code: def test_given_non_contiguous_data_when_calling_setdiff2d_then_does_not_raise_error():
      X = np.random.normal(loc=0, scale=1, size=1000)
      Y = X + np.random.normal(loc=0, scale=1, size=1000)
      data = pd.DataFrame(data=dict(X=X, Y=Y))
  
      causal_model = gcm.StructuralCausalModel(nx.DiGraph([("X", "Y")]))
      gcm.auto.assign_causal_mechanisms(causal_model, data)
      gcm.fit(causal_model, data)
  
      generated_data = gcm.draw_samples(
          causal_model, num_samples=100000
      )
  
      setdiff2d(data.to_numpy(), generated_data.to_numpy())
  
imports: import random
  import networkx
  import numpy
  import pandas
  import pytest
  from _pytest.python_api import approx
  from dowhy import gcm
  from dowhy.gcm.util.general import apply_catboost_encoding, apply_one_hot_encoding, auto_apply_encoders, auto_fit_encoders, fit_catboost_encoders, fit_one_hot_encoders, has_categorical, is_categorical, is_discrete, set_random_seed, setdiff2d, shape_into_2d
label_desc: Use image node_id 10 for calling a global function with example usage: test_given_non_contiguous_data_when_calling_setdiff2d_then_does_not_raise_error() without return types