Failed
gpkit.tests.from_paths.TestFiles.test_solar_npod_trade_py_mosek_conif (from gpkit.tests.from_paths.TestFiles-20210425161546)
Failing for the past 1 build
(Since Failed
)
Error Message
None
Stacktrace
Traceback (most recent call last): File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/tests/helpers.py", line 55, in test testfn(name, import_dict, path)(self) File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/tests/from_paths.py", line 48, in <lambda> lambda self: getattr(self, name)())) # pylint:disable=undefined-variable File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/tests/from_paths.py", line 37, in test_fn mod.test() File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/solar/solar/npod_trade.py", line 91, in test pods(Nplot=100) File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/solar/solar/npod_trade.py", line 21, in pods sol = M.localsolve() File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/constraints/prog_factories.py", line 132, in solvefn result = progsolve(solver, verbosity=verbosity, **solveargs) File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/constraints/sgp.py", line 181, in localsolve self.result = gp.generate_result(solver_out, verbosity=verbosity-3) File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/constraints/gp.py", line 263, in generate_result result = self._compile_result(solver_out) # NOTE: SIDE EFFECTS File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/constraints/gp.py", line 361, in _compile_result dlogv_dlogc = dv_dc * result["constants"][c]/val File "/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/keydict.py", line 176, in __getitem__ raise KeyError(key) KeyError: None
Standard Output
N=1 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 Aircraft.Empennage.VerticalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Aircraft.Wing.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Aircraft.Empennage.HorizontalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Mission.Climb.rho[0,4] 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 980 free variables in 1300 posynomial inequalities. N=1 Warning: skipped auto-differentiation of linked variable Aircraft1.Wing.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. 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 Aircraft1.Empennage.VerticalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Aircraft1.Empennage.HorizontalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Mission1.Climb.rho[0,2] 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 980 free variables in 1300 posynomial inequalities. Warning: skipped auto-differentiation of linked variable Aircraft2.Wing.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Aircraft2.Empennage.HorizontalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: linked function for Mission2.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 Aircraft2.Empennage.VerticalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Mission2.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 1.82 seconds. Warning: skipped auto-differentiation of linked variable Aircraft3.Wing.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Aircraft3.Empennage.HorizontalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: linked function for Mission3.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 Aircraft3.Empennage.VerticalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Mission3.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. Using solver 'mosek_conif' for 7672 free variables in 10814 posynomial inequalities. Solving took 3.08 seconds. Warning: skipped auto-differentiation of linked variable Aircraft4.Empennage.VerticalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Aircraft4.Empennage.HorizontalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: linked function for Mission4.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 Aircraft4.Wing.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Mission4.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. Warning: skipped auto-differentiation of linked variable Aircraft5.Empennage.VerticalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: linked function for Mission5.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 Aircraft5.Wing.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Aircraft5.Empennage.HorizontalTail.Planform.cbarmac because NotImplementedError("Automatic differentiation not yet supported for <class 'pint.quantity.build_quantity_class.<locals>.Quantity'> objects") was raised. Set `gpkit.settings["ad_errors_raise"] = True` to raise such Exceptions directly. Warning: skipped auto-differentiation of linked variable Mission5.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
/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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"])] /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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"])] /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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"])] /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/gassolar/environment/solar_irradiance.py:40: RuntimeWarning: overflow encountered in exp tau = np.exp(-0.175/costhsun) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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"])] /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/gassolar/environment/solar_irradiance.py:40: RuntimeWarning: overflow encountered in exp tau = np.exp(-0.175/costhsun) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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"])] /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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"])] /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/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)