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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 ccs_normalize(compIM, ccsnorm):
 """ normalize the ccs representation Parameters compIM: 2d array The CCS image in CCS representation ccsnorm: 2d array The normalization matrix in ccs representation Returns ------- compIM: 2d array The normalized CCS image Notes ----- (basically an element wise division for CCS) Should probably not be used from outside """

    compIM = np.asarray(compIM)
    ccsnorm = np.asarray(ccsnorm)
    ys = ccsnorm.shape[0]
    xs = ccsnorm.shape[1]
    # start with first column
    ccsnorm[2::2, 0] = ccsnorm[1:ys - 1:2, 0]
    # continue with middle columns
    ccsnorm[:, 2::2] = ccsnorm[:, 1:xs - 1:2]
    # finish whith last row if even
    if xs % 2 is 0:
        ccsnorm[2::2, xs - 1] = ccsnorm[1:ys - 1:2, xs - 1]
    # solve problem with 0/0
    ccsnorm[ccsnorm == 0] = np.nextafter(0., 1., dtype = ccsnorm.dtype)

    res = compIM / ccsnorm
    return res