Failed
gpkit.tests.from_paths.TestFiles.test_gpkitmodels_GP_aircraft_wing_wing_test_py_mosek_cli (from gpkit.tests.from_paths.TestFiles-20190901125953)
Failing for the past 1 build
(Since Failed
)
Error Message
'str' object is not callable
Stacktrace
Traceback (most recent call last): File "/Users/jenkins/workspace/gplibrary_Push_Models/mosek/gpkit/gpkit/tests/helpers.py", line 64, in test testfn(name, import_dict, path)(self) File "/Users/jenkins/workspace/gplibrary_Push_Models/mosek/gpkit/gpkit/tests/from_paths.py", line 51, in <lambda> lambda self: getattr(self, name)())) # pylint:disable=undefined-variable File "/Users/jenkins/workspace/gplibrary_Push_Models/mosek/gpkit/gpkit/tests/from_paths.py", line 37, in test_fn mod = __import__(os.path.basename(path)[:-3]) File "wing_test.py", line 2, in <module> File "/Users/jenkins/workspace/gplibrary_Push_Models/mosek/venv2_gpkit/lib/python2.7/site-packages/gpkitmodels/GP/aircraft/wing/wing.py", line 7, in <module> from .wing_core import WingCore File "/Users/jenkins/workspace/gplibrary_Push_Models/mosek/venv2_gpkit/lib/python2.7/site-packages/gpkitmodels/GP/aircraft/wing/wing_core.py", line 3, in <module> from gpkitmodels.GP.materials import foamhd File "/Users/jenkins/workspace/gplibrary_Push_Models/mosek/venv2_gpkit/lib/python2.7/site-packages/gpkitmodels/GP/materials/__init__.py", line 1, in <module> from composite import CFRPFabric, CFRPUD, Kevlar File "/Users/jenkins/workspace/gplibrary_Push_Models/mosek/venv2_gpkit/lib/python2.7/site-packages/gpkitmodels/GP/materials/composite.py", line 3, in <module> class CFRPFabric(Model): File "/Users/jenkins/workspace/gplibrary_Push_Models/mosek/venv2_gpkit/lib/python2.7/site-packages/gpkitmodels/GP/materials/composite.py", line 22, in CFRPFabric @parse_variables(__doc__, globals()) TypeError: 'str' object is not callable
Standard Output
SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (3.4e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (4.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (4.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (3.4e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (4.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (4.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again. Beginning signomial solve. Using solver 'mosek' Solving for 20 variables. Solving took 0.0118 seconds. Using solver 'mosek' Solving for 20 variables. Solving took 0.0119 seconds. Using solver 'mosek' Solving for 20 variables. Solving took 0.00928 seconds. Using solver 'mosek' Solving for 20 variables. Solving took 0.012 seconds. Solving took 4 GP solves and 0.0507 seconds. Beginning signomial solve. Using solver 'mosek_cli' Solving for 20 variables. Solving took 0.232 seconds. Using solver 'mosek_cli' Solving for 20 variables. Solving took 0.238 seconds. Using solver 'mosek_cli' Solving for 20 variables. Solving took 0.228 seconds. Using solver 'mosek_cli' Solving for 20 variables. Solving took 0.374 seconds. Solving took 4 GP solves and 1.08 seconds.