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)
