@property
    def density(self):
        return float(sum(len(d.vector) for d in self.documents)) / len(self.vector) ** 2

    # Following methods rely on Document.vector:
    # frequent sets, cosine similarity, nearest neighbors, search, clustering, 
    # information gain, latent semantic analysis.
Yields the overall word coverage as a number between 0.0-1.0.
dataset/ETHPy150Open clips/pattern/pattern/vector/__init__.py/Model.density