Пример #1
0
    def __init__(self):
        config = Baseline()

        config_changes = {
            'description':
            'Run REPM and HLCM with bidding choice only',
            'models': [
                "real_estate_price_model",
                "household_relocation_model",
                "household_location_choice_model_with_price_adj",
            ],
            #            'models_in_year': {2000:
            #                               [   "household_relocation_model_for_2000",
            #                                   "household_location_choice_model_for_2000",]
            #                           },
            'years': (2001, 2001),
        }
        config.replace(config_changes)
        config["models_configuration"][
            "household_location_choice_model_with_price_adj"] = {}
        config["models_configuration"]["household_location_choice_model_with_price_adj"]["controller"] = \
              HouseholdLocationChoiceModelWithPriceAdjConfigurationCreator(
                  location_set = "building",
                  sampler = "opus_core.samplers.weighted_sampler",
                  sample_size_locations = 50,
                  input_index = 'hrm_index',
            #                  filter = 'building.unit_price',
                  demand_string="demand",
                  capacity_string = "urbansim_parcel.building.vacant_residential_units",
                  nchunks=1,
                  lottery_max_iterations=20
                  ).execute()
        #        config['models_configuration']['household_location_choice_model_with_price_adj']['controller']['run']['arguments']['chunk_specification'] = "{'nchunks':1}"
        self.merge(config)
Пример #2
0
    def __init__(self):
        config = Baseline()

        config_changes = {
            "description": "Run REPM and HLCM with bidding choice only",
            "models": [
                "real_estate_price_model",
                "household_relocation_model",
                "household_location_choice_model_with_price_adj",
            ],
            #            'models_in_year': {2000:
            #                               [   "household_relocation_model_for_2000",
            #                                   "household_location_choice_model_for_2000",]
            #                           },
            "years": (2001, 2001),
        }
        config.replace(config_changes)
        config["models_configuration"]["household_location_choice_model_with_price_adj"] = {}
        config["models_configuration"]["household_location_choice_model_with_price_adj"][
            "controller"
        ] = HouseholdLocationChoiceModelWithPriceAdjConfigurationCreator(
            location_set="building",
            sampler="opus_core.samplers.weighted_sampler",
            sample_size_locations=50,
            input_index="hrm_index",
            #                  filter = 'building.unit_price',
            demand_string="demand",
            capacity_string="urbansim_parcel.building.vacant_residential_units",
            nchunks=1,
            lottery_max_iterations=20,
        ).execute()
        #        config['models_configuration']['household_location_choice_model_with_price_adj']['controller']['run']['arguments']['chunk_specification'] = "{'nchunks':1}"
        self.merge(config)
    def __init__(self):
        config = Baseline()

        config_changes = {
            'description':'assigning jobs to workers',
            'models_in_year':{2001:[ "work_at_home_choice_model",],
                              2002:[ "workplace_choice_model_for_resident" ] },
            'years': (2001,2002),
            'datasets_to_cache_after_each_model':['person'],
        }
        config.replace(config_changes)
        
        self.merge(config)
        self['models_configuration']['work_at_home_choice_model']['controller']['run']['arguments']['run_choice_model'] = False
        self['models_configuration']['work_at_home_choice_model']['controller']['run']['arguments']['choose_job_only_in_residence_zone'] = False
Пример #4
0
    def __init__(self):
        config = Baseline()

        config_changes = {
            'description':
            'assigning jobs to workers',
            'models': [
                #"process_pipeline_events",
                "real_estate_price_model",
                "expected_sale_price_model",
                "development_proposal_choice_model",
                "building_construction_model",
                "household_transition_model",
                "employment_transition_model",
                "household_relocation_model",
                "household_location_choice_model",
                "employment_relocation_model",
                {
                    "employment_location_choice_model": {
                        'group_members': '_all_'
                    }
                },
                "work_at_home_choice_model",
                "workplace_choice_model_for_resident",
                'distribute_unplaced_jobs_model'
            ],
            #                {2001:[ "work_at_home_choice_model",],
            #                              2002:[ "workplace_choice_model_for_resident" ] },
            'years': (2001, 2006),
            #            'datasets_to_cache_after_each_model':['person'],
        }

