def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_resources = 'hrm_resources'
return Configuration({
'import': {
'urbansim.models.%s_creator' % self._model_name: 'HouseholdRelocationModelCreator'
},
'init': {
'arguments': {'debuglevel': self.debuglevel,
'location_id_name': "'%s'" % self.location_id_name,
'probabilities': get_string_or_None(self.probabilities),
},
'name': 'HouseholdRelocationModelCreator().get_model'
},
'prepare_for_run': {
'arguments': {
'rate_storage': 'base_cache_storage',
'rate_table': get_string_or_None(self.rate_table),
'rate_dataset_name': get_string_or_None(self.rate_dataset_name),
},
'name': 'prepare_for_run',
'output': _resources,
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'resources': _resources,
},
'output': self.output_index,
}
})
def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_resources = 'hrm_resources'
return Configuration({
'import': {
'urbansim.models.%s_creator' % self._model_name:
'HouseholdRelocationModelCreator'
},
'init': {
'arguments': {
'debuglevel': self.debuglevel,
'location_id_name': "'%s'" % self.location_id_name,
'probabilities': get_string_or_None(self.probabilities),
},
'name': 'HouseholdRelocationModelCreator().get_model'
},
'prepare_for_run': {
'arguments': {
'rate_storage': 'base_cache_storage',
'rate_table': get_string_or_None(self.rate_table),
'what': "'%s'" % self.what,
},
'name': 'prepare_for_run',
'output': _resources,
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'resources': _resources,
},
'output': self.output_index,
}
})
def execute(self):
return Configuration({
'import': {
self.module_name: self.class_name
},
'init': {
'arguments': {'debuglevel': self.debuglevel,
'filter': get_string_or_None(self.filter),
'dataset_pool': 'dataset_pool'},
'name': 'DistributeUnplacedJobsModel'
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'data_objects': 'datasets',
'location_set': self.location_set,
'agents_filter': get_string_or_None(self.agents_filter),
}
}
})
def execute(self):
return Configuration({
'import': {
self.module_name: self.class_name
},
'init': {
'arguments': {
'debuglevel': self.debuglevel,
'filter': get_string_or_None(self.filter),
'dataset_pool': 'dataset_pool'
},
'name': 'DistributeUnplacedJobsModel'
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'data_objects': 'datasets',
'location_set': self.location_set,
'agents_filter': get_string_or_None(self.agents_filter),
}
}
})
def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_coefficients = "coefficients"
_specification = "specification"
_projects = "projects"
return Configuration(
{
"estimate": {
"arguments": {
"agent_set": _projects,
"data_objects": "datasets",
"debuglevel": self.debuglevel,
"specification": _specification,
},
"output": "(%s, _)" % _coefficients,
},
"import": {
"urbansim.models.development_project_location_choice_model_creator": "DevelopmentProjectLocationChoiceModelCreator"
},
"init": {
"arguments": {
"location_set": self.location_set,
"model_configuration": "model_configuration['development_project_types']['%s']"
% self.project_type,
"project_type": "'%s'" % self.project_type,
"submodel_string": get_string_or_None(self.submodel_string),
},
"name": "DevelopmentProjectLocationChoiceModelCreator().get_model",
},
"prepare_for_estimate": {
"arguments": {
"base_year": "resources['base_year']",
"categories": "model_configuration['development_project_types']['%s']['categories']"
% self.project_type,
"events_for_estimation_storage": "base_cache_storage",
"events_for_estimation_table": "'%s'" % self.events_for_estimation_table,
"specification_storage": "base_cache_storage",
"specification_table": "'%s'" % self.specification_table,
"urbansim_constant": "urbansim_constant",
},
"name": "prepare_for_estimate",
"output": "(%s, %s)" % (_specification, _projects),
},
"prepare_for_run": {
"arguments": {
"coefficients_storage": "base_cache_storage",
"coefficients_table": "'%s'" % self.coefficients_table,
"specification_storage": "base_cache_storage",
"specification_table": "'%s'" % self.specification_table,
},
"name": "prepare_for_run",
"output": "(%s, %s)" % (_specification, _coefficients),
},
"run": {
"arguments": {
"agent_set": self.input_agent_set,
"chunk_specification": "{'records_per_chunk':%s}" % self.records_per_chunk,
"coefficients": _coefficients,
