code: def test_and_early_stopping_strategy(self) -> None:
      exp = get_test_map_data_experiment(
          num_trials=5, num_fetches=3, num_complete=5
      )
      """
          Data looks like this:
          arm_name metric_name        mean  sem  trial_index  timestamp
          0       0_0      branin  146.138620  0.0            0          0
          1       0_0      branin  117.388086  0.0            0          1
          2       0_0      branin   99.950007  0.0            0          2
          3       1_0      branin  113.057480  0.0            1          0
          4       1_0      branin   90.815154  0.0            1          1
          5       1_0      branin   77.324501  0.0            1          2
          6       2_0      branin   44.627226  0.0            2          0
          7       2_0      branin   35.847504  0.0            2          1
          8       2_0      branin   30.522333  0.0            2          2
          9       3_0      branin  143.375669  0.0            3          0
          10      3_0      branin  115.168704  0.0            3          1
          11      3_0      branin   98.060315  0.0            3          2
          12      4_0      branin   65.033535  0.0            4          0
          13      4_0      branin   52.239184  0.0            4          1
          14      4_0      branin   44.479018  0.0            4          2
          """
      idcs = set(exp.trials.keys())
  
      left_early_stopping_strategy = ThresholdEarlyStoppingStrategy(
          metric_threshold=50, min_progression=1
      )
  
      right_early_stopping_strategy = ThresholdEarlyStoppingStrategy(
          metric_threshold=80, min_progression=1
      )
  
      and_early_stopping_strategy = AndEarlyStoppingStrategy(
          left=left_early_stopping_strategy,
          right=right_early_stopping_strategy,
      )
  
      left_should_stop = (
          left_early_stopping_strategy.should_stop_trials_early(
              trial_indices=idcs, experiment=exp
          )
      )
      right_should_stop = (
          right_early_stopping_strategy.should_stop_trials_early(
              trial_indices=idcs, experiment=exp
          )
      )
      and_should_stop = (
          and_early_stopping_strategy.should_stop_trials_early(
              trial_indices=idcs, experiment=exp
          )
      )
  
      intersection = set(left_should_stop.keys()).intersection(
          set(right_should_stop.keys())
      )
  
      for idc in idcs:
          if idc in intersection:
              self.assertIn(idc, and_should_stop.keys())
          else:
              self.assertNotIn(idc, and_should_stop.keys())
  
imports: from typing import Any, Dict, Optional, Set
  import numpy
  import pandas
  from ax.core.base_trial import TrialStatus
  from ax.core.experiment import Experiment
  from ax.core.map_data import MapData
  from ax.early_stopping.strategies import BaseEarlyStoppingStrategy, ModelBasedEarlyStoppingStrategy, PercentileEarlyStoppingStrategy, ThresholdEarlyStoppingStrategy
  from ax.early_stopping.strategies.logical import AndEarlyStoppingStrategy, OrEarlyStoppingStrategy
  from ax.early_stopping.utils import align_partial_results
  from ax.exceptions.core import UnsupportedError
  from ax.utils.common.testutils import TestCase
  from ax.utils.common.typeutils import checked_cast
  from ax.utils.testing.core_stubs import get_branin_arms, get_branin_experiment, get_branin_experiment_with_timestamp_map_metric, get_experiment_with_multi_objective, get_test_map_data_experiment
  from pyre_extensions import none_throws
label_desc: Use image node_id 1 for calling the TestLogicalEarlyStoppingStrategy obj's underlying member method code with example usage: obj.test_and_early_stopping_strategy() without return types