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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 find_dt_artifacts(dt):
 r""" Finds points in a distance transform that are closer to wall than solid. These points could *potentially* be erroneously high since their distance values do not reflect the possibility that solid may have been present beyond the border of the image but lost by trimming. Parameters dt : ND-array The distance transform of the phase of interest Returns ------- image : ND-array An ND-array the same shape as ``dt`` with numerical values indicating the maximum amount of error in each volxel, which is found by subtracting the distance to nearest edge of image from the distance transform value. In other words, this is the error that would be found if there were a solid voxel lurking just beyond the nearest edge of the image. Obviously, voxels with a value of zero have no error. """

    temp = sp.ones(shape=dt.shape)*sp.inf
    for ax in range(dt.ndim):
        dt_lin = distance_transform_lin(sp.ones_like(temp, dtype=bool),
                                        axis=ax, mode='both')
        temp = sp.minimum(temp, dt_lin)
    result = sp.clip(dt - temp, a_min=0, a_max=sp.inf)
    return result