"data_objects": "datasets",
"debuglevel": self.debuglevel,
"specification": _specification,
}
},
}
)
def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_coefficients = 'coefficients'
_specification = 'specification'
_index = 'repm_index'
return Configuration({
'estimate': {
'arguments': {
'data_objects': 'datasets',
'dataset': self.dataset,
'outcome_attribute': "'%s'" % self.outcome_attribute,
'debuglevel': self.debuglevel,
'index': _index,
'specification': _specification,
},
'output': '(%s, _)' % _coefficients
},
'import': {
'urbansim.models.%s' % self._model_name: 'RealEstatePriceModel'
},
'init': {
'arguments': {
'dataset_pool': 'dataset_pool',
'debuglevel': self.debuglevel,
'filter_attribute': None,
'outcome_attribute': "'%s'" % self.outcome_attribute,
'submodel_string': get_string_or_None(self.submodel_string)
},
'name': 'RealEstatePriceModel'
},
'prepare_for_estimate': {
'arguments': {
'dataset': self.dataset,
'filter_variable': get_string_or_None(self.filter_variable),
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _index)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'chunk_specification': "{'nchunks':%s}" % self.nchunks,
'coefficients': _coefficients,
'data_objects': 'datasets',
'dataset': self.dataset,
'debuglevel': self.debuglevel,
'specification': _specification,
}
}
})
def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_coefficients = 'coefficients'
_specification = 'specification'
_projects = 'projects'
return Configuration({
'estimate': {
'arguments': {
'agent_set': _projects,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification
},
'output': '(%s, _)' % _coefficients
},
'import': {
'urbansim.models.development_project_location_choice_model_creator':
'DevelopmentProjectLocationChoiceModelCreator'
},
'init': {
'arguments': {
'location_set':
self.location_set,
'model_configuration':
"model_configuration['development_project_types']['%s']" %
self.project_type,
'project_type':
"'%s'" % self.project_type,
'submodel_string':
get_string_or_None(self.submodel_string),
},
'name':
'DevelopmentProjectLocationChoiceModelCreator().get_model'
},
'prepare_for_estimate': {
'arguments': {
'base_year':
"resources['base_year']",
'categories':
"model_configuration['development_project_types']['%s']['categories']"
% self.project_type,
'events_for_estimation_storage':
'base_cache_storage',
'events_for_estimation_table':
"'%s'" % self.events_for_estimation_table,
'specification_storage':
'base_cache_storage',
'specification_table':
"'%s'" % self.specification_table,
'urbansim_constant':
'urbansim_constant'
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _projects)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'agent_set': self.input_agent_set,
'chunk_specification':
"{'records_per_chunk':%s}" % self.records_per_chunk,
'coefficients': _coefficients,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification
}
}
})
def execute(self):
_coefficients = 'coefficients'
_specification = 'specification'
_index = 'index'
return Configuration({
'estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': _index,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
},
'output': '(%s, _)' % _coefficients
},
'import': {
'urbansim.models.%s' % self._model_name:
'HouseholdLocationChoiceModel'
},
'init': {
'arguments': {
'sampler':
get_string_or_None(self.sampler),
'choices':
"'%s'" % self.choices,
'estimation':
"'%s'" % self.estimation_procedure,
'dataset_pool':
'dataset_pool',
'location_set':
self.location_set,
'sample_size_locations':
self.sample_size_locations,
'capacity_string':
get_string_or_None(self.capacity_string),
'estimation_weight_string':
get_string_or_None(self.estimation_weight_string),
'simulation_weight_string':
get_string_or_None(self.simulation_weight_string),
'number_of_units_string':
get_string_or_None(self.number_of_units_string),
'number_of_agents_string':
get_string_or_None(self.number_of_agents_string),
'location_id_string':
get_string_or_None(self.location_id_name),
'submodel_string':
get_string_or_None(self.submodel_string),
'estimation_size_agents':
self.estimation_size_agents,
'filter':
get_string_or_None(self.location_filter),
'run_config':
self.run_config,
'estimate_config':
self.estimate_config,
"variable_package":
"'%s'" % self.variable_package
},
'name': 'HouseholdLocationChoiceModel'
