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> C:\Program Files\Git\cmd\git show-ref --tags -d # timeout=10
JENKINS-19022: warning: possible memory leak due to Git plugin usage; see: https://wiki.jenkins.io/display/JENKINS/Remove+Git+Plugin+BuildsByBranch+BuildData
Checking out Revision c75ab52bc2ed37746fbdde8ca3ee46872bacb6fe (origin/pr/1505/merge, origin/master)
> C:\Program Files\Git\cmd\git config core.sparsecheckout # timeout=10
> C:\Program Files\Git\cmd\git checkout -f c75ab52bc2ed37746fbdde8ca3ee46872bacb6fe # timeout=3
Commit message: "Merge f2a528ca0c0119e575425b9f3107f2bee6205d44 into f0dd8c91a29f337ee02188654d47aeea0ef11548"
Using 'Changelog to branch' strategy.
Run condition [Execution node ] enabling prebuild for step [Execute shell]
Run condition [Execution node ] enabling prebuild for step [Execute Windows batch command]
[description-setter] Description set: <a title="coverage" href="https://github.com/convexengineering/gpkit/pull/1505">PR 1505</a>: coverage
[Execution node] check if [windows10x64] is in [[macys, macys_VM, reynolds, reynolds-ubuntu16]]
Run condition [Execution node ] preventing perform for step [Execute shell]
[Execution node] check if [windows10x64] is in [[windows10x64, windows7x64]]
Run condition [Execution node ] enabling perform for step [Execute Windows batch command]
[mosek] $ cmd /c call C:\Users\jenkins\AppData\Local\Temp\jenkins4343674364562872875.bat
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>set PATH=C:\Anaconda3;C:\Anaconda3\Scripts;C:\Anaconda3\Library\bin;C:\Program Files (x86)\Common Files\Oracle\Java\javapath;C:\ProgramData\Oracle\Java\javapath;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\WINDOWS\System32\WindowsPowerShell\v1.0\;C:\Program Files\Mosek\8\tools\platform\win64x86\bin;C:\Program Files (x86)\Intel\Compiler\Fortran\9.1\EM64T\Bin;C:\WINDOWS\System32\OpenSSH\;C:\Program Files\Git\bin;C:\Program Files\TortoiseSVN\bin;C:\Program Files\Mosek\9.1\tools\platform\win64x86\bin;C:\Anaconda2;C:\Anaconda2\Scripts;C:\Anaconda2\Library\bin;C:\Users\jenkins\AppData\Local\Microsoft\WindowsApps;C:\Users\jenkins\AppData\Local\Programs\Python\Python38;C:\Users\jenkins\AppData\Local\Programs\Python\Python38\Scripts;%USERPROFILE%\AppData\Local\Microsoft\WindowsApps
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>echo C:\Anaconda3;C:\Anaconda3\Scripts;C:\Anaconda3\Library\bin;C:\Program Files (x86)\Common Files\Oracle\Java\javapath;C:\ProgramData\Oracle\Java\javapath;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\WINDOWS\System32\WindowsPowerShell\v1.0\;C:\Program Files\Mosek\8\tools\platform\win64x86\bin;C:\Program Files (x86)\Intel\Compiler\Fortran\9.1\EM64T\Bin;C:\WINDOWS\System32\OpenSSH\;C:\Program Files\Git\bin;C:\Program Files\TortoiseSVN\bin;C:\Program Files\Mosek\9.1\tools\platform\win64x86\bin;C:\Anaconda2;C:\Anaconda2\Scripts;C:\Anaconda2\Library\bin;C:\Users\jenkins\AppData\Local\Microsoft\WindowsApps;C:\Users\jenkins\AppData\Local\Programs\Python\Python38;C:\Users\jenkins\AppData\Local\Programs\Python\Python38\Scripts;%USERPROFILE%\AppData\Local\Microsoft\WindowsApps
C:\Anaconda3;C:\Anaconda3\Scripts;C:\Anaconda3\Library\bin;C:\Program Files (x86)\Common Files\Oracle\Java\javapath;C:\ProgramData\Oracle\Java\javapath;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\WINDOWS\System32\WindowsPowerShell\v1.0\;C:\Program Files\Mosek\8\tools\platform\win64x86\bin;C:\Program Files (x86)\Intel\Compiler\Fortran\9.1\EM64T\Bin;C:\WINDOWS\System32\OpenSSH\;C:\Program Files\Git\bin;C:\Program Files\TortoiseSVN\bin;C:\Program Files\Mosek\9.1\tools\platform\win64x86\bin;C:\Anaconda2;C:\Anaconda2\Scripts;C:\Anaconda2\Library\bin;C:\Users\jenkins\AppData\Local\Microsoft\WindowsApps;C:\Users\jenkins\AppData\Local\Programs\Python\Python38;C:\Users\jenkins\AppData\Local\Programs\Python\Python38\Scripts;%USERPROFILE%\AppData\Local\Microsoft\WindowsApps
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>where python
C:\Anaconda3\python.exe
C:\Users\jenkins\AppData\Local\Microsoft\WindowsApps\python.exe
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>python --version
Python 3.7.6
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>REM Create a virtualenv to install everything into
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>SET VENV=C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>virtualenv --system-site-packages C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit
Using base prefix 'C:\\Anaconda3'
No LICENSE.txt / LICENSE found in source
New python executable in C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\Scripts\python.exe
copying C:\Anaconda3\python.exe => C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\Scripts\python.exe
Installing setuptools, pip, wheel...
done.
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>call C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\Scripts\activate.bat
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>python -m pip install --upgrade pip
Requirement already up-to-date: pip in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (20.1.1)
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install --upgrade ad
Requirement already up-to-date: ad in c:\anaconda3\lib\site-packages (1.3.2)
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install --upgrade unittest-xml-reporting
Collecting unittest-xml-reporting
Using cached unittest_xml_reporting-3.0.2-py2.py3-none-any.whl (19 kB)
Installing collected packages: unittest-xml-reporting
Successfully installed unittest-xml-reporting-3.0.2
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install --upgrade pandas
Requirement already up-to-date: pandas in c:\anaconda3\lib\site-packages (1.0.5)
Requirement already satisfied, skipping upgrade: pytz>=2017.2 in c:\anaconda3\lib\site-packages (from pandas) (2020.1)
Requirement already satisfied, skipping upgrade: python-dateutil>=2.6.1 in c:\anaconda3\lib\site-packages (from pandas) (2.8.1)
Requirement already satisfied, skipping upgrade: numpy>=1.13.3 in c:\anaconda3\lib\site-packages (from pandas) (1.19.0)
Requirement already satisfied, skipping upgrade: six>=1.5 in c:\anaconda3\lib\site-packages (from python-dateutil>=2.6.1->pandas) (1.15.0)
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install --upgrade matplotlib
Requirement already up-to-date: matplotlib in c:\anaconda3\lib\site-packages (3.2.2)
Requirement already satisfied, skipping upgrade: cycler>=0.10 in c:\anaconda3\lib\site-packages (from matplotlib) (0.10.0)
Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in c:\anaconda3\lib\site-packages (from matplotlib) (2.4.7)
Requirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in c:\anaconda3\lib\site-packages (from matplotlib) (1.2.0)
Requirement already satisfied, skipping upgrade: numpy>=1.11 in c:\anaconda3\lib\site-packages (from matplotlib) (1.19.0)
Requirement already satisfied, skipping upgrade: python-dateutil>=2.1 in c:\anaconda3\lib\site-packages (from matplotlib) (2.8.1)
Requirement already satisfied, skipping upgrade: six in c:\anaconda3\lib\site-packages (from cycler>=0.10->matplotlib) (1.15.0)
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install --upgrade coverage
Requirement already up-to-date: coverage in c:\anaconda3\lib\site-packages (5.2)
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install --upgrade numpy
Requirement already up-to-date: numpy in c:\anaconda3\lib\site-packages (1.19.0)
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install --upgrade scipy
Requirement already up-to-date: scipy in c:\anaconda3\lib\site-packages (1.5.1)
Requirement already satisfied, skipping upgrade: numpy>=1.14.5 in c:\anaconda3\lib\site-packages (from scipy) (1.19.0)
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install --upgrade pint==0.9
Collecting pint==0.9
Using cached Pint-0.9-py2.py3-none-any.whl (138 kB)
Installing collected packages: pint
Attempting uninstall: pint
Found existing installation: Pint 0.14
Not uninstalling pint at c:\anaconda3\lib\site-packages, outside environment c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit
Can't uninstall 'Pint'. No files were found to uninstall.
Successfully installed pint-0.9
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>if mosek == cvxopt (
pip install --upgrade cvxopt || exit /b 666
python -c "import cvxopt; print(cvxopt.__version__)"
set GPKITSOLVERS=cvxopt
)
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>REM for mosek9/mosek_conif
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>REM if mosek==mosek python -c "__import__('mosek').Env()"
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>if mosek == mosek (
msktestlic
set GPKITSOLVERS=mosek_cli
)
Problem
Name :
Objective sense : min
Type : LO (linear optimization problem)
Constraints : 1
Cones : 0
Scalar variables : 5000
Matrix variables : 0
Integer variables : 0
Optimizer started.
Mosek license manager: License path: C:\Users\jenkins\mosek\mosek.lic
Mosek license manager: Checkout license feature 'PTS' from flexlm.
Mosek license manager: Checkout time 0.02. r: 0 status: 0
Interior-point optimizer started.
Presolve started.
Eliminator started.
Freed constraints in eliminator : 0
Eliminator terminated.
Eliminator - tries : 1 time : 0.00
Lin. dep. - tries : 0 time : 0.00
Lin. dep. - number : 0
Presolve terminated. Time: 0.00
Interior-point optimizer terminated. Time: 0.00.
Optimizer terminated. Time: 0.03
************************************
A license was checked out correctly.
************************************
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>python -c "import scipy; print(scipy.__version__)"
1.5.1
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>python -c "import numpy; print(numpy.__version__)"
1.19.0
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>python -c "import pint; print(pint.__version__)"
0.9
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>python -c "import gpkit; print(gpkit.settings)"
No filename given.
Usage:
mskexpopt FILENAME [-primal] [-dual] [-p parameterfile]
Return code: 1052
Description: MSK_RES_ERR_FILE_OPEN [An error occurred while opening a file.]
..........................C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\keydict.py:227: 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
value = np.array([clean_value(key, v) for v in value])
.................................................................................................................................................................
----------------------------------------------------------------------
Ran 187 tests in 55.769s
OK
Found no installed solvers, beginning a build.
# Building GPkit version 1.0.0pre
# Moving to the directory from which GPkit was imported.
Attempting to find and build solvers:
# Looking for `mosek_cli`
# (A "success" is if mskexpopt complains that
# we haven't specified a file for it to open.)
# Calling 'mskexpopt'
##
### CALL BEGINS
### CALL ENDS
##
Found mosek_cli in the default PATH
# Looking for `mosek_conif`
# Trying to import mosek...
# Did not find
# mosek_conif
# Looking for `cvxopt`
# Trying to import cvxopt...
Found cvxopt in the default PYTHONPATH
Replaced found solvers (['mosek_cli', 'cvxopt']) with environment var GPKITSOLVERS (mosek_cli)
Found the following solvers: mosek_cli
# Replacing directory env
GPkit is now installed with solver(s) ['mosek_cli']
To incorporate new solvers at a later date, run `gpkit.build()`.
If any tests didn't pass, please post the output above
(starting from "Found no installed solvers, beginning a build.")
to gpkit@mit.edu or https://github.com/convexengineering/gpkit/issues/new
so we can prevent others from having these errors.
The same goes for any other bugs you encounter with GPkit:
send 'em our way, along with any interesting models, speculative features,
comments, discussions, or clarifications you feel like sharing.
Finally, we hope you find our documentation (https://gpkit.readthedocs.io/)
and engineering-design models (https://github.com/convexengineering/gplibrary/)
to be useful resources for your own applications.
Enjoy!
