Console Output

Started by upstream project "CE_gpkit_PR_unit_tests" build number 3223
originally caused by:
 GitHub pull request #1570 of commit 7a1d69fa19e2f12c4b7864a6380a43d2f979cba9, no merge conflicts.
Running as SYSTEM
[EnvInject] - Loading node environment variables.
Building remotely on windows10x64 in workspace C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt
The recommended git tool is: NONE
using credential 3614a4cf-01de-4393-97de-73734b7dd5a2
Wiping out workspace first.
Cloning the remote Git repository
Cloning repository https://github.com/convexengineering/gpkit
 > git init C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt # timeout=10
Fetching upstream changes from https://github.com/convexengineering/gpkit
 > git --version # timeout=10
 > git --version # 'git version 2.33.0.windows.2'
using GIT_SSH to set credentials 
 > git fetch --tags --force --progress -- https://github.com/convexengineering/gpkit +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/convexengineering/gpkit # timeout=10
 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/convexengineering/gpkit # timeout=10
Fetching upstream changes from https://github.com/convexengineering/gpkit
using GIT_SSH to set credentials 
 > git fetch --tags --force --progress -- https://github.com/convexengineering/gpkit +refs/pull/*:refs/remotes/origin/pr/* +refs/heads/master:refs/remotes/origin/master # timeout=10
Merging Revision e720d6bc7895d37e7d0adf63d95187bced49a9e0 (refs/remotes/origin/pr/1570/merge) to origin/master, UserMergeOptions{mergeRemote='origin', mergeTarget='master', mergeStrategy='DEFAULT', fastForwardMode='FF'}
 > git rev-parse "origin/master^{commit}" # timeout=10
 > git config core.sparsecheckout # timeout=10
 > git checkout -f origin/master # timeout=3
 > git remote # timeout=10
 > git config --get remote.origin.url # timeout=10
using GIT_SSH to set credentials 
 > git merge --ff e720d6bc7895d37e7d0adf63d95187bced49a9e0 # timeout=10
 > git rev-parse "HEAD^{commit}" # timeout=10
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 > git show-ref --tags -d # timeout=10
JENKINS-19022: warning: possible memory leak due to Git plugin usage; see: https://plugins.jenkins.io/git/#remove-git-plugin-buildsbybranch-builddata-script
Checking out Revision e720d6bc7895d37e7d0adf63d95187bced49a9e0 (origin/pr/1570/merge, origin/master)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f e720d6bc7895d37e7d0adf63d95187bced49a9e0 # timeout=3
Commit message: "Merge 7a1d69fa19e2f12c4b7864a6380a43d2f979cba9 into 5480de33feb08aa679079f414bfd4da070b52caf"
Using 'Changelog to branch' strategy.
The recommended git tool is: NONE
using credential 3614a4cf-01de-4393-97de-73734b7dd5a2
 > git rev-parse "e720d6bc7895d37e7d0adf63d95187bced49a9e0^{commit}" # timeout=10
The recommended git tool is: NONE
using credential 3614a4cf-01de-4393-97de-73734b7dd5a2
[GitCheckoutListener] Recording commits of 'git https://github.com/convexengineering/gpkit'
[GitCheckoutListener] Found previous build 'CE_gpkit_PR_unit_tests/buildnode=windows10x64,optimizer=cvxopt #3222' that contains recorded Git commits
[GitCheckoutListener] -> Starting recording of new commits since '825a6a8'
[GitCheckoutListener] -> Using head commit 'e720d6b' as starting point
[GitCheckoutListener] -> Git commit decorator successfully obtained 'hudson.plugins.git.browser.GithubWeb@14aafdb9' to render commit links
[GitCheckoutListener] -> Recorded 200 new commits
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="allow ast printing to be excluded, add .inner() method to nomialarray" href="https://github.com/convexengineering/gpkit/pull/1570">PR 1570</a>: allow ast printing to be excluded, add .inner() method to nomialarray
[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]]
Run condition [Execution node ] enabling perform for step [Execute Windows batch command]
[cvxopt] $ cmd /c call C:\Users\jenkins\AppData\Local\Temp\jenkins9721484851091362858.bat

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>REM download test scripts 

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>git clone ssh://acdl.mit.edu/home/svnroot/JenkinsGPkit 
Cloning into 'JenkinsGPkit'...

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>REM run tests 

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>call C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\JenkinsGPkit\gpkit_unit_tests.bat  

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>REM turn on the anaconda console 

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>call JenkinsGPKit/conda_activate.bat 

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>REM turn on the anaconda console 

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>call C:\Miniconda3\Scripts\activate.bat 

(base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>if 0 NEQ 0 goto activate_conda 

(base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>echo on 

(base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>virtualenv --system-site-packages C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins 
created virtual environment CPython3.9.12.final.0-64 in 4682ms
  creator CPython3Windows(dest=C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins, clear=False, no_vcs_ignore=False, global=True)
  seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=C:\Users\jenkins\AppData\Local\pypa\virtualenv)
    added seed packages: pip==22.0.4, setuptools==60.10.0, wheel==0.37.1
  activators BashActivator,BatchActivator,FishActivator,PowerShellActivator,PythonActivator,XonshActivator

(base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>call C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins\Scripts\activate.bat 
gcc (x86_64-posix-seh-rev0, Built by MinGW-W64 project) 6.4.0
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

