Diff of the two buildlogs: -- --- b1/build.log 2025-02-23 21:01:01.513347527 +0000 +++ b2/build.log 2025-02-23 22:01:47.552550306 +0000 @@ -1,6 +1,6 @@ I: pbuilder: network access will be disabled during build -I: Current time: Sat Mar 28 15:14:11 -12 2026 -I: pbuilder-time-stamp: 1774754051 +I: Current time: Mon Feb 24 11:01:04 +14 2025 +I: pbuilder-time-stamp: 1740344464 I: Building the build Environment I: extracting base tarball [/var/cache/pbuilder/unstable-reproducible-base.tgz] I: copying local configuration @@ -28,52 +28,84 @@ dpkg-source: info: applying asteval-nameerror.patch I: Not using root during the build. I: Installing the build-deps -I: user script /srv/workspace/pbuilder/2093964/tmp/hooks/D02_print_environment starting +I: user script /srv/workspace/pbuilder/356560/tmp/hooks/D01_modify_environment starting +debug: Running on ionos11-amd64. +I: Changing host+domainname to test build reproducibility +I: Adding a custom variable just for the fun of it... +I: Changing /bin/sh to bash +'/bin/sh' -> '/bin/bash' +lrwxrwxrwx 1 root root 9 Feb 23 21:01 /bin/sh -> /bin/bash +I: Setting pbuilder2's login shell to /bin/bash +I: Setting pbuilder2's GECOS to second user,second room,second work-phone,second home-phone,second other +I: user script /srv/workspace/pbuilder/356560/tmp/hooks/D01_modify_environment finished +I: user script /srv/workspace/pbuilder/356560/tmp/hooks/D02_print_environment starting I: set - BUILDDIR='/build/reproducible-path' - BUILDUSERGECOS='first user,first room,first work-phone,first home-phone,first other' - BUILDUSERNAME='pbuilder1' - BUILD_ARCH='amd64' - DEBIAN_FRONTEND='noninteractive' - DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=42 ' - DISTRIBUTION='unstable' - HOME='/root' - HOST_ARCH='amd64' + BASH=/bin/sh + BASHOPTS=checkwinsize:cmdhist:complete_fullquote:extquote:force_fignore:globasciiranges:globskipdots:hostcomplete:interactive_comments:patsub_replacement:progcomp:promptvars:sourcepath + BASH_ALIASES=() + BASH_ARGC=() + BASH_ARGV=() + BASH_CMDS=() + BASH_LINENO=([0]="12" [1]="0") + BASH_LOADABLES_PATH=/usr/local/lib/bash:/usr/lib/bash:/opt/local/lib/bash:/usr/pkg/lib/bash:/opt/pkg/lib/bash:. + BASH_SOURCE=([0]="/tmp/hooks/D02_print_environment" [1]="/tmp/hooks/D02_print_environment") + BASH_VERSINFO=([0]="5" [1]="2" [2]="37" [3]="1" [4]="release" [5]="x86_64-pc-linux-gnu") + BASH_VERSION='5.2.37(1)-release' + BUILDDIR=/build/reproducible-path + BUILDUSERGECOS='second user,second room,second work-phone,second home-phone,second other' + BUILDUSERNAME=pbuilder2 + BUILD_ARCH=amd64 + DEBIAN_FRONTEND=noninteractive + DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=20 ' + DIRSTACK=() + DISTRIBUTION=unstable + EUID=0 + FUNCNAME=([0]="Echo" [1]="main") + GROUPS=() + HOME=/root + HOSTNAME=i-capture-the-hostname + HOSTTYPE=x86_64 + HOST_ARCH=amd64 IFS=' ' - INVOCATION_ID='553a5eee44bc4aea8238f09207fc67cf' - LANG='C' - LANGUAGE='en_US:en' - LC_ALL='C' - MAIL='/var/mail/root' - OPTIND='1' - PATH='/usr/sbin:/usr/bin:/sbin:/bin:/usr/games' - PBCURRENTCOMMANDLINEOPERATION='build' - PBUILDER_OPERATION='build' - PBUILDER_PKGDATADIR='/usr/share/pbuilder' - PBUILDER_PKGLIBDIR='/usr/lib/pbuilder' - PBUILDER_SYSCONFDIR='/etc' - PPID='2093964' - PS1='# ' - PS2='> ' + INVOCATION_ID=76e311077f7e4bc6a28f03a8af7c311f + LANG=C + LANGUAGE=et_EE:et + LC_ALL=C + MACHTYPE=x86_64-pc-linux-gnu + MAIL=/var/mail/root + OPTERR=1 + OPTIND=1 + OSTYPE=linux-gnu + PATH=/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path + PBCURRENTCOMMANDLINEOPERATION=build + PBUILDER_OPERATION=build + PBUILDER_PKGDATADIR=/usr/share/pbuilder + PBUILDER_PKGLIBDIR=/usr/lib/pbuilder + PBUILDER_SYSCONFDIR=/etc + PIPESTATUS=([0]="0") + POSIXLY_CORRECT=y + PPID=356560 PS4='+ ' - PWD='/' - SHELL='/bin/bash' - SHLVL='2' - SUDO_COMMAND='/usr/bin/timeout -k 18.1h 18h /usr/bin/ionice -c 3 /usr/bin/nice /usr/sbin/pbuilder --build --configfile /srv/reproducible-results/rbuild-debian/r-b-build.SD3UrmmW/pbuilderrc_pD1g --distribution unstable --hookdir /etc/pbuilder/first-build-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/unstable-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.SD3UrmmW/b1 --logfile b1/build.log lmfit-py_1.3.2-2.dsc' - SUDO_GID='110' - SUDO_UID='105' - SUDO_USER='jenkins' - TERM='unknown' - TZ='/usr/share/zoneinfo/Etc/GMT+12' - USER='root' - _='/usr/bin/systemd-run' - http_proxy='http://213.165.73.152:3128' + PWD=/ + SHELL=/bin/bash + SHELLOPTS=braceexpand:errexit:hashall:interactive-comments:posix + SHLVL=3 + SUDO_COMMAND='/usr/bin/timeout -k 24.1h 24h /usr/bin/ionice -c 3 /usr/bin/nice -n 11 /usr/bin/unshare --uts -- /usr/sbin/pbuilder --build --configfile /srv/reproducible-results/rbuild-debian/r-b-build.SD3UrmmW/pbuilderrc_uEai --distribution unstable --hookdir /etc/pbuilder/rebuild-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/unstable-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.SD3UrmmW/b2 --logfile b2/build.log lmfit-py_1.3.2-2.dsc' + SUDO_GID=111 + SUDO_UID=106 + SUDO_USER=jenkins + TERM=unknown + TZ=/usr/share/zoneinfo/Etc/GMT-14 + UID=0 + USER=root + _='I: set' + http_proxy=http://46.16.76.132:3128 I: uname -a - Linux ionos5-amd64 6.12.9+bpo-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.12.9-1~bpo12+1 (2025-01-19) x86_64 GNU/Linux + Linux i-capture-the-hostname 6.1.0-31-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.128-1 (2025-02-07) x86_64 GNU/Linux I: ls -l /bin - lrwxrwxrwx 1 root root 7 Nov 22 2024 /bin -> usr/bin -I: user script /srv/workspace/pbuilder/2093964/tmp/hooks/D02_print_environment finished + lrwxrwxrwx 1 root root 7 Nov 22 14:40 /bin -> usr/bin +I: user script /srv/workspace/pbuilder/356560/tmp/hooks/D02_print_environment finished -> Attempting to satisfy build-dependencies -> Creating pbuilder-satisfydepends-dummy package Package: pbuilder-satisfydepends-dummy @@ -393,7 +425,7 @@ Get: 240 http://deb.debian.org/debian unstable/main amd64 python3-setuptools-scm all 8.1.0-1 [40.5 kB] Get: 241 http://deb.debian.org/debian unstable/main amd64 python3-sphinx-gallery all 0.17.1-1 [401 kB] Get: 242 http://deb.debian.org/debian unstable/main amd64 python3-uncertainties all 3.2.2-1 [54.7 kB] -Fetched 154 MB in 4s (39.2 MB/s) +Fetched 154 MB in 29s (5376 kB/s) Preconfiguring packages ... Selecting previously unselected package libpython3.13-minimal:amd64. (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 19775 files and directories currently installed.) @@ -1175,8 +1207,8 @@ Setting up tzdata (2025a-2) ... Current default time zone: 'Etc/UTC' -Local time is now: Sun Mar 29 03:15:38 UTC 2026. -Universal Time is now: Sun Mar 29 03:15:38 UTC 2026. +Local time is now: Sun Feb 23 21:06:02 UTC 2025. +Universal Time is now: Sun Feb 23 21:06:02 UTC 2025. Run 'dpkg-reconfigure tzdata' if you wish to change it. Setting up unicode-data (15.1.0-1) ... @@ -1405,7 +1437,11 @@ Building tag database... -> Finished parsing the build-deps I: Building the package -I: Running cd /build/reproducible-path/lmfit-py-1.3.2/ && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games" HOME="/nonexistent/first-build" dpkg-buildpackage -us -uc -b && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games" HOME="/nonexistent/first-build" dpkg-genchanges -S > ../lmfit-py_1.3.2-2_source.changes +I: user script /srv/workspace/pbuilder/356560/tmp/hooks/A99_set_merged_usr starting +Not re-configuring usrmerge for unstable +I: user script /srv/workspace/pbuilder/356560/tmp/hooks/A99_set_merged_usr finished +hostname: Name or service not known +I: Running cd /build/reproducible-path/lmfit-py-1.3.2/ && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path" HOME="/nonexistent/second-build" dpkg-buildpackage -us -uc -b && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path" HOME="/nonexistent/second-build" dpkg-genchanges -S > ../lmfit-py_1.3.2-2_source.changes dpkg-buildpackage: info: source package lmfit-py dpkg-buildpackage: info: source version 1.3.2-2 dpkg-buildpackage: info: source distribution unstable @@ -1457,17 +1493,17 @@ running build running build_py creating build/lib/lmfit -copying lmfit/lineshapes.py -> build/lib/lmfit -copying lmfit/models.py -> build/lib/lmfit +copying lmfit/__init__.py -> build/lib/lmfit copying lmfit/parameter.py -> build/lib/lmfit +copying lmfit/minimizer.py -> build/lib/lmfit copying lmfit/model.py -> build/lib/lmfit +copying lmfit/models.py -> build/lib/lmfit +copying lmfit/_ampgo.py -> build/lib/lmfit copying lmfit/version.py -> build/lib/lmfit -copying lmfit/minimizer.py -> build/lib/lmfit -copying lmfit/__init__.py -> build/lib/lmfit +copying lmfit/jsonutils.py -> build/lib/lmfit copying lmfit/confidence.py -> build/lib/lmfit copying lmfit/printfuncs.py -> build/lib/lmfit -copying lmfit/jsonutils.py -> build/lib/lmfit -copying lmfit/_ampgo.py -> build/lib/lmfit +copying lmfit/lineshapes.py -> build/lib/lmfit running egg_info writing lmfit.egg-info/PKG-INFO writing dependency_links to lmfit.egg-info/dependency_links.txt @@ -1482,22 +1518,22 @@ running install_lib creating build/bdist.linux-x86_64/wheel creating build/bdist.linux-x86_64/wheel/lmfit -copying build/lib/lmfit/lineshapes.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/models.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/__init__.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/parameter.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/minimizer.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/model.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/models.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/_ampgo.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/version.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/minimizer.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/__init__.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/jsonutils.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/confidence.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/printfuncs.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/jsonutils.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/_ampgo.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/lineshapes.py -> build/bdist.linux-x86_64/wheel/./lmfit running install_egg_info Copying lmfit.egg-info to build/bdist.linux-x86_64/wheel/./lmfit-1.3.2.egg-info running install_scripts creating build/bdist.linux-x86_64/wheel/lmfit-1.3.2.dist-info/WHEEL -creating '/build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.12_lmfit/.tmp-3yveuzkj/lmfit-1.3.2-py3-none-any.whl' and adding 'build/bdist.linux-x86_64/wheel' to it +creating '/build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.12_lmfit/.tmp-2qg25szo/lmfit-1.3.2-py3-none-any.whl' and adding 'build/bdist.linux-x86_64/wheel' to it adding 'lmfit/__init__.py' adding 'lmfit/_ampgo.py' adding 'lmfit/confidence.py' @@ -1539,22 +1575,22 @@ running install_lib creating build/bdist.linux-x86_64/wheel creating build/bdist.linux-x86_64/wheel/lmfit -copying build/lib/lmfit/lineshapes.