code: def test_regression_summary():
      # little luck getting this test to pass (It should?), can be used for
      # visual testing of the regression.summary table
      # fixed, might fail at minute changes
      from statsmodels.regression.tests.test_regression import TestOLS
  
      # from test_regression import TestOLS
      import time
      from string import Template
  
      t = time.localtime()
      desired = Template(
          """     Summary of Regression Results
  =======================================
  | Dependent Variable:                y|
  | Model:                           OLS|
  | Method:                Least Squares|
  | Date:               $XXcurrentXdateXX|
  | Time:                       $XXtimeXXX|
  | # obs:                          16.0|
  | Df residuals:                    9.0|
  | Df model:                        6.0|
  ==============================================================================
  |                   coefficient     std. error    t-statistic          prob. |
  ------------------------------------------------------------------------------
  | x1                      15.06          84.91         0.1774         0.8631 |
  | x2                   -0.03582        0.03349        -1.0695         0.3127 |
  | x3                     -2.020         0.4884        -4.1364         0.0025 |
  | x4                     -1.033         0.2143        -4.8220         0.0009 |
  | x5                   -0.05110         0.2261        -0.2261         0.8262 |
  | x6                      1829.          455.5         4.0159         0.0030 |
  | const              -3.482e+06      8.904e+05        -3.9108         0.0036 |
  ==============================================================================
  |                          Models stats                      Residual stats  |
  ------------------------------------------------------------------------------
  | R-squared:                     0.9955   Durbin-Watson:              2.559  |
  | Adjusted R-squared:            0.9925   Omnibus:                   0.7486  |
  | F-statistic:                    330.3   Prob(Omnibus):             0.6878  |
  | Prob (F-statistic):         4.984e-10   JB:                        0.6841  |
  | Log likelihood:                -109.6   Prob(JB):                  0.7103  |
  | AIC criterion:                  233.2   Skew:                      0.4200  |
  | BIC criterion:                  238.6   Kurtosis:                   2.434  |
  ------------------------------------------------------------------------------"""
      ).substitute(
          XXcurrentXdateXX=str(time.strftime("%a, %d %b %Y", t)),
          XXtimeXXX=str(time.strftime("%H:%M:%S", t)),
      )
      desired = str(desired)
      aregression = TestOLS()
      TestOLS.setup_class()
      results = aregression.res1
      # be quiet!
      original_filters = warnings.filters[:]  # copy original
      warnings.simplefilter("ignore")
      try:
          r_summary = str(results.summary_old())
      finally:
          warnings.filters = original_filters  # restore filters
  
      ##    print('###')
      ##    print(r_summary)
      ##    print('###')
      ##    print(desired)
      ##    print('###')
      actual = r_summary
      import numpy as np
  
      actual = "\n".join(line.rstrip() for line in actual.split("\n"))
      #    print len(actual), len(desired)
      #    print repr(actual)
      #    print repr(desired)
      #    counter = 0
      #    for c1,c2 in zip(actual, desired):
      #        if not c1==c2 and counter<20:
      #            print c1,c2
      #            counter += 1
      np.testing.assert_(actual == desired)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_regression_summary() without return types