def _update_cascade_selection(self):
composite_model_name = self.modelSelection.currentText()
cascade_models = list_cascade_models(composite_model_name)
previous_cascade_selection = self.cascadeSelection.currentText()
cascade_type_names = [
get_meta_info('cascade_models', model)['cascade_type_name']
for model in cascade_models
]
self.cascadeSelection.clear()
self.cascadeSelection.addItems(cascade_type_names)
if previous_cascade_selection in cascade_type_names:
self.cascadeSelection.setCurrentText(previous_cascade_selection)
elif 'Cascade' in cascade_type_names:
self.cascadeSelection.setCurrentText('Cascade')
if not cascade_type_names:
self.noCascades.setChecked(True)
self._update_cascade_selection_possible()
self.useCascades.setDisabled(True)
else:
self.useCascades.setEnabled(True)
self.useCascades.setChecked(True)
self._update_cascade_selection_possible()
def get_models_meta_info():
"""Get the meta information tags for all the models returned by get_models_list()
Returns:
dict of dict: The first dictionary indexes the model names to the meta tags, the second holds the meta
information.
"""
from mdt.lib.components import get_meta_info, get_component_list
return {model: get_meta_info('composite_models', model) for model in get_component_list('composite_models')}
def get_models_meta_info():
"""Get the meta information tags for all the models returned by get_models_list()
Returns:
dict of dict: The first dictionary indexes the model names to the meta tags, the second holds the meta
information.
"""
from mdt.lib.components import list_cascade_models, list_composite_models, get_meta_info, get_component_list
meta_info = {}
for model_type in ('composite_models', 'cascade_models'):
model_list = get_component_list(model_type)
for model in model_list:
meta_info.update({model: get_meta_info(model_type, model)})
return meta_info