code: def test_ThompsonSamplerMinWeight(self) -> None:
      generator = ThompsonSampler(min_weight=0.01)
      generator.fit(
          # pyre-fixme[6]: For 1st param expected `List[List[List[Union[None,
          #  bool, float, int, str]]]]` but got `List[List[List[int]]]`.
          Xs=self.Xs,
          # pyre-fixme[6]: For 2nd param expected `List[List[float]]` but got
          #  `List[List[int]]`.
          Ys=self.Ys,
          # pyre-fixme[6]: For 3rd param expected `List[List[float]]` but got
          #  `List[List[int]]`.
          Yvars=self.Yvars,
          # pyre-fixme[6]: For 4th param expected `List[List[Union[None, bool,
          #  float, int, str]]]` but got `List[List[int]]`.
          parameter_values=self.parameter_values,
          outcome_names=self.outcome_names,
      )
      arms, weights, _ = generator.gen(
          n=5,
          # pyre-fixme[6]: For 2nd param expected `List[List[Union[None, bool,
          #  float, int, str]]]` but got `List[List[int]]`.
          parameter_values=self.parameter_values,
          objective_weights=np.ones(1),
      )
      self.assertEqual(arms, [[4, 4], [3, 3], [2, 2]])
      for weight, expected_weight in zip(
          weights, [3 * i for i in [0.725, 0.225, 0.05]]
      ):
          self.assertAlmostEqual(weight, expected_weight, 1)
  
file_path: Ax/ax/models/tests/test_thompson.py
imports: import numpy
  from ax.exceptions.model import ModelError
  from ax.models.discrete.thompson import ThompsonSampler
  from ax.utils.common.testutils import TestCase
label_desc: Use image node_id 4 for calling the ThompsonSamplerTest obj's underlying member method code with example usage: obj.test_ThompsonSamplerMinWeight() without return types