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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 von_neumann_entropy(self, t_max=100):
 """Calculate Von Neumann Entropy Determines the Von Neumann entropy of the diffusion affinities at varying levels of `t`. The user should select a value of `t` around the "knee" of the entropy curve. We require that 'fit' stores the value of `PHATE.diff_op` in order to calculate the Von Neumann entropy. Parameters t_max : int, default: 100 Maximum value of `t` to test Returns ------- entropy : array, shape=[t_max] The entropy of the diffusion affinities for each value of `t` """

        t = np.arange(t_max)
        return t, vne.compute_von_neumann_entropy(self.diff_op, t_max=t_max)