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Requirement already satisfied: six>=1.5 in c:\miniconda3\lib\site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)
Installing collected packages: pyparsing, pillow, kiwisolver, fonttools, cycler, packaging, matplotlib
Successfully installed cycler-0.11.0 fonttools-4.32.0 kiwisolver-1.4.2 matplotlib-3.5.1 packaging-21.3 pillow-9.1.0 pyparsing-3.0.8
Collecting coverage
  Using cached coverage-6.3.2-cp39-cp39-win_amd64.whl (187 kB)
Installing collected packages: coverage
Successfully installed coverage-6.3.2
Requirement already satisfied: numpy in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_jenkins\lib\site-packages (1.22.3)
Collecting scipy
  Using cached scipy-1.8.0-cp39-cp39-win_amd64.whl (36.9 MB)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_jenkins\lib\site-packages (from scipy) (1.22.3)
Installing collected packages: scipy
Successfully installed scipy-1.8.0
Collecting pint
  Using cached Pint-0.19.1-py3-none-any.whl
Installing collected packages: pint
Successfully installed pint-0.19.1
Collecting ipysankeywidget
  Using cached ipysankeywidget-0.4.1-py2.py3-none-any.whl (1.2 MB)
Collecting ipywidgets>=7.0.0
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Collecting widgetsnbextension~=3.6.0
  Using cached widgetsnbextension-3.6.0-py2.py3-none-any.whl (1.6 MB)
Collecting ipython>=4.0.0
  Using cached ipython-8.2.0-py3-none-any.whl (750 kB)
Collecting ipython-genutils~=0.2.0
  Using cached ipython_genutils-0.2.0-py2.py3-none-any.whl (26 kB)
Collecting ipykernel>=4.5.1
  Using cached ipykernel-6.13.0-py3-none-any.whl (131 kB)
Collecting nbformat>=4.2.0
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Collecting traitlets>=4.3.1
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Collecting jupyterlab-widgets>=1.0.0
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Collecting debugpy>=1.0
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Collecting tornado>=6.1
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Collecting nest-asyncio
  Using cached nest_asyncio-1.5.5-py3-none-any.whl (5.2 kB)
Collecting jupyter-client>=6.1.12
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  Using cached psutil-5.9.0-cp39-cp39-win_amd64.whl (245 kB)
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Collecting matplotlib-inline>=0.1
  Using cached matplotlib_inline-0.1.3-py3-none-any.whl (8.2 kB)
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  Using cached stack_data-0.2.0-py3-none-any.whl (21 kB)
Collecting decorator
  Using cached decorator-5.1.1-py3-none-any.whl (9.1 kB)
Requirement already satisfied: setuptools>=18.5 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_jenkins\lib\site-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->ipysankeywidget) (60.10.0)
Collecting pygments>=2.4.0
  Using cached Pygments-2.11.2-py3-none-any.whl (1.1 MB)
Collecting backcall
  Using cached backcall-0.2.0-py2.py3-none-any.whl (11 kB)
Collecting pickleshare
  Using cached pickleshare-0.7.5-py2.py3-none-any.whl (6.9 kB)
Collecting jedi>=0.16
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Requirement already satisfied: colorama in c:\miniconda3\lib\site-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->ipysankeywidget) (0.4.4)
Collecting prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0
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Collecting jsonschema>=2.6
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Collecting jupyter-core
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Collecting notebook>=4.4.1
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Collecting parso<0.9.0,>=0.8.0
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Collecting pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0
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Collecting entrypoints
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Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_jenkins\lib\site-packages (from jupyter-client>=6.1.12->ipykernel>=4.5.1->ipywidgets>=7.0.0->ipysankeywidget) (2.8.2)
Collecting pyzmq>=22.3
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Requirement already satisfied: pywin32>=1.0 in c:\miniconda3\lib\site-packages (from jupyter-core->nbformat>=4.2.0->ipywidgets>=7.0.0->ipysankeywidget) (302)
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Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_jenkins\lib\site-packages (from packaging->ipykernel>=4.5.1->ipywidgets>=7.0.0->ipysankeywidget) (3.0.8)
WARNING: Skipping page https://pypi.org/simple/executing/ because the GET request got Content-Type: .The only supported Content-Type is text/html
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  Using cached jedi-0.18.0-py2.py3-none-any.whl (1.4 MB)
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  Using cached debugpy-1.5.1-cp39-cp39-win_amd64.whl (4.4 MB)
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Installing collected packages: webencodings, wcwidth, Send2Trash, pickleshare, mistune, ipython-genutils, fastjsonschema, backcall, traitlets, tornado, tinycss2, soupsieve, pyzmq, pywinpty, pyrsistent, pygments, psutil, prompt-toolkit, prometheus-client, parso, pandocfilters, nest-asyncio, MarkupSafe, jupyterlab-widgets, jupyterlab-pygments, entrypoints, defusedxml, decorator, debugpy, bleach, attrs, terminado, matplotlib-inline, jupyter-core, jsonschema, jinja2, jedi, beautifulsoup4, argon2-cffi-bindings, nbformat, jupyter-client, ipython, argon2-cffi, nbclient, ipykernel, nbconvert, notebook, widgetsnbextension, ipywidgets, ipysankeywidget
Successfully installed MarkupSafe-2.1.1 Send2Trash-1.8.0 argon2-cffi-21.3.0 argon2-cffi-bindings-21.2.0 attrs-21.4.0 backcall-0.2.0 beautifulsoup4-4.11.1 bleach-5.0.0 debugpy-1.6.0 decorator-5.1.1 defusedxml-0.7.1 entrypoints-0.4 fastjsonschema-2.15.3 ipykernel-6.13.0 ipysankeywidget-0.4.1 ipython-7.32.0 ipython-genutils-0.2.0 ipywidgets-7.7.0 jedi-0.18.1 jinja2-3.1.1 jsonschema-4.4.0 jupyter-client-7.2.2 jupyter-core-4.10.0 jupyterlab-pygments-0.2.2 jupyterlab-widgets-1.1.0 matplotlib-inline-0.1.3 mistune-0.8.4 nbclient-0.6.0 nbconvert-6.5.0 nbformat-5.3.0 nest-asyncio-1.5.5 notebook-6.4.11 pandocfilters-1.5.0 parso-0.8.3 pickleshare-0.7.5 prometheus-client-0.14.1 prompt-toolkit-3.0.29 psutil-5.9.0 pygments-2.11.2 pyrsistent-0.18.1 pywinpty-2.0.5 pyzmq-22.3.0 soupsieve-2.3.2.post1 terminado-0.13.3 tinycss2-1.1.1 tornado-6.1 traitlets-5.1.1 wcwidth-0.2.5 webencodings-0.5.1 widgetsnbextension-3.6.0
Collecting plotly
  Using cached plotly-5.7.0-py2.py3-none-any.whl (28.8 MB)
Requirement already satisfied: six in c:\miniconda3\lib\site-packages (from plotly) (1.16.0)
Collecting tenacity>=6.2.0
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Installing collected packages: tenacity, plotly
Successfully installed plotly-5.7.0 tenacity-8.0.1
Collecting cvxopt
  Using cached cvxopt-1.3.0-cp39-cp39-win_amd64.whl (12.7 MB)
Installing collected packages: cvxopt
Successfully installed cvxopt-1.3.0
1.3.0
1.8.0
1.22.3
0.19.1
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_unit_tests\cvxopt\gpkit\small_scripts.py:71: SyntaxWarning: "is" with a literal. Did you mean "=="?
  if sweep is "sweep" and (isinstance(value, Iterable) or  # pylint: disable=literal-comparison
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\nomials\math.py:586: SyntaxWarning: "is" with a literal. Did you mean "=="?
  if posy is 0:  # pylint: disable=literal-comparison
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\nomials\math.py:590: SyntaxWarning: "is" with a literal. Did you mean "=="?
  if negy is 0:  # pylint: disable=literal-comparison
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\breakdowns.py:390: SyntaxWarning: "is" with a literal. Did you mean "=="?
  subhmap.units = None if units is 1 else units
..........................................................................................................................................................................E......................................
======================================================================
ERROR: test_breakdowns_cvxopt (gpkit.tests.t_examples.TestExamples)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\tests\helpers.py", line 55, in test
    testfn(name, import_dict, path)(self)
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\tests\helpers.py", line 90, in test
    imported[name] = importlib.import_module(name)
  File "C:\Miniconda3\lib\importlib\__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1030, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1007, in _find_and_load
  File "<frozen importlib._bootstrap>", line 986, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 680, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 850, in exec_module
  File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\breakdowns.py", line 11, in <module>
    sol = pickle.load(open(dirpath+"solar_13.p", "rb"))
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins\lib\site-packages\pint\util.py", line 429, in __setstate__
    self._d, self._one, self._non_int_type = state
ValueError: too many values to unpack (expected 3)