},
'prepare_for_estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_for_estimation_storage': 'base_cache_storage',
'agents_for_estimation_table':
"'%s'" % self.agents_for_estimation_table_name,
'data_objects': 'datasets',
'index_to_unplace': self.index_to_unplace,
'join_datasets':
'%s' % self.join_agents_for_estimation_with_all_agents,
'portion_to_unplace': self.portion_to_unplace,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
'filter':
get_string_or_None(self.agent_filter_for_estimation)
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _index)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': self.input_index,
'chunk_specification': self.chunk_specification,
'coefficients': _coefficients,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
'maximum_runs': self.maximum_runs
}
}
})
def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_coefficients = 'coefficients'
_specification = 'specification'
_projects = 'projects'
return Configuration({
'estimate': {
'arguments': {
'agent_set': _projects,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification
},
'output': '(%s, _)' % _coefficients
},
'import': {
'urbansim_zone.models.development_project_location_choice_model': 'DevelopmentProjectLocationChoiceModel'
},
'init': {
'arguments': {
'location_set': self.location_set,
'project_type': "'%s'" % self.project_type,
'sampler': get_string_or_None(self.sampler),
'submodel_string': get_string_or_None(self.submodel_string),
'capacity_string': get_string_or_None(self.capacity_string),
},
'name': 'DevelopmentProjectLocationChoiceModel'
},
'prepare_for_estimate': {
'arguments': {
'base_year': 'base_year',
'events_for_estimation_storage': 'base_cache_storage',
'events_for_estimation_table': "'%s'" % self.events_for_estimation_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
'urbansim_constant': 'urbansim_constant',
'units': "'%s'" % self.units
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _projects)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'agent_set': self.input_agent_set,
'chunk_specification': "{'records_per_chunk':%s}" % self.records_per_chunk,
'coefficients': _coefficients,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification
}
}
})
def execute(self):
_coefficients = 'coefficients'
_specification = 'specification'
_index = 'index'
return Configuration({
'estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': _index,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
},
'output': '(%s, _)' % _coefficients
},
'import': {
#'urbansim.models.%s' % self._model_name: 'HouseholdLocationChoiceModelWithPriceAdj'
self._model_name: 'HouseholdLocationChoiceModelWithPriceAdj' #model module in current directory
},
'init': {
'arguments': {
'sampler': get_string_or_None(self.sampler),
'choices': "'%s'" % self.choices,
'estimation': "'%s'" % self.estimation_procedure,
'dataset_pool': 'dataset_pool',
'location_set': self.location_set,
'sample_size_locations': self.sample_size_locations,
'capacity_string': get_string_or_None(self.capacity_string),
'demand_string': get_string_or_None(self.demand_string),
'number_of_units_string': get_string_or_None(self.number_of_units_string),
'number_of_agents_string': get_string_or_None(self.number_of_agents_string),
'run_config': {'lottery_max_iterations': self.lottery_max_iterations}
},
'name': 'HouseholdLocationChoiceModelWithPriceAdj'
},
'prepare_for_estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_for_estimation_storage': 'base_cache_storage',
'agents_for_estimation_table': "'%s'" % self.agents_for_estimation_table_name,
'data_objects': 'datasets',
'index_to_unplace': self.input_index,
'join_datasets': 'True',
'portion_to_unplace': self.portion_to_unplace,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _index)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': self.input_index,
'chunk_specification': "{'nchunks':%s}" % self.nchunks,
'coefficients': _coefficients,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
'maximum_runs': self.maximum_runs
}
}
})
def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_coefficients = 'coefficients'
_specification = 'specification'
_index = 'index'
try:
attribute_to_group_by_dataset_name, attribute_to_group_by_attribute_name = self.attribute_to_group_by.split('.')
