@property
    def vector(self):
        # Notes: 
        # 1) Model.vector is the dictionary of all (word, 0.0)-items.
        # 2) Model.vector(document) returns a copy with the document's word frequencies.
        #    This is the full vector, as opposed to the sparse Document.vector.
        #    Words in a document that are not in the model are ignored,
        #    i.e., the document was not in the model, this can be the case in Model.search().
        # See: Vector.__call__().
        if not self._vector:
            self._vector = Vector(((w, 0.0) for w in chain(*(d.terms for d in self.documents))), sparse=False)
        return self._vector
Returns a Vector dict of (word, 0.0)-items from the vector space model.
dataset/ETHPy150Open clips/pattern/pattern/vector/__init__.py/Model.vector