----------------------------------------------------------------------
Ran 209 tests in 15.146s

FAILED (errors=1)
Found no installed solvers, beginning a build.
# Building GPkit version 1.1
# 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 (cvxopt)

Found the following solvers: cvxopt
#     Replacing directory env

GPkit is now installed with solver(s) ['cvxopt']
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': ['cvxopt'], 'default_solver': 'cvxopt', 'just built!': True}

Running tests...
----------------------------------------------------------------------
..........................................................................................................................................................................E......................................
======================================================================
ERROR [0.027s]: test_breakdowns_cvxopt (gpkit.tests.t_examples.TestExamples)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\tests\helpers.py", line 55, in test
    testfn(name, import_dict, path)(self)
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\tests\helpers.py", line 90, in test
    imported[name] = importlib.import_module(name)
  File "C:\Miniconda3\lib\importlib\__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1030, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1007, in _find_and_load
  File "<frozen importlib._bootstrap>", line 986, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 680, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 850, in exec_module
  File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\breakdowns.py", line 11, in <module>
    sol = pickle.load(open(dirpath+"solar_13.p", "rb"))
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins\lib\site-packages\pint\util.py", line 429, in __setstate__
    self._d, self._one, self._non_int_type = state
ValueError: too many values to unpack (expected 3)

----------------------------------------------------------------------
Ran 209 tests in 15.253s

FAILED (errors=1)

Generating XML reports...
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins\lib\site-packages\coverage\control.py:793: CoverageWarning: No data was collected. (no-data-collected)
  self._warn("No data was collected.", slug="no-data-collected")
hello world
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\breakdowns.py:390: SyntaxWarning: "is" with a literal. Did you mean "=="?
  subhmap.units = None if units is 1 else units
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\nomials\math.py:586: SyntaxWarning: "is" with a literal. Did you mean "=="?
  if posy is 0:  # pylint: disable=literal-comparison
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\nomials\math.py:590: SyntaxWarning: "is" with a literal. Did you mean "=="?
  if negy is 0:  # pylint: disable=literal-comparison
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\small_scripts.py:71: SyntaxWarning: "is" with a literal. Did you mean "=="?
  if sweep is "sweep" and (isinstance(value, Iterable) or  # pylint: disable=literal-comparison
Wrote HTML report to htmlcov\index.html
Obtaining file:///C:/Users/jenkins/workspace/CE_gpkit_PR_unit_tests/cvxopt
  Preparing metadata (setup.py): started
  Preparing metadata (setup.py): finished with status 'done'
Installing collected packages: gpkit
  Running setup.py develop for gpkit
Successfully installed gpkit
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.]
..........................................................................................................................................................................E......................................
======================================================================
ERROR: test_breakdowns_cvxopt (gpkit.tests.t_examples.TestExamples)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\gpkit\tests\helpers.py", line 55, in test
    testfn(name, import_dict, path)(self)
  File "c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\gpkit\tests\helpers.py", line 90, in test
    imported[name] = importlib.import_module(name)
  File "C:\Miniconda3\lib\importlib\__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1030, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1007, in _find_and_load
  File "<frozen importlib._bootstrap>", line 986, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 680, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 850, in exec_module
  File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\breakdowns.py", line 11, in <module>
    sol = pickle.load(open(dirpath+"solar_13.p", "rb"))
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins\lib\site-packages\pint\util.py", line 429, in __setstate__
    self._d, self._one, self._non_int_type = state
ValueError: too many values to unpack (expected 3)

----------------------------------------------------------------------
Ran 209 tests in 14.428s

FAILED (errors=1)
Found no installed solvers, beginning a build.
# Building GPkit version 1.1
# 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 (cvxopt)

Found the following solvers: cvxopt
#     Replacing directory env

GPkit is now installed with solver(s) ['cvxopt']
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!