        from psrc.configs.create_travel_model_configuration import create_travel_model_configuration
        travel_model_configuration = create_travel_model_configuration(
            'baseline_travel_model_psrc_2008_lmwang',
            emme2_batch_file='MODEL1-0.BAT',
            mode='full',
            years_to_run={
                2005: '2006_v1.0aTG',
                2010: '2010_v1.0aTG',
                2015: '2010_v1.0aTG_2015',
                2020: '2020_v1.0aTG'
            })
        config['travel_model_configuration'] = travel_model_configuration
        config.replace(config_changes)

        self.merge(config)
Пример #5
0
    def __init__(self):
        config = Baseline()

        config_changes = {
            'description':'assigning jobs to workers',
            'models_in_year':{2001:[ "work_at_home_choice_model",],
                              2002:[ "workplace_choice_model_for_resident" ] },
            'years': (2001,2002),
            'datasets_to_cache_after_each_model':['person'],
        }
        config.replace(config_changes)
        
        self.merge(config)
        self['models_configuration']['work_at_home_choice_model']['controller']['run']['arguments']['run_choice_model'] = True
        self['models_configuration']['work_at_home_choice_model']['controller']['run']['arguments']['choose_job_only_in_residence_zone'] = True
        self['models_configuration']['work_at_home_choice_model']['controller']['init']['arguments']['filter'] = "'job.building_type==2'"
        self['models_configuration']['work_at_home_choice_model']['controller']['prepare_for_run']['arguments']['agents_filter'] = "'urbansim_parcel.person.is_worker'"
        self['models_configuration']['workplace_choice_model_for_resident']['controller']['init']['arguments']["run_config"].merge({"capacity_string":"job.building_type==1"})
        self['models_configuration']['workplace_choice_model_for_resident']['controller']['init']['arguments']["filter"] = "'job.building_type==1'"
        self['models_configuration']['workplace_choice_model_for_resident']['controller']['run']['arguments']["agents_filter"] = "'urbansim_parcel.person.is_non_home_based_worker'"
        self['models_configuration']['workplace_choice_model_for_resident']['controller']['run']['arguments']["chunk_specification"] = "{'records_per_chunk':20000}"
    def __init__(self):
        config = Baseline()

        config_changes = {
            'description': 'assigning jobs to workers',
            'models_in_year': {
                2001: [
                    "work_at_home_choice_model",
                ],
                2002: ["workplace_choice_model_for_resident"]
            },
            'years': (2001, 2002),
            'datasets_to_cache_after_each_model': ['person'],
        }
        config.replace(config_changes)

        self.merge(config)
        self['models_configuration']['work_at_home_choice_model'][
            'controller']['run']['arguments']['run_choice_model'] = False
        self['models_configuration']['work_at_home_choice_model'][
            'controller']['run']['arguments'][
                'choose_job_only_in_residence_zone'] = False
Пример #7
0
    def __init__(self):
        config = Baseline()

        config_changes = {
            'description':'assigning jobs to workers',
            'models':[
                #"process_pipeline_events",
                "real_estate_price_model",
                "expected_sale_price_model",
                "development_proposal_choice_model",
                "building_construction_model",
                "household_transition_model",
                "employment_transition_model",
                "household_relocation_model",
                "household_location_choice_model",
                "employment_relocation_model",
                {"employment_location_choice_model":{'group_members': '_all_'}},
                "work_at_home_choice_model",                
                "workplace_choice_model_for_resident",
                'distribute_unplaced_jobs_model'
                ],
#                {2001:[ "work_at_home_choice_model",],
#                              2002:[ "workplace_choice_model_for_resident" ] },
            'years': (2001,2006),
#            'datasets_to_cache_after_each_model':['person'],
        }
        
        from psrc.configs.create_travel_model_configuration import create_travel_model_configuration
        travel_model_configuration = create_travel_model_configuration('baseline_travel_model_psrc_2008_lmwang', 
                                                                       emme2_batch_file='MODEL1-0.BAT',
                                                                       mode='full', years_to_run={2005: '2006_v1.0aTG',
                                                                                                  2010: '2010_v1.0aTG', 
                                                                                                  2015: '2010_v1.0aTG_2015', 
                                                                                                  2020: '2020_v1.0aTG'})
        config['travel_model_configuration'] = travel_model_configuration
        config.replace(config_changes)
        
