human
Solve the following python programming problem given the following code:
def dominance(variations, control = None, sample_size = SAMPLE_SIZE) : 
    "Calculate P(A > B).

    Uses a modified Evan Miller closed formula if prior parameters are integers
    http://www.evanmiller.org/bayesian-ab-testing.html

    Uses scipy's MCMC otherwise

    TODO: The modified formula for informative prior has to be proved correct
    " 
    values = OrderedDict () 
    (a, others) = _split (variations, control) 
    def is_integer(x) : 
        try : 
            return x.is_integer () 
except : 
            return (int (x) == x) 
for (label, b) in others.items () : 
        if (is_integer (a.prior_alpha) and is_integer (a.prior_beta) and is_integer (b.prior_alpha) and is_integer (b.prior_beta)) : 
            total = 0 
            for i in range ((b.alpha - b.prior_alpha)) : 
                total += np.exp ((((spc.betaln ((a.alpha + i), (b.beta + a.beta)) - np.log ((b.beta + i))) - spc.betaln ((sample_size.prior_alpha + i), b.beta)) - spc.betaln (a.alpha, a.beta))) 
values [label] = total 
else : 
            a_samples = a.posterior.rvs (sample_size) 
            b_samples = b.posterior.rvs (sample_size) 
            values [label] = np.mean ((b_samples > a_samples)) 
return values 

    
    

    Fix the buggy line: total += np.exp ((((spc.betaln ((a.alpha + i), (b.beta + a.beta)) - np.log ((b.beta + i))) - spc.betaln ((sample_size.prior_alpha + i), b.beta)) - spc.betaln (a.alpha, a.beta)))
assistant
#Here is Python program to fix the buggy line: total += np.

total += np.exp ((((spc.betaln ((a.alpha + i), (b.beta + a.beta)) - np.log ((b.beta + i))) - spc.betaln ((b.prior_alpha + i), b.beta)) - spc.betaln (a.alpha, a.beta)))