Failed

run_tests.TestSimulation_cvxopt.test_table_diff (from run_tests.TestSimulation_cvxopt-20200415154010)

Error Message

Lists differ: ['L/D[553 chars]& 1.5e-01 & 1.95e-01 & 1.96e-01 & 1.88e-01\n',[164 chars]3\n'] != ['L/D[553 chars]& 1.59e-01 & 2.44e-01 & 2.52e-01 & 2.27e-01\n'[165 chars]3\n']  First differing element 10: 'V_{f_{avail}} & 1.5e-01 & 1.95e-01 & 1.96e-01 & 1.88e-01\n' 'V_{f_{avail}} & 1.59e-01 & 2.44e-01 & 2.52e-01 & 2.27e-01\n'  Diff is 1179 characters long. Set self.maxDiff to None to see it.

Stacktrace

Traceback (most recent call last):
  File "/jenkins/workspace/CE_robust_PR/cvxopt/robust/testing/t_simulation.py", line 107, in test_table_diff
    self.assertEqual(open(origfilename, 'r').readlines(), open(filename, 'r').readlines())
AssertionError: Lists differ: ['L/D[553 chars]& 1.5e-01 & 1.95e-01 & 1.96e-01 & 1.88e-01\n',[164 chars]3\n'] != ['L/D[553 chars]& 1.59e-01 & 2.44e-01 & 2.52e-01 & 2.27e-01\n'[165 chars]3\n']

First differing element 10:
'V_{f_{avail}} & 1.5e-01 & 1.95e-01 & 1.96e-01 & 1.88e-01\n'
'V_{f_{avail}} & 1.59e-01 & 2.44e-01 & 2.52e-01 & 2.27e-01\n'

Diff is 1179 characters long. Set self.maxDiff to None to see it.
		

Standard Output

SGP not convergent: Cost rose by 9% on GP solve 2. Details can be found in `m.program.results` or by solving at a higher verbosity. Note that convergence is not guaranteed for models with SignomialEqualities.

SGP not convergent: Cost rose by 9.4% on GP solve 2. Details can be found in `m.program.results` or by solving at a higher verbosity. Note that convergence is not guaranteed for models with SignomialEqualities.

SGP not convergent: Cost rose by 0.33% on GP solve 4. Details can be found in `m.program.results` or by solving at a higher verbosity. Note that convergence is not guaranteed for models with SignomialEqualities.

SGP not convergent: Cost rose by 9% on GP solve 2. Details can be found in `m.program.results` or by solving at a higher verbosity. Note that convergence is not guaranteed for models with SignomialEqualities.

SGP not convergent: Cost rose by 9% on GP solve 2. Details can be found in `m.program.results` or by solving at a higher verbosity. Note that convergence is not guaranteed for models with SignomialEqualities.

	

Standard Error