

def __init__(self, X):
    assert ((X.ndim == 2) and (X >= 0).all())
    (self.N, self.K) = X.shape
    alpha = 1
    self.pi = ((X + alpha).astype(np.float) / (X + alpha).sum(axis=1)[:, None])
    self.multinomials = []
    for pi_n in self.pi:
        self.multinomials.append(Multinomial(weights=alpha, K=self.K))

dataset/ETHPy150Open HIPS/pgmult/pgmult/distributions.py IndependentMultinomialsModel.__init__/VarMisuse@114/125 `pi_n`->`alpha`