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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 uncertainty_timescales(self):
 """Estimate of the element-wise asymptotic standard deviation in the model implied timescales. Returns ------- sigma_timescales : np.array, shape=(n_timescales,) The estimated symptotic standard deviation in the implied timescales. References .. [1] Hinrichs, Nina Singhal, and Vijay S. Pande. "Calculation of the distribution of eigenvalues and eigenvectors in Markovian state models for molecular dynamics." J. Chem. Phys. 126.24 (2007):
 244101. """

        # drop the first eigenvalue
        u = self.eigenvalues_[1:]
        sigma_eigs = self.uncertainty_eigenvalues()[1:]

        sigma_ts = sigma_eigs / (u * np.log(u)**2)
        return sigma_ts