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Passed
gpkit.tests.from_paths.TestFiles.test_model_jho_py_mosek_conif (from gpkit.tests.from_paths.TestFiles-20200710203322)
Standard Output
Warning: skipped auto-differentiation of linked variable Mission.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 Mission.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.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. Starting a sequence of GP solves for 8 free variables in 6 locally-GP constraints and for 847 free variables in 2010 posynomial inequalities. Solving took 0.976 seconds and 4 GP solves. Warning: skipped auto-differentiation of linked variable Mission.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 Mission.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.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. Starting a sequence of GP solves for 8 free variables in 6 locally-GP constraints and for 847 free variables in 2010 posynomial inequalities. Solving took 1.05 seconds and 4 GP solves.
Standard Error
<string>:6: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. /Users/jenkins/workspace/CE_gplibrary_Push_research_models/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_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:83: 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_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/prog_factories.py:32: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. array_calulated[v.veckey] = np.array(ofn(kdc)) /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:136: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order, subok=True) /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:136: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order, subok=True) /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:136: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order, subok=True) /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:136: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order, subok=True) <string>:6: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. /Users/jenkins/workspace/CE_gplibrary_Push_research_models/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_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:83: 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_gplibrary_Push_research_models/mosek/gpkit/gpkit/constraints/prog_factories.py:32: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. array_calulated[v.veckey] = np.array(ofn(kdc)) /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:136: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order, subok=True) /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:136: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order, subok=True) /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:136: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order, subok=True) /Users/jenkins/workspace/CE_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:136: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order, subok=True) <string>:6: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. /Users/jenkins/workspace/CE_gplibrary_Push_research_models/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_gplibrary_Push_research_models/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:83: 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)