datasketch/minhash.py
def count(self):
        '''Estimate the cardinality count based on the technique described in
        `this paper <http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=365694>`_.

        Returns:
            int: The estimated cardinality of the set represented by this MinHash.
        '''
        k = len(self)
        return np.float(k) / np.sum(self.hashvalues / np.float(_max_hash)) - 1.0
def count(self):
        '''Estimate the cardinality count based on the technique described in
        `this paper <http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=365694>`_.

        Returns:
            int: The estimated cardinality of the set represented by this MinHash.
        '''
        k = len(self)
        return np.float(k) / np.sum(self.hashvalues / np.float(_max_hash)) - 1.0
def count ( self ) : k = len ( self ) return np . float ( k ) / np . sum ( self . hashvalues / np . float ( _max_hash ) ) - 1.0
Estimate the cardinality count based on the technique described in
        `this paper <http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=365694>`_.

        Returns:
            int: The estimated cardinality of the set represented by this MinHash.
Estimate the cardinality count based on the technique described in this paper <http : // ieeexplore . ieee . org / stamp / stamp . jsp?arnumber = 365694 > _ .