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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_D_square_min(atoms_now, atoms_old, i_now, j_now, delta_plus_epsilon=None):
 """ Calculate the D^2_min norm of Falk and Langer """

    nat = len(atoms_now)
    assert len(atoms_now) == len(atoms_old)

    pos_now = atoms_now.positions
    pos_old = atoms_old.positions

    # Compute current and old distance vectors. Note that current distance
    # vectors cannot be taken from the neighbor calculation, because neighbors
    # are calculated from the sheared cell while these distance need to come
    # from the unsheared cell. Taking the distance from the unsheared cell
    # make periodic boundary conditions (and flipping of cell) a lot easier.
    dr_now = mic(pos_now[i_now] - pos_now[j_now], atoms_now.cell)
    dr_old = mic(pos_old[i_now] - pos_old[j_now], atoms_old.cell)

    # Sanity check: Shape needs to be identical!
    assert dr_now.shape == dr_old.shape

    if delta_plus_epsilon is None:
        # Get minimum strain tensor
        delta_plus_epsilon = get_delta_plus_epsilon(nat, i_now, dr_now, dr_old)

    # Spread epsilon out for each neighbor index
    delta_plus_epsilon_n = delta_plus_epsilon[i_now]

    # Compute D^2_min
    d_sq_n = np.sum(
        (
        dr_now-
        np.sum(delta_plus_epsilon_n.reshape(-1,3,3)*dr_old.reshape(-1,1,3),
               axis=2)
        )**2,
        axis=1)

    # For each atom, sum over all neighbors
    d_sq = np.bincount(i_now, weights=d_sq_n)

    return delta_plus_epsilon, d_sq