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/models.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/__init__.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/parameter.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/minimizer.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/model.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/models.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/_ampgo.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/version.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/minimizer.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/__init__.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/jsonutils.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/confidence.py -> build/bdist.linux-x86_64/wheel/./lmfit copying build/lib/lmfit/printfuncs.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/jsonutils.py -> build/bdist.linux-x86_64/wheel/./lmfit -copying build/lib/lmfit/_ampgo.py -> build/bdist.linux-x86_64/wheel/./lmfit +copying build/lib/lmfit/lineshapes.py -> build/bdist.linux-x86_64/wheel/./lmfit running install_egg_info Copying lmfit.egg-info to build/bdist.linux-x86_64/wheel/./lmfit-1.3.2.egg-info running install_scripts creating build/bdist.linux-x86_64/wheel/lmfit-1.3.2.dist-info/WHEEL -creating '/build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/.tmp-lruj4idr/lmfit-1.3.2-py3-none-any.whl' and adding 'build/bdist.linux-x86_64/wheel' to it +creating '/build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/.tmp-o3kpxvvd/lmfit-1.3.2-py3-none-any.whl' and adding 'build/bdist.linux-x86_64/wheel' to it adding 'lmfit/__init__.py' adding 'lmfit/_ampgo.py' adding 'lmfit/confidence.py' @@ -1583,7 +1619,7 @@ platform linux -- Python 3.12.9, pytest-8.3.4, pluggy-1.5.0 rootdir: /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.12_lmfit/build configfile: pyproject.toml -plugins: cov-5.0.0, typeguard-4.4.1 +plugins: typeguard-4.4.1, cov-5.0.0 collected 662 items tests/test_1variable.py . [ 0%] @@ -1704,7 +1740,7 @@ ---------- coverage: platform linux, python 3.12.9-final-0 ----------- Coverage HTML written to dir htmlcov -=========== 650 passed, 12 skipped, 18 warnings in 150.01s (0:02:30) =========== +=========== 650 passed, 12 skipped, 18 warnings in 863.05s (0:14:23) =========== I: pybuild pybuild:334: rm -fr /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.12_lmfit/build/NIST_STRD /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.12_lmfit/build/examples; find /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.12_lmfit/build -name "*.sav" -delete I: pybuild pybuild:308: cp -r NIST_STRD examples /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/build I: pybuild base:311: cd /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/build; python3.13 -m pytest tests @@ -1712,7 +1748,7 @@ platform linux -- Python 3.13.2, pytest-8.3.4, pluggy-1.5.0 rootdir: /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/build configfile: pyproject.toml -plugins: cov-5.0.0, typeguard-4.4.1 +plugins: typeguard-4.4.1, cov-5.0.0 collected 662 items tests/test_1variable.py . [ 0%] @@ -1735,7 +1771,7 @@ tests/test_least_squares.py ..... [ 21%] tests/test_lineshapes.py ............................................... [ 28%] .......................................... [ 35%] -tests/test_manypeaks_speed.py . [ 