code: def lowest(self, rtol=1.e-5, atol=1.e-8):
          
  
          if len(self) == 0:
              # empty so all are lowest
              return self.copy()
  
          record = self.record
  
          # want all the rows within tolerance of the minimal energy
          close = np.isclose(record.energy,
                             np.min(record.energy),
                             rtol=rtol, atol=atol)
          record = record[close]
  
          return type(self)(record, self.variables, copy.deepcopy(self.info),
                            self.vartype)
docs: Return a sample set containing the lowest-energy samples.
  
          A sample is included if its energy is within tolerance of the lowest
          energy in the sample set. The following equation is used to determine
          if two values are equivalent:
  
          absolute(`a` - `b`) <= (`atol` + `rtol` * absolute(`b`))
  
          See :func:`numpy.isclose` for additional details and caveats.
  
          Args:
              rtol (float, optional, default=1.e-5):
                  The relative tolerance (see above).
  
              atol (float, optional, default=1.e-8):
                  The absolute tolerance (see above).
  
          Returns:
              :obj:`.SampleSet`: A new sample set containing the lowest energy
              samples as delimited by configured tolerances from the lowest energy
              sample in the current sample set.
  
          Examples:
              >>> sampleset = dimod.ExactSolver().sample_ising({'a': .001},
              ...                                              {('a', 'b'): -1})
              >>> print(sampleset.lowest())
                 a  b energy num_oc.
              0 -1 -1 -1.001       1
              ['SPIN', 1 rows, 1 samples, 2 variables]
              >>> print(sampleset.lowest(atol=.1))
                 a  b energy num_oc.
              0 -1 -1 -1.001       1
              1 +1 +1 -0.999       1
              ['SPIN', 2 rows, 2 samples, 2 variables]
  
          Note:
              "Lowest energy" is the lowest energy in the sample set. This is not
              always the "ground energy" which is the lowest energy possible
              for a binary quadratic model.