Solved after 33 passes, cost logtol +/-0.000992
values of l: [ 1.  2.  3.  4.  5.  6.  7.  8.  9. 10.]
values of A: [ 2.0  5.0  10.0  17.0  26.0  37.0  50.0  65.0  82.0  101.0] meter ** 2
cost lower bound:
[3.99999897e+00 2.49990635e+01 9.99519417e+01 2.88964405e+02
 6.75761038e+02 1.36887689e+03 2.49888336e+03 4.22418997e+03
 6.72085595e+03 1.02009910e+04]

cost estimate:
[3.99999897e+00 2.50021684e+01 1.00001162e+02 2.89043164e+02
 6.76096986e+02 1.36923920e+03 2.50043987e+03 4.22599006e+03
 6.72550897e+03 1.02009910e+04]

cost upper bound:
[3.99999897e+00 2.50052737e+01 1.00050406e+02 2.89121944e+02
 6.76433102e+02 1.36960161e+03 2.50199736e+03 4.22779092e+03
 6.73016521e+03 1.02009910e+04]

Solved after  3 passes, cost logtol +/-0
Table of solutions used in the autosweep:

Optimal Cost
------------
 [ 0.333     1         123       ]

Free Variables
--------------
A : [ 0.577     1         11.1     ]  [m**2]

Fixed Variables
---------------
l : [ 1         3         10       ]  [m]

Variable Sensitivities
----------------------
l : [ +1        +2.5      +4       ]

Most Sensitive Constraints (in last sweep)
------------------------------------------
    +2 : A >= (l/3)^2


Optimal Cost
------------
 1.621

Free Variables
--------------
dx : 1.2                                                             [m]   Length of an element
 M : [ 1.98e+03  1.27e+03  713       317       79.2      0.0002   ]  [N*m] Internal moment
 V : [ 660       528       396       264       132       0.0002   ]  [N]   Internal shear
th : [ 0.0002    0.177     0.285     0.341     0.363     0.367    ]        Slope
 w : [ 0.0002    0.107     0.384     0.76      1.18      1.62     ]  [m]   Displacement

BoundsChecking
==============

Cost Function
-------------
 F

Constraints
-----------
 F >= D + T
 D = rf*V^2*Ap
 Ap = nu
 T = mf*V
 mf >= mi + mb
 mf = rf*V
 Fs <= mi
Traceback (most recent call last):
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\breakdowns.py", line 11, in <module>
    sol = pickle.load(open(dirpath+"solar_13.p", "rb"))
  File "C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins\lib\site-packages\pint\util.py", line 429, in __setstate__
    self._d, self._one, self._non_int_type = state
ValueError: too many values to unpack (expected 3)
<DEBUG> Model is feasible with these modifications:

Arbitrarily Bounded Variables
-----------------------------
   value near upper bound of 1e+30: y
 sensitive to upper bound of 1e+30: y

Relaxed Constants
-----------------
  x_min [ft]: relaxed from 2 to 1

# Now let's try a model unsolvable with relaxed constants

<DEBUG> Model is not feasible with relaxed constants and bounded variables.
<DEBUG> Model is feasible with these modifications:

Relaxed Constraints
-------------------
   1: 3500% relaxed, from    x [ft] >= 1 [yd]
                       to 36*x [ft] >= 1 [yd]

# And one that's only unbounded

<DEBUG> Model is feasible with these modifications:

Arbitrarily Bounded Variables
-----------------------------
   value near upper bound of 1e+30: y
 sensitive to upper bound of 1e+30: y

<DEBUG> Model seems feasible without modification, or only needs relaxations of less than 1%. Check the returned solution for details.
from gpkit import Variable, VectorVariable  # Demonstration of nomenclature syntax
# 
#     Lines that end in "Variables" will be parsed as a scalar variable table
#     until the next blank line.
# 
#     Variables
#     ---------
A = self.A = Variable('A', 'm^2', 'surface area')  # from 'A       [m^2]  surface area'
V = self.V = Variable('V', 100, 'L', 'minimum volume')  # from 'V   100 [L]    minimum volume'
# 
#     Lines that end in "Variables of length $N" will be parsed as vector
#     variables of length $N until the next blank line.
# 
#     Variables of length 3
#     ---------------------
s = self.s = VectorVariable(3, 's', 'm', 'side length')  # from 's       [m]    side length'
# 
#     Let's introduce more variables: (any line ending in "Variables" is parsed)
# 
#     Zoning Variables
#     ----------------
h = self.h = Variable('h', 1, 'm', 'minimum height')  # from 'h     1 [m]    minimum height'
# 
#     Upper Unbounded
#     ---------------
#     A
# 
#     The ordering of these blocks doesn't affect anything; order them in the
#     way that makes the most sense to someone else reading your model.
#     

Optimal Cost
------------
 1.465

Free Variables
--------------
A : 1.465                             [m**2] surface area
s : [ 0.316     0.316     1        ]  [m]    side length

Fixed Variables
---------------
V : 100  [l] minimum volume
h : 1    [m] minimum height

Variable Sensitivities
----------------------
V : +0.57  minimum volume
h : +0.3   minimum height

Most Sensitive Constraints
--------------------------
    +1 : A >= 2*(s[0]*s[1] + s[1]*s[2] + s[2]*s[0])
 +0.57 : V <= s[:].prod()
  +0.3 : s[2] >= h


Optimal Cost
------------
 0.7071

Free Variables
--------------
x : 0.7854
y : 0.7071


Optimal Cost
------------
 0.005511

Free Variables
--------------
x : 8.165
y : 4.082
z : 5.443

Most Sensitive Constraints
--------------------------
  +1.5 : 2*x*y + 2*x*z + 2*y*z <= 200
 +0.17 : x >= 2*y

The optimal value is 0.005511.

