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