        self.merge(config)
                'person_id': arange(len(hh_ids)) + 1,
                'household_id': array(hh_ids),
                'member_id': array(member_ids),
                'is_worker': array(is_worker),
                'job_id': array(job_ids),
            },
        )

        persons = PersonDataset(in_storage=in_storage,
                                in_table_name=persons_table_name)
        persons.write_dataset(out_storage=out_storage,
                              out_table_name=persons_table_name)


if __name__ == '__main__':
    config = Baseline()
    config.replace(
        {
            'scenario_database_configuration':
            ScenarioDatabaseConfiguration(
                database_name='psrc_2005_parcel_baseyear', ),
            'estimation_database_configuration':
            EstimationDatabaseConfiguration(
                database_name='psrc_2005_parcel_baseyear_change_20080219', ),
            'dataset_pool_configuration':
            DatasetPoolConfiguration(
                package_order=['urbansim_parcel', 'urbansim', 'opus_core'], ),
            'low_memory_mode':
            False,
            'cache_directory':
            '/urbansim_cache/psrc_parcel/persons',
        in_storage.write_table(
                table_name=persons_table_name,
                table_data={
                    'person_id':arange(len(hh_ids))+1,
                    'household_id':array(hh_ids),
                    'member_id':array(member_ids),
                    'is_worker':array(is_worker),                    
                    'job_id':array(job_ids),
                    },
            )

        persons = PersonDataset(in_storage=in_storage, in_table_name=persons_table_name)
        persons.write_dataset(out_storage=out_storage, out_table_name=persons_table_name)

if __name__ == '__main__':
    config = Baseline()
    config.replace({
        'scenario_database_configuration': ScenarioDatabaseConfiguration(
            database_name = 'psrc_2005_parcel_baseyear',
            ),
        'estimation_database_configuration': EstimationDatabaseConfiguration(
            database_name = 'psrc_2005_parcel_baseyear_change_20080219',
            ),
        'dataset_pool_configuration': DatasetPoolConfiguration(
            package_order=['urbansim_parcel','urbansim', 'opus_core'],
            ),
        'low_memory_mode': False,
        'cache_directory': '/urbansim_cache/psrc_parcel/persons',
        'debuglevel':7,
        'base_year': 2000,
        'years': (2000,2000),
    def __init__(self):
        config = PsrcParcelConfiguration()
        config[
            'creating_baseyear_cache_configuration'].cache_directory_root = r'/Users/hana/urbansim_cache/psrc/data_preparation/run_zipcodes'
        config[
            'creating_baseyear_cache_configuration'].baseyear_cache.existing_cache_to_copy = r'/Users/hana/urbansim_cache/psrc/data_preparation/cache_for_zipcodes'
        #config['scenario_database_configuration'].database_name = 'psrc_2005_parcel_baseyear_data_prep_start'
        config[
            'scenario_database_configuration'].database_name = 'psrc_2005_parcel_baseyear_data_prep_business_zip'
        config_changes = {
            'description':
            'data preparation for PSRC parcel (buildings)',
            'flush_variables':
            False,
            'cache_directory':
            '/Users/hana/urbansim_cache/psrc/data_preparation/cache_for_zipcodes',
            'dataset_pool_configuration':
            DatasetPoolConfiguration(package_order=[
                'psrc_parcel', 'urbansim_parcel', 'urbansim', 'opus_core'
            ], ),
            'base_year':
            2000,
            'years': (2001, 2003),
            'models_in_year': {
                2001: [
                    "employment_relocation_model", {
                        "employment_location_choice_model": {
                            "group_members": "_all_"
                        }
                    }
                ],
                2002: [
                    "employment_relocation_model",
                    "governmental_employment_location_choice_model",
                ],
                2003: [
                    "employment_relocation_model",
                    "governmental_employment_location_choice_model_without_filter"
                ]
            },
            "datasets_to_preload": {
                'zone': {},
                'job': {},
                'building': {},
                "job_building_type": {},
                "zipcode": {}
            },
            "datasets_to_cache_after_each_model":
            ['parcel', 'building', 'job']
        }
        #use configuration in config as defaults and merge with config_changes
        config.replace(config_changes)
        self.merge(config)