{'installed_solvers': ['mosek_cli'], 'default_solver': 'mosek_cli', 'just built!': True}
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>REM Install gpkit to run the documentation examples
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>pip install -e C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek || exit /b 666
Obtaining file:///C:/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/windows10x64/optimizer/mosek
Requirement already satisfied: numpy>=1.16.4 in c:\anaconda3\lib\site-packages (from gpkit==1.0.0) (1.19.0)
Requirement already satisfied: pint>=0.8.1 in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkit==1.0.0) (0.9)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from gpkit==1.0.0) (1.5.1)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit==1.0.0) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit==1.0.0) (1.2.5)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit==1.0.0) (2019.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit==1.0.0) (2019.0)
Installing collected packages: gpkit
Running setup.py develop for gpkit
Successfully installed gpkit
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>REM Show the settings file
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>type C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\env\settings
installed_solvers :
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>python -c "from gpkit.tests.test_repo import test_repos; test_repos(xmloutput=True)"
No filename given.
Usage:
mskexpopt FILENAME [-primal] [-dual] [-p parameterfile]
Return code: 1052
Description: MSK_RES_ERR_FILE_OPEN [An error occurred while opening a file.]
..........................C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\keydict.py:227: 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
value = np.array([clean_value(key, v) for v in value])
.................................................................................................................................................................Cloning into 'gplibrary'...
Obtaining file:///C:/Users/jenkins/workspace/CE_gpkit_PR_research_models/buildnode/windows10x64/optimizer/mosek/gplibrary
Installing collected packages: gpkitmodels
Running setup.py develop for gpkitmodels
Successfully installed gpkitmodels
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Collecting git+https://github.com/hoburg/turbofan.git
Cloning https://github.com/hoburg/turbofan.git to c:\users\jenkins\appdata\local\temp\pip-req-build-ya5lxod3
Running command git clone -q https://github.com/hoburg/turbofan.git 'C:\Users\jenkins\AppData\Local\Temp\pip-req-build-ya5lxod3'
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from turbofan==0.0.0.0) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from turbofan==0.0.0.0) (1.5.1)
Requirement already satisfied: pint in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from turbofan==0.0.0.0) (0.9)
Requirement already satisfied: future in c:\anaconda3\lib\site-packages (from turbofan==0.0.0.0) (0.18.2)
Building wheels for collected packages: turbofan
Building wheel for turbofan (setup.py): started
Building wheel for turbofan (setup.py): finished with status 'done'
Created wheel for turbofan: filename=turbofan-0.0.0.0-py3-none-any.whl size=44145 sha256=96c0903e2a7f57481b14aa7e855f3391a9416003ddd93dd0b4fdc862482c55be
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-pa5gps4a\wheels\5e\94\24\992cb23a6749c3bad249589806341b6bef6786d3794831a01c
Successfully built turbofan
Installing collected packages: turbofan
Successfully installed turbofan-0.0.0.0
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\spaircraft
Requirement already satisfied: turbofan in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from SPaircraft==0.0.0) (0.0.0.0)
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from SPaircraft==0.0.0) (1.0.0)
Requirement already satisfied: future in c:\anaconda3\lib\site-packages (from SPaircraft==0.0.0) (0.18.2)
Requirement already satisfied: pint in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from turbofan->SPaircraft==0.0.0) (0.9)
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from turbofan->SPaircraft==0.0.0) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from turbofan->SPaircraft==0.0.0) (1.5.1)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit->SPaircraft==0.0.0) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit->SPaircraft==0.0.0) (1.2.5)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit->SPaircraft==0.0.0) (2019.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit->SPaircraft==0.0.0) (2019.0)
Building wheels for collected packages: SPaircraft
Building wheel for SPaircraft (setup.py): started
Building wheel for SPaircraft (setup.py): finished with status 'done'
Created wheel for SPaircraft: filename=SPaircraft-0.0.0-py3-none-any.whl size=1844 sha256=181b729fa400d82a2e941866551efae15bb4675ea8f0b360c4939b683ba784df
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-dhpinxia\wheels\58\f1\65\17c31d55c70a1ddaf318b574e4f9979e5f67ac924448f94707
Successfully built SPaircraft
Installing collected packages: SPaircraft
Successfully installed SPaircraft-0.0.0
adding test for 'SPaircraft.py'
Running tests...
----------------------------------------------------------------------
.Starting a sequence of GP solves
for 317 free variables
in 136 locally-GP constraints
and for 1198 free variables
in 4705 posynomial inequalities.
GP Solve 1
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.953 seconds.
Solved cost was 3.965e+40.
GP Solve 2
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.868 seconds.
Solved cost was 4.013e+10.
GP Solve 3
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.912 seconds.
Solved cost was 3.195e+05.
GP Solve 4
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.947 seconds.
Solved cost was 2.931e+04.
GP Solve 5
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.894 seconds.
Solved cost was 2.498e+04.
GP Solve 6
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.797 seconds.
Solved cost was 2.381e+04.
GP Solve 7
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.84 seconds.
Solved cost was 2.328e+04.
GP Solve 8
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.802 seconds.
Solved cost was 2.303e+04.
Solving took 8.46 seconds and 8 GP solves.
Solves with these variables bounded:
sensitive to lower bound: Mission.Aircraft.HorizontalTail.WingBox.I_{cap}
value near lower bound: Mission.Aircraft.LandingGear.h_{nacelle}, Mission.Aircraft.Wing.WingNoStruct.\bar{A}_{fuel, max}, Mission.Aircraft.HorizontalTail.WingBox.I_{cap}, Mission.Aircraft.HorizontalTail.WingBox.M_r
WEIGHT DIFFERENCES
Total Fuel Weight Percent Diff: [-14.58138901]
Total Aircraft Weight Percent Diff: [-0.74792307]
Engine Weight Percent Diff: -31.678669848251474
Fuselage Weight Percent Diff: 2.6526976812611798
Payload Weight Percent Diff: [-0.04052335]
VT Weight Percent Diff: 36.22086550945204
HT Weight Percent Diff: -97.00046433394179
Wing Weight Percent Diff: 6.301579926786856
WING DIFFERENCES
Wing Span Percent Diff: -4.037425783973113
Wing Area Percent Diff: 20.489118201482633
HORIZONTAL TAIL DIFFERENCES
HT Area Percent Diff: 31.219036551287207
VERTICAL TAIL DIFFERENCES
VT Span Percent Diff: 0.9750022574577574
VT Area Percent Diff: -48.98410860424179
CRUISE SEGMENT 1 DRAG DIFFERENCES
Overall Cd Percent Diff: [-29.23181213]
L/D Percent Diff: [16.07570307]
Nacelle Cd Percent Diff: [-2.28162624]
HT Cd Percent Diff: [-97.20243713] dimensionless
Fuselage Cd Percent Diff: [108.78744865]
VT Cd Percent Diff: [-35.67333248] dimensionless
Wing Cd percent Diff: [-29.62869661]
Induced Drag Cd Percent Diff: [-33.69791978]
CRUISE SEGMENT 1 TSFC DIFFERENCES
Initial Cruise TSFC Percent Diff: [-5.5429688]
FUSELAGE DIFFERENCES
Weight of HB material: -30.56154398578863
Weight of VB material: 115.86605373880947
Fan Propulsive Efficiency in Cruise Segment 1
---------------------
[0.80046743]
Starting a sequence of GP solves
for 317 free variables
in 136 locally-GP constraints
and for 1198 free variables
in 4705 posynomial inequalities.
GP Solve 1
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.853 seconds.
Solved cost was 3.964e+40.
GP Solve 2
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.799 seconds.
Solved cost was 4.018e+10.
GP Solve 3
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.792 seconds.
Solved cost was 3.192e+05.
GP Solve 4
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.865 seconds.
Solved cost was 2.931e+04.
GP Solve 5
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.794 seconds.
Solved cost was 2.498e+04.
GP Solve 6
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.813 seconds.
Solved cost was 2.381e+04.
GP Solve 7
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.946 seconds.
Solved cost was 2.328e+04.
GP Solve 8
Using solver 'mosek_cli'
for 1198 free variables
in 4705 posynomial inequalities.
Solving took 0.881 seconds.
Solved cost was 2.303e+04.
Solving took 7.87 seconds and 8 GP solves.
Solves with these variables bounded:
sensitive to lower bound: Mission1.Aircraft.HorizontalTail.WingBox.I_{cap}
value near lower bound: Mission1.Aircraft.HorizontalTail.WingBox.M_r, Mission1.Aircraft.Wing.WingNoStruct.\bar{A}_{fuel, max}, Mission1.Aircraft.HorizontalTail.WingBox.I_{cap}, Mission1.Aircraft.LandingGear.h_{nacelle}
WEIGHT DIFFERENCES
Total Fuel Weight Percent Diff: [-14.58138901]
Total Aircraft Weight Percent Diff: [-0.74792307]
Engine Weight Percent Diff: -31.679831300991662
Fuselage Weight Percent Diff: 2.6537242133706
Payload Weight Percent Diff: [-0.04052335]
VT Weight Percent Diff: 36.22059306799342
HT Weight Percent Diff: -97.00044933622597
Wing Weight Percent Diff: 6.301579926786856
WING DIFFERENCES
Wing Span Percent Diff: -4.037329821350915
Wing Area Percent Diff: 20.489359179959926
HORIZONTAL TAIL DIFFERENCES
HT Area Percent Diff: 31.219167770389394
VERTICAL TAIL DIFFERENCES
VT Span Percent Diff: 0.9750022574577574
VT Area Percent Diff: -48.98415962010767
CRUISE SEGMENT 1 DRAG DIFFERENCES
Overall Cd Percent Diff: [-29.23195366]
L/D Percent Diff: [16.07593522]
Nacelle Cd Percent Diff: [-2.28348287]
HT Cd Percent Diff: [-97.20243993] dimensionless
Fuselage Cd Percent Diff: [108.78744865]
VT Cd Percent Diff: [-35.67352546] dimensionless
Wing Cd percent Diff: [-29.62869661]
Induced Drag Cd Percent Diff: [-33.69798608]
CRUISE SEGMENT 1 TSFC DIFFERENCES
Initial Cruise TSFC Percent Diff: [-5.5426382]
FUSELAGE DIFFERENCES
Weight of HB material: -30.51514360116808
Weight of VB material: 115.86929175390065
Fan Propulsive Efficiency in Cruise Segment 1
---------------------
[0.80046359]
----------------------------------------------------------------------
Ran 1 test in 21.651s
OK
Generating XML reports...
Cloning into 'robust'...
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\robust
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from robust==0.0.0) (1.0.0)
ERROR: Could not find a version that satisfies the requirement gplibrary (from robust==0.0.0) (from versions: none)
ERROR: No matching distribution found for gplibrary (from robust==0.0.0)
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\robust
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from robust==0.0.0) (1.0.0)
ERROR: Could not find a version that satisfies the requirement gplibrary (from robust==0.0.0) (from versions: none)
ERROR: No matching distribution found for gplibrary (from robust==0.0.0)
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\robust
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from robust==0.0.0) (1.0.0)
ERROR: Could not find a version that satisfies the requirement gplibrary (from robust==0.0.0) (from versions: none)
ERROR: No matching distribution found for gplibrary (from robust==0.0.0)
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\robust
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from robust==0.0.0) (1.0.0)
ERROR: Could not find a version that satisfies the requirement gplibrary (from robust==0.0.0) (from versions: none)
ERROR: No matching distribution found for gplibrary (from robust==0.0.0)
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\robust
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from robust==0.0.0) (1.0.0)
ERROR: Could not find a version that satisfies the requirement gplibrary (from robust==0.0.0) (from versions: none)
ERROR: No matching distribution found for gplibrary (from robust==0.0.0)
adding test for 'run_tests.py'
Running tests...
----------------------------------------------------------------------
Running tests...
----------------------------------------------------------------------
...................SGP not convergent: Cost rose by 8% on GP solve 2. 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.
SGP not convergent: Cost rose by 8% on GP solve 2. 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.
SGP not convergent: Cost rose by 8% on GP solve 2. 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.
SGP not convergent: Cost rose by 2.7% on GP solve 2. 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.
Final solution let signomial constraints slacken by 0.065%. Calling .localsolve with a higher `pccp_penalty` (it was 200 this time) will reduce final slack if the model is solvable with less. If you think it might not be, check by solving with `use_pccp=False, x0=(this model's final solution)`.
Solution check warning: Sum of nu^T * A did not vanish.
