code: def check_ttest_tvalues(results):
      # test that t_test has same results a params, bse, tvalues, ...
      res = results
      mat = np.eye(len(res.params))
      tt = res.t_test(mat)
  
      assert_allclose(tt.effect, res.params, rtol=1e-12)
      # TODO: tt.sd and tt.tvalue are 2d also for single regressor, squeeze
      assert_allclose(np.squeeze(tt.sd), res.bse, rtol=1e-10)
      assert_allclose(np.squeeze(tt.tvalue), res.tvalues, rtol=1e-12)
      assert_allclose(tt.pvalue, res.pvalues, rtol=5e-10)
      assert_allclose(tt.conf_int(), res.conf_int(), rtol=1e-10)
  
      # test params table frame returned by t_test
      table_res = np.column_stack(
          (
              res.params,
              res.bse,
              res.tvalues,
              res.pvalues,
              res.conf_int(),
          )
      )
      table2 = tt.summary_frame().values
      assert_allclose(table2, table_res, rtol=1e-12)
  
      # TODO: move this to test_attributes ?
      assert_(hasattr(res, "use_t"))
  
      tt = res.t_test(mat[0])
      tt.summary()  # smoke test for #1323
      pvalues = np.asarray(res.pvalues)
      assert_allclose(tt.pvalue, pvalues[0], rtol=5e-10)
  
file_path: statsmodels/statsmodels/tools/_testing.py
imports: import os
  import sys
  from packaging.version import Version, parse
  import numpy
  from numpy.testing import assert_allclose, assert_
  import pandas
label_desc: Use image node_id 1 for calling a global function with example usage: check_ttest_tvalues(results) without return types