code: def test_predict_offset(self):
      res = self.res
      data = self.data
  
      fitted = res.fittedvalues.iloc[1:10:2]
      offset = np.arange(len(fitted))
      fitted = fitted + offset
  
      pred = res.predict(data.iloc[1:10:2], offset=offset)
      pdt.assert_index_equal(pred.index, fitted.index)
      assert_allclose(pred.values, fitted.values, rtol=1e-13)
  
      # plain dict
      xd = dict(zip(data.columns, data.iloc[1:10:2].values.T))
      pred = res.predict(xd, offset=offset)
      assert_equal(pred.index, np.arange(len(pred)))
      assert_allclose(pred.values, fitted.values, rtol=1e-13)
  
      # offset as pandas.Series
      data2 = data.iloc[1:10:2].copy()
      data2["offset"] = offset
      pred = res.predict(data2, offset=data2["offset"])
      pdt.assert_index_equal(pred.index, fitted.index)
      assert_allclose(pred.values, fitted.values, rtol=1e-13)
  
      # check nan in exog is ok, preserves index matching offset length
      data2 = data.iloc[1:10:2].copy()
      data2["offset"] = offset
      data2.iloc[0, 1] = np.nan
      pred = res.predict(data2, offset=data2["offset"])
      pdt.assert_index_equal(pred.index, fitted.index)
      fitted_nan = fitted.copy()
      fitted_nan.iloc[0] = np.nan
      assert_allclose(pred.values, fitted_nan.values, 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 TestPredictGLM obj's underlying member method code with example usage: obj.test_predict_offset() without return types