Final solution let signomial constraints slacken by 6%. Calling .localsolve with a higher `pccp_penalty` (it was 200 this time) will reduce final slack if the model is solvable with less. If you think it might not be, check by solving with `use_pccp=False, x0=(this model's final solution)`.
Solution check warning: Sum of nu^T * A did not vanish.
Final solution let signomial constraints slacken by 28%. Calling .localsolve with a higher `pccp_penalty` (it was 200 this time) will reduce final slack if the model is solvable with less. If you think it might not be, check by solving with `use_pccp=False, x0=(this model's final solution)`.
SGP not convergent: Cost rose by 0.02% 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.
SGP not convergent: Cost rose by 0.0067% 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.
Final solution let signomial constraints slacken by 0.0075%. Calling .localsolve with a higher `pccp_penalty` (it was 200 this time) will reduce final slack if the model is solvable with less. If you think it might not be, check by solving with `use_pccp=False, x0=(this model's final solution)`.
Final solution let signomial constraints slacken by 0.00097%. Calling .localsolve with a higher `pccp_penalty` (it was 200 this time) will reduce final slack if the model is solvable with less. If you think it might not be, check by solving with `use_pccp=False, x0=(this model's final solution)`.
SGP not convergent: Cost rose by 0.0043% on GP solve 3. 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.
SGP not convergent: Cost rose by 0.068% on GP solve 3. 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.
.SGP not convergent: Cost rose by 8% on GP solve 2. 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.
SGP not convergent: Cost rose by 8.1% on GP solve 2. 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.
SGP not convergent: Cost rose by 0.46% 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.
SGP not convergent: Cost rose by 8% on GP solve 2. 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.
SGP not convergent: Cost rose by 8% on GP solve 2. 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.
E
======================================================================
ERROR [10.378s]: test_table_diff (run_tests.TestSimulation_mosek_cli)
----------------------------------------------------------------------
Traceback (most recent call last):
File "C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\robust\robust\testing\t_simulation.py", line 107, in test_table_diff
self.assertAlmostEqual(open(origfilename, 'r').readlines(), open(filename, 'r').readlines())
File "C:\Anaconda3\Lib\unittest\case.py", line 883, in assertAlmostEqual
diff = abs(first - second)
TypeError: unsupported operand type(s) for -: 'list' and 'list'
----------------------------------------------------------------------
Ran 21 tests in 127.606s
FAILED (errors=1)
Generating XML reports...
.
----------------------------------------------------------------------
Ran 1 test in 129.189s
OK
Generating XML reports...
Cloning into 'shopping'...
adding test for 'test.py'
Running tests...
----------------------------------------------------------------------
Using solver 'mosek_cli'
for 25 free variables
in 40 posynomial inequalities.
Solving took 0.205 seconds.
.Using solver 'mosek_cli'
for 25 free variables
in 40 posynomial inequalities.
Solving took 0.199 seconds.
.
----------------------------------------------------------------------
Ran 2 tests in 0.699s
OK
Generating XML reports...
Cloning into 'gassolar'...
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Requirement already satisfied: pandas in c:\anaconda3\lib\site-packages (1.0.5)
Requirement already satisfied: python-dateutil>=2.6.1 in c:\anaconda3\lib\site-packages (from pandas) (2.8.1)
Requirement already satisfied: pytz>=2017.2 in c:\anaconda3\lib\site-packages (from pandas) (2020.1)
Requirement already satisfied: numpy>=1.13.3 in c:\anaconda3\lib\site-packages (from pandas) (1.19.0)
Requirement already satisfied: six>=1.5 in c:\anaconda3\lib\site-packages (from python-dateutil>=2.6.1->pandas) (1.15.0)
Collecting git+https://github.com/hoburg/gpfit.git
Cloning https://github.com/hoburg/gpfit.git to c:\users\jenkins\appdata\local\temp\pip-req-build-85mt2w0a
Running command git clone -q https://github.com/hoburg/gpfit.git 'C:\Users\jenkins\AppData\Local\Temp\pip-req-build-85mt2w0a'
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from gpfit==0.1) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from gpfit==0.1) (1.5.1)
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from gpfit==0.1) (1.0.0)
Requirement already satisfied: pint>=0.8.1 in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkit->gpfit==0.1) (0.9)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit->gpfit==0.1) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit->gpfit==0.1) (1.2.5)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit->gpfit==0.1) (2019.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit->gpfit==0.1) (2019.0)
Building wheels for collected packages: gpfit
Building wheel for gpfit (setup.py): started
Building wheel for gpfit (setup.py): finished with status 'done'
Created wheel for gpfit: filename=gpfit-0.1-py3-none-any.whl size=25631 sha256=fc138a00a95ecada29486646c351f9a8a07294179890279eedf0c04ed4d37e73
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-oomrlb3i\wheels\57\29\3e\8d7ba8db76ea975ecfe679ec45f25d64a6eaec893d16b3d378
Successfully built gpfit
Installing collected packages: gpfit
Successfully installed gpfit-0.1
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gassolar
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from gassolar==0.0.0.0) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from gassolar==0.0.0.0) (1.5.1)
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from gassolar==0.0.0.0) (1.0.0)
Requirement already satisfied: pandas in c:\anaconda3\lib\site-packages (from gassolar==0.0.0.0) (1.0.5)
Requirement already satisfied: gpfit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gassolar==0.0.0.0) (0.1)
Requirement already satisfied: pint>=0.8.1 in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkit->gassolar==0.0.0.0) (0.9)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit->gassolar==0.0.0.0) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit->gassolar==0.0.0.0) (1.2.5)
Requirement already satisfied: python-dateutil>=2.6.1 in c:\anaconda3\lib\site-packages (from pandas->gassolar==0.0.0.0) (2.8.1)
Requirement already satisfied: pytz>=2017.2 in c:\anaconda3\lib\site-packages (from pandas->gassolar==0.0.0.0) (2020.1)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit->gassolar==0.0.0.0) (2019.0)
Requirement already satisfied: six>=1.5 in c:\anaconda3\lib\site-packages (from python-dateutil>=2.6.1->pandas->gassolar==0.0.0.0) (1.15.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit->gassolar==0.0.0.0) (2019.0)
Building wheels for collected packages: gassolar
Building wheel for gassolar (setup.py): started
Building wheel for gassolar (setup.py): finished with status 'done'
Created wheel for gassolar: filename=gassolar-0.0.0.0-py3-none-any.whl size=4895568 sha256=47d42cf942ae1cc24b2aa53d8f9a690523f8c69a8e220854884846182a22b109
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-v1qoyeqf\wheels\a2\1c\f6\c311a0b154a3c7abb5c7361061ad8b0fb10d2da48901ad2ba0
Successfully built gassolar
Installing collected packages: gassolar
Successfully installed gassolar-0.0.0.0
adding test for 'gassolar/gas/gas.py'
adding test for 'gassolar/solar/solar.py'
Running tests...
----------------------------------------------------------------------
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
.Using solver 'mosek_cli'
for 592 free variables
in 918 posynomial inequalities.
Solving took 0.498 seconds.
Warning: Variable Mission.Climb.FlightSegment.AircraftPerf.EnginePerf.P_{total}[:]/Mission.Climb.FlightSegment.Aircraf could cause inaccurate result because it is above upper bound. Solution is 1.0000 but bound is 0.9685
Starting a sequence of GP solves
for 8 free variables
in 2 locally-GP constraints
and for 600 free variables
in 926 posynomial inequalities.
Solving took 2.48 seconds and 4 GP solves.
Warning: Variable Mission1.Climb.FlightSegment.AircraftPerf.EnginePerf.P_{total}[:]/Mission1.Climb.FlightSegment.Aircr could cause inaccurate result because it is above upper bound. Solution is 1.0000 but bound is 0.9685
Using solver 'mosek_cli'
for 1250 free variables
in 1872 posynomial inequalities.
Solving took 0.762 seconds.
Warning: Variable Mission.FlightSegment.AircraftPerf.WingAero.Re could cause inaccurate result because it is below lower bound. Solution is 102558.6388 but bound is 150000.0000
Warning: Variable Mission.FlightSegment10.AircraftPerf.WingAero.Re could cause inaccurate result because it is below lower bound. Solution is 102558.6388 but bound is 150000.0000
Starting a sequence of GP solves
for 38 free variables
in 12 locally-GP constraints
and for 1298 free variables
in 1930 posynomial inequalities.
Solving took 3.22 seconds and 4 GP solves.
Warning: Variable Mission1.FlightSegment.AircraftPerf.WingAero.Re could cause inaccurate result because it is below lower bound. Solution is 103379.2971 but bound is 150000.0000
Warning: Variable Mission1.FlightSegment10.AircraftPerf.WingAero.Re could cause inaccurate result because it is below lower bound. Solution is 103406.1793 but bound is 150000.0000
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages\gassolar\environment\solar_irradiance.py:40: RuntimeWarning: overflow encountered in exp
tau = np.exp(-0.175/costhsun)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages\gassolar\environment\solar_irradiance.py:40: RuntimeWarning: overflow encountered in exp
tau = np.exp(-0.175/costhsun)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
.
----------------------------------------------------------------------
Ran 2 tests in 14.049s
OK
Generating XML reports...
Cloning into 'jho'...
Requirement already satisfied: pandas in c:\anaconda3\lib\site-packages (1.0.5)
Requirement already satisfied: python-dateutil>=2.6.1 in c:\anaconda3\lib\site-packages (from pandas) (2.8.1)
Requirement already satisfied: numpy>=1.13.3 in c:\anaconda3\lib\site-packages (from pandas) (1.19.0)
Requirement already satisfied: pytz>=2017.2 in c:\anaconda3\lib\site-packages (from pandas) (2020.1)
Requirement already satisfied: six>=1.5 in c:\anaconda3\lib\site-packages (from python-dateutil>=2.6.1->pandas) (1.15.0)
Collecting git+https://github.com/hoburg/gpfit.git
Cloning https://github.com/hoburg/gpfit.git to c:\users\jenkins\appdata\local\temp\pip-req-build-fsggauh5
Running command git clone -q https://github.com/hoburg/gpfit.git 'C:\Users\jenkins\AppData\Local\Temp\pip-req-build-fsggauh5'
Requirement already satisfied (use --upgrade to upgrade): gpfit==0.1 from git+https://github.com/hoburg/gpfit.git in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from gpfit==0.1) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from gpfit==0.1) (1.5.1)
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from gpfit==0.1) (1.0.0)
Requirement already satisfied: pint>=0.8.1 in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkit->gpfit==0.1) (0.9)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit->gpfit==0.1) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit->gpfit==0.1) (1.2.5)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit->gpfit==0.1) (2019.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit->gpfit==0.1) (2019.0)
Building wheels for collected packages: gpfit
Building wheel for gpfit (setup.py): started
Building wheel for gpfit (setup.py): finished with status 'done'
Created wheel for gpfit: filename=gpfit-0.1-py3-none-any.whl size=25631 sha256=19f26c52b250823019bfeca3ff8dd87eea0ef9c9aba36824b40ffbabb5064270
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-ahgul71c\wheels\57\29\3e\8d7ba8db76ea975ecfe679ec45f25d64a6eaec893d16b3d378
Successfully built gpfit
adding test for 'model/jho.py'
adding test for 'model/print_perf.py'
Running tests...