Optimal Cost
------------
 1

Model Sensitivities
-------------------
  +1.0 : System.Fleet2
       : System.Fleet2.Vehicle

Free Variables
--------------
  | System.Fleet2
z : [ 1        ]

  | System.Fleet2.Vehicle
a : [ 1         1        ]

Fixed Variables
---------------
  | System.Fleet2
x : [ 4        ]
y : [ 3         1        ]

Variable Sensitivities
----------------------
  | System.Fleet2
y : [   -       +0.25    ]

Most Sensitive Constraints
--------------------------
       | System.Fleet2
    +1 : z[0] >= a[0,0]*y[0,0]/x[0] + y[1,0]/x[0]*a[1,0]

       | System.Fleet2.Vehicle
 +0.75 : a[0,0] >= 1
 +0.25 : a[1,0] >= 1


Optimal Cost
------------
 3

Model Sensitivities
-------------------
  +1.0 : System2.Fleet2
       : System2.Fleet2.Vehicle

Free Variables
--------------
  | System2.Fleet2
z : [ 1         1         1        ]

  | System2.Fleet2.Vehicle
a : [ 1         1         1
      1         1         1         ]

Fixed Variables
---------------
  | System2.Fleet2
x : [ 4         4         4        ]
y : [ 3         3         3
      1         1         1         ]

Variable Sensitivities
----------------------
  | System2.Fleet2
y : [   -         -         -
      +0.083    +0.083    +0.083    ]

Most Sensitive Constraints
--------------------------
       | System2.Fleet2
 +0.33 : z[0] >= a[0,0]*y[0,0]/x[0] + y[1,0]/x[0]*a[1,0]
 +0.33 : z[1] >= a[0,1]*y[0,1]/x[1] + y[1,1]/x[1]*a[1,1]
 +0.33 : z[2] >= a[0,2]*y[0,2]/x[2] + y[1,2]/x[2]*a[1,2]

       | System2.Fleet2.Vehicle
 +0.25 : a[0,0] >= 1
 +0.25 : a[0,1] >= 1


Optimal Cost
------------
 20

Swept Variables
---------------
y : [ 1         2         3        ]

Free Variables
--------------
x : [ 2         6         12       ]

Fixed Variables
---------------
z : [ 1         4         9        ]

Variable Sensitivities
----------------------
y : [ +0.15     +0.5      +1       ]

Most Sensitive Constraints
--------------------------
  +0.6 : x[2] >= y[2] + z[2]
  +0.3 : x[1] >= y[1] + z[1]
  +0.1 : x[0] >= y[0] + z[0]


Optimal Cost
------------
 15

Free Variables
--------------
  | Yum1.Cake
y : [ 3         3         3         3         3        ]

Fixed Variables
---------------
  | Yum1.Cake.Pie
x : [ 2         2         2         2         2
      3         3         3         3         3         ]
z : [ 1         1         1         1         1
      1         1         1         1         1         ]

Variable Sensitivities
----------------------
  | Yum1.Cake.Pie
x : [ +7.1e-07  +7.1e-07  +7.1e-07  +7.1e-07  +7.1e-07
      +0.2      +0.2      +0.2      +0.2      +0.2      ]

Most Sensitive Constraints
--------------------------
       | Yum1.Cake
  +0.2 : y[0] >= x[1,0]
  +0.2 : y[1] >= x[1,1]
  +0.2 : y[2] >= x[1,2]
  +0.2 : y[3] >= x[1,3]
  +0.2 : y[4] >= x[1,4]


Optimal Cost
------------
 3

Free Variables
--------------
  | Yum2.Cake
y : [ 3        ]

Fixed Variables
---------------
  | Yum2.Cake.Pie
x : [ 2         3        ]
z : [ 1         1        ]

Variable Sensitivities
----------------------
  | Yum2.Cake.Pie
x : [ +8.4e-08  +1       ]

Most Sensitive Constraints
--------------------------
       | Yum2.Cake
    +1 : y[0] >= x[1,0]


Optimal Cost
------------
 [ 1.41      2.14      2.68      3.13     ... ]

~~~~~~~~
WARNINGS
~~~~~~~~
Freed Choice Variables
----------------------
This model has the discretized choice variables [x], but since the 'cvxopt' solver doesn't support discretization they were treated as continuous variables.
~~~~~~~~

Swept Variables
---------------
numerator : [ 0.5
              1.15
              1.8
              2.45
              3.1
              3.75
              4.4
              5.05
              5.7
              6.35
              7         ]

Free Variables
--------------
x : [ 0.707
      1.07
      1.34
      1.57
      1.76
      1.94
      2.1
      2.25
      2.39
      2.52
      2.65      ]

Variable Sensitivities
----------------------
numerator : [ +0.5
              +0.5
              +0.5
              +0.5
              +0.5
              +0.5
              +0.5
              +0.5
              +0.5
              +0.5
              +0.5      ]

Most Sensitive Constraints (in last sweep)
------------------------------------------
(none)

Getting the only var 'E': PowerSystem.Battery.E [MJ]
The top-level var 'm': PowerSystem.m [lb]
All the variables 'm': [gpkit.Variable(PowerSystem.Battery.m [lb]), gpkit.Variable(PowerSystem.Motor.m [lb]), gpkit.Variable(PowerSystem.m [lb])]

Cost Function
-------------
 Wfuel[0]

Constraints
-----------
 Mission
  "fuel constraints":
    Wfuel[:-1] >= Wfuel[1:] + Wburn[:-1]
    Wfuel[3] >= Wburn[3]

  FlightSegment
   AircraftP
    Wburn[:] >= 0.1*D[:]
    Aircraft.W + Wfuel[:] <= 0.5*Mission.FlightSegment.FlightState.rho[:]*CL[:]*S*V[:]^2
    "performance":
      WingAero
       D[:] >= 0.5*Mission.FlightSegment.FlightState.rho[:]*V[:]^2*CD[:]*S
       Re[:] = Mission.FlightSegment.FlightState.rho[:]*V[:]*c/mu[:]
       CD[:] >= 0.074/Re[:]^0.2 + CL[:]^2/PI/A/e[:]

   FlightState
    (no constraints)

 Aircraft
  Aircraft.W >= Fuselage.W + Wing.W
  Fuselage
   (no constraints)

  Wing
   c = (S/A)^0.5
   Wing.W >= S*Wing.rho

Optimal Cost
------------
 1.091

Model Sensitivities
-------------------
  +2.5 : Mission
  +2.4 : Mission.FlightSegment.AircraftP
  +2.1 : Mission.FlightSegment.AircraftP.WingAero
  +1.4 : Aircraft
  +0.5 : Aircraft.Wing

Free Variables
--------------
      | Aircraft
    W : 144.1                                       [lbf]   weight

      | Aircraft.Wing
    S : 44.14                                       [ft**2] surface area
    W : 44.14                                       [lbf]   weight
    c : 1.279                                       [ft]    mean chord

      | Mission.FlightSegment.AircraftP
Wburn : [ 0.274     0.273     0.272     0.272    ]  [lbf]   segment fuel burn
Wfuel : [ 1.09      0.817     0.544     0.272    ]  [lbf]   fuel weight

      | Mission.FlightSegment.AircraftP.WingAero
    D : [ 2.74      2.73      2.72      2.72     ]  [lbf]   drag force

Insensitive Constraints |below +1e-05|
--------------------------------------
(none)

Solution Diff (for selected variables)
======================================
(argument is the baseline solution)

Constraint Differences
**********************
@@ -31,3 +31,4 @@
   Wing
    c = (S/A)^0.5
    Wing.W >= S*Wing.rho
+ Wburn[:] >= 0.2*D[:]

**********************

Relative Differences |above 1%|
-------------------------------
Wburn : [ +102.1%   +101.6%   +101.1%   +100.5%  ] segment fuel burn
Wfuel : [ +101.3%   +101.1%   +100.8%   +100.5%  ] fuel weight
    D : [   +1.1%       -         -         -    ] drag force

C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_jenkins\lib\site-packages\matplotlib\cbook\__init__.py:1298: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.
  return np.asarray(x, float)
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\plot_sweep1d.py:20: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure.
  f.show()
C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\plot_sweep1d.py:28: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure.
  f.show()
Original model
==============

Cost Function
-------------
 x

Constraints
-----------
 x <= x_max
 x >= x_min

With constraints relaxed equally
================================

Cost Function
-------------
 C

Constraints
-----------
 "minimum relaxation":
   C >= 1
 "relaxed constraints":
   x <= C*x_max
   x_min <= C*x

Optimal Cost
------------
 1.414

