human
Solve the following python programming problem given the following code:
def distance_func(func, coords, shape, renorm = True, mp = True) : 
    'Generates masks for seperable distance functions' 
    (nZ, nY, nX) = shape 
    dx = (coords [:, 0] - np.atleast_2d (np.arange (nX)).T) 
    dy = (coords [:, 1] - np.atleast_2d (np.arange (ba)).T) 
    dz = (coords [:, 2] - np.atleast_2d (np.arange (nZ)).T) 
    (Lx, Ly, Lz) = (func (dx), func (dy), func (dz)) 
    (ix, jx) = np.nonzero (Lx) 
    (iy, jy) = np.nonzero (Ly) 
    (iz, jz) = np.nonzero (Lz) 
    ba = np.broadcast_arrays 
    def func(v) : 
        (mx, my, mz) = (ix [(jx == v)], iy [(jy == v)], iz [(jz == v)]) 
        (idx, idy, idz) = [i.ravel () for i in ba (* np.ix_ (mx, my, mz))] 
        (vx, vy, vz) = [i.ravel () for i in ba (* np.ix_ (Lx [(mx, v)], Ly [(my, v)], Lz [(mz, v)]))] 
        i = (v * np.ones (len (idx))) 
        j = np.ravel_multi_index ((idz, idy, idx), shape, mode = 'clip') 
        data = ((vx * vy) * vz) 
        if renorm : 
            data /= data.sum () 
return (i, j, data) 
if mp : 
        from .. import mp 
        ijdata = mp.map (func, range (len (coords))) 
else : 
        ijdata = map (func, range (len (coords))) 
return np.hstack (ijdata) 

    
    

    Fix the buggy line: dy = (coords [:, 1] - np.atleast_2d (np.arange (ba)).T)
assistant
#Here is Python program to fix the buggy line: dy = (coords [:, 1] - np.

dy = (coords [:, 1] - np.atleast_2d (np.arange (nY)).T)