Started by upstream project "CE_gpkit_PR_unit_tests" build number 3207 originally caused by: GitHub pull request #1566 of commit f865710224e2832214d39aab62919617de3cfde6, 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 0d8dffc88fe82e4f59f8620293976bab740f5adc (refs/remotes/origin/pr/1566/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 0d8dffc88fe82e4f59f8620293976bab740f5adc # timeout=10 > git rev-parse "HEAD^{commit}" # timeout=10 Seen branch in repository origin/breakdowns Seen branch in repository origin/cleanbreakdowns Seen branch in repository origin/debug_1461 Seen branch in repository origin/ecos Seen branch in repository origin/equality Seen branch in repository origin/fmincon_update Seen branch in repository origin/integer Seen branch in repository origin/jsondiff Seen 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origin/pr/991/head Seen branch in repository origin/pr/994/head Seen branch in repository origin/pr/994/merge Seen branch in repository origin/pr/995/head Seen branch in repository origin/pr/998/head Seen branch in repository origin/py3only Seen branch in repository origin/rileyfork Seen branch in repository origin/robustSPpaper Seen branch in repository origin/sage Seen branch in repository origin/varexp Seen branch in repository origin/xu_constraints Seen branch in repository origin/xu_examples Seen 697 remote branches > 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 0d8dffc88fe82e4f59f8620293976bab740f5adc (origin/pr/1566/merge, origin/master) > git config core.sparsecheckout # timeout=10 > git checkout -f 0d8dffc88fe82e4f59f8620293976bab740f5adc # timeout=3 Commit message: "Merge f865710224e2832214d39aab62919617de3cfde6 into c8cf2b30ce1c3d28f135352bd584a0130e903e3f" Using 'Changelog to branch' strategy. The recommended git tool is: NONE using credential 3614a4cf-01de-4393-97de-73734b7dd5a2 > git rev-parse "0d8dffc88fe82e4f59f8620293976bab740f5adc^{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 #3206' that contains recorded Git commits [GitCheckoutListener] -> Starting recording of new commits since 'e148e94' [GitCheckoutListener] -> Using head commit '0d8dffc' as starting point [GitCheckoutListener] -> Git commit decorator successfully obtained 'hudson.plugins.git.browser.GithubWeb@4e0408eb' 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: PR 1566: Clean breakdowns [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\jenkins16901367861092207251.bat 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 conda_activate (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>where python C:\Miniconda3\python.exe C:\Users\jenkins\AppData\Local\Microsoft\WindowsApps\python.exe (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>python --version Python 3.9.7 (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>REM Create a virtualenv to install everything into (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>SET VENV=C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_gpkit (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_gpkit created virtual environment CPython3.9.7.final.0-64 in 2225ms creator CPython3Windows(dest=C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_gpkit, 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==21.3.1, setuptools==59.5.0, wheel==0.36.2 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_gpkit\Scripts\activate.bat (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>python -m pip install --upgrade pip Requirement already satisfied: pip in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (21.3.1) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade adce Collecting adce Using cached adce-1.3.3.2-py3-none-any.whl Installing collected packages: adce Successfully installed adce-1.3.3.2 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade unittest-xml-reporting Collecting unittest-xml-reporting Using cached unittest_xml_reporting-3.0.4-py2.py3-none-any.whl (19 kB) Installing collected packages: unittest-xml-reporting Successfully installed unittest-xml-reporting-3.0.4 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade xmlrunner Collecting xmlrunner Using cached xmlrunner-1.7.7-py3-none-any.whl Installing collected packages: xmlrunner Successfully installed xmlrunner-1.7.7 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade pandas Collecting pandas Using cached pandas-1.3.5-cp39-cp39-win_amd64.whl (10.2 MB) Collecting pytz>=2017.3 Using cached pytz-2021.3-py2.py3-none-any.whl (503 kB) Collecting python-dateutil>=2.7.3 Using cached python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) Collecting numpy>=1.17.3 Using cached numpy-1.22.0-cp39-cp39-win_amd64.whl (14.7 MB) Requirement already satisfied: six>=1.5 in c:\miniconda3\lib\site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0) Installing collected packages: pytz, python-dateutil, numpy, pandas Successfully installed numpy-1.22.0 pandas-1.3.5 python-dateutil-2.8.2 pytz-2021.3 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade matplotlib Collecting matplotlib Using cached matplotlib-3.5.1-cp39-cp39-win_amd64.whl (7.2 MB) Requirement already satisfied: numpy>=1.17 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from matplotlib) (1.22.0) Collecting packaging>=20.0 Using cached packaging-21.3-py3-none-any.whl (40 kB) Requirement already satisfied: python-dateutil>=2.7 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from matplotlib) (2.8.2) Collecting fonttools>=4.22.0 Using cached fonttools-4.28.5-py3-none-any.whl (890 kB) Collecting kiwisolver>=1.0.1 Using cached kiwisolver-1.3.2-cp39-cp39-win_amd64.whl (52 kB) Collecting cycler>=0.10 Using cached cycler-0.11.0-py3-none-any.whl (6.4 kB) Collecting pillow>=6.2.0 Using cached Pillow-9.0.0-cp39-cp39-win_amd64.whl (3.2 MB) Collecting pyparsing>=2.2.1 Using cached pyparsing-3.0.6-py3-none-any.whl (97 kB) 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, packaging, kiwisolver, fonttools, cycler, matplotlib Successfully installed cycler-0.11.0 fonttools-4.28.5 kiwisolver-1.3.2 matplotlib-3.5.1 packaging-21.3 pillow-9.0.0 pyparsing-3.0.6 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade coverage Collecting coverage Using cached coverage-6.2-cp39-cp39-win_amd64.whl (183 kB) Installing collected packages: coverage Successfully installed coverage-6.2 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade numpy Requirement already satisfied: numpy in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (1.22.0) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade scipy Collecting scipy Using cached scipy-1.7.3-cp39-cp39-win_amd64.whl (34.3 MB) Requirement already satisfied: numpy<1.23.0,>=1.16.5 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from scipy) (1.22.0) Installing collected packages: scipy Successfully installed scipy-1.7.3 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade pint Collecting pint Using cached Pint-0.18-py2.py3-none-any.whl (209 kB) Requirement already satisfied: packaging in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from pint) (21.3) Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from packaging->pint) (3.0.6) Installing collected packages: pint Successfully installed pint-0.18 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade ipysankeywidget Collecting ipysankeywidget Using cached ipysankeywidget-0.4.1-py2.py3-none-any.whl (1.2 MB) Collecting ipywidgets>=7.0.0 Using cached ipywidgets-7.6.5-py2.py3-none-any.whl (121 kB) Collecting widgetsnbextension~=3.5.0 Using cached widgetsnbextension-3.5.2-py2.py3-none-any.whl (1.6 MB) Collecting jupyterlab-widgets>=1.0.0 Using cached jupyterlab_widgets-1.0.2-py3-none-any.whl (243 kB) Collecting nbformat>=4.2.0 Using cached nbformat-5.1.3-py3-none-any.whl (178 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-6.6.1-py3-none-any.whl (126 kB) Collecting ipython>=4.0.0 Using cached ipython-7.31.0-py3-none-any.whl (792 kB) Collecting traitlets>=4.3.1 Using cached traitlets-5.1.1-py3-none-any.whl (102 kB) Collecting tornado<7.0,>=4.2 Using cached tornado-6.1-cp39-cp39-win_amd64.whl (422 kB) Collecting nest-asyncio Using cached nest_asyncio-1.5.4-py3-none-any.whl (5.1 kB) Collecting debugpy<2.0,>=1.0.0 Using cached debugpy-1.5.1-cp39-cp39-win_amd64.whl (4.4 MB) Collecting matplotlib-inline<0.2.0,>=0.1.0 Using cached matplotlib_inline-0.1.3-py3-none-any.whl (8.2 kB) Collecting jupyter-client<8.0 Using cached jupyter_client-7.1.0-py3-none-any.whl (129 kB) Collecting pickleshare Using cached pickleshare-0.7.5-py2.py3-none-any.whl (6.9 kB) Collecting jedi>=0.16 Using cached jedi-0.18.1-py2.py3-none-any.whl (1.6 MB) Requirement already satisfied: setuptools>=18.5 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->ipysankeywidget) (59.5.0) Collecting pygments Using cached Pygments-2.11.2-py3-none-any.whl (1.1 MB) Collecting decorator Using cached decorator-5.1.1-py3-none-any.whl (9.1 kB) Collecting colorama Using cached colorama-0.4.4-py2.py3-none-any.whl (16 kB) Collecting prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 Using cached prompt_toolkit-3.0.24-py3-none-any.whl (374 kB) Collecting backcall Using cached backcall-0.2.0-py2.py3-none-any.whl (11 kB) Collecting jupyter-core Using cached jupyter_core-4.9.1-py3-none-any.whl (86 kB) Collecting jsonschema!