(self, attr, cur_value)
return sorted(additional_values)
get_random_domain returns a random sample of at most size
        'self.max_sample' of domain values for 'attr' that is NOT 'cur_value'.
get_random_domain returns a random sample of at most size
        'self.max_sample' of domain values for 'attr' that is NOT 'cur_value'.
get_random_domain returns a random sample of at most size self . max_sample of domain values for attr that is NOT cur_value .
def get_random_domain(self, attr, cur_value):
        """
        get_random_domain returns a random sample of at most size
        'self.max_sample' of domain values for 'attr' that is NOT 'cur_value'.
        """
        domain_pool = set(self.single_stats[attr].keys())
        # We should not have any NULLs since we do not keep track of their
        # counts.
        assert NULL_REPR not in domain_pool
        domain_pool.discard(cur_value)
        domain_pool = sorted(list(domain_pool))
        size = len(domain_pool)
        if size > 0:
            k = min(self.max_sample, size)
            additional_values = np.random.choice(domain_pool, size=k, replace=False)
        else:
            additional_values = []
        return sorted(additional_values)
def get_random_domain ( self , attr , cur_value ) : domain_pool = set ( self . single_stats [ attr ] . keys ( ) ) # We should not have any NULLs since we do not keep track of their # counts. assert NULL_REPR not in domain_pool domain_pool . discard ( cur_value ) domain_pool = sorted ( list ( domain_pool ) ) size = len ( domain_pool ) if size > 0 : k = min ( self . max_sample , size ) additional_values = np . random . choice ( domain_pool , size = k , replace = False ) else : additional_values = [ ] return sorted ( additional_values )