'Evaluate several instances concurrently.
Parameters
X : ndarray
Evaluate this data.
Returns
res : ndarray, bool
Array of evaluations.'

def evaluate_data(self, X):

    curr_covered = np.ones(X.shape[0], dtype=bool)
    for selector in self.selectors:
        curr_covered &= selector.filter_data(X)
    return curr_covered