=2.5.0,>=2.4 Using cached jsonschema-4.3.3-py3-none-any.whl (71 kB) Collecting notebook>=4.4.1 Using cached notebook-6.4.6-py3-none-any.whl (9.9 MB) Collecting parso<0.9.0,>=0.8.0 Using cached parso-0.8.3-py2.py3-none-any.whl (100 kB) Collecting pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 Using cached pyrsistent-0.18.0-cp39-cp39-win_amd64.whl (62 kB) Collecting attrs>=17.4.0 Using cached attrs-21.4.0-py2.py3-none-any.whl (60 kB) Collecting entrypoints Using cached entrypoints-0.3-py2.py3-none-any.whl (11 kB) Requirement already satisfied: python-dateutil>=2.1 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from jupyter-client<8.0->ipykernel>=4.5.1->ipywidgets>=7.0.0->ipysankeywidget) (2.8.2) Collecting pyzmq>=13 Using cached pyzmq-22.3.0-cp39-cp39-win_amd64.whl (1.0 MB) 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) Collecting jinja2 Using cached Jinja2-3.0.3-py3-none-any.whl (133 kB) Collecting nbconvert Using cached nbconvert-6.4.0-py3-none-any.whl (557 kB) Collecting prometheus-client Using cached prometheus_client-0.12.0-py2.py3-none-any.whl (57 kB) Collecting Send2Trash>=1.8.0 Using cached Send2Trash-1.8.0-py3-none-any.whl (18 kB) Collecting terminado>=0.8.3 Using cached terminado-0.12.1-py3-none-any.whl (15 kB) Collecting argon2-cffi Using cached argon2_cffi-21.3.0-py3-none-any.whl (14 kB) Collecting wcwidth Using cached wcwidth-0.2.5-py2.py3-none-any.whl (30 kB) Requirement already satisfied: six>=1.5 in c:\miniconda3\lib\site-packages (from python-dateutil>=2.1->jupyter-client<8.0->ipykernel>=4.5.1->ipywidgets>=7.0.0->ipysankeywidget) (1.16.0) Collecting pywinpty>=1.1.0 Using cached pywinpty-1.1.6-cp39-none-win_amd64.whl (1.4 MB) Collecting argon2-cffi-bindings Using cached argon2_cffi_bindings-21.2.0-cp36-abi3-win_amd64.whl (30 kB) Collecting MarkupSafe>=2.0 Using cached MarkupSafe-2.0.1-cp39-cp39-win_amd64.whl (14 kB) Collecting defusedxml Using cached defusedxml-0.7.1-py2.py3-none-any.whl (25 kB) Collecting bleach Using cached bleach-4.1.0-py2.py3-none-any.whl (157 kB) Collecting nbclient<0.6.0,>=0.5.0 Using cached nbclient-0.5.9-py3-none-any.whl (69 kB) Collecting jupyterlab-pygments Using cached jupyterlab_pygments-0.1.2-py2.py3-none-any.whl (4.6 kB) Collecting pandocfilters>=1.4.1 Using cached pandocfilters-1.5.0-py2.py3-none-any.whl (8.7 kB) Collecting testpath Using cached testpath-0.5.0-py3-none-any.whl (84 kB) Collecting mistune<2,>=0.8.1 Using cached mistune-0.8.4-py2.py3-none-any.whl (16 kB) Requirement already satisfied: cffi>=1.0.1 in c:\miniconda3\lib\site-packages (from argon2-cffi-bindings->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->ipysankeywidget) (1.15.0) Collecting webencodings Using cached webencodings-0.5.1-py2.py3-none-any.whl (11 kB) Requirement already satisfied: packaging in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->ipysankeywidget) (21.3) Requirement already satisfied: pycparser in c:\miniconda3\lib\site-packages (from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->ipysankeywidget) (2.21) Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\venv_gpkit\lib\site-packages (from packaging->bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->ipysankeywidget) (3.0.6) Installing collected packages: traitlets, pyrsistent, attrs, wcwidth, tornado, pyzmq, parso, nest-asyncio, jupyter-core, jsonschema, ipython-genutils, entrypoints, webencodings, pygments, prompt-toolkit, pickleshare, nbformat, matplotlib-inline, MarkupSafe, jupyter-client, jedi, decorator, colorama, backcall, testpath, pywinpty, pandocfilters, nbclient, mistune, jupyterlab-pygments, jinja2, ipython, defusedxml, debugpy, bleach, argon2-cffi-bindings, terminado, Send2Trash, prometheus-client, nbconvert, ipykernel, argon2-cffi, notebook, widgetsnbextension, jupyterlab-widgets, ipywidgets, ipysankeywidget Successfully installed MarkupSafe-2.0.1 Send2Trash-1.8.0 argon2-cffi-21.3.0 argon2-cffi-bindings-21.2.0 attrs-21.4.0 backcall-0.2.0 bleach-4.1.0 colorama-0.4.4 debugpy-1.5.1 decorator-5.1.1 defusedxml-0.7.1 entrypoints-0.3 ipykernel-6.6.1 ipysankeywidget-0.4.1 ipython-7.31.0 ipython-genutils-0.2.0 ipywidgets-7.6.5 jedi-0.18.1 jinja2-3.0.3 jsonschema-4.3.3 jupyter-client-7.1.0 jupyter-core-4.9.1 jupyterlab-pygments-0.1.2 jupyterlab-widgets-1.0.2 matplotlib-inline-0.1.3 mistune-0.8.4 nbclient-0.5.9 nbconvert-6.4.0 nbformat-5.1.3 nest-asyncio-1.5.4 notebook-6.4.6 pandocfilters-1.5.0 parso-0.8.3 pickleshare-0.7.5 prometheus-client-0.12.0 prompt-toolkit-3.0.24 pygments-2.11.2 pyrsistent-0.18.0 pywinpty-1.1.6 pyzmq-22.3.0 terminado-0.12.1 testpath-0.5.0 tornado-6.1 traitlets-5.1.1 wcwidth-0.2.5 webencodings-0.5.1 widgetsnbextension-3.5.2 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>pip install --upgrade plotly Collecting plotly Using cached plotly-5.5.0-py2.py3-none-any.whl (26.5 MB) Requirement already satisfied: six in c:\miniconda3\lib\site-packages (from plotly) (1.16.0) Collecting tenacity>=6.2.0 Using cached tenacity-8.0.1-py3-none-any.whl (24 kB) Installing collected packages: tenacity, plotly Successfully installed plotly-5.5.0 tenacity-8.0.1 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>if cvxopt == cvxopt ( pip install --upgrade cvxopt || exit /b 666 python -c "import cvxopt; print(cvxopt.