Failed
gpkit.tests.from_paths.TestFiles.test_gpkitmodels_GP_aircraft_prop_prop_test_py_mosek_conif (from gpkit.tests.from_paths.TestFiles-20210802120742)
Failing for the past 1 build
(Since Failed
)
Error Message
No module named 'gpfit.fit_constraintset'
Stacktrace
Traceback (most recent call last): File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/tests/helpers.py", line 55, in test testfn(name, import_dict, path)(self) File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/tests/from_paths.py", line 48, in <lambda> lambda self: getattr(self, name)())) # pylint:disable=undefined-variable File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/tests/from_paths.py", line 34, in test_fn mod = __import__(os.path.basename(path)[:-3]) File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gplibrary/gpkitmodels/GP/aircraft/prop/prop_test.py", line 2, in <module> from gpkitmodels.GP.aircraft.prop.propeller import Propeller, ActuatorProp File "/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.9/site-packages/gpkitmodels/GP/aircraft/prop/propeller.py", line 5, in <module> from gpfit.fit_constraintset import XfoilFit ModuleNotFoundError: No module named 'gpfit.fit_constraintset'
Standard Output
Starting a sequence of GP solves for 4 free variables in 1 locally-GP constraints and for 21 free variables in 22 posynomial inequalities. GP Solve 1 Using solver 'mosek_cli' for 21 free variables in 22 posynomial inequalities. Solving took 0.0327 seconds. Solved cost was 5717. GP Solve 2 Using solver 'mosek_cli' for 21 free variables in 22 posynomial inequalities. Solving took 0.0278 seconds. Solved cost was 4538. GP Solve 3 Using solver 'mosek_cli' for 21 free variables in 22 posynomial inequalities. Solving took 0.0275 seconds. Solved cost was 4536. GP Solve 4 Using solver 'mosek_cli' for 21 free variables in 22 posynomial inequalities. Solving took 0.0309 seconds. Solved cost was 4536. Solving took 0.125 seconds and 4 GP solves. Starting a sequence of GP solves for 4 free variables in 1 locally-GP constraints and for 21 free variables in 22 posynomial inequalities. GP Solve 1 Using solver 'mosek_conif' for 21 free variables in 22 posynomial inequalities. Solving took 0.0132 seconds. Solved cost was 5717. GP Solve 2 Using solver 'mosek_conif' for 21 free variables in 22 posynomial inequalities. Solving took 0.0112 seconds. Solved cost was 4538. GP Solve 3 Using solver 'mosek_conif' for 21 free variables in 22 posynomial inequalities. Solving took 0.0112 seconds. Solved cost was 4536. GP Solve 4 Using solver 'mosek_conif' for 21 free variables in 22 posynomial inequalities. Solving took 0.0111 seconds. Solved cost was 4536. Solving took 0.0498 seconds and 4 GP solves.
Standard Error
/Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py:174: UserWarning: SGP not convergent: Cost rose by 6.1% (1588.61 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. pywarnings.warn( /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py:174: UserWarning: SGP not convergent: Cost rose by 6.1% (1588.61 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. pywarnings.warn( /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py:174: UserWarning: SGP not convergent: Cost rose by 25% (3053.31 to 3816.14) 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. pywarnings.warn( /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/sgp.py:174: UserWarning: SGP not convergent: Cost rose by 0.32% (3808.98 to 3821.21) on GP solve 4. Details can be found in `m.program.results` or by solving at a higher verbosity. Note convergence is not guaranteed for models with SignomialEqualities. pywarnings.warn(