----------------------------------------------------------------------
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
EE
======================================================================
ERROR [1.573s]: test_model_jho_py_mosek_cli (gpkit.tests.from_paths.TestFiles)
----------------------------------------------------------------------
Traceback (most recent call last):
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\set.py", line 86, in __init__
self._update(subconstraint)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\set.py", line 114, in _update
self.substitutions.update(constraint.substitutions)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\keydict.py", line 157, in update
self[k] = v
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\keydict.py", line 220, in __setitem__
goodvals = ~np.isnan(value)
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\helpers.py", line 59, in test
testfn(name, import_dict, path)(self)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\from_paths.py", line 48, in <lambda>
lambda self: getattr(self, name)())) # pylint:disable=undefined-variable
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\from_paths.py", line 37, in test_fn
mod.test()
File "C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\jho\model\jho.py", line 366, in test
model = Mission()
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\model.py", line 71, in __init__
CostedConstraintSet.__init__(self, cost, constraints, substitutions)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\costed.py", line 25, in __init__
ConstraintSet.__init__(self, constraints, subs)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\set.py", line 88, in __init__
raise badelement(self, i, constraint) from e
ValueError: Invalid ConstraintSet element '[<gpkit.Climb object containing 2 top-level constraint(s) and 933 variable(s)>, <gpkit.Cruise object containing 2 top-level constraint(s) and 364 variable(s)>, <gpkit.Loiter object containing 2 top-level constraint(s) and 612 variable(s)>, <gpkit.Cruise object containing 2 top-level constraint(s) and 364 variable(s)>]' <class 'list'> was between Aircraft
========
Cost
----
1
Constraints
-----------
Fuselage
FuelTank
Mission.Aircraft.Fuselage.FuelTank.W >= f*W_{fuel-tot}
\mathcal{V}/Mission.Aircraft.Fuselage.FuelTank.m_{fac} >= W_{fuel-tot}/\rho_{fuel}
FuselageSkin
m >= S_{wet}*\rho_{kevlar}*Mission.Aircraft.Fuselage.FuselageSkin.t
Mission.Aircraft.Fuselage.FuselageSkin.W >= m*Mission.Aircraft.Fuselage.FuselageSkin.g
Mission.Aircraft.Fuselage.FuselageSkin.t >= t_{min}
Mission.Aircraft.Fuselage.FuselageSkin.I <= PI*R^3*Mission.Aircraft.Fuselage.FuselageSkin.t
I_G >= m*(4*R^2 + 4*R*Mission.Aircraft.Fuselage.FuselageSkin.t + Mission.Aircraft.Fuselage.FuselageSkin.t^2)
l_{body} = l_{body}
Mission.Aircraft.Fuselage.FuselageSkin.E = Mission.Aircraft.Fuselage.FuselageSkin.E
k_{body} = l_{body}/R
S_{wet} >= S_{body} + S_{nose} + S_{bulk}
S_{body} >= 2PI*R*l_{body}
S_{nose}^1.6 >= 2PI*R^2^1.6*(0.333 + 0.667*k_{nose}^1.6)
S_{bulk} >= R^2*(0.0123*k_{bulk}^2 + 1.52*k_{bulk} + 0.502)
\mathcal{V}_{body} <= PI*R^2*l_{body}
Mission.Aircraft.Fuselage.l <= 3*R*k_{body}*k_{nose}*k_{bulk}^0.3333333333333333
Mission.Aircraft.Fuselage.S >= PI*R^2
\mathcal{V}_{body} >= \mathcal{V}
Mission.Aircraft.Fuselage.W/Mission.Aircraft.Fuselage.m_{fac} >= Mission.Aircraft.Fuselage.FuelTank.W + Mission.Aircraft.Fuselage.FuselageSkin.W
Wing
Mission.Aircraft.Wing.W/Mission.Aircraft.Wing.mfac >= Mission.Aircraft.Wing.WingSkin.W + Mission.Aircraft.Wing.CapSpar.W + Mission.Aircraft.Wing.WingCore.W
Planform
Mission.Aircraft.Wing.Planform.b^2 = Mission.Aircraft.Wing.Planform.S*Mission.Aircraft.Wing.Planform.AR
cave[:] = cbave[:]*Mission.Aircraft.Wing.Planform.S/Mission.Aircraft.Wing.Planform.b
Mission.Aircraft.Wing.Planform.croot = Mission.Aircraft.Wing.Planform.S/Mission.Aircraft.Wing.Planform.b*cbar[0]
Mission.Aircraft.Wing.Planform.cmac = Mission.Aircraft.Wing.Planform.croot*Mission.Aircraft.Wing.Planform.cbarmac
WingSkin
Mission.Aircraft.Wing.WingSkin.W >= CFRPFabric.rho*Mission.Aircraft.Wing.Planform.S*2*Mission.Aircraft.Wing.WingSkin.t*g
Mission.Aircraft.Wing.WingSkin.t >= tmin
CFRPFabric.tau >= 1/Mission.Aircraft.Wing.WingSkin.Jtbar/Mission.Aircraft.Wing.Planform.croot^2/Mission.Aircraft.Wing.WingSkin.t*Mission.Aircraft.Wing.WingSkin.Cmw*Mission.Aircraft.Wing.Planform.S*Mission.Aircraft.Wing.WingSkin.rhosl*Mission.Aircraft.Wing.WingSkin.Vne^2
CapSpar
I[:]/Mission.Aircraft.Wing.CapSpar.mfac <= 2*w[:]*t[:]*(hin[:]/2)^2
dm[:] >= (CFRPUD.rho*2*w[:]*t[:] + 2*tshear[:]*CFRPFabric.rho*(hin[:] + 2*t[:]) + FoamHD.rho*w[:]*hin[:])*Mission.Aircraft.Wing.Planform.b/2*deta[:]
Mission.Aircraft.Wing.CapSpar.W >= 2*dm[:].sum()*g
w[:] <= wlim*cave[:]
cave[:]*Mission.Aircraft.Wing.Planform.tau >= hin[:] + 2*t[:]
Sy[:]*(hin[:]/2 + t[:]) <= I[:]
tshear[:] >= tmin
WingCore
Mission.Aircraft.Wing.WingCore.W >= 2*(g*FoamHD.rho*Mission.Aircraft.Wing.WingCore.Abar*cave[:]^2*Mission.Aircraft.Wing.Planform.b/2*deta[:]).sum()
mw*(1 + 2/Mission.Aircraft.Wing.Planform.AR) >= 6.28
DF70
W_{DF70} <= Mission.Aircraft.DF70.W/Mission.Aircraft.DF70.m_{fac}
P_{sl-max} = P_{sl-max}
Empennage
HorizontalTail
Mission.Aircraft.Empennage.HorizontalTail.W/Mission.Aircraft.Empennage.HorizontalTail.mfac >= Mission.Aircraft.Empennage.HorizontalTail.WingSkin.W + Mission.Aircraft.Empennage.HorizontalTail.WingCore.W
Planform
Mission.Aircraft.Empennage.HorizontalTail.Planform.b^2 = Mission.Aircraft.Empennage.HorizontalTail.Planform.S*Mission.Aircraft.Empennage.HorizontalTail.Planform.AR
cave[:] = cbave[:]*Mission.Aircraft.Empennage.HorizontalTail.Planform.S/Mission.Aircraft.Empennage.HorizontalTail.Planform.b
Mission.Aircraft.Empennage.HorizontalTail.Planform.croot = Mission.Aircraft.Empennage.HorizontalTail.Planform.S/Mission.Aircraft.Empennage.HorizontalTail.Planform.b*cbar[0]
Mission.Aircraft.Empennage.HorizontalTail.Planform.cmac = Mission.Aircraft.Empennage.HorizontalTail.Planform.croot*Mission.Aircraft.Empennage.HorizontalTail.Planform.cbarmac
WingSkin
Mission.Aircraft.Empennage.HorizontalTail.WingSkin.W >= CFRPFabric.rho*Mission.Aircraft.Empennage.HorizontalTail.Planform.S*2*Mission.Aircraft.Empennage.HorizontalTail.WingSkin.t*g
Mission.Aircraft.Empennage.HorizontalTail.WingSkin.t >= tmin
CFRPFabric.tau >= 1/Mission.Aircraft.Empennage.HorizontalTail.WingSkin.Jtbar/Mission.Aircraft.Empennage.HorizontalTail.Planform.croot^2/Mission.Aircraft.Empennage.HorizontalTail.WingSkin.t*Mission.Aircraft.Empennage.HorizontalTail.WingSkin.Cmw*Mission.Aircraft.Empennage.HorizontalTail.Planform.S*Mission.Aircraft.Empennage.HorizontalTail.WingSkin.rhosl*Mission.Aircraft.Empennage.HorizontalTail.WingSkin.Vne^2
WingCore
Mission.Aircraft.Empennage.HorizontalTail.WingCore.W >= 2*(g*FoamHD.rho*Mission.Aircraft.Empennage.HorizontalTail.WingCore.Abar*cave[:]^2*Mission.Aircraft.Empennage.HorizontalTail.Planform.b/2*deta[:]).sum()
mh*(1 + 2/Mission.Aircraft.Empennage.HorizontalTail.Planform.AR) <= 6.28
VerticalTail
Mission.Aircraft.Empennage.VerticalTail.W/Mission.Aircraft.Empennage.VerticalTail.mfac >= Mission.Aircraft.Empennage.VerticalTail.WingSkin.W + Mission.Aircraft.Empennage.VerticalTail.WingCore.W
Planform
Mission.Aircraft.Empennage.VerticalTail.Planform.b^2 = Mission.Aircraft.Empennage.VerticalTail.Planform.S*Mission.Aircraft.Empennage.VerticalTail.Planform.AR
cave[:] = cbave[:]*Mission.Aircraft.Empennage.VerticalTail.Planform.S/Mission.Aircraft.Empennage.VerticalTail.Planform.b
Mission.Aircraft.Empennage.VerticalTail.Planform.croot = Mission.Aircraft.Empennage.VerticalTail.Planform.S/Mission.Aircraft.Empennage.VerticalTail.Planform.b*cbar[0]
Mission.Aircraft.Empennage.VerticalTail.Planform.cmac = Mission.Aircraft.Empennage.VerticalTail.Planform.croot*Mission.Aircraft.Empennage.VerticalTail.Planform.cbarmac
WingSkin
Mission.Aircraft.Empennage.VerticalTail.WingSkin.W >= CFRPFabric.rho*Mission.Aircraft.Empennage.VerticalTail.Planform.S*2*Mission.Aircraft.Empennage.VerticalTail.WingSkin.t*g
Mission.Aircraft.Empennage.VerticalTail.WingSkin.t >= tmin
CFRPFabric.tau >= 1/Mission.Aircraft.Empennage.VerticalTail.WingSkin.Jtbar/Mission.Aircraft.Empennage.VerticalTail.Planform.croot^2/Mission.Aircraft.Empennage.VerticalTail.WingSkin.t*Mission.Aircraft.Empennage.VerticalTail.WingSkin.Cmw*Mission.Aircraft.Empennage.VerticalTail.Planform.S*Mission.Aircraft.Empennage.VerticalTail.WingSkin.rhosl*Mission.Aircraft.Empennage.VerticalTail.WingSkin.Vne^2
WingCore
Mission.Aircraft.Empennage.VerticalTail.WingCore.W >= 2*(g*FoamHD.rho*Mission.Aircraft.Empennage.VerticalTail.WingCore.Abar*cave[:]^2*Mission.Aircraft.Empennage.VerticalTail.Planform.b/2*deta[:]).sum()
TailBoom
I[:] <= PI*t[:]*d[:]^3/8
Sy[:] <= 2*I[:]/d[:]
dm[:] >= PI*CFRPFabric.rho*d[:]*Mission.Aircraft.Empennage.TailBoom.deta*t[:]*kfac*Mission.Aircraft.Empennage.TailBoom.l
Mission.Aircraft.Empennage.TailBoom.W/Mission.Aircraft.Empennage.TailBoom.mfac >= g*dm[:].sum()
t[:] >= tmin
Mission.Aircraft.Empennage.TailBoom.S = Mission.Aircraft.Empennage.TailBoom.l*PI*d[0]
Mission.Aircraft.Empennage.TailBoom.b = 2*Mission.Aircraft.Empennage.TailBoom.l
Mission.Aircraft.Empennage.W/Mission.Aircraft.Empennage.mfac >= Mission.Aircraft.Empennage.HorizontalTail.W + Mission.Aircraft.Empennage.VerticalTail.W + Mission.Aircraft.Empennage.TailBoom.W
Mission.Aircraft.Empennage.TailBoom.l >= lh
Mission.Aircraft.Empennage.TailBoom.l >= lv
Pylon
Mission.Aircraft.Pylon.S >= 2*Mission.Aircraft.Pylon.l*Mission.Aircraft.Pylon.h
