Passed

gpkit.tests.from_paths.TestFiles.test_gpkitmodels_GP_aircraft_motor_motor_test_py_cvxopt (from gpkit.tests.from_paths.TestFiles-20210629210708)

Standard Output

Using solver 'cvxopt'
 for 11 free variables
  in 14 posynomial inequalities.
Solving took 0.0407 seconds.
Using solver 'cvxopt'
 for 9 free variables
  in 15 posynomial inequalities.
Solving took 0.0089 seconds.
Using solver 'cvxopt'
 for 25 free variables
  in 35 posynomial inequalities.
Solving took 0.0162 seconds.
Using solver 'cvxopt'
 for 25 free variables
  in 35 posynomial inequalities.
Solving took 0.0173 seconds.
Starting a sequence of GP solves
 for 53 free variables
  in 11 locally-
...[truncated 2183 chars]...
econds.
Solved cost was 5717.

GP Solve 2
Using solver 'cvxopt'
 for 21 free variables
  in 22 posynomial inequalities.
Solving took 0.0132 seconds.
Solved cost was 4538.

GP Solve 3
Using solver 'cvxopt'
 for 21 free variables
  in 22 posynomial inequalities.
Solving took 0.0131 seconds.
Solved cost was 4536.

GP Solve 4
Using solver 'cvxopt'
 for 21 free variables
  in 22 posynomial inequalities.
Solving took 0.0128 seconds.
Solved cost was 4536.

Solving took 0.0569 seconds and 4 GP solves.
	

Standard Error

/jenkins/workspace/CE_gplibrary_Push_research_models/cvxopt/venv2_gpkit/lib/python3.5/site-packages/pint/quantity.py:1377: UnitStrippedWarning: The unit of the quantity is stripped.
  warnings.warn("The unit of the quantity is stripped.", UnitStrippedWarning)
/jenkins/workspace/CE_gplibrary_Push_research_models/cvxopt/venv2_gpkit/lib/python3.5/site-packages/pint/quantity.py:1377: UnitStrippedWarning: The unit of the quantity is stripped.
  warnings.warn("The unit of the quantity is stripped.", 
...[truncated 3047 chars]...
ty is stripped.
  warnings.warn("The unit of the quantity is stripped.", UnitStrippedWarning)
/jenkins/workspace/CE_gplibrary_Push_research_models/cvxopt/gpkit/gpkit/constraints/sgp.py:179: UserWarning: SGP not convergent: Cost rose by 6.1% (1588.62 to 1685.18) on GP solve 2. Details can be found in `m.program.results` or by solving at a higher verbosity. Note convergence is not guaranteed for models with SignomialEqualities.
  % (100*(cost - prevcost)/prevcost, prevcost, cost, len(self.gps)))