~~~~~~~~
WARNINGS
~~~~~~~~
Relaxed Constraints
-------------------
All constraints relaxed by 42%
~~~~~~~~

Free Variables
--------------
x : 1.414

  | Relax
C : 1.414

Fixed Variables
---------------
x_max : 1
x_min : 2

Variable Sensitivities
----------------------
x_max : -0.5
x_min : +0.5

Most Sensitive Constraints
--------------------------
  +0.5 : x <= C*x_max
  +0.5 : x_min <= C*x


C (1.41)
  breaks down into:
    C (1.41)
      which in: x <= C*x_max (sensitivity +0.5)
      { through a factor of 1/x_max (1, fixed) }
      breaks down into:
        x (1.41)
          which in: x_min <= C*x (sensitivity +0.5)
          breaks down into:
            { through a factor of 1/C (0.707) }
            x_min (2, fixed)

With constraints relaxed individually
=====================================

Cost Function
-------------
 C[:].prod()*x^0.01

Constraints
-----------
 "minimum relaxation":
   C[:] >= 1
 "relaxed constraints":
   x <= C[0]*x_max
   x_min <= C[1]*x

Optimal Cost
------------
 2

~~~~~~~~
WARNINGS
~~~~~~~~
Relaxed Constraints
-------------------
   1:  100% relaxed, from     x >= x_min
                       to x_min <= 2*x
~~~~~~~~

Free Variables
--------------
x : 1

  | Relax1
C : [ 1         2        ]

Fixed Variables
---------------
x_max : 1
x_min : 2

Variable Sensitivities
----------------------
x_min : +1
x_max : -0.99

Most Sensitive Constraints
--------------------------
    +1 : x_min <= C[1]*x
 +0.99 : x <= C[0]*x_max
 +0.01 : C[0] >= 1


With constants relaxed individually
===================================

Cost Function
-------------
 [Relax2.x_max, Relax2.x_min].prod()*x^0.01

Constraints
-----------
 Relax2
  "original constraints":
    x <= x_max
    x >= x_min
  "relaxation constraints":
    "x_max":
      Relax2.x_max >= 1
      x_max >= OriginalValues.x_max/Relax2.x_max
      x_max <= OriginalValues.x_max*Relax2.x_max
    "x_min":
      Relax2.x_min >= 1
      x_min >= OriginalValues.x_min/Relax2.x_min
      x_min <= OriginalValues.x_min*Relax2.x_min

Optimal Cost
------------
 2

~~~~~~~~
WARNINGS
~~~~~~~~
Relaxed Constants
-----------------
  x_min: relaxed from 2 to 1
~~~~~~~~

Free Variables
--------------
    x : 1
x_max : 1
x_min : 1

      | Relax2
x_max : 1
x_min : 2

Fixed Variables
---------------
      | Relax2.OriginalValues
x_max : 1
x_min : 2

Variable Sensitivities
----------------------
x_min : +1
x_max : -0.99

Most Sensitive Constraints
--------------------------
    +1 : x >= x_min
    +1 : x_min >= OriginalValues.x_min/Relax2.x_min
 +0.99 : x <= x_max
 +0.99 : x_max <= OriginalValues.x_max*Relax2.x_max


SINGLE
======

Optimal Cost
------------
 303.1

Free Variables
--------------
  A : 8.46              aspect ratio
C_D : 0.02059           Drag coefficient of wing
C_L : 0.4988            Lift coefficent of wing
C_f : 0.003599          skin friction coefficient
  D : 303.1      [N]    total drag force
 Re : 3.675e+06         Reynold's number
  S : 16.44      [m**2] total wing area
  V : 38.15      [m/s]  cruising speed
  W : 7341       [N]    total aircraft weight
W_w : 2401       [N]    wing weight

Solution Diff
=============
(argument is the baseline solution)

** no constraint differences **

Relative Differences |above 1%|
-------------------------------
The largest is +0%.