W_{zfw} >= Mission.Aircraft.Fuselage.W + Mission.Aircraft.Wing.W + Mission.Aircraft.DF70.W + Mission.Aircraft.Empennage.W + Mission.Aircraft.Pylon.W + W_{pay} + W_{avn}
Vh <= Mission.Aircraft.Empennage.HorizontalTail.Planform.S*lh/Mission.Aircraft.Wing.Planform.S^2*Mission.Aircraft.Wing.Planform.b
Vv = Mission.Aircraft.Empennage.VerticalTail.Planform.S*lv/Mission.Aircraft.Wing.Planform.S/Mission.Aircraft.Wing.Planform.b
Mission.Aircraft.Wing.Planform.CLmax/mw <= Mission.Aircraft.Empennage.HorizontalTail.Planform.CLmax/mh
w_{antenna} <= Mission.Aircraft.Empennage.VerticalTail.Planform.croot*Mission.Aircraft.Empennage.VerticalTail.Planform.lam
Mission.Aircraft.Empennage.VerticalTail.Planform.b >= l_{antenna}
Mission.Aircraft.Empennage.TailBoom.l >= lh + Mission.Aircraft.Empennage.HorizontalTail.Planform.croot
\mathcal{V}_{pay} <= (PI/1.5)*k_{nose}*R^3
\mathcal{V}_{body} >= \mathcal{V} + \mathcal{V}_{avn}
Mission.Aircraft.DF70.h <= 2*R and AircraftLoading
===============
Cost
----
1
Constraints
-----------
TailBoomBending
dx[:] = Mission.Aircraft.Empennage.TailBoom.deta
qne[:]*Mission.Aircraft.Empennage.HorizontalTail.Planform.S <= Mission.AircraftLoading.TailBoomBending.F
\bar{EI}[:] <= CFRPFabric.E*I[:]/Mission.AircraftLoading.TailBoomBending.F/l^2/2
Mr[:] >= \bar{M}[:-1]*Mission.AircraftLoading.TailBoomBending.F*l
Mr[:]/Sy[:] <= CFRPFabric.sigma
Mission.AircraftLoading.TailBoomBending.th = \theta[1]
Mission.AircraftLoading.TailBoomBending.kappa >= \bar{\delta}[1]*Mission.Aircraft.Empennage.HorizontalTail.Planform.CLmax*Mission.AircraftLoading.TailBoomBending.Nsafety
Beam
\bar{M}[:-1] >= \bar{M}[1:] + 0.5*dx[:]*(\bar{S}[:-1] + \bar{S}[1:])
\bar{M}[1] >= Mission.AircraftLoading.TailBoomBending.Beam.\bar{M}_{tip}
\theta[0] >= Mission.AircraftLoading.TailBoomBending.Beam.\theta_{root}
\theta[1:] >= \theta[:-1] + 0.5*dx[:]*(\bar{M}[1:] + \bar{M}[:-1])/\bar{EI}[:]
\bar{\delta}[0] >= Mission.AircraftLoading.TailBoomBending.Beam.\bar{\delta}_{root}
\bar{\delta}[1:] >= \bar{\delta}[:-1] + 0.5*dx[:]*(\theta[1:] + \theta[:-1])
TailBoomBending1
dx[:] = Mission.Aircraft.Empennage.TailBoom.deta
qne[:]*Mission.Aircraft.Empennage.VerticalTail.Planform.S <= Mission.AircraftLoading.TailBoomBending1.F
\bar{EI}[:] <= CFRPFabric.E*I[:]/Mission.AircraftLoading.TailBoomBending1.F/l^2/2
Mr[:] >= \bar{M}[:-1]*Mission.AircraftLoading.TailBoomBending1.F*l
Mr[:]/Sy[:] <= CFRPFabric.sigma
Mission.AircraftLoading.TailBoomBending1.th = \theta[1]
Mission.AircraftLoading.TailBoomBending1.kappa >= \bar{\delta}[1]*Mission.Aircraft.Empennage.VerticalTail.Planform.CLmax*Mission.AircraftLoading.TailBoomBending1.Nsafety
Beam
\bar{M}[:-1] >= \bar{M}[1:] + 0.5*dx[:]*(\bar{S}[:-1] + \bar{S}[1:])
\bar{M}[1] >= Mission.AircraftLoading.TailBoomBending1.Beam.\bar{M}_{tip}
\theta[0] >= Mission.AircraftLoading.TailBoomBending1.Beam.\theta_{root}
\theta[1:] >= \theta[:-1] + 0.5*dx[:]*(\bar{M}[1:] + \bar{M}[:-1])/\bar{EI}[:]
\bar{\delta}[0] >= Mission.AircraftLoading.TailBoomBending1.Beam.\bar{\delta}_{root}
\bar{\delta}[1:] >= \bar{\delta}[:-1] + 0.5*dx[:]*(\theta[1:] + \theta[:-1])
SparLoading
S[:-1] >= S[1:] + 0.5*deta[:]*b/2*(q[:-1] + q[1:])
M[:-1] >= M[1:] + 0.5*deta[:]*b/2*(S[:-1] + S[1:])
N = Mission.AircraftLoading.SparLoading.Nsafety*Nmax
q[:] >= N*W/b*cbar[:]
S[11] >= Stip
M[11] >= Mtip
th[0] >= throot
th[1:] >= th[:-1] + 0.5*deta[:]*b/2*(M[1:] + M[:-1])/CFRPUD.E/I[:]
w[0] >= wroot
w[1:] >= w[:-1] + 0.5*deta[:]*b/2*(th[1:] + th[:-1])
M[:-1]/Sy[:] <= CFRPUD.sigma
Mission.AircraftLoading.SparLoading.kappa >= w[11]/(b/2)
FuselageLoading
FuselageSkinL
M_h >= Mission.AircraftLoading.FuselageLoading.FuselageSkinL.N_{max}*W_{cent}/4*l_{body}
Mission.AircraftLoading.FuselageLoading.FuselageSkinL.\sigma_{Kevlar} >= M_h*R/Mission.Aircraft.Fuselage.FuselageSkin.I
Mission.AircraftLoading.FuselageLoading.FuselageSkinL.q >= W_{cent}*Mission.AircraftLoading.FuselageLoading.FuselageSkinL.N_{max}/l_{body}
\kappa*l_{body}/2 >= Mission.AircraftLoading.FuselageLoading.FuselageSkinL.q*(l_{body}/2)^4/8*Mission.Aircraft.Fuselage.FuselageSkin.E*Mission.Aircraft.Fuselage.FuselageSkin.I
FuselageLanding
Mission.AircraftLoading.FuselageLoading.FuselageLanding.F >= W_{cent}*Mission.AircraftLoading.FuselageLoading.FuselageLanding.N_{max}
a >= Mission.AircraftLoading.FuselageLoading.FuselageLanding.F/m
\dot{\omega} >= a/(l_{body}/2)
M_G >= I_G*\dot{\omega}
Mission.AircraftLoading.FuselageLoading.FuselageLanding.\sigma_{Kevlar} >= M_G*R/Mission.Aircraft.Fuselage.FuselageSkin.I
TailBoomFlexibility
Fne >= 1 + mh*Mission.AircraftLoading.TailBoomBending.th
sph1*mw*Fne/mh/Vh + deda <= 1
sph2 <= Vh*CLhmin/Mission.Aircraft.Wing.Planform.CLmax
deda >= mw*Mission.Aircraft.Wing.Planform.S/b/4/PI/lh
sph1 + sph2 >= SMcorr + CM/Mission.Aircraft.Wing.Planform.CLmax.
======================================================================
ERROR [0.870s]: test_model_print_perf_py_mosek_cli (gpkit.tests.from_paths.TestFiles)
----------------------------------------------------------------------
Traceback (most recent call last):
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\set.py", line 86, in __init__
self._update(subconstraint)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\set.py", line 114, in _update
self.substitutions.update(constraint.substitutions)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\keydict.py", line 157, in update
self[k] = v
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\keydict.py", line 220, in __setitem__
goodvals = ~np.isnan(value)
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\helpers.py", line 59, in test
testfn(name, import_dict, path)(self)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\from_paths.py", line 48, in <lambda>
lambda self: getattr(self, name)())) # pylint:disable=undefined-variable
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\tests\from_paths.py", line 37, in test_fn
mod.test()
File "C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\jho\model\print_perf.py", line 194, in test
M = Mission(DF70=True)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\model.py", line 71, in __init__
CostedConstraintSet.__init__(self, cost, constraints, substitutions)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\costed.py", line 25, in __init__
ConstraintSet.__init__(self, constraints, subs)
File "c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gpkit\constraints\set.py", line 88, in __init__
raise badelement(self, i, constraint) from e
ValueError: Invalid ConstraintSet element '[<gpkit.Climb object containing 2 top-level constraint(s) and 933 variable(s)>, <gpkit.Cruise object containing 2 top-level constraint(s) and 364 variable(s)>, <gpkit.Loiter object containing 2 top-level constraint(s) and 612 variable(s)>, <gpkit.Cruise object containing 2 top-level constraint(s) and 364 variable(s)>]' <class 'list'> was between Aircraft
========
Cost
----
1
Constraints
-----------
Fuselage
FuelTank
Mission1.Aircraft.Fuselage.FuelTank.W >= f*W_{fuel-tot}
\mathcal{V}/Mission1.Aircraft.Fuselage.FuelTank.m_{fac} >= W_{fuel-tot}/\rho_{fuel}
FuselageSkin
m >= S_{wet}*\rho_{kevlar}*Mission1.Aircraft.Fuselage.FuselageSkin.t
Mission1.Aircraft.Fuselage.FuselageSkin.W >= m*Mission1.Aircraft.Fuselage.FuselageSkin.g
Mission1.Aircraft.Fuselage.FuselageSkin.t >= t_{min}
Mission1.Aircraft.Fuselage.FuselageSkin.I <= PI*R^3*Mission1.Aircraft.Fuselage.FuselageSkin.t
I_G >= m*(4*R^2 + 4*R*Mission1.Aircraft.Fuselage.FuselageSkin.t + Mission1.Aircraft.Fuselage.FuselageSkin.t^2)
l_{body} = l_{body}
Mission1.Aircraft.Fuselage.FuselageSkin.E = Mission1.Aircraft.Fuselage.FuselageSkin.E
k_{body} = l_{body}/R
S_{wet} >= S_{body} + S_{nose} + S_{bulk}
S_{body} >= 2PI*R*l_{body}
S_{nose}^1.6 >= 2PI*R^2^1.6*(0.333 + 0.667*k_{nose}^1.6)
S_{bulk} >= R^2*(0.0123*k_{bulk}^2 + 1.52*k_{bulk} + 0.502)
\mathcal{V}_{body} <= PI*R^2*l_{body}
Mission1.Aircraft.Fuselage.l <= 3*R*k_{body}*k_{nose}*k_{bulk}^0.3333333333333333
Mission1.Aircraft.Fuselage.S >= PI*R^2
\mathcal{V}_{body} >= \mathcal{V}
Mission1.Aircraft.Fuselage.W/Mission1.Aircraft.Fuselage.m_{fac} >= Mission1.Aircraft.Fuselage.FuelTank.W + Mission1.Aircraft.Fuselage.FuselageSkin.W
Wing
Mission1.Aircraft.Wing.W/Mission1.Aircraft.Wing.mfac >= Mission1.Aircraft.Wing.WingSkin.W + Mission1.Aircraft.Wing.CapSpar.W + Mission1.Aircraft.Wing.WingCore.W
Planform
Mission1.Aircraft.Wing.Planform.b^2 = Mission1.Aircraft.Wing.Planform.S*Mission1.Aircraft.Wing.Planform.AR
cave[:] = cbave[:]*Mission1.Aircraft.Wing.Planform.S/Mission1.Aircraft.Wing.Planform.b
Mission1.Aircraft.Wing.Planform.croot = Mission1.Aircraft.Wing.Planform.S/Mission1.Aircraft.Wing.Planform.b*cbar[0]
Mission1.Aircraft.Wing.Planform.cmac = Mission1.Aircraft.Wing.Planform.croot*Mission1.Aircraft.Wing.Planform.cbarmac
WingSkin
Mission1.Aircraft.Wing.WingSkin.W >= CFRPFabric.rho*Mission1.Aircraft.Wing.Planform.S*2*Mission1.Aircraft.Wing.WingSkin.t*g
Mission1.Aircraft.Wing.WingSkin.t >= tmin
CFRPFabric.tau >= 1/Mission1.Aircraft.Wing.WingSkin.Jtbar/Mission1.Aircraft.Wing.Planform.croot^2/Mission1.Aircraft.Wing.WingSkin.t*Mission1.Aircraft.Wing.WingSkin.Cmw*Mission1.Aircraft.Wing.Planform.S*Mission1.Aircraft.Wing.WingSkin.rhosl*Mission1.Aircraft.Wing.WingSkin.Vne^2
CapSpar
I[:]/Mission1.Aircraft.Wing.CapSpar.mfac <= 2*w[:]*t[:]*(hin[:]/2)^2
dm[:] >= (CFRPUD.rho*2*w[:]*t[:] + 2*tshear[:]*CFRPFabric.rho*(hin[:] + 2*t[:]) + FoamHD.rho*w[:]*hin[:])*Mission1.Aircraft.Wing.Planform.b/2*deta[:]
Mission1.Aircraft.Wing.CapSpar.W >= 2*dm[:].sum()*g
w[:] <= wlim*cave[:]
cave[:]*Mission1.Aircraft.Wing.Planform.tau >= hin[:] + 2*t[:]
Sy[:]*(hin[:]/2 + t[:]) <= I[:]
tshear[:] >= tmin
