Passed

gpkit.tests.from_paths.TestFiles.test_gpkitmodels_GP_aircraft_tail_tail_tests_py_mosek (from gpkit.tests.from_paths.TestFiles-20190901164038)

Took 0.72 sec.

Standard Output

Using solver 'mosek'
Solving for 11 variables.
Solving took 0.03 seconds.
Using solver 'mosek_cli'
Solving for 11 variables.
Solving took 0.092 seconds.
Using solver 'mosek'
Solving for 9 variables.
Solving took 0.018 seconds.
Using solver 'mosek'
Solving for 25 variables.
Solving took 0.019 seconds.
Using solver 'mosek'
Solving for 25 variables.
Solving took 0.019 seconds.
Beginning signomial solve.
Solving took 16 GP solves and 0.894 seconds.
Using solver 'mosek_cli'
Solving for 9 variables.
Solving took 0.066 seconds.
Using solver 'mosek_cli'
Solving for 25 variables.
Solving took 0.075 seconds.
Using solver 'mosek_cli'
Solving for 25 variables.
Solving took 0.118 seconds.
Beginning signomial solve.
Solving took 16 GP solves and 2.74 seconds.
Using solver 'mosek'
Solving for 13 variables.
Solving took 0.034 seconds.
Beginning signomial solve.
Solving took 11 GP solves and 0.695 seconds.
Warning: Variable BladeElementProp.BladeElementPerf.cl[:] could cause inaccurate result because it is below lower bound. Solution is 0.6000 but bound is 0.4742
Warning: Variable BladeElementProp.BladeElementPerf.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1619897.9369 but bound is 700000.0000
Using solver 'mosek_cli'
Solving for 13 variables.
Solving took 0.069 seconds.
Beginning signomial solve.
Solving took 11 GP solves and 1.81 seconds.
Warning: Variable BladeElementProp.BladeElementPerf.cl[:] could cause inaccurate result because it is below lower bound. Solution is 0.6000 but bound is 0.4742
Warning: Variable BladeElementProp.BladeElementPerf.Re[:] could cause inaccurate result because it is above upper bound. Solution is 1619891.9379 but bound is 700000.0000
Warning: Variable TailAero.Re could cause inaccurate result because it is above upper bound. Solution is 2220953.3838 but bound is 1000000.0000
Warning: Variable TailAero1.Re could cause inaccurate result because it is above upper bound. Solution is 2499787.9776 but bound is 1000000.0000
Warning: Variable TailAero2.Re could cause inaccurate result because it is above upper bound. Solution is 2223878.3883 but bound is 1000000.0000
Warning: Variable TailAero3.Re could cause inaccurate result because it is above upper bound. Solution is 2223877.9590 but bound is 1000000.0000
Warning: Variable TailAero4.Re could cause inaccurate result because it is above upper bound. Solution is 1853897.1004 but bound is 1000000.0000
Warning: Variable TailAero5.Re could cause inaccurate result because it is above upper bound. Solution is 1853897.1004 but bound is 1000000.0000
Warning: Variable TailAero.Re could cause inaccurate result because it is above upper bound. Solution is 2220959.7939 but bound is 1000000.0000
Warning: Variable TailAero1.Re could cause inaccurate result because it is above upper bound. Solution is 2499796.7837 but bound is 1000000.0000
Warning: Variable TailAero2.Re could cause inaccurate result because it is above upper bound. Solution is 1860712.4314 but bound is 1000000.0000
Warning: Variable TailAero3.Re could cause inaccurate result because it is above upper bound. Solution is 1860712.4314 but bound is 1000000.0000
Warning: Variable TailAero4.Re could cause inaccurate result because it is above upper bound. Solution is 1853896.1324 but bound is 1000000.0000
Warning: Variable TailAero5.Re could cause inaccurate result because it is above upper bound. Solution is 1853896.1324 but bound is 1000000.0000
Warning: Variable WingAero.Re could cause inaccurate result because it is above upper bound. Solution is 1884891.6332 but bound is 700000.0000
Warning: Variable WingAero1.Re could cause inaccurate result because it is above upper bound. Solution is 1910419.6195 but bound is 700000.0000
Warning: Variable WingAero.Re could cause inaccurate result because it is above upper bound. Solution is 1910412.9866 but bound is 700000.0000
Warning: Variable WingAero1.Re could cause inaccurate result because it is above upper bound. Solution is 1910412.9866 but bound is 700000.0000
SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.
SP is not converging! Last GP iteration had a higher cost (3e+03) than the previous one (2.7e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.
SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (3.4e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.
SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (4.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.
SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (4.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.
SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (3.4e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.
SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (4.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.
SP is not converging! Last GP iteration had a higher cost (4.3e+03) than the previous one (4.3e+03). Results for each iteration are in (Model).program.results. If your model contains SignomialEqualities, note that convergence is not guaranteed: try replacing any SigEqs you can and solving again.
Beginning signomial solve.
Using solver 'mosek'
Solving for 20 variables.
Solving took 0.033 seconds.
Using solver 'mosek'
Solving for 20 variables.
Solving took 0.025 seconds.
Using solver 'mosek'
Solving for 20 variables.
Solving took 0.022 seconds.
Using solver 'mosek'
Solving for 20 variables.
Solving took 0.02 seconds.
Solving took 4 GP solves and 0.107 seconds.
Beginning signomial solve.
Using solver 'mosek_cli'
Solving for 20 variables.
Solving took 0.079 seconds.
Using solver 'mosek_cli'
Solving for 20 variables.
Solving took 0.097 seconds.
Using solver 'mosek_cli'
Solving for 20 variables.
Solving took 0.08 seconds.
Using solver 'mosek_cli'
Solving for 20 variables.
Solving took 0.112 seconds.
Solving took 4 GP solves and 0.384 seconds.

Standard Error

c:\anaconda2\lib\site-packages\pint\quantity.py:1377: UnitStrippedWarning: The unit of the quantity is stripped.
  warnings.warn("The unit of the quantity is stripped.", UnitStrippedWarning)