        self['models_configuration'][
            'non_home_based_employment_location_choice_model'] = {}
        self['models_configuration']['non_home_based_employment_location_choice_model']['controller'] = \
                   EmploymentLocationChoiceModelByZipcodesConfigurationCreator(
                                location_set = "building",
                                input_index = 'erm_index',
                                sampler = None,
                                records_per_chunk = 3000,
                                capacity_string = "urbansim_parcel.building.vacant_non_home_based_job_space",
                                number_of_units_string = None,
                                lottery_max_iterations=30
                                ).execute()
        self['models_configuration'][
            'governmental_employment_location_choice_model'] = {}
        self['models_configuration']['governmental_employment_location_choice_model']['controller'] = \
                   ScalingJobsModelByZipcodesConfigurationCreator(
                                location_set = "building",
                                input_index = 'erm_index',
                                filter = "urbansim_parcel.building.is_governmental"
                                ).execute()
        self['models_configuration']['governmental_employment_location_choice_model_without_filter'] = {}
        self['models_configuration']['governmental_employment_location_choice_model_without_filter']['controller'] = \
                   ScalingJobsModelByZipcodesConfigurationCreator(
                                location_set = "building",
                                input_index = 'erm_index',
                                ).execute()
        self['models_configuration'][
            'home_based_employment_location_choice_model'] = {}
        self['models_configuration']['home_based_employment_location_choice_model']['controller'] = \
                   EmploymentLocationChoiceModelByZipcodesConfigurationCreator(
                                location_set = "building",
                                input_index = 'erm_index',
                                sampler = None,
                                capacity_string = "urbansim_parcel.building.vacant_home_based_job_space",
                                number_of_units_string = None,
                                lottery_max_iterations=30
                                ).execute()
        self['models_configuration']['employment_relocation_model']['controller'] = \
                    EmploymentRelocationModelConfigurationCreator(
                               location_id_name = 'building_id',
                               probabilities = None,
                               rate_table=None,
                               output_index = 'erm_index').execute()
Пример #11
0
 def __init__(self):
     config = PsrcParcelConfiguration()
     config['creating_baseyear_cache_configuration'].cache_directory_root = r'/Users/hana/urbansim_cache/psrc/data_preparation/run'
     config['creating_baseyear_cache_configuration'].baseyear_cache.existing_cache_to_copy = r'/Users/hana/urbansim_cache/psrc/data_preparation/cache_tmp'
     config['scenario_database_configuration'].database_name = 'psrc_2005_parcel_baseyear_data_prep_start'
     config_changes = {
         'description':'data preparation for PSRC parcel (buildings)',
         'flush_variables': False,
         'cache_directory': '/Users/hana/urbansim_cache/psrc/data_preparation/cache',
         'dataset_pool_configuration': DatasetPoolConfiguration(
             package_order=['psrc_parcel', 'urbansim_parcel', 'urbansim', 'opus_core'],
             ),
         'base_year':2000,
         'years':(2001, 2005),
         'models_in_year': {
            2001: # Step 2 (Create new residential buildings)
            [ 
              "real_estate_price_model",
              "expected_sale_price_model",
              "development_proposal_choice_model",
              "building_construction_model",
             ],
            2002: # Step 3 (Assign buildings to households)
            [
              "household_relocation_model",
              "household_location_choice_model",
             ],
            2003: # Step 4 (Assign buildings to jobs with known parcel_id)
            [
             'assign_buildings_to_jobs'
             ],
            2004: # Step 5 (Create new non-residential buildings)
            [
              "expected_sale_price_model",
              "development_proposal_choice_model_nr",
              "building_construction_model",
             ],
           2005: # Step 6 (Assign buildings to remaining jobs)
           [
             "employment_relocation_model",
             {"employment_location_choice_model": {"group_members": "_all_" }},
             "employment_relocation_model",
             "governmental_employment_location_choice_model_without_filter"
            ]
        },
         "datasets_to_preload":{
                 'zone':{},
                 'household':{},
                 'job': {},
                 'building': {},
                 'parcel': {},
                 "job_building_type":{},
                 #'development_project_proposal': {}
             },
         #"low_memory_mode": True,
         "datasets_to_cache_after_each_model": [
                  'parcel', 'building', 'development_project_proposal', 'household', 'job',
                  'development_project_proposal_component'
                  ]
     }
     #use configuration in config as defaults and merge with config_changes
     config.replace(config_changes)
     self.merge(config)
     self['models_configuration']['development_proposal_choice_model']['controller']["import"] =  {
                    "psrc_parcel.models.development_proposal_sampling_model_by_zones":
                    "DevelopmentProposalSamplingModelByZones"
                    }
     self['models_configuration']['development_proposal_choice_model']['controller']["init"]["name"] =\
                     "DevelopmentProposalSamplingModelByZones"
     self['models_configuration']['development_proposal_choice_model']['controller']['run']['arguments']["zones"] = 'zone'
     self['models_configuration']['development_proposal_choice_model']['controller']['run']['arguments']["type"] = "'residential'"
     self['models_configuration']['development_proposal_choice_model']['controller']['run']['arguments']["n"] = 50
     self['models_configuration']['development_proposal_choice_model_nr'] = Configuration(self['models_configuration']['development_proposal_choice_model'])
     self['models_configuration']['development_proposal_choice_model_nr']['controller']['run']['arguments']["type"] = "'non_residential'"
     self['models_configuration']['expected_sale_price_model']['controller']["prepare_for_run"]['arguments']["parcel_filter_for_redevelopment"] = None
     #self['models_configuration']['expected_sale_price_model']['controller']["prepare_for_run"]['arguments']["create_proposal_set"] = False
     self['models_configuration']['expected_sale_price_model']['controller']["run"]['arguments']["chunk_specification"] = "{'nchunks': 5}"
     #self['models_configuration']['building_construction_model']['controller']["run"]['arguments']["consider_amount_built_in_parcels"] = False
     self['models_configuration']['building_construction_model']['controller']['run']['arguments']["current_year"] = 2000
     
