code: def test_1d(self):
      # one observation
      res = self.res
      data = self.data
  
      pred = res.predict(data.iloc[:1])
      pdt.assert_index_equal(pred.index, data.iloc[:1].index)
      fv = np.asarray(res.fittedvalues)
      assert_allclose(pred.values, fv[0], rtol=1e-13)
  
      fittedm = res.fittedvalues.mean()
      xmean = data.mean()
      pred = res.predict(xmean.to_frame().T)
      assert_equal(pred.index, np.arange(1))
      assert_allclose(pred, fittedm, rtol=1e-13)
  
      # Series
      pred = res.predict(data.mean())
      assert_equal(pred.index, np.arange(1))
      assert_allclose(pred.values, fittedm, rtol=1e-13)
  
      # dict with scalar value (is plain dict)
      # Note: this warns about dropped nan, even though there are None -FIXED
      pred = res.predict(data.mean().to_dict())
      assert_equal(pred.index, np.arange(1))
      assert_allclose(pred.values, fittedm, 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 2 for calling the CheckPredictReturns obj's underlying member method code with example usage: obj.test_1d() without return types