code: def test_changed_only():
      # Make sure the changed_only param is correctly used when True (default)
      lr = LogisticRegression(C=99)
      expected = """LogisticRegression(C=99)"""
      assert lr.__repr__() == expected
  
      # Check with a repr that doesn't fit on a single line
      lr = LogisticRegression(
          C=99,
          class_weight=0.4,
          fit_intercept=False,
          tol=1234,
          verbose=True,
      )
      expected = """
  LogisticRegression(C=99, class_weight=0.4, fit_intercept=False, tol=1234,
                     verbose=True)"""
      expected = expected[1:]  # remove first \n
      assert lr.__repr__() == expected
  
      imputer = SimpleImputer(missing_values=0)
      expected = """SimpleImputer(missing_values=0)"""
      assert imputer.__repr__() == expected
  
      # Defaults to np.nan, trying with float('NaN')
      imputer = SimpleImputer(missing_values=float("NaN"))
      expected = """SimpleImputer()"""
      assert imputer.__repr__() == expected
  
      # make sure array parameters don't throw error (see #13583)
      repr(LogisticRegressionCV(Cs=np.array([0.1, 1])))
  
imports: import re
  from pprint import PrettyPrinter
  import numpy
  from sklearn.utils._pprint import _EstimatorPrettyPrinter
  from sklearn.linear_model import LogisticRegressionCV
  from sklearn.pipeline import make_pipeline
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.feature_selection import SelectKBest, chi2
  from sklearn import config_context
label_desc: Use image node_id 2 for calling a global function with example usage: test_changed_only() without return types