def iter_max()

in align/models.py [0:0]

• 27 lines of code
• 6 McCabe index (conditional complexity)

    def iter_max(sim_matrix, max_count=2):
        alpha_ratio = 0.9
        m, n = sim_matrix.shape
        forward = np.eye(n)[sim_matrix.argmax(axis=1)]  # m x n
        backward = np.eye(m)[sim_matrix.argmax(axis=0)]  # n x m
        inter = forward * backward.transpose()

        if min(m, n) <= 2:
            return inter

        new_inter = np.zeros((m, n))
        count = 1
        while count < max_count:
            mask_x = 1.0 - np.tile(inter.sum(1)[:, np.newaxis], (1, n)).clip(0.0, 1.0)
            mask_y = 1.0 - np.tile(inter.sum(0)[np.newaxis, :], (m, 1)).clip(0.0, 1.0)
            mask = ((alpha_ratio * mask_x) + (alpha_ratio * mask_y)).clip(0.0, 1.0)
            mask_zeros = 1.0 - ((1.0 - mask_x) * (1.0 - mask_y))
            if mask_x.sum() < 1.0 or mask_y.sum() < 1.0:
                mask *= 0.0
                mask_zeros *= 0.0

            new_sim = sim_matrix * mask
            fwd = np.eye(n)[new_sim.argmax(axis=1)] * mask_zeros
            bac = np.eye(m)[new_sim.argmax(axis=0)].transpose() * mask_zeros
            new_inter = fwd * bac

            if np.array_equal(inter + new_inter, inter):
                break
            inter = inter + new_inter
            count += 1
        return inter