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gpkit.tests.from_paths.TestFiles.test_solar_sens_chart_py_mosek_conif (from gpkit.tests.from_paths.TestFiles-20210425161546)

Failing for the past 1 build (Since Failed #484 )
Took 2.1 sec.

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/sens_chart.py", line 97, in test
    result = model.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)