WingCore
Mission1.Aircraft.Wing.WingCore.W >= 2*(g*FoamHD.rho*Mission1.Aircraft.Wing.WingCore.Abar*cave[:]^2*Mission1.Aircraft.Wing.Planform.b/2*deta[:]).sum()
mw*(1 + 2/Mission1.Aircraft.Wing.Planform.AR) >= 6.28
DF70
W_{DF70} <= Mission1.Aircraft.DF70.W/Mission1.Aircraft.DF70.m_{fac}
P_{sl-max} = P_{sl-max}
Empennage
HorizontalTail
Mission1.Aircraft.Empennage.HorizontalTail.W/Mission1.Aircraft.Empennage.HorizontalTail.mfac >= Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.W + Mission1.Aircraft.Empennage.HorizontalTail.WingCore.W
Planform
Mission1.Aircraft.Empennage.HorizontalTail.Planform.b^2 = Mission1.Aircraft.Empennage.HorizontalTail.Planform.S*Mission1.Aircraft.Empennage.HorizontalTail.Planform.AR
cave[:] = cbave[:]*Mission1.Aircraft.Empennage.HorizontalTail.Planform.S/Mission1.Aircraft.Empennage.HorizontalTail.Planform.b
Mission1.Aircraft.Empennage.HorizontalTail.Planform.croot = Mission1.Aircraft.Empennage.HorizontalTail.Planform.S/Mission1.Aircraft.Empennage.HorizontalTail.Planform.b*cbar[0]
Mission1.Aircraft.Empennage.HorizontalTail.Planform.cmac = Mission1.Aircraft.Empennage.HorizontalTail.Planform.croot*Mission1.Aircraft.Empennage.HorizontalTail.Planform.cbarmac
WingSkin
Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.W >= CFRPFabric.rho*Mission1.Aircraft.Empennage.HorizontalTail.Planform.S*2*Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.t*g
Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.t >= tmin
CFRPFabric.tau >= 1/Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.Jtbar/Mission1.Aircraft.Empennage.HorizontalTail.Planform.croot^2/Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.t*Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.Cmw*Mission1.Aircraft.Empennage.HorizontalTail.Planform.S*Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.rhosl*Mission1.Aircraft.Empennage.HorizontalTail.WingSkin.Vne^2
WingCore
Mission1.Aircraft.Empennage.HorizontalTail.WingCore.W >= 2*(g*FoamHD.rho*Mission1.Aircraft.Empennage.HorizontalTail.WingCore.Abar*cave[:]^2*Mission1.Aircraft.Empennage.HorizontalTail.Planform.b/2*deta[:]).sum()
mh*(1 + 2/Mission1.Aircraft.Empennage.HorizontalTail.Planform.AR) <= 6.28
VerticalTail
Mission1.Aircraft.Empennage.VerticalTail.W/Mission1.Aircraft.Empennage.VerticalTail.mfac >= Mission1.Aircraft.Empennage.VerticalTail.WingSkin.W + Mission1.Aircraft.Empennage.VerticalTail.WingCore.W
Planform
Mission1.Aircraft.Empennage.VerticalTail.Planform.b^2 = Mission1.Aircraft.Empennage.VerticalTail.Planform.S*Mission1.Aircraft.Empennage.VerticalTail.Planform.AR
cave[:] = cbave[:]*Mission1.Aircraft.Empennage.VerticalTail.Planform.S/Mission1.Aircraft.Empennage.VerticalTail.Planform.b
Mission1.Aircraft.Empennage.VerticalTail.Planform.croot = Mission1.Aircraft.Empennage.VerticalTail.Planform.S/Mission1.Aircraft.Empennage.VerticalTail.Planform.b*cbar[0]
Mission1.Aircraft.Empennage.VerticalTail.Planform.cmac = Mission1.Aircraft.Empennage.VerticalTail.Planform.croot*Mission1.Aircraft.Empennage.VerticalTail.Planform.cbarmac
WingSkin
Mission1.Aircraft.Empennage.VerticalTail.WingSkin.W >= CFRPFabric.rho*Mission1.Aircraft.Empennage.VerticalTail.Planform.S*2*Mission1.Aircraft.Empennage.VerticalTail.WingSkin.t*g
Mission1.Aircraft.Empennage.VerticalTail.WingSkin.t >= tmin
CFRPFabric.tau >= 1/Mission1.Aircraft.Empennage.VerticalTail.WingSkin.Jtbar/Mission1.Aircraft.Empennage.VerticalTail.Planform.croot^2/Mission1.Aircraft.Empennage.VerticalTail.WingSkin.t*Mission1.Aircraft.Empennage.VerticalTail.WingSkin.Cmw*Mission1.Aircraft.Empennage.VerticalTail.Planform.S*Mission1.Aircraft.Empennage.VerticalTail.WingSkin.rhosl*Mission1.Aircraft.Empennage.VerticalTail.WingSkin.Vne^2
WingCore
Mission1.Aircraft.Empennage.VerticalTail.WingCore.W >= 2*(g*FoamHD.rho*Mission1.Aircraft.Empennage.VerticalTail.WingCore.Abar*cave[:]^2*Mission1.Aircraft.Empennage.VerticalTail.Planform.b/2*deta[:]).sum()
TailBoom
I[:] <= PI*t[:]*d[:]^3/8
Sy[:] <= 2*I[:]/d[:]
dm[:] >= PI*CFRPFabric.rho*d[:]*Mission1.Aircraft.Empennage.TailBoom.deta*t[:]*kfac*Mission1.Aircraft.Empennage.TailBoom.l
Mission1.Aircraft.Empennage.TailBoom.W/Mission1.Aircraft.Empennage.TailBoom.mfac >= g*dm[:].sum()
t[:] >= tmin
Mission1.Aircraft.Empennage.TailBoom.S = Mission1.Aircraft.Empennage.TailBoom.l*PI*d[0]
Mission1.Aircraft.Empennage.TailBoom.b = 2*Mission1.Aircraft.Empennage.TailBoom.l
Mission1.Aircraft.Empennage.W/Mission1.Aircraft.Empennage.mfac >= Mission1.Aircraft.Empennage.HorizontalTail.W + Mission1.Aircraft.Empennage.VerticalTail.W + Mission1.Aircraft.Empennage.TailBoom.W
Mission1.Aircraft.Empennage.TailBoom.l >= lh
Mission1.Aircraft.Empennage.TailBoom.l >= lv
Pylon
Mission1.Aircraft.Pylon.S >= 2*Mission1.Aircraft.Pylon.l*Mission1.Aircraft.Pylon.h
W_{zfw} >= Mission1.Aircraft.Fuselage.W + Mission1.Aircraft.Wing.W + Mission1.Aircraft.DF70.W + Mission1.Aircraft.Empennage.W + Mission1.Aircraft.Pylon.W + W_{pay} + W_{avn}
Vh <= Mission1.Aircraft.Empennage.HorizontalTail.Planform.S*lh/Mission1.Aircraft.Wing.Planform.S^2*Mission1.Aircraft.Wing.Planform.b
Vv = Mission1.Aircraft.Empennage.VerticalTail.Planform.S*lv/Mission1.Aircraft.Wing.Planform.S/Mission1.Aircraft.Wing.Planform.b
Mission1.Aircraft.Wing.Planform.CLmax/mw <= Mission1.Aircraft.Empennage.HorizontalTail.Planform.CLmax/mh
w_{antenna} <= Mission1.Aircraft.Empennage.VerticalTail.Planform.croot*Mission1.Aircraft.Empennage.VerticalTail.Planform.lam
Mission1.Aircraft.Empennage.VerticalTail.Planform.b >= l_{antenna}
Mission1.Aircraft.Empennage.TailBoom.l >= lh + Mission1.Aircraft.Empennage.HorizontalTail.Planform.croot
\mathcal{V}_{pay} <= (PI/1.5)*k_{nose}*R^3
\mathcal{V}_{body} >= \mathcal{V} + \mathcal{V}_{avn}
Mission1.Aircraft.DF70.h <= 2*R and AircraftLoading
===============
Cost
----
1
Constraints
-----------
TailBoomBending
dx[:] = Mission1.Aircraft.Empennage.TailBoom.deta
qne[:]*Mission1.Aircraft.Empennage.HorizontalTail.Planform.S <= Mission1.AircraftLoading.TailBoomBending.F
\bar{EI}[:] <= CFRPFabric.E*I[:]/Mission1.AircraftLoading.TailBoomBending.F/l^2/2
Mr[:] >= \bar{M}[:-1]*Mission1.AircraftLoading.TailBoomBending.F*l
Mr[:]/Sy[:] <= CFRPFabric.sigma
Mission1.AircraftLoading.TailBoomBending.th = \theta[1]
Mission1.AircraftLoading.TailBoomBending.kappa >= \bar{\delta}[1]*Mission1.Aircraft.Empennage.HorizontalTail.Planform.CLmax*Mission1.AircraftLoading.TailBoomBending.Nsafety
Beam
\bar{M}[:-1] >= \bar{M}[1:] + 0.5*dx[:]*(\bar{S}[:-1] + \bar{S}[1:])
\bar{M}[1] >= Mission1.AircraftLoading.TailBoomBending.Beam.\bar{M}_{tip}
\theta[0] >= Mission1.AircraftLoading.TailBoomBending.Beam.\theta_{root}
\theta[1:] >= \theta[:-1] + 0.5*dx[:]*(\bar{M}[1:] + \bar{M}[:-1])/\bar{EI}[:]
\bar{\delta}[0] >= Mission1.AircraftLoading.TailBoomBending.Beam.\bar{\delta}_{root}
\bar{\delta}[1:] >= \bar{\delta}[:-1] + 0.5*dx[:]*(\theta[1:] + \theta[:-1])
TailBoomBending1
dx[:] = Mission1.Aircraft.Empennage.TailBoom.deta
qne[:]*Mission1.Aircraft.Empennage.VerticalTail.Planform.S <= Mission1.AircraftLoading.TailBoomBending1.F
\bar{EI}[:] <= CFRPFabric.E*I[:]/Mission1.AircraftLoading.TailBoomBending1.F/l^2/2
Mr[:] >= \bar{M}[:-1]*Mission1.AircraftLoading.TailBoomBending1.F*l
Mr[:]/Sy[:] <= CFRPFabric.sigma
Mission1.AircraftLoading.TailBoomBending1.th = \theta[1]
Mission1.AircraftLoading.TailBoomBending1.kappa >= \bar{\delta}[1]*Mission1.Aircraft.Empennage.VerticalTail.Planform.CLmax*Mission1.AircraftLoading.TailBoomBending1.Nsafety
Beam
\bar{M}[:-1] >= \bar{M}[1:] + 0.5*dx[:]*(\bar{S}[:-1] + \bar{S}[1:])
\bar{M}[1] >= Mission1.AircraftLoading.TailBoomBending1.Beam.\bar{M}_{tip}
\theta[0] >= Mission1.AircraftLoading.TailBoomBending1.Beam.\theta_{root}
\theta[1:] >= \theta[:-1] + 0.5*dx[:]*(\bar{M}[1:] + \bar{M}[:-1])/\bar{EI}[:]
\bar{\delta}[0] >= Mission1.AircraftLoading.TailBoomBending1.Beam.\bar{\delta}_{root}
\bar{\delta}[1:] >= \bar{\delta}[:-1] + 0.5*dx[:]*(\theta[1:] + \theta[:-1])
SparLoading
S[:-1] >= S[1:] + 0.5*deta[:]*b/2*(q[:-1] + q[1:])
M[:-1] >= M[1:] + 0.5*deta[:]*b/2*(S[:-1] + S[1:])
N = Mission1.AircraftLoading.SparLoading.Nsafety*Nmax
q[:] >= N*W/b*cbar[:]
S[11] >= Stip
M[11] >= Mtip
th[0] >= throot
th[1:] >= th[:-1] + 0.5*deta[:]*b/2*(M[1:] + M[:-1])/CFRPUD.E/I[:]
w[0] >= wroot
w[1:] >= w[:-1] + 0.5*deta[:]*b/2*(th[1:] + th[:-1])
M[:-1]/Sy[:] <= CFRPUD.sigma
Mission1.AircraftLoading.SparLoading.kappa >= w[11]/(b/2)
FuselageLoading
FuselageSkinL
M_h >= Mission1.AircraftLoading.FuselageLoading.FuselageSkinL.N_{max}*W_{cent}/4*l_{body}
Mission1.AircraftLoading.FuselageLoading.FuselageSkinL.\sigma_{Kevlar} >= M_h*R/Mission1.Aircraft.Fuselage.FuselageSkin.I
Mission1.AircraftLoading.FuselageLoading.FuselageSkinL.q >= W_{cent}*Mission1.AircraftLoading.FuselageLoading.FuselageSkinL.N_{max}/l_{body}
\kappa*l_{body}/2 >= Mission1.AircraftLoading.FuselageLoading.FuselageSkinL.q*(l_{body}/2)^4/8*Mission1.Aircraft.Fuselage.FuselageSkin.E*Mission1.Aircraft.Fuselage.FuselageSkin.I
FuselageLanding
Mission1.AircraftLoading.FuselageLoading.FuselageLanding.F >= W_{cent}*Mission1.AircraftLoading.FuselageLoading.FuselageLanding.N_{max}
a >= Mission1.AircraftLoading.FuselageLoading.FuselageLanding.F/m
\dot{\omega} >= a/(l_{body}/2)
M_G >= I_G*\dot{\omega}
Mission1.AircraftLoading.FuselageLoading.FuselageLanding.\sigma_{Kevlar} >= M_G*R/Mission1.Aircraft.Fuselage.FuselageSkin.I
TailBoomFlexibility
Fne >= 1 + mh*Mission1.AircraftLoading.TailBoomBending.th
sph1*mw*Fne/mh/Vh + deda <= 1
sph2 <= Vh*CLhmin/Mission1.Aircraft.Wing.Planform.CLmax
deda >= mw*Mission1.Aircraft.Wing.Planform.S/b/4/PI/lh
sph1 + sph2 >= SMcorr + CM/Mission1.Aircraft.Wing.Planform.CLmax.
