Passed

gpkit.tests.from_paths.TestFiles.test_gassolar_solar_solar_py_mosek (from gpkit.tests.from_paths.TestFiles-20180110083840)

Took 19 sec.

Standard Output

Using solver 'mosek'
Solving for 593 variables.
Solving took 0.233 seconds.
Warning: Variable P_{ref}_Mission/Aircraft/Engine**-1*P_{sl-max}_Mission/Aircraft/Engine could cause inaccurate result because it is below lower bound. Solution is 0.2090 but bound is 0.2955
Warning: Variable [P_{shaft-max}_Mission/Climb/FlightSegment/AircraftPerf/EnginePerf_(0,)**-1*P_{total}_Mission/Climb/ could cause inaccurate result because it is above upper bound. Solution is 1.0000 but bound is 0.9685
Beginning signomial solve.
Solving took 4 GP solves and 1.98 seconds.
Warning: Variable P_{ref}_Mission.1/Aircraft.1/Engine.1**-1*P_{sl-max}_Mission.1/Aircraft.1/Engine.1 could cause inaccurate result because it is below lower bound. Solution is 0.2115 but bound is 0.2955
Warning: Variable [P_{shaft-max}_Mission.1/Climb.1/FlightSegment.2/AircraftPerf.2/EnginePerf.2_(0,)**-1*P_{total}_Miss could cause inaccurate result because it is above upper bound. Solution is 1.0000 but bound is 0.9685
Using solver 'mosek'
Solving for 593 variables.
Solving took 0.19 seconds.
Warning: Variable P_{ref}_Mission/Aircraft/Engine**-1*P_{sl-max}_Mission/Aircraft/Engine could cause inaccurate result because it is below lower bound. Solution is 0.2090 but bound is 0.2955
Warning: Variable [P_{shaft-max}_Mission/Climb/FlightSegment/AircraftPerf/EnginePerf_(0,)**-1*P_{total}_Mission/Climb/ could cause inaccurate result because it is above upper bound. Solution is 1.0000 but bound is 0.9685
Beginning signomial solve.
Solving took 4 GP solves and 111 seconds.
Warning: Variable P_{ref}_Mission.1/Aircraft.1/Engine.1**-1*P_{sl-max}_Mission.1/Aircraft.1/Engine.1 could cause inaccurate result because it is below lower bound. Solution is 0.2115 but bound is 0.2955
Warning: Variable [P_{shaft-max}_Mission.1/Climb.1/FlightSegment.2/AircraftPerf.2/EnginePerf.2_(0,)**-1*P_{total}_Miss could cause inaccurate result because it is above upper bound. Solution is 1.0000 but bound is 0.9685
Using solver 'mosek'
Solving for 1206 variables.
Solving took 1.42 seconds.
Warning: Variable Re_Mission/FlightSegment/AircraftPerf/WingAero could cause inaccurate result because it is below lower bound. Solution is 97517.0234 but bound is 150000.0000
Warning: Variable Re_Mission/FlightSegment.10/AircraftPerf.10/WingAero.10 could cause inaccurate result because it is below lower bound. Solution is 97518.5695 but bound is 150000.0000
1 is a constraining latitude
2 is a constraining latitude
3 is a constraining latitude
4 is a constraining latitude
5 is a constraining latitude
6 is a constraining latitude
7 is a constraining latitude
8 is a constraining latitude
9 is a constraining latitude
10 is a constraining latitude
11 is a constraining latitude
Beginning signomial solve.
Solving took 4 GP solves and 9.95 seconds.
Warning: Variable Re_Mission.1/FlightSegment.11/AircraftPerf.11/WingAero.11 could cause inaccurate result because it is below lower bound. Solution is 98164.7670 but bound is 150000.0000
Warning: Variable Re_Mission.1/FlightSegment.21/AircraftPerf.21/WingAero.21 could cause inaccurate result because it is below lower bound. Solution is 98166.2655 but bound is 150000.0000
1 is a constraining latitude
2 is a constraining latitude
3 is a constraining latitude
4 is a constraining latitude
5 is a constraining latitude
6 is a constraining latitude
7 is a constraining latitude
8 is a constraining latitude
9 is a constraining latitude
10 is a constraining latitude
11 is a constraining latitude
Using solver 'mosek_cli'
Solving for 1206 variables.
Solving took 1.98 seconds.
Warning: Variable Re_Mission/FlightSegment/AircraftPerf/WingAero could cause inaccurate result because it is below lower bound. Solution is 97516.8049 but bound is 150000.0000
Warning: Variable Re_Mission/FlightSegment.10/AircraftPerf.10/WingAero.10 could cause inaccurate result because it is below lower bound. Solution is 97518.7552 but bound is 150000.0000
1 is a constraining latitude
2 is a constraining latitude
3 is a constraining latitude
4 is a constraining latitude
5 is a constraining latitude
6 is a constraining latitude
7 is a constraining latitude
8 is a constraining latitude
9 is a constraining latitude
10 is a constraining latitude
11 is a constraining latitude
Beginning signomial solve.
Solving took 4 GP solves and 8.86 seconds.
Warning: Variable Re_Mission.1/FlightSegment.11/AircraftPerf.11/WingAero.11 could cause inaccurate result because it is below lower bound. Solution is 98164.5077 but bound is 150000.0000
Warning: Variable Re_Mission.1/FlightSegment.21/AircraftPerf.21/WingAero.21 could cause inaccurate result because it is below lower bound. Solution is 98166.4710 but bound is 150000.0000
1 is a constraining latitude
2 is a constraining latitude
3 is a constraining latitude
4 is a constraining latitude
5 is a constraining latitude
6 is a constraining latitude
7 is a constraining latitude
8 is a constraining latitude
9 is a constraining latitude
10 is a constraining latitude
11 is a constraining latitude

Standard Error

/jenkins/workspace/gpkit_ResearchModel_gassolar_PR/buildnode/reynolds/optimizer/mosek/venv2_gpkit/local/lib/python2.7/site-packages/gassolar/environment/solar_irradiance.py:40: RuntimeWarning: overflow encountered in exp
  tau = np.exp(-0.175/costhsun)
/jenkins/workspace/gpkit_ResearchModel_gassolar_PR/buildnode/reynolds/optimizer/mosek/venv2_gpkit/local/lib/python2.7/site-packages/gpfit/ba_init.py:79: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  b[:, k] = lstsq(X[inds.nonzero()], y[inds.nonzero()])[0][:, 0]
/jenkins/workspace/gpkit_ResearchModel_gassolar_PR/buildnode/reynolds/optimizer/mosek/venv2_gpkit/local/lib/python2.7/site-packages/gpfit/levenberg_marquardt.py:139: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  step = np.linalg.lstsq(augJ, augr)[0]