Exemplo n.º 1
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 def __init__(self):
     Configuration.__init__(self, config)
     self.merge(my_configuration)
     if not my_configuration[
             'creating_baseyear_cache_configuration'].cache_from_database:
         del self[
             "input_configuration"]  # don't bother with the database if everything is in cache
Exemplo n.º 2
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    def __init__(
        self,
        model,
        year,
        scenario_name=None,
        model_group=None,
        configuration=None,
        xml_configuration=None,
        cache_directory=None,
    ):
        self.model_group = model_group
        self.explored_model = model

        if configuration is None:
            if xml_configuration is None:
                raise StandardError, "Either dictionary based or XML based configuration must be given."
            config = xml_configuration.get_run_configuration(scenario_name)
        else:
            config = Configuration(configuration)

        self.scenario_models = config["models"]
        if config.get("models_in_year", None) is not None and config["models_in_year"].get(year, None) is not None:
            del config["models_in_year"][year]
        if model is not None:
            dependent_models = config["models_configuration"][model]["controller"].get("dependencies", [])
            config["models"] = dependent_models
            if model_group is None:
                config["models"] = config["models"] + [{model: ["run"]}]
            else:
                config["models"] = config["models"] + [{model: {"group_members": [{model_group: ["run"]}]}}]
        else:
            config["models"] = []

        config["years"] = [year, year]
        config["datasets_to_cache_after_each_model"] = []
        config["flush_variables"] = False

        self.config = Resources(config)
        self.xml_configuration = xml_configuration

        if cache_directory is None:
            cache_directory = config["creating_baseyear_cache_configuration"].baseyear_cache.existing_cache_to_copy
        self.simulation_state = SimulationState(
            new_instance=True, base_cache_dir=cache_directory, start_time=config.get("base_year", 0)
        )
        self.config["cache_directory"] = cache_directory

        SessionConfiguration(
            new_instance=True,
            package_order=self.config["dataset_pool_configuration"].package_order,
            in_storage=AttributeCache(),
        )
Exemplo n.º 3
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    def test_defaults(self):
        creator = BuildingTransitionModelConfigurationCreator()

        expected = Configuration({
            'import': {
                'urbansim.models.building_transition_model':
                'BuildingTransitionModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': 'debuglevel'
                },
                'name': 'BuildingTransitionModel'
            },
            'run': {
                'arguments': {
                    'building_categories': """{
                        'residential': array([1,2,3,5,10,20]), 
                        'commercial': 1000*array([1, 2, 5, 10]), 
                        'industrial': 1000*array([1,2,5,10])
                        }""",
                    'building_set': 'building',
                    'building_types_table': 'building_type',
                    'dataset_pool': 'dataset_pool',
                    'location_set': 'gridcell',
                    'vacancy_table': 'target_vacancy',
                    'year': 'year',
                }
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
Exemplo n.º 4
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    def execute(self):
        # Names of intermediate objects used to get data between steps
        # in this model process.
        _characteristics = 'characteristics'
        _control_totals = 'control_totals'

        return Configuration({
            'import': {
                'urbansim.models.%s' % self._model_name:
                'HouseholdTransitionModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': self.debuglevel,
                    'location_id_name': "'%s'" % self.location_id_name
                },
                'name': 'HouseholdTransitionModel'
            },
            'prepare_for_run': {
                'arguments': {
                    'storage': 'base_cache_storage'
                },
                'name': 'prepare_for_run',
                'output': '(%s, %s)' % (_control_totals, _characteristics)
            },
            'run': {
                'arguments': {
                    'characteristics': _characteristics,
                    'control_totals': _control_totals,
                    'household_set': self.household_set,
                    'year': 'year'
                }
            }
        })
 def test_defaults(self):
     creator = EmploymentRelocationModelConfigurationCreator()
     
     expected = Configuration({
         'import': {
             'urbansim.models.employment_relocation_model_creator': 'EmploymentRelocationModelCreator'
             },
         'init': {
             'arguments': {'debuglevel': 'debuglevel',
                           'location_id_name': "'grid_id'",
                           'probabilities': "'urbansim.employment_relocation_probabilities'"},
             'name': 'EmploymentRelocationModelCreator().get_model',
             
             },
         'prepare_for_run': {
             'arguments': {
                 'rate_storage': 'base_cache_storage',
                 'rate_table': "'annual_relocation_rates_for_jobs'",
                 'what': "'jobs'"
                 },
             'name': 'prepare_for_run',
             'output': 'erm_resources'
             },
         'run': {
             'arguments': {
                 'resources': 'erm_resources', 
                 'agent_set': 'job'
                 },
             'output': 'erm_index'
             }
         })
     
     result = creator.execute()
     self.assertDictsEqual(result, expected)
Exemplo n.º 6
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    def create_latex_tables_for_model(self, config, model_name, dir):
        """Write to directory dir a file containing a LaTeX table describing this model's 
        coefficients, and a file containing a LaTeX table describing this model's specification.
        Files will be named named <model_name>_coefficients.tex and <model_name>_specification.tex.
        """
        config = Configuration(config)
        model_system = ModelSystem()
        input_db, output_db = model_system._get_database_connections(config)
        sql_storage = StorageFactory().get_storage('sql_storage',
                                                   storage_location=input_db)
        #TODO: only do the next stuff if this model has coefficients
        if 'controller' not in config['models_configuration'][model_name]:
            return
        if 'prepare_for_run' not in config['models_configuration'][model_name][
                'controller']:
            return
        if 'coefficients' not in config['models_configuration'][model_name][
                'controller']['prepare_for_run']['output']:
            return
        specification_table_name = config['models_configuration'][
            model_name].get('specification_table', None)
        coefficents_table_name = config['models_configuration'][
            model_name].get('coefficients_table', None)
        (specification, coefficients) = prepare_specification_and_coefficients(
            specification_storage=sql_storage,
            specification_table=specification_table_name,
            coefficients_storage=sql_storage,
            coefficients_table=coefficents_table_name)

