code: def test_nopatsy(self):
      res = self.res
      data = self.data
      fitted = res.fittedvalues.iloc[1:10:2]
  
      # plain numpy array
      pred = res.predict(res.model.exog[1:10:2], transform=False)
      assert_allclose(pred, fitted.values, rtol=1e-13)
  
      # pandas DataFrame
      x = pd.DataFrame(
          res.model.exog[1:10:2],
          index=data.index[1:10:2],
          columns=res.model.exog_names,
      )
      pred = res.predict(x)
      pdt.assert_index_equal(pred.index, fitted.index)
      assert_allclose(pred.values, fitted.values, rtol=1e-13)
  
      # one observation - 1-D
      pred = res.predict(res.model.exog[1], transform=False)
      assert_allclose(pred, fitted.values[0], rtol=1e-13)
  
      # one observation - pd.Series
      pred = res.predict(x.iloc[0])
      pdt.assert_index_equal(pred.index, fitted.index[:1])
      assert_allclose(pred.values[0], fitted.values[0], rtol=1e-13)
  
file_path: statsmodels/statsmodels/base/tests/test_predict.py
imports: from statsmodels.compat.pandas import testing
  import numpy
  import pandas
  from numpy.testing import assert_allclose, assert_equal
  from statsmodels.regression.linear_model import OLS
  from statsmodels.genmod.generalized_linear_model import GLM
label_desc: Use image node_id 3 for calling the CheckPredictReturns obj's underlying member method code with example usage: obj.test_nopatsy() without return types