SWEEP
=====

Optimal Cost
------------
 [ 338       396       294       326       ]

Swept Variables
---------------
      V : [ 45        55        45        55       ]  [m/s] cruising speed
V_{min} : [ 20        20        25        25       ]  [m/s] takeoff speed

Free Variables
--------------
  A : [ 6.2       4.77      8.84      7.16     ]         aspect ratio
C_D : [ 0.0146    0.0123    0.0196    0.0157   ]         Drag coefficient of wing
C_L : [ 0.296     0.198     0.463     0.31     ]         Lift coefficent of wing
C_f : [ 0.00333   0.00314   0.00361   0.00342  ]         skin friction coefficient
  D : [ 338       396       294       326      ]  [N]    total drag force
 Re : [ 5.38e+06  7.24e+06  3.63e+06  4.75e+06 ]         Reynold's number
  S : [ 18.6      17.3      12.1      11.2     ]  [m**2] total wing area
  W : [ 6.85e+03  6.4e+03   6.97e+03  6.44e+03 ]  [N]    total aircraft weight
W_w : [ 1.91e+03  1.46e+03  2.03e+03  1.5e+03  ]  [N]    wing weight

Solution Diff
=============
(argument is the baseline solution)

** no constraint differences **

Relative Differences |above 1%|
-------------------------------
     Re : [  +46.4%    +97.1%     -1.1%    +29.2%  ] Reynold's number
    C_L : [  -40.6%    -60.2%     -7.2%    -37.9%  ] Lift coefficent of wing
      V : [  +18.0%    +44.2%    +18.0%    +44.2%  ] cruising speed
    W_w : [  -20.7%    -39.3%    -15.6%    -37.4%  ] wing weight
    C_D : [  -29.0%    -40.4%     -5.0%    -23.9%  ] Drag coefficient of wing
      A : [  -26.7%    -43.6%     +4.5%    -15.3%  ] aspect ratio
      S : [  +12.8%     +5.5%    -26.5%    -32.0%  ] total wing area
      D : [  +11.5%    +30.7%     -2.9%     +7.5%  ] total drag force
V_{min} : [   -9.1%     -9.1%    +13.6%    +13.6%  ] takeoff speed
      W : [   -6.8%    -12.8%     -5.1%    -12.2%  ] total aircraft weight
    C_f : [   -7.3%    -12.7%       -       -5.0%  ] skin friction coefficient

Absolute Differences |above 0.1|
--------------------------------
     Re : [ +1.7e+06  +3.6e+06  -4.1e+04  +1.1e+06 ]         Reynold's number
      W : [   -5e+02  -9.4e+02  -3.8e+02    -9e+02 ]  [N]    total aircraft weight
    W_w : [   -5e+02  -9.4e+02  -3.8e+02    -9e+02 ]  [N]    wing weight
      D : [      +35       +93      -8.8       +23 ]  [N]    total drag force
      V : [     +6.8       +17      +6.8       +17 ]  [m/s]  cruising speed
      S : [     +2.1      +0.9      -4.4      -5.3 ]  [m**2] total wing area
V_{min} : [       -2        -2        +3        +3 ]  [m/s]  takeoff speed
      A : [     -2.3      -3.7     +0.38      -1.3 ]         aspect ratio
    C_L : [     -0.2      -0.3        -      -0.19 ]         Lift coefficent of wing

Sensitivity Differences |above 0.1|
-----------------------------------
                  V : [ +0.59   +0.97   +0.25   +0.75  ] cruising speed
            V_{min} : [ -0.45   -0.67     -     -0.34  ] takeoff speed
          C_{L,max} : [ -0.23   -0.34     -     -0.17  ] max CL with flaps down
                  e : [ +0.15   +0.25     -     +0.19  ] Oswald efficiency factor
                W_0 : [   -     -0.17     -     -0.16  ] aircraft weight excluding wing
               \rho : [   -     +0.13     -     +0.19  ] density of air
(\frac{S}{S_{wet}}) : [ +0.13   +0.20     -     +0.11  ] wetted area ratio
                  k : [ +0.13   +0.20     -     +0.11  ] form factor
            N_{ult} : [ -0.11   -0.18     -     -0.14  ] ultimate load factor
     W_{W_{coeff1}} : [ -0.11   -0.18     -     -0.14  ] Wing Weight Coefficent 1
               \tau : [ +0.11   +0.18     -     +0.14  ] airfoil thickness to chord ratio


Optimal Cost
------------
 0.003674

Free Variables
--------------
d : 8.17   [m] depth
h : 8.163  [m] height
w : 4.081  [m] width

Fixed Variables
---------------
A_{floor} : 50   [m**2] upper limit, floor area
 A_{wall} : 200  [m**2] upper limit, wall area
    alpha : 2           lower limit, wall aspect ratio
     beta : 10          upper limit, wall aspect ratio
    delta : 10          upper limit, floor aspect ratio
    gamma : 2           lower limit, floor aspect ratio

Variable Sensitivities
----------------------
A_{wall} : -1.5  upper limit, wall area
   alpha : +0.5  lower limit, wall aspect ratio

Most Sensitive Constraints
--------------------------
  +1.5 : A_{wall} >= 2*h*w + 2*h*d
  +0.5 : alpha <= h/w


Optimal Cost
------------
 0.9

Free Variables
--------------
x : 0.9
y : 0.1

x values of each GP solve (note convergence)
2.50000, 0.92548, 0.90003, 0.90000

Optimal Cost
------------
 0.7854

Free Variables
--------------
x : 0.7854
y : 0.7854


Optimal Cost
------------
 [ 4.63e+03  6.23e+03  7.36e+03  ]

~~~~~~~~
WARNINGS
~~~~~~~~
Unexpectedly Loose Constraints in sweep 0
-----------------------------------------
0.5886 >= 0.5775 : V_{f_{avail}} >= V_f