        self.create_latex_table_for_coefficients_for_model(
            coefficients, model_name, dir)
        self.create_latex_table_for_specifications_for_model(
            specification, model_name, dir)
 def test_with_arguments(self):
     creator = EventsCoordinatorConfigurationCreator(
         location_set = 'location_set',
         development_type_set = 'development_type_set',
         input_events = 'input_events',
         output_changed_indices = 'output_changed_indices',
         output_processed_development_event_indices = 'output_processed_development_event_indices',
         )
     
     expected = Configuration({
         'import': {
             'urbansim.models.events_coordinator_and_storing': 'EventsCoordinatorAndStoring'
             },
         'init': {'name': 'EventsCoordinatorAndStoring'},
         'run': {
             'arguments': {
                 'current_year': 'year',
                 'development_event_set': 'input_events',
                 'development_type_set': 'development_type_set',
                 'location_set': 'location_set',
                 'model_configuration': 'model_configuration'
                 },
             'output': '(output_changed_indices, output_processed_development_event_indices)'
             }
         })
     
     result = creator.execute()
     self.assertDictsEqual(result, expected)
Exemplo n.º 8
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    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 test_with_arguments(self):
        creator = DevelopmentProjectTypeConfigurationCreator(
            categories=[9, 9, 9, 9],
            developable_maximum_unit_variable_full_name=
            'developable_maximum_unit_variable_full_name',
            developable_minimum_unit_variable_full_name=
            'developable_minimum_unit_variable_full_name',
            residential=False,
            units='units',
        )

        expected = Configuration({
            'categories':
            array([9, 9, 9, 9]),
            'developable_maximum_unit_variable_full_name':
            'developable_maximum_unit_variable_full_name',
            'developable_minimum_unit_variable_full_name':
            'developable_minimum_unit_variable_full_name',
            'residential':
            False,
            'units':
            'units'
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
Exemplo n.º 10
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 def execute(self):
     return Configuration({
         'import': {
             'urbansim.models.%s' % self._model_name:
             'BuildingTransitionModel'
         },
         'init': {
             'arguments': {
                 'debuglevel': self.debuglevel
             },
             'name': 'BuildingTransitionModel'
         },
         'run': {
             'arguments': {
                 'building_categories':  ### TODO: Construct this list from the development_project_type_configuration info
                 """{
                     'residential': array([1,2,3,5,10,20]), 
                     'commercial': 1000*array([1, 2, 5, 10]), 
                     'industrial': 1000*array([1,2,5,10])
                     }""",
                 'building_set': self.building_set,
                 'building_types_table': self.building_types_table,
                 'dataset_pool': 'dataset_pool',
                 'location_set': self.location_set,
                 'vacancy_table': self.vacancy_table,
                 'year': 'year',
             }
         }
     })
Exemplo n.º 11
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    def test_defaults(self):
        creator = HouseholdTransitionModelConfigurationCreator()

        expected = Configuration({
            'import': {
                'urbansim.models.household_transition_model':
                'HouseholdTransitionModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': 'debuglevel',
                    'location_id_name': "'grid_id'"
                },
                'name': 'HouseholdTransitionModel'
            },
            'prepare_for_run': {
                'arguments': {
                    'storage': 'base_cache_storage'
                },
                'name': 'prepare_for_run',
                'output': '(control_totals, characteristics)'
            },
            'run': {
                'arguments': {
                    'characteristics': 'characteristics',
                    'control_totals': 'control_totals',
                    'household_set': 'household',
                    'year': 'year'
                }
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
Exemplo n.º 12
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    def test_with_arguments(self):
        creator = BuildingRelocationModelConfigurationCreator(
            agent_set='agent_set',
            location_id_name='location_id_name',
            output_index='output_index',
        )

        expected = Configuration({
            'import': {
                'urbansim.models.agent_relocation_model':
                'AgentRelocationModel'
            },
            'init': {
                'arguments': {
                    'location_id_name': 'location_id_name',
                },
                'name': 'AgentRelocationModel'
            },
            'run': {
                'arguments': {
                    'agent_set': 'agent_set'
                },
                'output': 'output_index'
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
    def test_with_arguments(self):
        creator = DistributeUnplacedJobsModelConfigurationCreator(
            debuglevel=9999,
            agent_set='agent_set',
            location_set='location_set',
            agents_filter='job.sector_id==10')

        expected = Configuration({
            'import': {
                'urbansim.models.distribute_unplaced_jobs_model':
                'DistributeUnplacedJobsModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': 9999,
                    'filter': None,
                    'dataset_pool': 'dataset_pool'
                },
                'name': 'DistributeUnplacedJobsModel'
            },
            'run': {
                'arguments': {
                    'agent_set': 'agent_set',
                    'data_objects': 'datasets',
                    'location_set': 'location_set',
                    'agents_filter': "'job.sector_id==10'"
                }
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
Exemplo n.º 14
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    def get_resources_for_run_id_from_history(self,
                                              run_id,
                                              filter_by_status=False):
        """Returns the resources for this run_id, as stored in the run_activity table.
        """

        run_activity = self.services_db.get_table('run_activity')

        if filter_by_status:
            whereclause = and_(run_activity.c.status == 'started',
                               run_activity.c.run_id == int(run_id))
        else:
            whereclause = run_activity.c.run_id == int(run_id)

        query = select(columns=[run_activity.c.resources],
                       whereclause=whereclause)

        run_resources = self.services_db.execute(query).fetchone()

        if not run_resources:
            raise StandardError(
                "run_id %s doesn't exist on server %s" %
                (run_id, self.services_db.get_connection_string(scrub=True)))

        try:
            r = self._unpickle(run_resources[0])
            config = Configuration(r)
        except:
            logger.log_error(
                'Could not create the configuration file for run %i' % run_id)
            raise

        return config
    def test_with_arguments(self):
        creator = DevelopmentEventTransitionModelConfigurationCreator(
            output_events='output_events',
            input_projects='input_projects',
        )

        expected = Configuration({
            'import': {
                'urbansim_zone.models.development_event_transition_model':
                'DevelopmentEventTransitionModel'
            },
            'init': {
                'name': 'DevelopmentEventTransitionModel'
            },
            'run': {
                'arguments': {
                    'projects': 'input_projects',
                    'year': 'year'
                },
                'output': 'output_events',
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
Exemplo n.º 16
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    def test_defaults(self):
        creator = GovernmentalRegionalEmploymentLocationChoiceModelConfigurationCreator(
        )

