code: def test_get_aggregate_params(self):
      params = pipeline_dp.AggregateParams(
          noise_kind=pipeline_dp.NoiseKind.GAUSSIAN,
          metrics=[pipeline_dp.Metrics.COUNT],
          max_partitions_contributed=1,
          max_contributions_per_partition=1,
      )
  
      max_partitions_contributed = [10, 12, 15]
      noise_kind = [pipeline_dp.NoiseKind.LAPLACE] * 2 + [
          pipeline_dp.NoiseKind.GAUSSIAN
      ]
      selection_strategy = [
          pipeline_dp.PartitionSelectionStrategy.GAUSSIAN_THRESHOLDING
      ] * 3
      multi_params = analysis.MultiParameterConfiguration(
          max_partitions_contributed=max_partitions_contributed,
          noise_kind=noise_kind,
          partition_selection_strategy=selection_strategy,
      )
      self.assertTrue(3, multi_params.size)
  
      for i in range(multi_params.size):
          ith_params = multi_params.get_aggregate_params(params, i)
          params.max_partitions_contributed = (
              max_partitions_contributed[i]
          )
          params.noise_kind = noise_kind[i]
          params.partition_selection_strategy = selection_strategy[i]
          self.assertEqual(params, ith_params)
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  import analysis
  import pipeline_dp
label_desc: Use image node_id 2 for calling the MultiParameterConfiguration obj's underlying member method code with example usage: obj.test_get_aggregate_params() without return types