Failed
gpkit.tests.from_paths.TestFiles.test_solar_sens_chart_py_mosek_cli (from gpkit.tests.from_paths.TestFiles-20210414170406)
Failing for the past 1 build
(Since Failed
)
Error Message
Solver failed for an unknown reason. Relaxing constraints/constants, bounding variables, or using a different solver might fix it. Running `.debug()` or increasing verbosity may pinpoint the trouble.
Stacktrace
Traceback (most recent call last): File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\solvers\mosek_cli.py", line 87, in optimize solution_filename]).split(b"\n"): File "C:\Anaconda3\Lib\subprocess.py", line 411, in check_output **kwargs).stdout File "C:\Anaconda3\Lib\subprocess.py", line 512, in run output=stdout, stderr=stderr) subprocess.CalledProcessError: Command '['mskexpopt', 'C:\\Users\\jenkins\\AppData\\Local\\Temp\\tmpwfy29brx\\gpkit_mosek', '-sol', 'C:\\Users\\jenkins\\AppData\\Local\\Temp\\tmpwfy29brx\\gpkit_mosek.sol']' returned non-zero exit status 1001. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\gp.py", line 205, in solve k=self.k, p_idxs=self.p_idxs, **solverargs) File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\solvers\mosek_cli.py", line 95, in optimize raise UnknownInfeasible() from e gpkit.exceptions.UnknownInfeasible The above exception was the direct cause of the following exception: 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\sens_chart.py", line 97, in test result = model.localsolve() 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\sgp.py", line 159, in localsolve gen_result=False, **solveargs) File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\gp.py", line 242, in solve raise infeasibility.__class__(msg) from infeasibility gpkit.exceptions.UnknownInfeasible: Solver failed for an unknown reason. Relaxing constraints/constants, bounding variables, or using a different solver might fix it. Running `.debug()` or increasing verbosity may pinpoint the trouble.
Standard Output
Warning: linked function for Mission1.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 Mission1.Climb.rho[0,1] 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. Starting a sequence of GP solves for 85 free variables in 21 locally-GP constraints and for 954 free variables in 1269 posynomial inequalities.
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\pint\quantity.py:1377: UnitStrippedWarning: The unit of the quantity is stripped. warnings.warn("The unit of the quantity is stripped.", UnitStrippedWarning)