        expected = Configuration({
            'import': {
                'washtenaw.models.regional_scaling_jobs_model':
                'RegionalScalingJobsModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': 'debuglevel',
                    'filter': None,
                    'dataset_pool': 'dataset_pool'
                },
                'name': 'RegionalScalingJobsModel'
            },
            'run': {
                'arguments': {
                    'agent_set': 'job',
                    'agents_index': 'erm_index',
                    'data_objects': 'datasets',
                    'location_set': 'gridcell',
                }
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
    def test_defaults(self):
        creator = DevelopmentEventTransitionModelConfigurationCreator()

        expected = Configuration({
            'import': {
                'urbansim.models.development_event_transition_model':
                'DevelopmentEventTransitionModel'
            },
            'init': {
                'name': 'DevelopmentEventTransitionModel'
            },
            'prepare_for_run': {
                'arguments': {
                    'dev_projects': 'dptm_results',
                    'model_configuration': 'model_configuration'
                },
                'name': 'prepare_for_run',
                'output': '(all_project_types, all_project_units)'
            },
            'run': {
                'arguments': {
                    'debuglevel': 'debuglevel',
                    'projects': 'dptm_results',
                    'types': 'all_project_types',
                    'units': 'all_project_units',
                    'year': 'year'
                },
                'output': 'development_events'
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
 def test_with_arguments(self):
     creator = DevelopmentProjectTransitionModelConfigurationCreator(
         debuglevel = 9999,
         location_set = 'location_set',
         history_table = 'history_table',
         vacancy_table = 'vacancy_table',
         output_results = 'output_results',
         vacancy_variables = {'commercial': 'gridcell.my_commercial_vacant_var',
                             'industrial': 'gridcell.my_industrial_vacant_var'}
         )
     
     expected = Configuration({
         'import': {
             'urbansim.models.development_project_transition_model': 'DevelopmentProjectTransitionModel'
             },
         'init': {
             'arguments': {'debuglevel': 9999},
             'name': 'DevelopmentProjectTransitionModel'
             },
         'run': {
             'arguments': {
                 'history_table': 'history_table',
                 'location_set': 'location_set',
                 'model_configuration': 'model_configuration',
                 'resources': 'model_resources',
                 'vacancy_table': 'vacancy_table',
                 'year': 'year',
                 'resources': "{'industrial_vacant_variable': 'gridcell.my_industrial_vacant_var','commercial_vacant_variable': 'gridcell.my_commercial_vacant_var',}"
                 },
             'output': 'output_results'
             }
         })
     
     result = creator.execute()
     self.assertDictsEqual(result, expected)
    def execute(self):
        # Names of intermediate objects used to get data between steps
        # in this model process.
        _control_totals = 'control_totals'

        return Configuration({
            'import': {
                'urbansim.models.%s' % self._model_name:
                'EmploymentTransitionModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': self.debuglevel,
                    'location_id_name': "'%s'" % self.location_id_name,
                },
                'name': 'EmploymentTransitionModel'
            },
            'prepare_for_run': {
                'arguments': {
                    'storage': 'base_cache_storage'
                },
                'name': 'prepare_for_run',
                'output': _control_totals,
            },
            'run': {
                'arguments': {
                    'control_totals': _control_totals,
                    'job_building_types': self.job_building_types,
                    'job_set': self.job_set,
                    'year': 'year'
                }
            }
        })
 def test_defaults(self):
     creator = DevelopmentProjectTransitionModelConfigurationCreator()
     
     expected = Configuration({
         'import': {
             'urbansim.models.development_project_transition_model': 'DevelopmentProjectTransitionModel'
             },
         'init': {
             'arguments': {'debuglevel': 4},
             'name': 'DevelopmentProjectTransitionModel'
             },
         'run': {
             'arguments': {
                 'history_table': 'development_event_history',
                 'location_set': 'gridcell',
                 'model_configuration': 'model_configuration',
                 'resources': 'model_resources',
                 'vacancy_table': 'target_vacancy',
                 'year': 'year',
                 'resources': None
                 },
             'output': 'dptm_results'
             }
         })
     
     result = creator.execute()
     self.assertDictsEqual(result, expected)
Exemplo n.º 21
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    def test_with_arguments(self):
        creator = AddProjectsToBuildingsConfigurationCreator(
            input_projects='input_projects',
            units_names={
                'residential': 'my_units',
                'commercial': 'job_spaces'
            })

        expected = Configuration({
            'import': {
                'urbansim_zone.models.add_projects_to_buildings':
                'AddProjectsToBuildings'
            },
            'init': {
                'name': 'AddProjectsToBuildings'
            },
            'run': {
                'arguments': {
                    'projects':
                    'input_projects',
                    'building_set':
                    'building',
                    'building_type_set':
                    'building_type',
                    'location_id_name':
                    "'zone_id'",
                    'units_names':
                    "{'residential': 'my_units', 'commercial': 'job_spaces'}"
                },
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
    def test_defaults(self):
        creator = EmploymentTransitionModelConfigurationCreator()

        expected = Configuration({
            'import': {
                'urbansim.models.employment_transition_model':
                'EmploymentTransitionModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': 'debuglevel',
                    'location_id_name': "'grid_id'"
                },
                'name': 'EmploymentTransitionModel'
            },
            'prepare_for_run': {
                'arguments': {
                    'storage': 'base_cache_storage'
                },
                'name': 'prepare_for_run',
                'output': 'control_totals'
            },
            'run': {
                'arguments': {
                    'control_totals': 'control_totals',
                    'job_building_types': 'job_building_type',
                    'job_set': 'job',
                    'year': 'year'
                }
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
Exemplo n.º 23
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    def test_with_arguments(self):
        creator = GovernmentalEmploymentLocationChoiceModelConfigurationCreator(
            agent_set='agent_set',
            location_set='location_set',
            debuglevel=9999,
            input_index='input_index',
        )