except:
raise Exception("Attribute to group by must be of the form "
"'dataset_name.attribute_name', where dataset_name is the name "
"of the dataset containing the attribute to group by "
"(attribute_name). Received '%s'." % self.attribute_to_group_by)
return Configuration({
'estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': _index,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
},
'output': '(%s, _)' % _coefficients
},
'group_by_attribute': (attribute_to_group_by_dataset_name, attribute_to_group_by_attribute_name),
'import': {
'urbansim.models.%s' % self._model_name: 'EmploymentLocationChoiceModel'
},
'init': {
'arguments': {
'sampler': get_string_or_None(self.sampler),
'choices': "'%s'" % self.choices,
'estimation': "'%s'" % self.estimation_procedure,
'dataset_pool': 'dataset_pool',
'location_set': self.location_set,
'sample_size_locations': self.sample_size_locations,
'capacity_string': get_string_or_None(self.capacity_string),
'estimation_weight_string': get_string_or_None(self.estimation_weight_string),
'simulation_weight_string': get_string_or_None(self.simulation_weight_string),
'filter': get_string_or_None(self.filter),
'estimation_size_agents': self.estimation_size_agents,
'compute_capacity_flag': self.compute_capacity_flag,
'number_of_units_string': get_string_or_None(self.number_of_units_string),
'run_config': {'agent_units_string': get_string_or_None(self.agent_units_string),
'lottery_max_iterations': self.lottery_max_iterations},
'variable_package': "'%s'" % self.variable_package
},
'name': 'EmploymentLocationChoiceModel'
},
'prepare_for_estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_for_estimation_storage': 'base_cache_storage',
'agents_for_estimation_table': get_string_or_None(self.agents_for_estimation_table),
'join_datasets':self.join_datasets,
'data_objects': 'datasets',
'portion_to_unplace': self.portion_to_unplace,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
'filter': get_string_or_None(self.filter_for_estimation),
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _index)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': self.input_index,
'chunk_specification': "{'records_per_chunk':%s}" % self.records_per_chunk,
'coefficients': _coefficients,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
'maximum_runs': self.maximum_runs
}
}
})
def execute(self):
_coefficients = 'coefficients'
_specification = 'specification'
_index = 'index'
return Configuration({
'estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': _index,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
},
'output': '(%s, _)' % _coefficients
},
'import': {
'urbansim.models.%s' % self._model_name: 'HouseholdLocationChoiceModel'
},
'init': {
'arguments': {
'sampler': get_string_or_None(self.sampler),
'choices': "'%s'" % self.choices,
'estimation': "'%s'" % self.estimation_procedure,
'dataset_pool': 'dataset_pool',
'location_set': self.location_set,
'sample_size_locations': self.sample_size_locations,
'capacity_string': get_string_or_None(self.capacity_string),
'estimation_weight_string': get_string_or_None(self.estimation_weight_string),
'simulation_weight_string': get_string_or_None(self.simulation_weight_string),
'number_of_units_string': get_string_or_None(self.number_of_units_string),
'number_of_agents_string': get_string_or_None(self.number_of_agents_string),
'location_id_string': get_string_or_None(self.location_id_name),
'submodel_string': get_string_or_None(self.submodel_string),
'estimation_size_agents': self.estimation_size_agents,
'filter': get_string_or_None(self.location_filter),
'run_config': self.run_config,
'estimate_config': self.estimate_config,
"variable_package": "'%s'" % self.variable_package
},
'name': 'HouseholdLocationChoiceModel'
},
'prepare_for_estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_for_estimation_storage': 'base_cache_storage',
'agents_for_estimation_table': "'%s'" % self.agents_for_estimation_table_name,
'data_objects': 'datasets',
'index_to_unplace': self.index_to_unplace,
'join_datasets': '%s' % self.join_agents_for_estimation_with_all_agents,
'portion_to_unplace': self.portion_to_unplace,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
'filter': get_string_or_None(self.agent_filter_for_estimation)
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _index)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': self.input_index,
'chunk_specification': self.chunk_specification,
'coefficients': _coefficients,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
'maximum_runs': self.maximum_runs
}
}
})
def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_coefficients = 'coefficients'
_specification = 'specification'
_index = 'repm_index'
return Configuration({
'estimate': {
'arguments': {
'data_objects': 'datasets',
'dataset': self.dataset,
'outcome_attribute': "'%s'" % self.outcome_attribute,
'debuglevel': self.debuglevel,
'index': _index,
'specification': _specification,
},
'output': '(%s, _)' % _coefficients
},
'import': {
'urbansim.models.%s' % self._model_name: 'RealEstatePriceModel'
},
'init': {
'arguments': {
'dataset_pool': 'dataset_pool',
'debuglevel': self.debuglevel,
'filter_attribute': None,
'outcome_attribute': "'%s'" % self.outcome_attribute,
'submodel_string': get_string_or_None(self.submodel_string)
},
'name': 'RealEstatePriceModel'
},
'prepare_for_estimate': {
'arguments': {
'dataset': self.dataset,
'filter_variable':
get_string_or_None(self.filter_variable),
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _index)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'chunk_specification': "{'nchunks':%s}" % self.nchunks,
'coefficients': _coefficients,
'data_objects': 'datasets',
'dataset': self.dataset,
'debuglevel': self.debuglevel,
'specification': _specification,
}
}
})
def execute(self):
_coefficients = 'coefficients'
_specification = 'specification'
_index = 'index'
return Configuration({
'estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': _index,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
},
'output': '(%s, _)' % _coefficients
},
'import': {
#'urbansim.models.%s' % self._model_name: 'HouseholdLocationChoiceModelWithPriceAdj'
self._model_name:
'HouseholdLocationChoiceModelWithPriceAdj' #model module in current directory
},
'init': {
'arguments': {
'sampler':
get_string_or_None(self.sampler),
'choices':
"'%s'" % self.choices,
'estimation':
"'%s'" % self.estimation_procedure,
'dataset_pool':
'dataset_pool',
'location_set':
self.location_set,
'sample_size_locations':
self.sample_size_locations,
'capacity_string':
get_string_or_None(self.capacity_string),
'demand_string':
get_string_or_None(self.demand_string),
'number_of_units_string':
get_string_or_None(self.number_of_units_string),
'number_of_agents_string':
get_string_or_None(self.number_of_agents_string),
'run_config': {
'lottery_max_iterations': self.lottery_max_iterations
}
},
'name': 'HouseholdLocationChoiceModelWithPriceAdj'
},
'prepare_for_estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_for_estimation_storage': 'base_cache_storage',
'agents_for_estimation_table':
"'%s'" % self.agents_for_estimation_table_name,
'data_objects': 'datasets',
'index_to_unplace': self.input_index,
'join_datasets': 'True',
'portion_to_unplace': self.portion_to_unplace,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _index)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': self.input_index,
'chunk_specification': "{'nchunks':%s}" % self.nchunks,
'coefficients': _coefficients,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
'maximum_runs': self.maximum_runs
}
}
})
def execute(self):