Unexpectedly Loose Constraints in sweep 1
-----------------------------------------
0.7884 >= 0.7769 : V_{f_{avail}} >= V_f

Unexpectedly Loose Constraints in sweep 2
-----------------------------------------
0.9585 >= 0.9187 : V_{f_{avail}} >= V_f
~~~~~~~~

Swept Variables
---------------
V_f_wing : [ 0.1       0.3       0.5      ]  [m**3] fuel volume in the wing

Free Variables
--------------
       (CDA0) : [ 0.05      0.05      0.05     ]  [m**2] fuselage drag area
            A : [ 12.4      3.78      2.35     ]         aspect ratio
          C_D : [ 0.0136    0.011     0.0099   ]         drag coefficient
          C_L : [ 0.327     0.162     0.121    ]         lift coefficient of wing
          C_f : [ 0.00343   0.00284   0.00261  ]         skin friction coefficient
            D : [ 466       774       1e+03    ]  [N]    total drag force
          L/D : [ 24.1      14.8      12.2     ]         lift-to-drag ratio
           Re : [ 4.64e+06  1.21e+07  1.83e+07 ]         Reynold's number
            S : [ 22        29.7      35.6     ]  [m**2] total wing area
   T_{flight} : [ 16.6      13.4      12.3     ]  [h]    flight time
            V : [ 50.3      62.1      67.9     ]  [m/s]  cruising speed
          V_f : [ 0.577     0.777     0.919    ]  [m**3] fuel volume
V_{f_{avail}} : [ 0.589     0.788     0.958    ]  [m**3] fuel volume available
            W : [ 1.35e+04  1.45e+04  1.59e+04 ]  [N]    total aircraft weight
          W_f : [ 4.63e+03  6.23e+03  7.36e+03 ]  [N]    fuel weight
          W_w : [ 2.65e+03  2.05e+03  2.29e+03 ]  [N]    wing weight
     W_w_strc : [ 1.33e+03  269       151      ]  [N]    wing structural weight
     W_w_surf : [ 1.32e+03  1.78e+03  2.14e+03 ]  [N]    wing skin weight


Cost Function
-------------
 Wfuel[0]

Constraints
-----------
 Mission
  "fuel constraints":
    Wfuel[:-1] >= Wfuel[1:] + Wburn[:-1]
    Wfuel[3] >= Wburn[3]

  FlightSegment
   AircraftP
    Wburn[:] >= 0.1*D[:]
    Aircraft.W + Wfuel[:] <= 0.5*Mission.FlightSegment.FlightState.rho[:]*CL[:]*S*V[:]^2
    "performance":
      WingAero
       D[:] >= 0.5*Mission.FlightSegment.FlightState.rho[:]*V[:]^2*CD[:]*S
       Re[:] = Mission.FlightSegment.FlightState.rho[:]*V[:]*c/mu[:]
       CD[:] >= 0.074/Re[:]^0.2 + CL[:]^2/PI/A/e[:]

   FlightState
    (no constraints)

 Aircraft
  Aircraft.W >= Fuselage.W + Wing.W
  Fuselage
   (no constraints)

  Wing
   c = (S/A)^0.5
   Wing.W >= S*Wing.rho

Optimal Cost
------------
 1.091

Model Sensitivities
-------------------
  +2.5 : Mission
  +2.4 : Mission.FlightSegment.AircraftP
  +2.1 : Mission.FlightSegment.AircraftP.WingAero
  +1.4 : Aircraft
  +0.5 : Aircraft.Wing

Free Variables
--------------
      | Aircraft
    W : 144.1                                       [lbf]   weight

      | Aircraft.Wing
    S : 44.14                                       [ft**2] surface area
    W : 44.14                                       [lbf]   weight
    c : 1.279                                       [ft]    mean chord

      | Mission.FlightSegment.AircraftP
Wburn : [ 0.274     0.273     0.272     0.272    ]  [lbf]   segment fuel burn
Wfuel : [ 1.09      0.817     0.544     0.272    ]  [lbf]   fuel weight

      | Mission.FlightSegment.AircraftP.WingAero
    D : [ 2.74      2.73      2.72      2.72     ]  [lbf]   drag force

Insensitive Constraints |below +1e-05|
--------------------------------------
(none)

Solution Diff (for selected variables)
======================================
(argument is the baseline solution)

Constraint Differences
**********************
@@ -31,3 +31,4 @@
   Wing
    c = (S/A)^0.5
    Wing.W >= S*Wing.rho
+ Wburn[:] >= 0.2*D[:]

**********************

Relative Differences |above 1%|
-------------------------------
Wburn : [ +102.1%   +101.6%   +101.1%   +100.5%  ] segment fuel burn
Wfuel : [ +101.3%   +101.1%   +100.8%   +100.5%  ] fuel weight
    D : [   +1.1%       -         -         -    ] drag force


Optimal Cost
------------
 1e-30

~~~~~~~~
WARNINGS
~~~~~~~~
Arbitrarily Bounded Variables
-----------------------------
   value near upper bound of 1e+30: x
 sensitive to upper bound of 1e+30: x
~~~~~~~~

Free Variables
--------------
x : 1e+30

SCALAR

Optimal Cost
------------
 1

Free Variables
--------------
x : 1

__________

VECTORIZED

Optimal Cost
------------
 2

Free Variables
--------------
x : [ 1         2         1        ]

Infeasible monomial equality: Cannot convert from 'V [m**3]' to 'M [kg]'

Optimal Cost
------------
 1.293

Free Variables
--------------
A : 1.293                             [m**2] Surface Area of the Tank
V : 0.1                               [m**3] Volume of the Tank
d : [ 0.464     0.464     0.464    ]  [m]    Dimension Vector

Optimal cost:  1
Optimal x val: 1
Build step 'Console output (build log) parsing' changed build result to FAILURE
[Cobertura] Publishing Cobertura coverage report...

Recording test results
[Checks API] No suitable checks publisher found.
[WS-CLEANUP] Deleting project workspace...
[WS-CLEANUP] Deferred wipeout is used...
[WS-CLEANUP] done
Finished: FAILURE