For very big datasets, we might not need to load every features, it would be usefull to load only usefull features
class Sample:
def load(self, feature_identifiers: list[FeatureIdentifier]).
...
As we are using the pycgns lib, we might be forced to load the whole mesh for each Sample
, but we can discard useless features from the loaded tree before processing the next Sample
.