# Names of intermediate objects used to get data between steps
# in this model process.
_coefficients = 'coefficients'
_specification = 'specification'
_index = 'index'
try:
attribute_to_group_by_dataset_name, attribute_to_group_by_attribute_name = self.attribute_to_group_by.split(
'.')
except:
raise Exception(
"Attribute to group by must be of the form "
"'dataset_name.attribute_name', where dataset_name is the name "
"of the dataset containing the attribute to group by "
"(attribute_name). Received '%s'." %
self.attribute_to_group_by)
return Configuration({
'estimate': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': _index,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
},
'output': '(%s, _)' % _coefficients
},
'group_by_attribute': (attribute_to_group_by_dataset_name,
attribute_to_group_by_attribute_name),
'import': {
'urbansim.models.%s' % self._model_name:
'EmploymentLocationChoiceModel'
},
'init': {
'arguments': {
'sampler':
get_string_or_None(self.sampler),
'choices':
"'%s'" % self.choices,
'estimation':
"'%s'" % self.estimation_procedure,
'dataset_pool':
'dataset_pool',
'location_set':
self.location_set,
'sample_size_locations':
self.sample_size_locations,
'capacity_string':
get_string_or_None(self.capacity_string),
'estimation_weight_string':
get_string_or_None(self.estimation_weight_string),
'simulation_weight_string':
get_string_or_None(self.simulation_weight_string),
'filter':
get_string_or_None(self.filter),
'estimation_size_agents':
self.estimation_size_agents,
'compute_capacity_flag':
self.compute_capacity_flag,
'number_of_units_string':
get_string_or_None(self.number_of_units_string),
'run_config': {
'agent_units_string':
get_string_or_None(self.agent_units_string),
'lottery_max_iterations':
self.lottery_max_iterations
},
'variable_package':
"'%s'" % self.variable_package
},
'name': 'EmploymentLocationChoiceModel'
},
'prepare_for_estimate': {
'arguments': {
'agent_set':
self.agent_set,
'agents_for_estimation_storage':
'base_cache_storage',
'agents_for_estimation_table':
get_string_or_None(self.agents_for_estimation_table),
'join_datasets':
self.join_datasets,
'data_objects':
'datasets',
'portion_to_unplace':
self.portion_to_unplace,
'specification_storage':
'base_cache_storage',
'specification_table':
"'%s'" % self.specification_table,
'filter':
get_string_or_None(self.filter_for_estimation),
},
'name': 'prepare_for_estimate',
'output': '(%s, %s)' % (_specification, _index)
},
'prepare_for_run': {
'arguments': {
'coefficients_storage': 'base_cache_storage',
'coefficients_table': "'%s'" % self.coefficients_table,
'specification_storage': 'base_cache_storage',
'specification_table': "'%s'" % self.specification_table,
},
'name': 'prepare_for_run',
'output': '(%s, %s)' % (_specification, _coefficients)
},
'run': {
'arguments': {
'agent_set': self.agent_set,
'agents_index': self.input_index,
'chunk_specification':
"{'records_per_chunk':%s}" % self.records_per_chunk,
'coefficients': _coefficients,
'data_objects': 'datasets',
'debuglevel': self.debuglevel,
'specification': _specification,
'maximum_runs': self.maximum_runs
}
}
})