     self['models_configuration']['household_location_choice_model'] = {}
     self['models_configuration']['household_location_choice_model']['controller'] = \
                HouseholdLocationChoiceModelByZonesConfigurationCreator(
                             location_set = "building",
                             sampler = None,
                             input_index = 'hrm_index',
                             capacity_string = "urbansim_parcel.building.vacant_residential_units",
                             number_of_units_string = None,
                             nchunks=1,
                             lottery_max_iterations=20
                             ).execute()
     self['models_configuration']['household_relocation_model']['controller'] = \
                 HouseholdRelocationModelConfigurationCreator(
                            location_id_name = 'building_id',
                            probabilities = None,
                            rate_table=None,
                            output_index = 'hrm_index').execute()
                            
     self['models_configuration']['non_home_based_employment_location_choice_model'] = {}
     self['models_configuration']['non_home_based_employment_location_choice_model']['controller'] = \
                EmploymentLocationChoiceModelByZonesConfigurationCreator(
                             location_set = "building",
                             input_index = 'erm_index',
                             sampler = None,
                             capacity_string = "urbansim_parcel.building.vacant_non_home_based_job_space",
                             number_of_units_string = None,
                             lottery_max_iterations=30
                             ).execute()
     self['models_configuration']['governmental_employment_location_choice_model'] = {}
     self['models_configuration']['governmental_employment_location_choice_model']['controller'] = \
                ScalingJobsModelByZonesConfigurationCreator(
                             location_set = "building",
                             input_index = 'erm_index',
                             filter = "urbansim_parcel.building.is_governmental"
                             ).execute()
     self['models_configuration']['governmental_employment_location_choice_model_without_filter'] = {}
     self['models_configuration']['governmental_employment_location_choice_model_without_filter']['controller'] = \
                ScalingJobsModelByZonesConfigurationCreator(
                             location_set = "building",
                             input_index = 'erm_index',
                             ).execute()
     self['models_configuration']['home_based_employment_location_choice_model'] = {}
     self['models_configuration']['home_based_employment_location_choice_model']['controller'] = \
                EmploymentLocationChoiceModelByZonesConfigurationCreator(
                             location_set = "building",
                             input_index = 'erm_index',
                             sampler = None,
                             capacity_string = "urbansim_parcel.building.vacant_home_based_job_space",
                             number_of_units_string = None,
                             lottery_max_iterations=30
                             ).execute()
     self['models_configuration']['employment_relocation_model']['controller'] = \
                 EmploymentRelocationModelConfigurationCreator(
                            location_id_name = 'building_id',
                            probabilities = None,
                            rate_table=None,
                            output_index = 'erm_index').execute()
                            
