def _load_features_from_dataset(self, features=None, image_type=None,<EOL>threshold=<NUM_LIT>):
self.feature_names = self.dataset.feature_table.feature_names<EOL>if features is not None:<EOL><INDENT>self.feature_names = [f for f in features<EOL>if f in self.feature_names]<EOL><DEDENT>from neurosynth.analysis import meta<EOL>self.feature_images = meta.analyze_features(<EOL>self.dataset, self.feature_names, image_type=image_type,<EOL>threshold=threshold)<EOL>if self.masker.layers:<EOL><INDENT>in_mask = self.masker.get_mask(in_global_mask=True)<EOL>self.feature_images = self.feature_images[in_mask, :]<EOL><DEDENT>
Load feature image data from the current Dataset instance. See
        load_features() for documentation.