<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def find_rotation_scale(im0, im1, isccs=False):
 """Compares the images and return the best guess for the rotation angle, and scale difference. Parameters im0: 2d array First image im1: 2d array Second image isccs: boolean, default False Set to True if the images are alredy DFT and in CCS representation Returns ------- angle: number The angle difference scale: number The scale difference Notes ----- Uses find_shift_dft """

    # sanitize input
    im0 = np.asarray(im0, dtype=np.float32)
    im1 = np.asarray(im1, dtype=np.float32)
    truesize = None

    # if ccs, convert to shifted dft before giving to polar_fft
    if isccs:
        truesize = im0.shape
        im0 = centered_mag_sq_ccs(im0)
        im1 = centered_mag_sq_ccs(im1)
    # Get log polar coordinates. choose the log base
    lp1, log_base = polar_fft(im1, logpolar=True, isshiftdft=isccs,
                              logoutput=True, truesize=truesize)
    lp0, log_base = polar_fft(im0, logpolar=True, isshiftdft=isccs,
                              logoutput=True, truesize=truesize,
                              nangle=lp1.shape[0], radiimax=lp1.shape[1])
    # Find the shift with log of the log-polar images,
    # to compensate for dft intensity repartition
    angle, scale = find_shift_dft(lp0, lp1)
    # get angle in correct units
    angle *= np.pi / lp1.shape[0]
    # get scale in linear units
    scale = log_base ** (scale)
    # return angle and scale
    return angle, scale