code: def test_score_laplace_noise_invalid_values_throws_exception(self):
      params = construct_params(
          aggregation_noise_kind=pipeline_dp.NoiseKind.LAPLACE,
          aggregation_eps=0.9,
          max_partitions_contributed_upper_bound=100,
      )
      number_of_partitions = 200
      l0_histogram = hist.Histogram(
          name=hist.HistogramType.L0_CONTRIBUTIONS,
          bins=[
              hist.FrequencyBin(
                  lower=1, upper=2, count=100, sum=100, max=1
              ),
              hist.FrequencyBin(
                  lower=2, upper=6, count=10, sum=10, max=5
              ),
              hist.FrequencyBin(
                  lower=6, upper=100, count=20, sum=20, max=60
              ),
          ],
      )
      l0_scoring_function = (
          private_contribution_bounds.L0ScoringFunction(
              params, number_of_partitions, l0_histogram
          )
      )
  
      with self.assertRaises(RuntimeError):
          l0_scoring_function.score(-1)
  
      with self.assertRaises(RuntimeError):
          l0_scoring_function.score(0)
  
file_path: pipelinedp/tests/private_contribution_bounds_test.py
imports: import unittest
  import pipeline_dp
  from pipeline_dp.dataset_histograms import histograms
  from pipeline_dp import private_contribution_bounds
label_desc: Use image node_id 5 for calling the L0ScoringFunctionTest obj's underlying member method code with example usage: obj.test_score_laplace_noise_invalid_values_throws_exception() without return types