code: def from_pcount(nevents):
          
          if nevents < 0:
              raise ValueError('Poisson parameter `nevents` must be nonnegative')
          return Uval(np.random.gamma(nevents + 1, size=uval_nsamples))
docs: We assume a Poisson process. nevents is the number of events in
          some interval. The distribution of values is the distribution of the
          Poisson rate parameter given this observed number of events, where the
          "rate" is in units of events per interval of the same duration. The
          max-likelihood value is nevents, but the mean value is nevents + 1.
          The gamma distribution is obtained by assuming an improper, uniform
          prior for the rate between 0 and infinity.