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 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 prepare_for_run(self, specification_storage=None, specification_table=None, coefficients_storage=None, coefficients_table=None, agent_set=None, agents_filter=None, data_objects=None, **kwargs): spec, coeff = prepare_specification_and_coefficients( specification_storage=specification_storage, specification_table=specification_table, coefficients_storage=coefficients_storage, coefficients_table=coefficients_table, **kwargs) if agents_filter is not None: agent_set.compute_variables(agents_filter, resources=Resources(data_objects)) index = where( agent_set.get_attribute( VariableName(agents_filter).get_alias()) > 0)[0] return (spec, coeff, index)
def prepare_for_run(self, dataset=None, dataset_filter=None, filter_threshold=0, **kwargs): spec, coef = prepare_specification_and_coefficients(**kwargs) if (dataset is not None) and (dataset_filter is not None): filter_values = dataset.compute_variables([dataset_filter], dataset_pool=self.dataset_pool) index = where(filter_values > filter_threshold)[0] else: index = None return (spec, coef, index)
def prepare_for_run(self, specification_storage=None, specification_table=None, coefficients_storage=None, coefficients_table=None, data_objects=None, **kwargs): spec, coeff = prepare_specification_and_coefficients(specification_storage=specification_storage, specification_table=specification_table, coefficients_storage=coefficients_storage, coefficients_table=coefficients_table, **kwargs) return (spec, coeff)
def prepare_for_run(self, dataset=None, dataset_filter=None, filter_threshold=0, **kwargs): spec, coef = prepare_specification_and_coefficients(**kwargs) if (dataset is not None) and (dataset_filter is not None): filter_values = dataset.compute_variables( [dataset_filter], dataset_pool=self.dataset_pool) index = where(filter_values > filter_threshold)[0] else: index = None return (spec, coef, index)
def prepare_for_run(self, specification_storage=None, specification_table=None, coefficients_storage=None, coefficients_table=None, agent_set=None, agents_filter=None, data_objects=None, **kwargs): spec, coeff = prepare_specification_and_coefficients(specification_storage=specification_storage, specification_table=specification_table, coefficients_storage=coefficients_storage, coefficients_table=coefficients_table, **kwargs) if agents_filter is not None: agent_set.compute_variables(agents_filter, resources=Resources(data_objects)) index = where(agent_set.get_attribute(VariableName(agents_filter).get_alias()) > 0)[0] return (spec, coeff, index)