code: def test_exponential_coefficient_effect():
      a1 = -10
      a0 = -2
      t = np.array([0.0, 0.02, 0.04, 0.06, 0.08, 0.1])
  
      df = pd.DataFrame(dict(t=t, y=np.exp(a0 + a1 * t)))
  
      result = exponential_coefficient_effect(
          df, treatment_column="t", outcome_column="y"
      )
      assert round(result, 3) == a1
  
file_path: fklearn/tests/causal/test_effects.py
imports: import pandas
  import numpy
  from fklearn.causal.effects import linear_effect, spearman_effect, pearson_effect, exponential_coefficient_effect, logistic_coefficient_effect
label_desc: Use image node_id 4 for calling a global function with example usage: test_exponential_coefficient_effect() without return types