20769173fc5100fd8b60ca7d77a0b7dd5d6225fd,skbio/tree/_nj.py,,_compute_q,#Any#,172

Before Change

    
    q = np.zeros(dm.shape)
    n = dm.shape[0]
    for i in range(n):
        for j in range(i):
            q[i, j] = q[j, i] = \
                ((n - 2) * dm[i, j]) - dm[i].sum() - dm[j].sum()
    return DistanceMatrix(q, dm.ids)


def _compute_collapsed_dm(dm, i, j, disallow_negative_branch_length,

After Change

    q = np.zeros(dm.shape)
    n = dm.shape[0]
    dmv = dm.to_data_frame().values
    big_sum = np.array([dmv.sum(1)] * dm.shape[0])
    big_sum_diffs = big_sum + big_sum.T
    q = (n - 2) * dmv - big_sum_diffs
    np.fill_diagonal(q, 0)
    return DistanceMatrix(q, dm.ids)

Instances