code: def test_alignment():
      y, X, treatment, tau, b, e = synthetic_data(
          mode=1, n=100000, p=NUM_FEATURES, sigma=1.0
      )
      alpha = np.quantile(y, 0.25)
      adj = alignment(alpha, e, treatment)
  
      assert y.shape == adj.shape
  
file_path: causalml/tests/test_sensitivity.py
imports: import pandas
  import numpy
  from sklearn.linear_model import LinearRegression
  from causalml.dataset import synthetic_data
  from causalml.inference.meta import BaseXLearner
  from causalml.metrics.sensitivity import Sensitivity
  from causalml.metrics.sensitivity import SensitivityPlaceboTreatment, SensitivityRandomCause
  from causalml.metrics.sensitivity import SensitivityRandomReplace, SensitivitySelectionBias
  from causalml.metrics.sensitivity import one_sided, alignment, one_sided_att, alignment_att
  from .const import TREATMENT_COL, SCORE_COL, OUTCOME_COL, NUM_FEATURES
label_desc: Use image node_id 7 for calling a global function with example usage: test_alignment() without return types