code: def test_predict_nondataframe():
      df = pd.DataFrame(
          [[3, 0.030], [10, 0.060], [20, 0.120]],
          columns=["BSA", "Absorbance"],
      )
  
      model = ols("Absorbance ~ BSA", data=df)
      fit = model.fit()
      error = patsy.PatsyError
      with pytest.raises(error):
          fit.predict([0.25])
  
imports: from statsmodels.compat.pandas import assert_series_equal
  from io import StringIO
  import warnings
  import numpy
  import numpy.testing
  import pandas
  import patsy
  import pytest
  from statsmodels.datasets import cpunish
  from statsmodels.datasets.longley import load, load_pandas
  from statsmodels.formula.api import ols
  from statsmodels.formula.formulatools import make_hypotheses_matrices
  from statsmodels.tools import add_constant
  from statsmodels.tools.testing import assert_equal
label_desc: Use image node_id 7 for calling a global function with example usage: test_predict_nondataframe() without return types