code: def test_weighted_percentile_zero_weight():
      y = np.empty(102, dtype=np.float64)
      y.fill(1.0)
      sw = np.ones(102, dtype=np.float64)
      sw.fill(0.0)
      score = _weighted_percentile(y, sw, 50)
      assert approx(score) == 1.0
  
file_path: scikit-learn/sklearn/utils/tests/test_stats.py
imports: import numpy
  from numpy.testing import assert_allclose
  from pytest import approx
  from sklearn.utils.stats import _weighted_percentile
label_desc: Use image node_id 3 for calling a global function with example usage: test_weighted_percentile_zero_weight() without return types