        expected = Configuration({
            'import': {
                'urbansim.models.scaling_jobs_model': 'ScalingJobsModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': 9999,
                    'filter': None,
                    'dataset_pool': 'dataset_pool'
                },
                'name': 'ScalingJobsModel',
            },
            'run': {
                'arguments': {
                    'agent_set': 'agent_set',
                    'agents_index': 'input_index',
                    'data_objects': 'datasets',
                    'location_set': 'location_set',
                }
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
    def test_defaults(self):
        creator = DistributeUnplacedJobsModelConfigurationCreator()

        expected = Configuration({
            'import': {
                'urbansim.models.distribute_unplaced_jobs_model':
                'DistributeUnplacedJobsModel'
            },
            'init': {
                'arguments': {
                    'debuglevel': 'debuglevel',
                    'filter': None,
                    'dataset_pool': 'dataset_pool'
                },
                'name': 'DistributeUnplacedJobsModel'
            },
            'run': {
                'arguments': {
                    'agent_set': 'job',
                    'data_objects': 'datasets',
                    'location_set': 'gridcell',
                    'agents_filter': None
                }
            }
        })

        result = creator.execute()
        self.assertDictsEqual(result, expected)
Exemplo n.º 25
0
    def update_config_for_multiple_runs(self, config):
        models_to_update = config.get('models_with_sampled_coefficients', [])
        if 'models_in_year' not in config.keys():
            config['models_in_year'] = {}
        if config['models_in_year'].get(config['base_year'] + 1, None) is None:
            config['models_in_year'][config['base_year'] +
                                     1] = config.get('models')

        for umodel in models_to_update:
            try:
                i = config['models_in_year'][config['base_year'] +
                                             1].index(umodel)
                new_model_name = '%s_sampled_coef' % umodel
                config['models_in_year'][config['base_year'] +
                                         1][i] = new_model_name
            except:
                pass
            config["models_configuration"][new_model_name] = Configuration(
                config["models_configuration"][umodel])
            config["models_configuration"][new_model_name]["controller"][
                "prepare_for_run"]["arguments"]["sample_coefficients"] = True
            config["models_configuration"][new_model_name]["controller"][
                "prepare_for_run"]["arguments"]["distribution"] = "'normal'"
            config["models_configuration"][new_model_name]["controller"][
                "prepare_for_run"]["arguments"][
                    "cache_storage"] = "base_cache_storage"
    def execute(self):
        # Names of intermediate objects used to get data between steps
        # in this model process.
        _types = 'all_project_types'
        _units = 'all_project_units'

        return Configuration({
            'import': {
                'urbansim.models.%s' % self._model_name:
                'DevelopmentEventTransitionModel'
            },
            'init': {
                'name': 'DevelopmentEventTransitionModel'
            },
            'prepare_for_run': {
                'arguments': {
                    'dev_projects': self.input_projects,
                    'model_configuration': 'model_configuration'
                },
                'name': 'prepare_for_run',
                'output': '(%s, %s)' % (_types, _units)
            },
            'run': {
                'arguments': {
                    'debuglevel': self.debuglevel,
                    'projects': self.input_projects,
                    'types': _types,
                    'units': _units,
                    'year': 'year'
                },
                'output': self.output_events,
            }
        })
Exemplo n.º 27
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    def execute(self):
        # Names of intermediate objects used to get data between steps
        # in this model process.
        _coefficients = 'coefficients'
        _specification = 'specification'

        return Configuration({
            'estimate': {
                'arguments': {
                    'agent_set': self.agent_set,
                    'data_objects': 'datasets',
                    'debuglevel': self.debuglevel,
                    'procedure': "'%s'" % self.estimation_procedure,
                    'specification': _specification,
                },
                'output': '(%s, _)' % _coefficients
            },
            'import': {
                'urbansim.models.%s' % self._model_name:
                'AutoOwnershipChoiceModel'
            },
            'init': {
                'arguments': {
                    'choice_attribute_name':
                    "'%s'" % self.choice_attribute_name,
                    'choice_set': list(self.choice_set),
                },
                'name': 'AutoOwnershipChoiceModel'
            },
            'prepare_for_estimate': {
                'arguments': {
                    'specification_storage': 'base_cache_storage',
                    'specification_table': "'%s'" % self.specification_table
                },
                'name': 'prepare_for_estimate',
                'output': '(%s)' % _specification
            },
            '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,
                    'chunk_specification':
                    "{'records_per_chunk':%s}" % self.records_per_chunk,
                    'coefficients': _coefficients,
                    'data_objects': 'datasets',
                    'specification': _specification,
                }
            }
        })
Exemplo n.º 28
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    def test_regression_model_with_constant_variation(self):
        """Estimate the model and run it on the same data as the estimation. The result should be equal to the original data.
        If there is a change in the explanatory variables, the result should not be equal.
        """
        storage = StorageFactory().get_storage('dict_storage')

        table_name = 'dataset_table'
        data = {
            "attr1": array([30, 0, 90, 100, 65, 50]),
            "attr2": array([2002, 1968, 1880, 1921, 1956, 1989]),
            "attr3": array([0.5, 0.1, 0.3, 0.9, 0.2, 0.8]),
            "outcome": array([20, 40, 15, 5, 40, 30], dtype="int32"),
            "id": array([1, 2, 3, 4, 5, 6])
        }
        storage.write_table(table_name=table_name, table_data=data)
        dataset = Dataset(in_storage=storage,
                          in_table_name=table_name,
                          id_name="id")

        specification = EquationSpecification(variables=("attr1", "attr2",
                                                         "attr3", "constant"),
                                              coefficients=("b1", "b2", "b3",
                                                            "constant"))

        model = RegressionModelWithAdditionInitialResiduals(
            outcome_attribute="outcome")
        coef, dummy = model.estimate(
            specification,
            dataset,
            outcome_attribute="outcome",
            procedure="opus_core.estimate_linear_regression")
        result = model.run(specification, coef, dataset)

        # if estimated and run on the same data, it should give the original outcome
        self.assertEqual(ma.allequal(result, data["outcome"]), True)

        # if some values changed it shoudn't be the same for those elements
        dataset.set_values_of_one_attribute("attr1", array([32, 10]),
                                            arange(2))
        result2 = model.run(specification, coef, dataset)
        self.assertEqual(ma.allequal(result2[0:2], data["outcome"][0:2]),
                         False)
        self.assertEqual(ma.allequal(result2[2:], data["outcome"][2:]), True)

