Failed
gpkit.tests.from_paths.TestFiles.test_solar_season_py_mosek_cli (from gpkit.tests.from_paths.TestFiles-20210414170406)
Failing for the past 1 build
(Since Failed
)
Error Message
Aircraft.Wing.Planform.eta[:]
Stacktrace
Traceback (most recent call last): File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\helpers.py", line 55, in test testfn(name, import_dict, path)(self) File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\from_paths.py", line 48, in <lambda> lambda self: getattr(self, name)())) # pylint:disable=undefined-variable File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\from_paths.py", line 37, in test_fn mod.test() File "C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\solar\solar\season.py", line 60, in test _ = season(lats=[20], days=[355]) File "C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\solar\solar\season.py", line 24, in season sol = M.solve() File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\prog_factories.py", line 132, in solvefn result = progsolve(solver, verbosity=verbosity, **solveargs) File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\gp.py", line 238, in solve return self.model.debug(solver=solver) File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\model.py", line 179, in debug feas = Model(tants.relaxvars.prod()**30 * self.cost, tants) File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\model.py", line 70, in __init__ CostedConstraintSet.__init__(self, cost, constraints, substitutions) File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\costed.py", line 26, in __init__ ConstraintSet.__init__(self, constraints, subs, bonusvks=self.cost.vks) File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\set.py", line 102, in __init__ if np.isnan(self.substitutions[key.veckey][key.idx]): File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\keydict.py", line 176, in __getitem__ raise KeyError(key) KeyError: Aircraft.Wing.Planform.eta[:]
Standard Output
Warning: linked function for Mission.Climb.dh did not return a united value. Modifying it to do so (e.g. by using `()` instead of `[]` to access variables) would reduce the risk of errors. Warning: skipped auto-differentiation of linked variable Mission.Climb.rho[0,0] because ValueError('The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()') was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Using solver 'mosek_cli' for 7672 free variables in 10814 posynomial inequalities. Solving took 0.74 seconds. Solver failed for an unknown reason. Relaxing constraints/constants, bounding variables, or using a different solver might fix it. Since the model solved in less than a second, let's run `.debug()` to analyze what happened. `
Standard Error
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages\gpfit\fit_constraintset.py:46: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray. for k in range(fitdata["K"])] C:\Anaconda3\lib\site-packages\numpy\core\_asarray.py:102: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray. return array(a, dtype, copy=False, order=order) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages\gassolar\environment\solar_irradiance.py:40: RuntimeWarning: overflow encountered in exp tau = np.exp(-0.175/costhsun) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages\pint\quantity.py:1377: UnitStrippedWarning: The unit of the quantity is stripped. warnings.warn("The unit of the quantity is stripped.", UnitStrippedWarning) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages\pint\quantity.py:1377: UnitStrippedWarning: The unit of the quantity is stripped. warnings.warn("The unit of the quantity is stripped.", UnitStrippedWarning)