----------------------------------------------------------------------
Ran 2 tests in 2.443s
FAILED (errors=2)
Generating XML reports...
Cloning into 'turbofan'...
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\turbofan
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from turbofan==0.0.0.0) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from turbofan==0.0.0.0) (1.5.1)
Requirement already satisfied: pint in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from turbofan==0.0.0.0) (0.9)
Requirement already satisfied: future in c:\anaconda3\lib\site-packages (from turbofan==0.0.0.0) (0.18.2)
Building wheels for collected packages: turbofan
Building wheel for turbofan (setup.py): started
Building wheel for turbofan (setup.py): finished with status 'done'
Created wheel for turbofan: filename=turbofan-0.0.0.0-py3-none-any.whl size=44145 sha256=995657e9da49e62f9af7137f6214397009531dd0d312c6ae78ac524b80f39ab6
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-37evphfu\wheels\8a\cf\c8\e6641237d4c8b318a2fb3b33b8c09ab0beefe8395db18dad6e
Successfully built turbofan
Installing collected packages: turbofan
Attempting uninstall: turbofan
Found existing installation: turbofan 0.0.0.0
Uninstalling turbofan-0.0.0.0:
Successfully uninstalled turbofan-0.0.0.0
Successfully installed turbofan-0.0.0.0
adding test for 'turbofan/engine_test.py'
Running tests...
----------------------------------------------------------------------
.
----------------------------------------------------------------------
Ran 1 test in 0.014s
OK
Generating XML reports...
Cloning into 'solar'...
Requirement already satisfied: pandas in c:\anaconda3\lib\site-packages (1.0.5)
Requirement already satisfied: python-dateutil>=2.6.1 in c:\anaconda3\lib\site-packages (from pandas) (2.8.1)
Requirement already satisfied: pytz>=2017.2 in c:\anaconda3\lib\site-packages (from pandas) (2020.1)
Requirement already satisfied: numpy>=1.13.3 in c:\anaconda3\lib\site-packages (from pandas) (1.19.0)
Requirement already satisfied: six>=1.5 in c:\anaconda3\lib\site-packages (from python-dateutil>=2.6.1->pandas) (1.15.0)
Collecting git+https://github.com/convexengineering/gpfit.git
Cloning https://github.com/convexengineering/gpfit.git to c:\users\jenkins\appdata\local\temp\pip-req-build-pt50oov0
Running command git clone -q https://github.com/convexengineering/gpfit.git 'C:\Users\jenkins\AppData\Local\Temp\pip-req-build-pt50oov0'
Requirement already satisfied (use --upgrade to upgrade): gpfit==0.1 from git+https://github.com/convexengineering/gpfit.git in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from gpfit==0.1) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from gpfit==0.1) (1.5.1)
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from gpfit==0.1) (1.0.0)
Requirement already satisfied: pint>=0.8.1 in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkit->gpfit==0.1) (0.9)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit->gpfit==0.1) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit->gpfit==0.1) (1.2.5)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit->gpfit==0.1) (2019.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit->gpfit==0.1) (2019.0)
Building wheels for collected packages: gpfit
Building wheel for gpfit (setup.py): started
Building wheel for gpfit (setup.py): finished with status 'done'
Created wheel for gpfit: filename=gpfit-0.1-py3-none-any.whl size=25631 sha256=cf835f7f8dd7ead9a3820387f714fb152f389db5422a6c75e910cbb81f33dc91
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-lrv339hn\wheels\68\65\b3\0afb13c0a818424d0e07427d1c5a4312849fc7491f18bd34a0
Successfully built gpfit
Collecting git+https://github.com/convexengineering/gassolar.git
Cloning https://github.com/convexengineering/gassolar.git to c:\users\jenkins\appdata\local\temp\pip-req-build-ry8mn9fo
Running command git clone -q https://github.com/convexengineering/gassolar.git 'C:\Users\jenkins\AppData\Local\Temp\pip-req-build-ry8mn9fo'
Requirement already satisfied (use --upgrade to upgrade): gassolar==0.0.0.0 from git+https://github.com/convexengineering/gassolar.git in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from gassolar==0.0.0.0) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from gassolar==0.0.0.0) (1.5.1)
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from gassolar==0.0.0.0) (1.0.0)
Requirement already satisfied: pandas in c:\anaconda3\lib\site-packages (from gassolar==0.0.0.0) (1.0.5)
Requirement already satisfied: gpfit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gassolar==0.0.0.0) (0.1)
Requirement already satisfied: pint>=0.8.1 in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkit->gassolar==0.0.0.0) (0.9)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit->gassolar==0.0.0.0) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit->gassolar==0.0.0.0) (1.2.5)
Requirement already satisfied: python-dateutil>=2.6.1 in c:\anaconda3\lib\site-packages (from pandas->gassolar==0.0.0.0) (2.8.1)
Requirement already satisfied: pytz>=2017.2 in c:\anaconda3\lib\site-packages (from pandas->gassolar==0.0.0.0) (2020.1)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit->gassolar==0.0.0.0) (2019.0)
Requirement already satisfied: six>=1.5 in c:\anaconda3\lib\site-packages (from python-dateutil>=2.6.1->pandas->gassolar==0.0.0.0) (1.15.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit->gassolar==0.0.0.0) (2019.0)
Building wheels for collected packages: gassolar
Building wheel for gassolar (setup.py): started
Building wheel for gassolar (setup.py): finished with status 'done'
Created wheel for gassolar: filename=gassolar-0.0.0.0-py3-none-any.whl size=4895568 sha256=85e3e3923196a379d5a1c00d27861bcaea0a0324f86dc47833b18c7512c2811e
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-x7t9p92j\wheels\84\16\d2\54d8f9e64f486a627f1c5353e5786ffa7a35c88bec592de580
Successfully built gassolar
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\solar
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from solar==0.0.0.0) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from solar==0.0.0.0) (1.5.1)
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from solar==0.0.0.0) (1.0.0)
Requirement already satisfied: pandas in c:\anaconda3\lib\site-packages (from solar==0.0.0.0) (1.0.5)
Requirement already satisfied: gpfit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from solar==0.0.0.0) (0.1)
Requirement already satisfied: gpkitmodels in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gplibrary (from solar==0.0.0.0) (0.0.0.0)
Requirement already satisfied: pint>=0.8.1 in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkit->solar==0.0.0.0) (0.9)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit->solar==0.0.0.0) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit->solar==0.0.0.0) (1.2.5)
Requirement already satisfied: pytz>=2017.2 in c:\anaconda3\lib\site-packages (from pandas->solar==0.0.0.0) (2020.1)
Requirement already satisfied: python-dateutil>=2.6.1 in c:\anaconda3\lib\site-packages (from pandas->solar==0.0.0.0) (2.8.1)
Requirement already satisfied: future in c:\anaconda3\lib\site-packages (from gpkitmodels->solar==0.0.0.0) (0.18.2)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit->solar==0.0.0.0) (2019.0)
Requirement already satisfied: six>=1.5 in c:\anaconda3\lib\site-packages (from python-dateutil>=2.6.1->pandas->solar==0.0.0.0) (1.15.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit->solar==0.0.0.0) (2019.0)
Building wheels for collected packages: solar
Building wheel for solar (setup.py): started
Building wheel for solar (setup.py): finished with status 'done'
Created wheel for solar: filename=solar-0.0.0.0-py3-none-any.whl size=14959 sha256=991427dd1f86737cd20cace5833569477ee2dbd17cd9b5b4729caa0d118b9f0c
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-9qq5czmz\wheels\d0\b1\e6\cfdfa6a79426f3c9ac822b9884ce7cc02391bcb2bb75b48230
Successfully built solar
Installing collected packages: solar
Successfully installed solar-0.0.0.0
adding test for 'solar/sens_chart.py'
adding test for 'solar/season.py'
adding test for 'solar/npod_trade.py'
Running tests...
----------------------------------------------------------------------
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
.
N=1
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 3.63 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
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 3.36 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
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 3.3 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
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 2.88 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
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 3.09 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
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 2.51 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
Using solver 'mosek_cli'
for 7672 free variables
in 10814 posynomial inequalities.
Solving took 3.13 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
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages\gassolar\environment\solar_irradiance.py:40: RuntimeWarning: overflow encountered in exp
tau = np.exp(-0.175/costhsun)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
.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 2.4 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
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\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"])]
C:\Anaconda3\lib\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
.
----------------------------------------------------------------------
Ran 3 tests in 46.607s
OK
Generating XML reports...
fatal: destination path 'gplibrary' already exists and is not an empty directory.
fatal: destination path 'gplibrary' already exists and is not an empty directory.
fatal: destination path 'gplibrary' already exists and is not an empty directory.
fatal: destination path 'gplibrary' already exists and is not an empty directory.
fatal: destination path 'gplibrary' already exists and is not an empty directory.