        # check if exclusion of missing values is working
        dataset.set_values_of_one_attribute("outcome", array([0, 0]),
                                            array([2, 4]))
        dataset.delete_one_attribute("_init_error_outcome")
        model.run(specification,
                  coef,
                  dataset,
                  run_config=Configuration(
                      {'exclude_missing_values_from_initial_error': True}))
        initial_error = dataset.get_attribute("_init_error_outcome")
        self.assertEqual(ma.allequal(initial_error[array([2, 4])], 0), True)
        self.assertEqual(ma.allequal(initial_error[array([0, 1, 3, 4, 5])], 0),
                         False)
Exemplo n.º 29
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    def execute(self):
        development_project_types = {}

        for development_project_type, config in self.development_project_type_set.iteritems(
        ):
            development_project_types[
                development_project_type] = config.execute()

        return Configuration(development_project_types)
Exemplo n.º 30
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    def execute(self):
        # Names of intermediate objects used to get data between steps
        # in this model process.
        _coefficients = 'coefficients'
        _specification = 'specification'
        _index = 'index'

        return Configuration({
            'estimate': {
                'arguments': {
                    'data_objects': 'datasets',
                    'dataset': self.dataset,
                    'debuglevel': self.debuglevel,
                    'index': _index,
                    'specification': _specification,
                    'procedure': "'%s'" % self.estimation_procedure
                },
                'output': '(%s, _)' % _coefficients
            },
            'import': {
                'urbansim.models.%s' % self._model_name:
                'ResidentialLandShareModel'
            },
            'init': {
                'name': 'ResidentialLandShareModel'
            },
            'prepare_for_estimate': {
                'arguments': {
                    'dataset': self.dataset,
                    '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': {
                    'coefficients': _coefficients,
                    'data_objects': 'datasets',
                    'dataset': self.dataset,
                    'debuglevel': self.debuglevel,
                    'index': self.input_changed_indices,
                    'specification': _specification
                }
            }
        })
Exemplo n.º 31
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 def __new__(cls, *args, **kwargs):
     an_instance = object.__new__(cls)
     default_config = Configuration(an_instance.get_configuration())["init"]
     config = None
     if "model_configuration" in kwargs.keys():
         config = kwargs["model_configuration"]
         del kwargs["model_configuration"]
     an_instance.model_configuration = default_config.merge_defaults_with_arguments_and_config(
                             config, **kwargs)
                             
     if 'run' in map(lambda (name, obj): name, getmembers(an_instance, isroutine)):
         run_method = an_instance.run
         def config_run_method (*req_args, **opt_args):
             default_config = Configuration(an_instance.get_configuration())["run"]
             an_instance.model_configuration = default_config.merge_defaults_with_arguments_and_config(
                             an_instance.model_configuration, **opt_args)
             results = run_method(*req_args, **opt_args)                
             return results
         an_instance.run = config_run_method                        
Exemplo n.º 32
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    def __init__(self):
        Configuration.__init__(self)
        self['residential_regional_development_project_location_choice_model'] = {
                    'controller': RegionalDevelopmentProjectLocationChoiceModelConfigurationCreator(
                        project_type = 'residential',
                        coefficients_table = 'residential_development_location_choice_model_coefficients',
                        specification_table = 'residential_development_location_choice_model_specification',
                        #submodel_string = None
                        ).execute(),
                    }
        self['commercial_regional_development_project_location_choice_model'] = {
                    'controller': RegionalDevelopmentProjectLocationChoiceModelConfigurationCreator(
                        project_type = 'commercial',
                        coefficients_table = 'commercial_development_location_choice_model_coefficients',
                        specification_table = 'commercial_development_location_choice_model_specification',
                        #submodel_string = None
                        ).execute(),
                    }
        self['industrial_regional_development_project_location_choice_model'] = {
                    'controller': RegionalDevelopmentProjectLocationChoiceModelConfigurationCreator(
                        project_type = 'industrial',
                        coefficients_table = 'industrial_development_location_choice_model_coefficients',
                        specification_table = 'industrial_development_location_choice_model_specification',
                        #submodel_string = None
                        ).execute(),
                    }
        self['regional_development_project_transition_model'] =  {
                    'controller': RegionalDevelopmentProjectTransitionModelConfigurationCreator(
                        output_results = 'dptm_results',
                        ).execute(),
                    }
        self['regional_household_transition_model'] = {
                    'controller': RegionalHouseholdTransitionModelConfigurationCreator().execute(),
                    }
        self['regional_employment_transition_model'] = {
                    'controller': RegionalEmploymentTransitionModelConfigurationCreator().execute(),
                    }
        self['regional_employment_location_choice_model'] = {
                    'controller': RegionalEmploymentLocationChoiceModelConfigurationCreator(
                        ).execute(),
                    }
        self['home_based_regional_employment_location_choice_model'] = {
                    'controller': HomeBasedRegionalEmploymentLocationChoiceModelConfigurationCreator(
                        ).execute(),
                    }
        self['governmental_regional_employment_location_choice_model'] = {
                    'controller': GovernmentalRegionalEmploymentLocationChoiceModelConfigurationCreator(
                        ).execute(),
                    }
        self['regional_household_location_choice_model'] = {
                    'controller': RegionalHouseholdLocationChoiceModelConfigurationCreator(
                        ).execute(),
                                                            }
        self['regional_household_relocation_model'] = {
                    'controller': RegionalHouseholdRelocationModelConfigurationCreator(
                        ).execute(),
                    }
        self['regional_employment_relocation_model'] = {
                    'controller': RegionalEmploymentRelocationModelConfigurationCreator(
                        ).execute(),
                    }
        self['regional_distribute_unplaced_jobs_model'] = {
                    'controller': RegionalDistributeUnplacedJobsModelConfigurationCreator(
                        ).execute(),
                    }
        self['jobs_event_model'] = {
                    'controller': JobsEventModelConfigurationCreator(
                        ).execute(),
                    }
        self['households_event_model'] = {
                    'controller': HouseholdsEventModelConfigurationCreator(
                        ).execute(),
                    }

