Passed
gpkit.tests.from_paths.TestFiles.test_solar_season_py_mosek_conif (from gpkit.tests.from_paths.TestFiles-20210427182629)
Standard Output
N=1 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: 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[0,1] 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 980 free variables in 1300 posynomial inequalities. Solving took 0.686 seconds and 4 GP solves. Warning: Variable Mission.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 0.8904 but bound is 0.9465 Warning: Variable Mission.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1632919.3776 but bound is 600000.0000 Warning: Variable Mission.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1259329.5070 but bound is 1000000.0000 N=3 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: 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.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 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: skipped auto-differentiation of linked variable Mission1.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. Starting a sequence of GP solves for 97 free variables in 23 locally-GP constraints and for 1032 free variables in 1384 posynomial inequalities. Solving took 0.755 seconds and 4 GP solves. Warning: Variable Mission1.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.1135 but bound is 0.9465 Warning: Variable Mission1.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1036209.6021 but bound is 600000.0000 Warning: Variable Mission1.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1006641.3990 but bound is 1000000.0000 N=5 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 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.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 Mission2.Climb.rho[0,3] 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 1084 free variables in 1492 posynomial inequalities. Solving took 0.77 seconds and 4 GP solves. Warning: Variable Mission2.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.0043 but bound is 0.9465 Warning: Variable Mission2.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1329202.9037 but bound is 600000.0000 Warning: Variable Mission2.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1208149.0070 but bound is 1000000.0000 N=7 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.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 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 Mission3.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 115 free variables in 27 locally-GP constraints and for 1136 free variables in 1624 posynomial inequalities. Solving took 0.849 seconds and 4 GP solves. Warning: Variable Mission3.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.1643 but bound is 0.9465 Warning: Variable Mission3.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 976138.7332 but bound is 600000.0000 Warning: Variable Mission3.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1042059.9154 but bound is 1000000.0000 N=9 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: 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: 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.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 Mission4.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 124 free variables in 29 locally-GP constraints and for 1188 free variables in 1780 posynomial inequalities. Solving took 0.915 seconds and 4 GP solves. Warning: Variable Mission4.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.1567 but bound is 0.9465 Warning: Variable Mission4.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1007396.6632 but bound is 600000.0000 Warning: Variable Mission4.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1092544.5684 but bound is 1000000.0000 N=0 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: 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: 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 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. Solving took 0.759 seconds and 4 GP solves. Warning: Variable Mission5.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.0536 but bound is 0.9465 Warning: Variable Mission5.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1119116.3963 but bound is 600000.0000 N=1 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: 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[0,1] 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 980 free variables in 1300 posynomial inequalities. Solving took 1.12 seconds and 4 GP solves. Warning: Variable Mission.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 0.8904 but bound is 0.9465 Warning: Variable Mission.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1632908.2447 but bound is 600000.0000 Warning: Variable Mission.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1259324.3535 but bound is 1000000.0000 N=3 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: 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.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 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: skipped auto-differentiation of linked variable Mission1.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. Starting a sequence of GP solves for 97 free variables in 23 locally-GP constraints and for 1032 free variables in 1384 posynomial inequalities. Solving took 1.77 seconds and 6 GP solves. Warning: Variable Mission1.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.1135 but bound is 0.9465 Warning: Variable Mission1.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1036203.0676 but bound is 600000.0000 Warning: Variable Mission1.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1006643.9407 but bound is 1000000.0000 N=5 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 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.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 Mission2.Climb.rho[0,3] 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 1084 free variables in 1492 posynomial inequalities. Solving took 1.95 seconds and 8 GP solves. Warning: Variable Mission2.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.0043 but bound is 0.9465 Warning: Variable Mission2.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1329205.7762 but bound is 600000.0000 Warning: Variable Mission2.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1208151.7377 but bound is 1000000.0000 N=7 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.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 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 Mission3.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 115 free variables in 27 locally-GP constraints and for 1136 free variables in 1624 posynomial inequalities. Solving took 0.964 seconds and 4 GP solves. Warning: Variable Mission3.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.1643 but bound is 0.9465 Warning: Variable Mission3.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 976141.3865 but bound is 600000.0000 Warning: Variable Mission3.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1042058.8711 but bound is 1000000.0000 N=9 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: 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: 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.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 Mission4.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 124 free variables in 29 locally-GP constraints and for 1188 free variables in 1780 posynomial inequalities. Solving took 1.52 seconds and 4 GP solves. Warning: Variable Mission4.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.1567 but bound is 0.9465 Warning: Variable Mission4.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1007400.0344 but bound is 600000.0000 Warning: Variable Mission4.Climb.AircraftDrag.TailAero1.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1092545.0391 but bound is 1000000.0000 N=0 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: 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: 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 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. Solving took 1.03 seconds and 4 GP solves. Warning: Variable Mission5.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.0536 but bound is 0.9465 Warning: Variable Mission5.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1119112.5767 but bound is 600000.0000 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: 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.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[0,1] 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_cli' for 7672 free variables in 10814 posynomial inequalities. Solving took 1.68 seconds. Warning: Variable Mission.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.2008 but bound is 0.9465 Warning: Variable Mission.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 839120.8369 but bound is 600000.0000 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: 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.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[0,1] 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 3.01 seconds. Warning: Variable Mission.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.2008 but bound is 0.9465 Warning: Variable Mission.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 839124.1476 but bound is 600000.0000 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: 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[0,1] 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. Solving took 0.772 seconds and 4 GP solves. Warning: Variable Mission.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.0536 but bound is 0.9465 Warning: Variable Mission.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1119116.3963 but bound is 600000.0000 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: 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.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 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: skipped auto-differentiation of linked variable Mission1.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. Starting a sequence of GP solves for 85 free variables in 21 locally-GP constraints and for 954 free variables in 1269 posynomial inequalities. Solving took 1.21 seconds and 4 GP solves. Warning: Variable Mission1.Climb.AircraftDrag.WingAero.CL[:] could cause inaccurate result because it is below lower bound. Solution is 1.0536 but bound is 0.9465 Warning: Variable Mission1.Climb.AircraftDrag.WingAero.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1119114.5188 but bound is 600000.0000
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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/gpkit/constraints/sgp.py:178: UserWarning: SGP not convergent: Cost rose by 0.00026% on GP solve 4. Details can be found in `m.program.results` or by solving at a higher verbosity. Note that convergence is not guaranteed for models with SignomialEqualities. % (100*(cost - prevcost)/prevcost, len(self.gps))) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/gpkit/constraints/sgp.py:178: UserWarning: SGP not convergent: Cost rose by 0.0011% on GP solve 4. Details can be found in `m.program.results` or by solving at a higher verbosity. Note that convergence is not guaranteed for models with SignomialEqualities. % (100*(cost - prevcost)/prevcost, len(self.gps))) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/gpkit/constraints/sgp.py:178: UserWarning: SGP not convergent: Cost rose by 0.00037% on GP solve 6. Details can be found in `m.program.results` or by solving at a higher verbosity. Note that convergence is not guaranteed for models with SignomialEqualities. % (100*(cost - prevcost)/prevcost, len(self.gps))) /Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs) /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/numpy/core/_asarray.py:171: 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_gpkit_PR_research_models/buildnode/macys_VM/optimizer/mosek/venv2_gpkit/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return ufunc.reduce(obj, axis, dtype, out, **passkwargs)