     self['models_configuration']['assign_buildings_to_jobs'] = {}
     self['models_configuration']['assign_buildings_to_jobs']['controller'] = {
               "import": {
                  "psrc_parcel.data_preparation.assign_bldgs_to_jobs_when_multiple_bldgs_in_parcel": "RunAssignBldgsToJobs"
                  },
               "init": {
                        "name": "RunAssignBldgsToJobs"
                        },
               "run": {
                       "arguments": {
                                     "job_dataset": "job",
                                     "dataset_pool": "dataset_pool"}
                       }
                   }
Пример #12
0
          'repm': ['real_estate_price_model', 'psrc_parcel.estimation.repm_specification', None],
          'wcm' : ['workplace_choice_model_for_resident', 'wcm_specification', None],
          'wahcm': ['work_at_home_choice_model', 'wahcm_specification', None],
          'dppcm': ['development_project_proposal_choice_model', 'dppcm_specification', None]
          }

if __name__ == '__main__':
    try: import wingdbstub
    except: pass
    model = 'hlcm'
    #model = 'elcm-non-home-based'
    #model = 'elcm-home_based'
    #model = 'repm'
    #model = 'wcm'
    #model = 'wahcm'
    #model = 'dppcm'

    config = Baseline()
    if 'models_in_year' in config.keys():
        del config['models_in_year']    
    config.merge(my_configuration)
    config['config_changes_for_estimation'] = ConfigChangesForEstimation()
    ## set base_year and years to 2006 for HLCM for the psrc_parcel project
    config['config_changes_for_estimation']['household_location_choice_model'].merge({'base_year': 2006, 'years':(2006, 2006)})
    
    er = EstimationRunner(models[model][0], specification_module=models[model][1], model_group=models[model][2],
                           configuration=config, save_estimation_results=False)
    er.estimate()
    #er.predict()
    #er.create_prediction_success_table(geography_id_expression='choice.is_chosen')
    def __init__(self):
        config = PsrcParcelConfiguration()
        config['creating_baseyear_cache_configuration'].cache_directory_root = r'/Users/hana/urbansim_cache/psrc/data_preparation/run_zipcodes'
        config['creating_baseyear_cache_configuration'].baseyear_cache.existing_cache_to_copy = r'/Users/hana/urbansim_cache/psrc/data_preparation/cache_for_zipcodes'
        #config['scenario_database_configuration'].database_name = 'psrc_2005_parcel_baseyear_data_prep_start'
        config['scenario_database_configuration'].database_name = 'psrc_2005_parcel_baseyear_data_prep_business_zip'
        config_changes = {
            'description':'data preparation for PSRC parcel (buildings)',
            'flush_variables': False,
            'cache_directory': '/Users/hana/urbansim_cache/psrc/data_preparation/cache_for_zipcodes',
            'dataset_pool_configuration': DatasetPoolConfiguration(
                package_order=['psrc_parcel', 'urbansim_parcel', 'urbansim', 'opus_core'],
                ),
            'base_year':2000,
            'years':(2001, 2003),
            'models_in_year': {
              2001: 
              [
                "employment_relocation_model",
                {"employment_location_choice_model": {"group_members": "_all_" }}
              ],
              2002: [
                "employment_relocation_model",
                "governmental_employment_location_choice_model",
                    ],
              2003: [
                "employment_relocation_model",
                "governmental_employment_location_choice_model_without_filter"
               ]
           },
            "datasets_to_preload":{
                    'zone':{},
                    'job': {},
                    'building': {},
                    "job_building_type":{},
                    "zipcode": {}
                },
            "datasets_to_cache_after_each_model": [
                     'parcel', 'building',  'job'
                     ]
        }
        #use configuration in config as defaults and merge with config_changes
        config.replace(config_changes)
        self.merge(config)