#if __name__ == '__main__':
#    ControllerConfiguration()
Exemplo n.º 33
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 def __init__(self, data={}):
     """The argument 'data' is a python native dictionary (class 'dict').
     """ 
     Configuration.__init__(self, data)
 def __init__(self):
     Configuration.__init__(self, data = {
         'scenario_database_configuration':ScenarioDatabaseConfiguration(
             database_name = "washtenaw_class",
             ),
         'datasets_to_cache_after_each_model':[],
         'low_memory_mode':False,
         'creating_baseyear_cache_configuration':CreatingBaseyearCacheConfiguration(
             unroll_gridcells = True,
             cache_from_database = False,
             baseyear_cache = BaseyearCacheConfiguration(
                 existing_cache_to_copy = '/urbansim_cache/workshop/cache_source',
                 #years_to_cache  = range(1996,2001)
                 ),
             tables_to_cache = [
                 'annual_employment_control_totals',
                 'annual_household_control_totals',
                 'buildings',
                 'building_types',
                 'development_event_history',
                 'gridcells',
                 'households',
                 'job_building_types',
                 'jobs',
                 'travel_data',
                 'zones',
                 'counties',
                 'commercial_development_location_choice_model_coefficients',
                 'commercial_development_location_choice_model_specification',
                 'commercial_employment_location_choice_model_coefficients',
                 'commercial_employment_location_choice_model_specification',
                 'home_based_employment_location_choice_model_specification',
                 'home_based_employment_location_choice_model_coefficients',
                 'industrial_employment_location_choice_model_coefficients',
                 'industrial_employment_location_choice_model_specification',
                 'industrial_development_location_choice_model_coefficients',
                 'industrial_development_location_choice_model_specification',
                 'residential_development_location_choice_model_coefficients',
                 'residential_development_location_choice_model_specification',
                 'fazes',
                 'urbansim_constants',
                 'household_location_choice_model_coefficients',
                 'household_location_choice_model_specification',
                 'land_price_model_coefficients',
                 'land_price_model_specification',
                 'residential_land_share_model_coefficients',
                 'residential_land_share_model_specification',
                 'plan_type_group_definitions',
                 'plan_type_groups',
                 'large_areas',
                 'household_characteristics_for_ht',
                 'development_types',
                 'development_type_group_definitions',
                 'development_constraints',
                 'annual_relocation_rates_for_households',
                 'annual_relocation_rates_for_jobs',
                 'base_year',
                 'cities',
                 'development_events',
                 'development_type_groups',
                 'employment_adhoc_sector_group_definitions',
                 'employment_adhoc_sector_groups',
                 'employment_sectors',
                 'plan_types',
                 'race_names',
                 'target_vacancies',
                 'jobs_for_estimation',
                 'households_for_estimation',
                 'development_events_exogenous',
                 'job_building_types'
                 ],
             tables_to_cache_nchunks = {'gridcells':1},
             tables_to_copy_to_previous_years = {
                 'development_type_group_definitions':1995,
                 'development_type_groups':1995,
                 'development_types':1995,
                 'development_constraints':1995,
                 'urbansim_constants':1995,
                 },
             ),
         'dataset_pool_configuration': DatasetPoolConfiguration(
             package_order=['washtenaw', 'urbansim', 'opus_core'],
             ),
         'base_year': 2000,
         'years': (2000,2000),
         })
Exemplo n.º 35
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 def __init__(self):
     Configuration.__init__(self, config)
     self.merge(my_configuration)
     if not my_configuration['creating_baseyear_cache_configuration'].cache_from_database:
         del self["input_configuration"] # don't bother with the database if everything is in cache
Exemplo n.º 36
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 def __getitem__(self, key):
     """First check for key in my configuration; then check in Session configuration"""
     try:
         return Configuration.__getitem__(self, key)
     except KeyError:
         return SessionConfiguration().get_dataset_from_pool(key)
Exemplo n.º 37
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# Opus/UrbanSim urban simulation software.
# Copyright (C) 2010-2011 University of California, Berkeley, 2005-2009 University of Washington
# See opus_core/LICENSE

from urbansim.configs.base_config_zone import run_configuration as config
from urbansim.configs.estimation_base_config import estimation_configuration
from opus_core.configuration import Configuration

