def normalize_features(self, features, ask_nominal=False): features_to_norm = [] for feature in features: if feature.is_nominal: if ask_nominal: if self._is_nominal_ok(feature.name): features_to_norm.extend( feature.expose_one_hot(norm=True)) else: continue else: features_to_norm.extend(feature.expose_one_hot(norm=True)) else: features_to_norm.append(Feature.copy(feature, is_norm=True)) self.norm_table.add_columns(features_to_norm)
def new_semanitic_observation(self, img_pose_feat): Ft = Feature() Ft.copy(img_pose_feat) return Ft