code: def test_when_estimate_counterfactual_without_observed_or_noise_data_then_raise_error():
      (
          causal_model,
          _,
      ) = _create_and_fit_simple_probabilistic_causal_model()
  
      with pytest.raises(ValueError):
          counterfactual_samples(causal_model, dict(X0=lambda x: 10))
  
imports: import networkx
  import numpy
  import pandas
  import pytest
  from flaky import flaky
  from pytest import approx
  from dowhy.gcm import AdditiveNoiseModel, ClassifierFCM, DiscreteAdditiveNoiseModel, EmpiricalDistribution, InvertibleStructuralCausalModel, ProbabilisticCausalModel, auto, average_causal_effect, counterfactual_samples, fit, interventional_samples
  from dowhy.gcm.ml import create_hist_gradient_boost_regressor, create_linear_regressor, create_logistic_regression_classifier
label_desc: Use image node_id 12 for calling a global function with example usage: test_when_estimate_counterfactual_without_observed_or_noise_data_then_raise_error() without return types