run_configuration = Configuration(config)
run_configuration.merge(estimation_configuration)
run_configuration["models_configuration"]["prepare_datasets_for_aggregation"]["controller"]["run"]["arguments"] = {
                     "datasets_variables": "{household: ['urbansim.household.zone_id'], " + 
                         "job: ['urbansim.job.zone_id'], " + 
                         "building: ['urbansim.building.zone_id'], " + 
                         "zone: ['urbansim.zone.industrial_sqft_per_job', " + 
                                  "'urbansim.zone.commercial_sqft_per_job', " + 
                                  "'is_near_arterial = zone.aggregate(urbansim.gridcell.is_near_arterial, function=aggregate)', " + 
                                  "'is_near_highway = zone.aggregate(urbansim.gridcell.is_near_highway, function=aggregate)', " + 
                                  "'acres_of_land = zone.aggregate(urbansim.gridcell.acres_of_land)', " + 
                                  "'urbansim.zone.avg_val_per_unit_commercial', " + 
                                  "'urbansim.zone.avg_val_per_unit_industrial', " + 
                                  "'urbansim.zone.avg_val_per_unit_governmental', " + 
                                  "'urbansim.zone.avg_val_per_unit_vacant_land', " + 
                                  "'urbansim.zone.avg_val_per_unit_residential', ]" + 
                             "}",
                      "data_objects": "datasets"
                      }
run_configuration["models_configuration"]["household_location_choice_model"]["controller"]["run"]["arguments"]["maximum_runs"]=1
run_configuration["models_configuration"]["employment_location_choice_model"]["controller"]["run"]["arguments"]["maximum_runs"]=1
    def __init__(self):
        Configuration.__init__(self)
        self['models'] = [
                'real_estate_price_model',
                'development_project_transition_model',
                'commercial_development_project_location_choice_model',
                'industrial_development_project_location_choice_model',
                'residential_development_project_location_choice_model',
                'add_projects_to_buildings',
                'household_transition_model',
                'employment_transition_model',
                'household_relocation_model',
                'household_location_choice_model',
                'employment_relocation_model',
                {   'employment_location_choice_model': {   'group_members': '_all_'}},
                'distribute_unplaced_jobs_model',
                ]
        self['model_system'] = 'urbansim.model_coordinators.model_system'
        my_controller_configuration = {
        'real_estate_price_model': RealEstatePriceModelConfigurationCreator(
            dataset='building', 
            outcome_attribute = 'ln_unit_price=ln(building.avg_value)',
            submodel_string = 'building_type_id',
            filter_variable = None,
            ).execute(),
        'residential_development_project_location_choice_model': DevelopmentProjectLocationChoiceModelConfigurationCreator(
                        project_type = 'residential',
                        coefficients_table = 'residential_development_location_choice_model_coefficients',
                        specification_table = 'residential_development_location_choice_model_specification',
                        units = 'residential_units',
                        sampler = None,
                        capacity_string = 'urbansim_zone.zone.developable_residential_units',
                        ).execute(),
        'commercial_development_project_location_choice_model': DevelopmentProjectLocationChoiceModelConfigurationCreator(
                        project_type = 'commercial',
                        coefficients_table = 'commercial_development_location_choice_model_coefficients',
                        specification_table = 'commercial_development_location_choice_model_specification',
                        units = 'commercial_job_spaces',
                        sampler = None,
                        ).execute(),
        'industrial_development_project_location_choice_model': DevelopmentProjectLocationChoiceModelConfigurationCreator(
                        project_type = 'industrial',
                        coefficients_table = 'industrial_development_location_choice_model_coefficients',
                        specification_table = 'industrial_development_location_choice_model_specification',
                        units = 'industrial_job_spaces',
                        sampler = None,
                        ).execute(),
         'development_project_transition_model': DevelopmentProjectTransitionModelConfigurationCreator(
                        vacancy_variables = {"commercial": "urbansim_zone.zone.number_of_vacant_commercial_jobs",
                                             "industrial": "urbansim_zone.zone.number_of_vacant_industrial_jobs"
                                            },
                        output_results = 'dptm_results',
                        ).execute(),
        'add_projects_to_buildings': AddProjectsToBuildingsConfigurationCreator().execute(), 
        'employment_transition_model': 
                  EmploymentTransitionModelConfigurationCreator(
            location_id_name="zone_id",
            ).execute(),
        'household_transition_model': 
                  HouseholdTransitionModelConfigurationCreator(
            location_id_name="zone_id",
            ).execute(),
 
        'employment_relocation_model': 
                  EmploymentRelocationModelConfigurationCreator(
                               location_id_name = 'zone_id',
                               output_index = 'erm_index').execute(),
                               
        'household_relocation_model': HouseholdRelocationModelConfigurationCreator(
                        location_id_name = 'zone_id',
                        output_index = 'hrm_index',
                        ).execute(),
        'household_location_choice_model': HouseholdLocationChoiceModelConfigurationCreator(
                        location_set = "zone",
                        capacity_string = 'urbansim_zone.zone.vacant_residential_units',
                        estimation_weight_string = 'urbansim_zone.zone.vacant_residential_units',
                        portion_to_unplace = 1/3.0,
                        nchunks = 3,
                        number_of_units_string = None,                       
                        input_index = 'hrm_index',
                        ).execute(),
         'employment_location_choice_model': 
                   EmploymentLocationChoiceModelConfigurationCreator(
                                location_set = "zone",
                                input_index = 'erm_index',
                                agents_for_estimation_table = "jobs_for_estimation",
                                estimation_weight_string = None,
                                number_of_units_string = None,
                                portion_to_unplace = 0,
                                capacity_string = "urbansim_zone.zone.number_of_vacant_SSS_jobs",
                                ).execute(),
                                       
          'home_based_employment_location_choice_model': 
                   EmploymentLocationChoiceModelConfigurationCreator(
                                location_set = "zone",
                                input_index = 'erm_index',
                                estimation_weight_string = "urbansim.zone.number_of_households",
                                agents_for_estimation_table = None, # will take standard jobs table 
                                estimation_size_agents = 0.5,
                                number_of_units_string = None,
                                portion_to_unplace = 0,
                                capacity_string = "urbansim.zone.number_of_households",
                                ).execute(),
            'governmental_employment_location_choice_model': 
                   GovernmentalEmploymentLocationChoiceModelConfigurationCreator(
                        input_index = 'erm_index',
                        location_set = 'zone'
                        ).execute(),      
            'distribute_unplaced_jobs_model':  DistributeUnplacedJobsModelConfigurationCreator(
                                    location_set = 'zone'
                                            ).execute(),   
        }
        self['models_configuration'] = {}
        for model in my_controller_configuration.keys():
            if model not in self["models_configuration"].keys():
                self["models_configuration"][model] = {}
            self['models_configuration'][model]['controller'] = my_controller_configuration[model]