Requirement already satisfied: pandas in c:\anaconda3\lib\site-packages (1.0.5)
Requirement already satisfied: pytz>=2017.2 in c:\anaconda3\lib\site-packages (from pandas) (2020.1)
Requirement already satisfied: numpy>=1.13.3 in c:\anaconda3\lib\site-packages (from pandas) (1.19.0)
Requirement already satisfied: python-dateutil>=2.6.1 in c:\anaconda3\lib\site-packages (from pandas) (2.8.1)
Requirement already satisfied: six>=1.5 in c:\anaconda3\lib\site-packages (from python-dateutil>=2.6.1->pandas) (1.15.0)
Collecting git+https://github.com/hoburg/gpfit.git
Cloning https://github.com/hoburg/gpfit.git to c:\users\jenkins\appdata\local\temp\pip-req-build-nzoxchgr
Running command git clone -q https://github.com/hoburg/gpfit.git 'C:\Users\jenkins\AppData\Local\Temp\pip-req-build-nzoxchgr'
Requirement already satisfied (use --upgrade to upgrade): gpfit==0.1 from git+https://github.com/hoburg/gpfit.git in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages
Requirement already satisfied: numpy in c:\anaconda3\lib\site-packages (from gpfit==0.1) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from gpfit==0.1) (1.5.1)
Requirement already satisfied: gpkit in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek (from gpfit==0.1) (1.0.0)
Requirement already satisfied: pint>=0.8.1 in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkit->gpfit==0.1) (0.9)
Requirement already satisfied: ad in c:\anaconda3\lib\site-packages (from gpkit->gpfit==0.1) (1.3.2)
Requirement already satisfied: cvxopt>=1.1.8 in c:\anaconda3\lib\site-packages (from gpkit->gpfit==0.1) (1.2.5)
Requirement already satisfied: mkl in c:\anaconda3\lib\site-packages (from cvxopt>=1.1.8->gpkit->gpfit==0.1) (2019.0)
Requirement already satisfied: intel-openmp in c:\anaconda3\lib\site-packages (from mkl->cvxopt>=1.1.8->gpkit->gpfit==0.1) (2019.0)
Building wheels for collected packages: gpfit
Building wheel for gpfit (setup.py): started
Building wheel for gpfit (setup.py): finished with status 'done'
Created wheel for gpfit: filename=gpfit-0.1-py3-none-any.whl size=25631 sha256=ee7daddf0fe90c9ab68ec6cc61b5706299114f854ac16ffe177d5c788de1b495
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-ch1epc2q\wheels\57\29\3e\8d7ba8db76ea975ecfe679ec45f25d64a6eaec893d16b3d378
Successfully built gpfit
Processing c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\gplibrary
Requirement already satisfied: numpy>=1.12 in c:\anaconda3\lib\site-packages (from gpkitmodels==0.0.0.0) (1.19.0)
Requirement already satisfied: scipy in c:\anaconda3\lib\site-packages (from gpkitmodels==0.0.0.0) (1.5.1)
Requirement already satisfied: pint in c:\users\jenkins\workspace\ce_gpkit_pr_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\lib\site-packages (from gpkitmodels==0.0.0.0) (0.9)
Requirement already satisfied: future in c:\anaconda3\lib\site-packages (from gpkitmodels==0.0.0.0) (0.18.2)
Building wheels for collected packages: gpkitmodels
Building wheel for gpkitmodels (setup.py): started
Building wheel for gpkitmodels (setup.py): finished with status 'done'
Created wheel for gpkitmodels: filename=gpkitmodels-0.0.0.0-py3-none-any.whl size=66720 sha256=d8b261de59deade73fd25fc70995e4dd0d3f0657d7845ff1bffe25321c21cc94
Stored in directory: C:\Users\jenkins\AppData\Local\Temp\pip-ephem-wheel-cache-_ia4xnag\wheels\3a\08\1c\526fc9a8cf18eb28480014ce08b336c1b19614a06a54e4184c
Successfully built gpkitmodels
Installing collected packages: gpkitmodels
Attempting uninstall: gpkitmodels
Found existing installation: gpkitmodels 0.0.0.0
Uninstalling gpkitmodels-0.0.0.0:
Successfully uninstalled gpkitmodels-0.0.0.0
Successfully installed gpkitmodels-0.0.0.0
adding test for 'gpkitmodels/GP/aircraft/wing/wing_test.py'
adding test for 'gpkitmodels/GP/aircraft/tail/tail_tests.py'
adding test for 'gpkitmodels/GP/aircraft/fuselage/test_fuselage.py'
adding test for 'gpkitmodels/GP/aircraft/prop/prop_test.py'
adding test for 'gpkitmodels/GP/aircraft/motor/motor_test.py'
adding test for 'gpkitmodels/SP/SimPleAC/SimPleAC.py'
adding test for 'gpkitmodels/SP/SimPleAC/SimPleAC_mission.py'
adding test for 'gpkitmodels/SP/SimPleAC/SimPleAC_multimission.py'
Running tests...
----------------------------------------------------------------------
Using solver 'mosek_cli'
for 11 free variables
in 14 posynomial inequalities.
Solving took 0.189 seconds.
.Using solver 'mosek_cli'
for 9 free variables
in 15 posynomial inequalities.
Solving took 0.143 seconds.
Using solver 'mosek_cli'
for 25 free variables
in 35 posynomial inequalities.
Solving took 0.141 seconds.
Using solver 'mosek_cli'
for 25 free variables
in 35 posynomial inequalities.
Solving took 0.151 seconds.
Starting a sequence of GP solves
for 53 free variables
in 11 locally-GP constraints
and for 129 free variables
in 211 posynomial inequalities.
Solving took 3.62 seconds and 16 GP solves.
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
.Using solver 'mosek_cli'
for 13 free variables
in 16 posynomial inequalities.
Solving took 0.171 seconds.
Starting a sequence of GP solves
for 53 free variables
in 11 locally-GP constraints
and for 117 free variables
in 190 posynomial inequalities.
Solving took 2.43 seconds and 11 GP solves.
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
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
.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 2223871.1577 but bound is 1000000.0000
Warning: Variable TailAero3.Re could cause inaccurate result because it is above upper bound. Solution is 2223871.1577 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
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
.Warning: Variable WingAero.Re could cause inaccurate result because it is above upper bound. Solution is 1884889.9591 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
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek\venv_gpkit\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)
..SGP not convergent: Cost rose by 6.1% on GP solve 2. 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.
SGP not convergent: Cost rose by 25% on GP solve 2. 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.
SGP not convergent: Cost rose by 0.32% 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.
.Starting a sequence of GP solves
for 4 free variables
in 1 locally-GP constraints
and for 21 free variables
in 22 posynomial inequalities.
GP Solve 1
Using solver 'mosek_cli'
for 21 free variables
in 22 posynomial inequalities.
Solving took 0.146 seconds.
Solved cost was 5717.
GP Solve 2
Using solver 'mosek_cli'
for 21 free variables
in 22 posynomial inequalities.
Solving took 0.152 seconds.
Solved cost was 4538.
GP Solve 3
Using solver 'mosek_cli'
for 21 free variables
in 22 posynomial inequalities.
Solving took 0.133 seconds.
Solved cost was 4536.
GP Solve 4
Using solver 'mosek_cli'
for 21 free variables
in 22 posynomial inequalities.
Solving took 0.19 seconds.
Solved cost was 4536.
Solving took 0.635 seconds and 4 GP solves.
.
----------------------------------------------------------------------
Ran 8 tests in 14.098s
OK
Generating XML reports...
Cloning into 'eVTOL'...
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adding test for 'models/model_tests.py'
Running tests...
----------------------------------------------------------------------
.
----------------------------------------------------------------------
Ran 1 test in 3.295s
OK
Generating XML reports...
----------------------------------------------------------------------
Ran 187 tests in 49.599s
OK
Found no installed solvers, beginning a build.
# Building GPkit version 1.0.0pre
# Moving to the directory from which GPkit was imported.
Attempting to find and build solvers:
# Looking for `mosek_cli`
# (A "success" is if mskexpopt complains that
# we haven't specified a file for it to open.)
# Calling 'mskexpopt'
##
### CALL BEGINS
### CALL ENDS
##
Found mosek_cli in the default PATH
# Looking for `mosek_conif`
# Trying to import mosek...
# Did not find
# mosek_conif
# Looking for `cvxopt`
# Trying to import cvxopt...
Found cvxopt in the default PYTHONPATH
Replaced found solvers (['mosek_cli', 'cvxopt']) with environment var GPKITSOLVERS (mosek_cli)
Found the following solvers: mosek_cli
# Replacing directory env
GPkit is now installed with solver(s) ['mosek_cli']
To incorporate new solvers at a later date, run `gpkit.build()`.
If any tests didn't pass, please post the output above
(starting from "Found no installed solvers, beginning a build.")
to gpkit@mit.edu or https://github.com/convexengineering/gpkit/issues/new
so we can prevent others from having these errors.
The same goes for any other bugs you encounter with GPkit:
send 'em our way, along with any interesting models, speculative features,
comments, discussions, or clarifications you feel like sharing.
Finally, we hope you find our documentation (https://gpkit.readthedocs.io/)
and engineering-design models (https://github.com/convexengineering/gplibrary/)
to be useful resources for your own applications.
Enjoy!
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/gplibrary.git']
attempt 1
calling ['pip', 'install', '--no-cache-dir', '--no-deps', '-e', 'gplibrary']
attempt 1
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/SPaircraft.git']
attempt 1
SETTINGS
defaultdict(<class 'str'>, {'skipsolvers': 'cvxopt', 'pip install': 'git+https://github.com/hoburg/turbofan.git', 'gpkit-models branch': 'master'})
calling ['pip', 'install', 'git+https://github.com/hoburg/turbofan.git']
attempt 1
calling ['pip', 'install', '.']
attempt 1
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/robust.git']
attempt 1
SETTINGS
defaultdict(<class 'str'>, {})
calling ['pip', 'install', '.']
attempt 1
attempt 2
attempt 3
attempt 4
attempt 5
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/shopping.git']
attempt 1
SETTINGS
defaultdict(<class 'str'>, {})
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/gassolar.git']
attempt 1
SETTINGS
defaultdict(<class 'str'>, {'pip install': 'pandas, git+https://github.com/hoburg/gpfit.git', 'gpkit-models branch': 'master', 'skipsolvers': 'cvxopt'})
calling ['pip', 'install', 'pandas']
attempt 1
calling ['pip', 'install', 'git+https://github.com/hoburg/gpfit.git']
attempt 1
calling ['pip', 'install', '.']
attempt 1
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/jho.git']
attempt 1
SETTINGS
defaultdict(<class 'str'>, {'pip install': 'pandas, git+https://github.com/hoburg/gpfit.git', 'gpkit-models branch': 'master', 'skipsolvers': 'cvxopt'})
calling ['pip', 'install', 'pandas']
attempt 1
calling ['pip', 'install', 'git+https://github.com/hoburg/gpfit.git']
attempt 1
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/turbofan.git']
attempt 1
SETTINGS
defaultdict(<class 'str'>, {'skipsolvers': 'cvxopt, mosek_cli', 'gpkit-models branch': 'master'})
calling ['pip', 'install', '.']
attempt 1
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/solar.git']
attempt 1
SETTINGS
defaultdict(<class 'str'>, {'pip install': 'pandas, git+https://github.com/convexengineering/gpfit.git, git+https://github.com/convexengineering/gassolar.git', 'gpkit-models branch': 'master', 'skipsolvers': 'cvxopt'})
calling ['pip', 'install', 'pandas']
attempt 1
calling ['pip', 'install', 'git+https://github.com/convexengineering/gpfit.git']
attempt 1
calling ['pip', 'install', 'git+https://github.com/convexengineering/gassolar.git']
attempt 1
calling ['pip', 'install', '.']
attempt 1
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/gplibrary.git']
attempt 1
attempt 2
attempt 3
attempt 4
attempt 5
SETTINGS
defaultdict(<class 'str'>, {'pip install': 'pandas, git+https://github.com/hoburg/gpfit.git'})
calling ['pip', 'install', 'pandas']
attempt 1
calling ['pip', 'install', 'git+https://github.com/hoburg/gpfit.git']
attempt 1
calling ['pip', 'install', '.']
attempt 1
calling ['git', 'clone', '--depth', '1', '-b', 'master', 'https://github.com/convexengineering/eVTOL.git']
attempt 1
SETTINGS
defaultdict(<class 'str'>, {'skipsolvers': 'cvxopt'})
(venv_gpkit) C:\Users\jenkins\workspace\CE_gpkit_PR_research_models\buildnode\windows10x64\optimizer\mosek>exit 0
Build step 'Console output (build log) parsing' changed build result to FAILURE
Recording test results
[WS-CLEANUP] Deleting project workspace...
[WS-CLEANUP] Deferred wipeout is used...
[WS-CLEANUP] done
Finished: FAILURE
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