
project_type=project_type,
units=units,
developable_maximum_unit_variable_full_name=developable_maximum_unit_variable_full_name,
developable_minimum_unit_variable_full_name=developable_minimum_unit_variable_full_name,
model_name="Development Project %s Location Choice Model" % project_type,
# residential = residential,
sampler=sampler,
utilities=utilities,
probabilities=probabilities,
choices=choices,
filter=filter,
submodel_string=submodel_string,
location_id_string = location_id_string,
run_config=run_config,
estimate_config=estimate_config,
debuglevel=debuglevel)
def __init__(self, group_member, location_set,
agents_grouping_attribute = 'building.building_type_id',
sampler = "opus_core.samplers.weighted_sampler",
utilities = "opus_core.linear_utilities",
choices = "urbansim.first_agent_first_choices",
probabilities = "opus_core.mnl_probabilities",
estimation = "opus_core.bhhh_mnl_estimation",
capacity_string = "is_developable_for_buildings_UNITS",
estimation_weight_string = None,
developable_maximum_unit_variable = "developable_maximum_buildings_UNITS",
developable_minimum_unit_variable = "developable_minimum_UNITS", # None means don't consider any minimum. For default, set it to empty string
number_of_agents_string = "buildings_SSS_space",
number_of_units_string = "total_maximum_development_SSS",
sample_proportion_locations = None,
sample_size_locations = 30,
estimation_size_agents = 1.0,
compute_capacity_flag = True,
filter = "developable_maximum_buildings_UNITS", # None doesn't use any filter
submodel_string = "size_category_SSS", # Put here None, if no submodels should be used.
nrecords_per_chunk_for_estimation_sampling = 1000, # put here None, if everything in 1 chunk
location_id_string = None,
run_config = None, estimate_config=None, debuglevel=0, dataset_pool=None, variable_package = "urbansim"):
""" 'group_member' is of type ModelGroupMember.
"""
group_member_name = group_member.get_member_name()
units = group_member.get_attribute_value("units")[0]
if capacity_string:
capacity_string = re.sub("UNITS", units, capacity_string)
capacity_string = re.sub("SSS", group_member_name, capacity_string)
if filter:
filter = re.sub("UNITS", units, filter)
filter = re.sub("SSS", group_member_name, filter)
if developable_maximum_unit_variable:
developable_maximum_unit_variable = re.sub("UNITS", units, developable_maximum_unit_variable)
developable_maximum_unit_variable = re.sub("SSS", group_member_name, developable_maximum_unit_variable)
if developable_minimum_unit_variable == "":
developable_minimum_unit_variable = "developable_minimum_%s" % units
elif developable_minimum_unit_variable:
developable_minimum_unit_variable = re.sub("UNITS", units, developable_minimum_unit_variable)
developable_minimum_unit_variable = re.sub("SSS", group_member_name, developable_minimum_unit_variable)
if submodel_string:
submodel_string = re.sub("UNITS", units, submodel_string)
submodel_string = re.sub("SSS", group_member_name, submodel_string)
if number_of_agents_string:
number_of_agents_string = re.sub('UNITS', units, number_of_agents_string)
number_of_agents_string = re.sub('SSS', group_member_name, number_of_agents_string)
if number_of_units_string:
number_of_units_string = re.sub('UNITS', units, number_of_units_string)
number_of_units_string = re.sub('SSS', group_member_name, number_of_units_string)
# create full names from (possibly) short names
tmpdict = Resources({"filter": filter, "max": developable_maximum_unit_variable,
"min": developable_minimum_unit_variable})
self.add_prefix_to_variable_names(["filter", "max", "min"], location_set, variable_package, resources=tmpdict)
filter = tmpdict["filter"]
if tmpdict["max"]:
self.developable_maximum_unit_variable = VariableName(tmpdict["max"])
else:
self.developable_maximum_unit_variable = None
if tmpdict["min"]:
self.developable_minimum_unit_variable = VariableName(tmpdict["min"])
else:
self.developable_minimum_unit_variable = None
self.project_type = group_member_name
self.units = units
run_config = merge_resources_with_defaults(run_config, [
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag),
("capacity_string", capacity_string),
("agent_units_string", "urbansim.building.building_size"),
("number_of_agents_string", number_of_agents_string),
("number_of_units_string", number_of_units_string),
])
estimate_config = merge_resources_with_defaults(estimate_config, [
("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents),
("weights_for_estimation_string", estimation_weight_string),
("capacity_string", capacity_string),
("compute_capacity_flag", compute_capacity_flag)])
if nrecords_per_chunk_for_estimation_sampling:
estimate_config["chunk_specification_for_estimation"] = ChunkSpecification({
"records_per_chunk": nrecords_per_chunk_for_estimation_sampling})
AgentLocationChoiceModelMember.__init__(self, group_member, location_set,
agents_grouping_attribute,
model_name = "Building Location Choice Model",
short_name = "BLCM",
sampler=sampler,
utilities=utilities,
probabilities=probabilities,
choices=choices,
filter=filter,
submodel_string=submodel_string,
location_id_string=location_id_string,
run_config=run_config,
estimate_config=estimate_config,
debuglevel=debuglevel,
dataset_pool=dataset_pool,
variable_package=variable_package)
