Since the entire depiction parameters constitute a high-dimensional feature space, random sampling doesn't necessarily guarantee even coverage. Instead of choosing parameters randomly, RanDepict can use depiction feature fingerprints to deal with this issue. This means that all depiction parameters as well as the presence or absence of the different augmentation types are summarised in bit arrays. Here, a 1 or a 0 in every position represents the presence or absence of a certain feature (exemplary illustration in Figure ). After computing all possible valid fingerprints, RDKit's implementation of the MaxMin algorithm is used to pick diverse samples. This way, diversity of depiction features is ensured. The set of all possible valid fingerprints is determined as the combination of all valid fingerprint building blocks in a given order. Here, a fingerprint building block is a valid subset of values that are linked to certain positions in the whole fingerprint which express one depiction feature. A valid fingerprint is a combination of values that does not lead to contradicting statements about the underlying chemical structure depiction.