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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 get_nsing(self,epsilon=1.0e-4):
 """ get the number of solution space dimensions given a ratio between the largest and smallest singular values Parameters epsilon: float singular value ratio Returns ------- nsing : float number of singular components above the epsilon ratio threshold Note ----- If nsing == nadj_par, then None is returned """

        mx = self.xtqx.shape[0]
        nsing = mx - np.searchsorted(
                np.sort((self.xtqx.s.x / self.xtqx.s.x.max())[:,0]),epsilon)
        if nsing == mx:
            self.logger.warn("optimal nsing=npar")
            nsing = None
        return nsing