code: def test_causal_discovery_using_data_minimize() -> None:
      # Optimization should return the same result since the true graph is not random and small
      np.random.seed(12)
      func = core.CausalDiscovery(generator="sachs")
      optimizer = ng.optimizers.OnePlusOne(
          parametrization=func.parametrization, budget=500
      )
      optimizer.parametrization.random_state = np.random.RandomState(12)
      recommendation = optimizer.minimize(func)
      recommendation_score = func(**recommendation.kwargs)
      assert np.isclose(
          20.498524203069657, recommendation_score, atol=1e-10
      )  # Optimal
      assert (
          len(recommendation.kwargs["network_links"])
          == func._nvars * (func._nvars - 1) // 2
      )
  
imports: import numpy
  import nevergrad
  from .None import core
label_desc: Use image node_id 2 for calling a global function with example usage: test_causal_discovery_using_data_minimize() without return types