code: def test_partial_dependence_display_kind_centered_interaction(
      pyplot,
      kind,
      clf_diabetes,
      diabetes,
  ):
      """Check that we properly center ICE and PD when passing kind as a string and as a
      list."""
      disp = PartialDependenceDisplay.from_estimator(
          clf_diabetes,
          diabetes.data,
          [0, 1],
          kind=kind,
          centered=True,
          subsample=5,
      )
  
      assert all(
          [
              ln._y[0] == 0.0
              for ln in disp.lines_.ravel()
              if ln is not None
          ]
      )
  
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose
  from scipy.stats.mstats import mquantiles
  from sklearn.compose import make_column_transformer
  from sklearn.datasets import load_diabetes, load_iris, make_classification, make_regression
  from sklearn.ensemble import GradientBoostingClassifier, GradientBoostingRegressor
  from sklearn.inspection import PartialDependenceDisplay
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import OneHotEncoder
  from sklearn.utils._testing import _convert_container
label_desc: Use image node_id 28 for calling a global function with example usage: test_partial_dependence_display_kind_centered_interaction(pyplot, kind, clf_diabetes, diabetes) without return types