                
        self["datasets_to_preload"] = {
                'building':{},
                'zone':{},
                'household':{},
                'job': {},
                'job_building_type':{},
                'target_vacancy':{},
                'development_event_history':{},
                'building_type': {}
                }
Exemplo n.º 39
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 def __init__(self):
     Configuration.__init__(self, self.__my_configuration())
Exemplo n.º 40
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 def config_run_method (*req_args, **opt_args):
     default_config = Configuration(an_instance.get_configuration())["run"]
     an_instance.model_configuration = default_config.merge_defaults_with_arguments_and_config(
                     an_instance.model_configuration, **opt_args)
     results = run_method(*req_args, **opt_args)                
     return results
 def get_configuration(self):
     run_configuration = Configuration(config)
     local_configuration = self.get_local_configuration()
     run_configuration.merge(local_configuration)
     return run_configuration
Exemplo n.º 42
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 def __init__(self):
     Configuration.__init__(
         self,
         data={
             "scenario_database_configuration": ScenarioDatabaseConfiguration(database_name="washtenaw_class"),
             "datasets_to_cache_after_each_model": [],
             "low_memory_mode": False,
             "creating_baseyear_cache_configuration": CreatingBaseyearCacheConfiguration(
                 unroll_gridcells=True,
                 cache_from_database=False,
                 baseyear_cache=BaseyearCacheConfiguration(
                     existing_cache_to_copy="/urbansim_cache/workshop/cache_source",
                     # years_to_cache  = range(1996,2001)
                 ),
                 tables_to_cache=[
                     "annual_employment_control_totals",
                     "annual_household_control_totals",
                     "buildings",
                     "building_types",
                     "development_event_history",
                     "gridcells",
                     "households",
                     "job_building_types",
                     "jobs",
                     "travel_data",
                     "zones",
                     "counties",
                     "commercial_development_location_choice_model_coefficients",
                     "commercial_development_location_choice_model_specification",
                     "commercial_employment_location_choice_model_coefficients",
                     "commercial_employment_location_choice_model_specification",
                     "home_based_employment_location_choice_model_specification",
                     "home_based_employment_location_choice_model_coefficients",
                     "industrial_employment_location_choice_model_coefficients",
                     "industrial_employment_location_choice_model_specification",
                     "industrial_development_location_choice_model_coefficients",
                     "industrial_development_location_choice_model_specification",
                     "residential_development_location_choice_model_coefficients",
                     "residential_development_location_choice_model_specification",
                     "fazes",
                     "urbansim_constants",
                     "household_location_choice_model_coefficients",
                     "household_location_choice_model_specification",
                     "land_price_model_coefficients",
                     "land_price_model_specification",
                     "residential_land_share_model_coefficients",
                     "residential_land_share_model_specification",
                     "plan_type_group_definitions",
                     "plan_type_groups",
                     "large_areas",
                     "household_characteristics_for_ht",
                     "development_types",
                     "development_type_group_definitions",
                     "development_constraints",
                     "annual_relocation_rates_for_households",
                     "annual_relocation_rates_for_jobs",
                     "base_year",
                     "cities",
                     "development_events",
                     "development_type_groups",
                     "employment_adhoc_sector_group_definitions",
                     "employment_adhoc_sector_groups",
                     "employment_sectors",
                     "plan_types",
                     "race_names",
                     "target_vacancies",
                     "jobs_for_estimation",
                     "households_for_estimation",
                     "development_events_exogenous",
                     "job_building_types",
                 ],
                 tables_to_cache_nchunks={"gridcells": 1},
                 tables_to_copy_to_previous_years={
                     "development_type_group_definitions": 1995,
                     "development_type_groups": 1995,
                     "development_types": 1995,
                     "development_constraints": 1995,
                     "urbansim_constants": 1995,
                 },
             ),
             "dataset_pool_configuration": DatasetPoolConfiguration(
                 package_order=["washtenaw", "urbansim", "opus_core"]
             ),
             "base_year": 2000,
             "years": (2000, 2000),
         },
     )
Exemplo n.º 43
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 def __init__(self):
     Configuration.__init__(self)
     estimation_changes = self._get_estimation_changes()
     self.merge(estimation_changes)
Exemplo n.º 44
0
    def __init__(self, model, specification_module=None,
                 xml_configuration=None, model_group=None, configuration={},
                 save_estimation_results=False):
        """
        If 'specification_module' is given, it contains the specification defined as a dictionary in a module.
        Alternatively, the specification can be passed in an xml format in the 'xml_configuration' argument
        (which should be an instance of XMLConfiguration).
        If both of those arguments are None, the specification is taken from the cache.
        'configuration' is an Opus configuration.
        It can contain an entry 'config_changes_for_estimation' which is a dictionary
        where keys are model names and values are controller changes for that model.
        If 'configuration' is None, it is taken from 'xml_configuration'.
        If xml_configuration is used, and if it has a non-empty expression library, the dictionary representing
        the expression library is added to the configuration under the key 'expression_library'.
        If save_estimation_results is True, the estimation results are saved in the output configuration
        (if given in 'configuration') and in the cache.
        """
        self.specification_module = specification_module
        self.xml_configuration = xml_configuration
        self.model_group = model_group
        self.estimated_model = model
        self.explored_model = model

        if configuration is None:
            if self.xml_configuration is None:
                raise StandardError, "Either dictionary based or XML based configuration must be given."
            config = self.xml_configuration.get_estimation_configuration(model, model_group)
        else:
            config = Configuration(configuration)
        config_changes = config.get('config_changes_for_estimation', {})

        specification_dict=None
        if self.xml_configuration is not None:
            specification_dict = self.xml_configuration.get_estimation_specification(model, model_group)

        if model_group is None:
            if model in config_changes.keys():
                config.merge(config_changes[model])
            else:
                config['models'] = [{model: ["estimate"]}]
            if specification_module is not None:
                config = update_controller_by_specification_from_module(
                                config, model, specification_module)
            elif specification_dict is not None:
                config = update_controller_by_specification_from_dict(config, model, specification_dict)
        else:
            if model in config_changes.keys():
                if model_group in config_changes[model]:
                    config.merge(config_changes[model][model_group])
                else:
                    config.merge(config_changes[model])
            else:
                config['models'] = [{model: {"group_members": [{model_group: ["estimate"]}]}}]
            if (specification_module is not None) or (specification_dict is not None):
                if '%s_%s' % (model_group, model) in config["models_configuration"].keys():
                    model_name_in_configuration = '%s_%s' % (model_group, model)
                else:
                    model_name_in_configuration = model
                if specification_module is not None:
                    config = update_controller_by_specification_from_module(config, model_name_in_configuration, specification_module)
                    config["models_configuration"][model_name_in_configuration]["controller"]["prepare_for_estimate"]["arguments"]["specification_dict"] = "spec['%s']" % model_group
                else:
                    config = update_controller_by_specification_from_dict(config, model, specification_dict[model_group])

            if model.startswith('%s_' % model_group):
                config['model_name_for_coefficients'] = model
            else:
                config['model_name_for_coefficients'] = '%s_%s' % (model_group, model)

        Estimator.__init__(self, config, save_estimation_results=save_estimation_results)
 def __init__(self):
     my_config = self._get_initial_config()
     Configuration.__init__(self, my_config)