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
