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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 compute_log_scales(lmin, lmax, Nscales, t1=1, t2=2):
 r""" Compute logarithm scales for wavelets. Parameters lmin : float Smallest non-zero eigenvalue. lmax : float Largest eigenvalue, i.e. :py:attr:`pygsp.graphs.Graph.lmax`. Nscales : int Number of scales. Returns ------- scales : ndarray List of scales of length Nscales. Examples -------- array([2. , 0.4472136, 0.1 ]) """

    scale_min = t1 / lmax
    scale_max = t2 / lmin
    return np.exp(np.linspace(np.log(scale_max), np.log(scale_min), Nscales))