__version__)" || exit /b 666 set GPKITSOLVERS=cvxopt ) Collecting cvxopt Using cached cvxopt-1.2.7-cp39-cp39-win_amd64.whl (9.5 MB) Installing collected packages: cvxopt Successfully installed cvxopt-1.2.7 1.2.7 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>REM for mosek9/mosek_conif (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>REM if cvxopt==mosek python -c "__import__('mosek').Env()" (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>if cvxopt == mosek ( msktestlic set GPKITSOLVERS=mosek_cli ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>python -c "import scipy; print(scipy.__version__)" 1.7.3 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>python -c "import numpy; print(numpy.__version__)" 1.22.0 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>python -c "import pint; print(pint.__version__)" 0.18 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>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_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:405: 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\small_classes.py:158: 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. v = np.array(v) ........C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\small_classes.py:158: 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. v = np.array(v) ............... ---------------------------------------------------------------------- Ran 209 tests in 14.676s OK Found no installed solvers, beginning a build. # Building GPkit version 1.0.0 # 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} (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>echo import gpkit.tests; gpkit.tests.run(xmloutput=True) 1>test.py (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>python test.py Running tests... ---------------------------------------------------------------------- ..........................................................................................................................................................................................C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\small_classes.py:158: 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. v = np.array(v) ........C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\small_classes.py:158: 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. v = np.array(v) ............... ---------------------------------------------------------------------- Ran 209 tests in 13.847s OK Generating XML reports... (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>REM just give coverage a dummy file (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>echo print("hello world") 1>test.py (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>coverage run --source=gpkit,docs/source/examples test.py || exit /b 666 C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_gpkit\lib\site-packages\coverage\control.py:768: CoverageWarning: No data was collected. (no-data-collected) self._warn("No data was collected.", slug="no-data-collected") hello world (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>coverage html -d htmlcov --omit=$COVERAGE_OMIT || exit /b 666 C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\gpkit\breakdowns.py:405: 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>if cvxopt == cvxopt ( pip install --no-cache-dir --no-deps -e C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt FOR %i IN ("C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\*.py") DO (python %i ) ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\autosweep.py ) 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_classes.py:158: 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. v = np.array(v) ........c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\gpkit\small_classes.py:158: 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. v = np.array(v) ............... ---------------------------------------------------------------------- Ran 209 tests in 13.066s OK Found no installed solvers, beginning a build. # Building GPkit version 1.0.0 # 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\beam.