        self['models_configuration']['non_home_based_employment_location_choice_model'] = {}
        self['models_configuration']['non_home_based_employment_location_choice_model']['controller'] = \
                   EmploymentLocationChoiceModelByZipcodesConfigurationCreator(
                                location_set = "building",
                                input_index = 'erm_index',
                                sampler = None,
                                records_per_chunk = 3000,
                                capacity_string = "urbansim_parcel.building.vacant_non_home_based_job_space",
                                number_of_units_string = None,
                                lottery_max_iterations=30
                                ).execute()
        self['models_configuration']['governmental_employment_location_choice_model'] = {}
        self['models_configuration']['governmental_employment_location_choice_model']['controller'] = \
                   ScalingJobsModelByZipcodesConfigurationCreator(
                                location_set = "building",
                                input_index = 'erm_index',
                                filter = "urbansim_parcel.building.is_governmental"
                                ).execute()
        self['models_configuration']['governmental_employment_location_choice_model_without_filter'] = {}
        self['models_configuration']['governmental_employment_location_choice_model_without_filter']['controller'] = \
                   ScalingJobsModelByZipcodesConfigurationCreator(
                                location_set = "building",
                                input_index = 'erm_index',
                                ).execute()
        self['models_configuration']['home_based_employment_location_choice_model'] = {}
        self['models_configuration']['home_based_employment_location_choice_model']['controller'] = \
                   EmploymentLocationChoiceModelByZipcodesConfigurationCreator(
                                location_set = "building",
                                input_index = 'erm_index',
                                sampler = None,
                                capacity_string = "urbansim_parcel.building.vacant_home_based_job_space",
                                number_of_units_string = None,
                                lottery_max_iterations=30
                                ).execute()
        self['models_configuration']['employment_relocation_model']['controller'] = \
                    EmploymentRelocationModelConfigurationCreator(
                               location_id_name = 'building_id',
                               probabilities = None,
                               rate_table=None,
                               output_index = 'erm_index').execute()
 def __init__(self):
     config = PsrcParcelConfiguration()
     config['creating_baseyear_cache_configuration'].cache_directory_root = r'/Users/hana/urbansim_cache/psrc/data_preparation/run'
     config['creating_baseyear_cache_configuration'].baseyear_cache.existing_cache_to_copy = r'/Users/hana/urbansim_cache/psrc/data_preparation/cache_tmp'
     config['scenario_database_configuration'].database_name = 'psrc_2005_parcel_baseyear_data_prep_start'
     config_changes = {
         'description':'data preparation for PSRC parcel (buildings)',
         'flush_variables': False,
         'cache_directory': '/Users/hana/urbansim_cache/psrc/data_preparation/cache',
         'dataset_pool_configuration': DatasetPoolConfiguration(
             package_order=['psrc_parcel', 'urbansim_parcel', 'urbansim', 'opus_core'],
             ),
         'base_year':2000,
         'years':(2001, 2005),
         'models_in_year': {
            2001: # Step 2 (Create new residential buildings)
            [ 
              "real_estate_price_model",
              "expected_sale_price_model",
              "development_proposal_choice_model",
              "building_construction_model",
             ],
            2002: # Step 3 (Assign buildings to households)
            [
              "household_relocation_model",
              "household_location_choice_model",
             ],
            2003: # Step 4 (Assign buildings to jobs with known parcel_id)
            [
             'assign_buildings_to_jobs'
             ],
            2004: # Step 5 (Create new non-residential buildings)
            [
              "expected_sale_price_model",
              "development_proposal_choice_model_nr",
              "building_construction_model",
             ],
           2005: # Step 6 (Assign buildings to remaining jobs)
           [
             "employment_relocation_model",
             {"employment_location_choice_model": {"group_members": "_all_" }},
             "employment_relocation_model",
             "governmental_employment_location_choice_model_without_filter"
            ]
        },
         "datasets_to_preload":{
                 'zone':{},
                 'household':{},
                 'job': {},
                 'building': {},
                 'parcel': {},
                 "job_building_type":{},
                 #'development_project_proposal': {}
             },
         #"low_memory_mode": True,
         "datasets_to_cache_after_each_model": [
                  'parcel', 'building', 'development_project_proposal', 'household', 'job',
                  'development_project_proposal_component'
                  ]
     }
     #use configuration in config as defaults and merge with config_changes
     config.replace(config_changes)
     self.merge(config)
     self['models_configuration']['development_proposal_choice_model']['controller']["import"] =  {
                    "psrc_parcel.models.development_proposal_sampling_model_by_zones":
                    "DevelopmentProposalSamplingModelByZones"
                    }
     self['models_configuration']['development_proposal_choice_model']['controller']["init"]["name"] =\
                     "DevelopmentProposalSamplingModelByZones"
     self['models_configuration']['development_proposal_choice_model']['controller']['run']['arguments']["zones"] = 'zone'
     self['models_configuration']['development_proposal_choice_model']['controller']['run']['arguments']["type"] = "'residential'"
     self['models_configuration']['development_proposal_choice_model']['controller']['run']['arguments']["n"] = 50
     self['models_configuration']['development_proposal_choice_model_nr'] = Configuration(self['models_configuration']['development_proposal_choice_model'])
     self['models_configuration']['development_proposal_choice_model_nr']['controller']['run']['arguments']["type"] = "'non_residential'"
     self['models_configuration']['expected_sale_price_model']['controller']["prepare_for_run"]['arguments']["parcel_filter_for_redevelopment"] = None
     #self['models_configuration']['expected_sale_price_model']['controller']["prepare_for_run"]['arguments']["create_proposal_set"] = False
     self['models_configuration']['expected_sale_price_model']['controller']["run"]['arguments']["chunk_specification"] = "{'nchunks': 5}"
     #self['models_configuration']['building_construction_model']['controller']["run"]['arguments']["consider_amount_built_in_parcels"] = False
     self['models_configuration']['building_construction_model']['controller']['run']['arguments']["current_year"] = 2000
     
     self['models_configuration']['household_location_choice_model'] = {}
     self['models_configuration']['household_location_choice_model']['controller'] = \
                HouseholdLocationChoiceModelByZonesConfigurationCreator(
                             location_set = "building",
                             sampler = None,
                             input_index = 'hrm_index',
                             capacity_string = "urbansim_parcel.building.vacant_residential_units",
                             number_of_units_string = None,
                             nchunks=1,
                             lottery_max_iterations=20
                             ).execute()
     self['models_configuration']['household_relocation_model']['controller'] = \
                 HouseholdRelocationModelConfigurationCreator(
                            location_id_name = 'building_id',
                            probabilities = None,
                            rate_table=None,
                            output_index = 'hrm_index').execute()
                            
     self['models_configuration']['non_home_based_employment_location_choice_model'] = {}
     self['models_configuration']['non_home_based_employment_location_choice_model']['controller'] = \
                EmploymentLocationChoiceModelByZonesConfigurationCreator(
                             location_set = "building",
                             input_index = 'erm_index',
                             sampler = None,
                             capacity_string = "urbansim_parcel.building.vacant_non_home_based_job_space",
                             number_of_units_string = None,
                             lottery_max_iterations=30
                             ).execute()
     self['models_configuration']['governmental_employment_location_choice_model'] = {}
     self['models_configuration']['governmental_employment_location_choice_model']['controller'] = \
                ScalingJobsModelByZonesConfigurationCreator(
                             location_set = "building",
                             input_index = 'erm_index',
                             filter = "urbansim_parcel.building.is_governmental"
                             ).execute()
     self['models_configuration']['governmental_employment_location_choice_model_without_filter'] = {}
     self['models_configuration']['governmental_employment_location_choice_model_without_filter']['controller'] = \
                ScalingJobsModelByZonesConfigurationCreator(
                             location_set = "building",
                             input_index = 'erm_index',
                             ).execute()
     self['models_configuration']['home_based_employment_location_choice_model'] = {}
     self['models_configuration']['home_based_employment_location_choice_model']['controller'] = \
                EmploymentLocationChoiceModelByZonesConfigurationCreator(
                             location_set = "building",
                             input_index = 'erm_index',
                             sampler = None,
                             capacity_string = "urbansim_parcel.building.vacant_home_based_job_space",
                             number_of_units_string = None,
                             lottery_max_iterations=30
                             ).execute()
     self['models_configuration']['employment_relocation_model']['controller'] = \
                 EmploymentRelocationModelConfigurationCreator(
                            location_id_name = 'building_id',
                            probabilities = None,
                            rate_table=None,
                            output_index = 'erm_index').execute()
                            
     self['models_configuration']['assign_buildings_to_jobs'] = {}
     self['models_configuration']['assign_buildings_to_jobs']['controller'] = {
               "import": {
                  "psrc_parcel.data_preparation.assign_bldgs_to_jobs_when_multiple_bldgs_in_parcel": "RunAssignBldgsToJobs"
                  },
               "init": {
                        "name": "RunAssignBldgsToJobs"
                        },
               "run": {
                       "arguments": {
                                     "job_dataset": "job",
                                     "dataset_pool": "dataset_pool"}
                       }
                   }