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\boundschecking.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\breakdowns.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\checking_result_changes.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\debug.py ) 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 Model is not feasible with relaxed constants and bounded variables. 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 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 Model seems feasible without modification, or only needs relaxations of less than 1%. Check the returned solution for details. (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\docstringparsing.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\evaluated_fixed_variables.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\evaluated_free_variables.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\external_constraint.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\external_function.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\external_sp.py ) Optimal Cost ------------ 0.7071 Free Variables -------------- x : 0.7854 y : 0.7071 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\freeing_fixed_variables.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\gettingstarted.py ) 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. (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\issue_1513.py ) 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] (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\issue_1522.py ) 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] (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\loose_constraintsets.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\migp.py ) 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) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\model_var_access.py ) 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])] (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\performance_modeling.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\plot_sweep1d.py ) c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\gpkit\small_classes.py:158: 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. v = np.array(v) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\venv_gpkit\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() (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\primal_infeasible_ex1.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\primal_infeasible_ex2.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\relaxation.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\simpleflight.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\simple_box.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\simple_sp.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\sin_approx_example.py ) Optimal Cost ------------ 0.7854 Free Variables -------------- x : 0.7854 y : 0.7854 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\sp_to_gp_sweep.py ) c:\users\jenkins\workspace\ce_gpkit_pr_unit_tests\cvxopt\gpkit\small_classes.py:158: 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. v = np.array(v) 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 ] [hr] 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\substitutions.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\sub_multi_values.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\tight_constraintsets.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\treemap.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\unbounded.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\vectorization.py ) (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\vectorize.py ) SCALAR Optimal Cost ------------ 1 Free Variables -------------- x : 1 __________ VECTORIZED Optimal Cost ------------ 2 Free Variables -------------- x : [ 1 2 1 ] (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\water_tank.py ) 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 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>(python C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt\docs\source\examples\x_greaterthan_1.py ) Optimal cost: 1 Optimal x val: 1 (venv_gpkit) (base) C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt>exit 0 [Cobertura] Publishing Cobertura coverage report... [Cobertura] No coverage results were found using the pattern 'coverage.xml' relative to 'C:\Users\jenkins\workspace\CE_gpkit_PR_unit_tests\cvxopt'. Did you enter a pattern relative to the correct directory? Did you generate the XML report(s) for Cobertura? [Cobertura] Skipped cobertura reports. 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: SUCCESS