35%] +tests/test_manypeaks_speed.py F [ 35%] tests/test_max_nfev.py ........................... [ 39%] tests/test_minimizer.py ............... [ 41%] tests/test_model.py .................................................... [ 49%] @@ -1755,6 +1791,31 @@ tests/test_shgo.py ...... [ 99%] tests/test_stepmodel.py .. [100%] +=================================== FAILURES =================================== +_____________________________ test_manypeaks_speed _____________________________ + + @pytest.mark.flaky(max_runs=5) + def test_manypeaks_speed(): + model = None + t0 = time.time() + for i in np.arange(500): + g = Model(gaussian, prefix=f'g{i}') + if model is None: + model = g + else: + model += g + t1 = time.time() + pars = model.make_params() + t2 = time.time() + _cpars = deepcopy(pars) # noqa: F841 + t3 = time.time() + + # these are very conservative tests that + # should be satisfied on nearly any machine +> assert (t3-t2) < 0.5 +E assert (1740346499.3353415 - 1740346498.6291325) < 0.5 + +tests/test_manypeaks_speed.py:33: AssertionError =============================== warnings summary =============================== tests/test_manypeaks_speed.py:15 /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/build/tests/test_manypeaks_speed.py:15: PytestUnknownMarkWarning: Unknown pytest.mark.flaky - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html @@ -1837,2002 +1898,26 @@ ---------- coverage: platform linux, python 3.13.2-final-0 ----------- Coverage HTML written to dir htmlcov -=========== 650 passed, 12 skipped, 19 warnings in 134.84s (0:02:14) =========== -I: pybuild pybuild:334: rm -fr /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/build/NIST_STRD /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/build/examples; find /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/build -name "*.sav" -delete - rm -fr -- /tmp/dh-xdg-rundir-DZzJeLvz - create-stamp debian/debhelper-build-stamp - dh_testroot -O--buildsystem=pybuild - dh_prep -O--buildsystem=pybuild - rm -f -- debian/python3-lmfit.substvars debian/python-lmfit-doc.substvars - rm -fr -- debian/.debhelper/generated/python3-lmfit/ debian/python3-lmfit/ debian/tmp/ debian/.debhelper/generated/python-lmfit-doc/ debian/python-lmfit-doc/ - dh_auto_install -O--buildsystem=pybuild - install -m0755 -d /build/reproducible-path/lmfit-py-1.3.2/debian/tmp - pybuild --install -i python{version} -p "3.12 3.13" --dest-dir=/build/reproducible-path/lmfit-py-1.3.2/debian/tmp -I: pybuild plugin_pyproject:178: Copying package built for python3.12 to destdir -I: pybuild plugin_pyproject:178: Copying package built for python3.13 to destdir - rm -f debian/python-lmfit-doc.debhelper.log debian/python3-lmfit.debhelper.log - debian/rules override_dh_installdocs-indep -make[1]: Entering directory '/build/reproducible-path/lmfit-py-1.3.2' -mv examples/example_emcee_Model_interface.py examples/nodoc_example_emcee_Model_interface.py -cp doc/sphinx/ext_mathjax.py doc/extensions.py -PYTHONPATH=. http_proxy='localhost' python3 -m sphinx -N -bhtml -D mathjax_path="/usr/share/javascript/mathjax/MathJax.js" doc/ .pybuild/html # HTML generator -Running Sphinx v8.1.3 -loading translations [en]... done -making output directory... done -Using Sphinx-Gallery to convert rst text blocks to markdown for .ipynb files. -loading intersphinx inventory 'py' from https://docs.python.org/3/objects.inv ... -loading intersphinx inventory 'numpy' from https://numpy.org/doc/stable/objects.inv ... -loading intersphinx inventory 'scipy' from https://docs.scipy.org/doc/scipy/objects.inv ... -loading intersphinx inventory 'matplotlib' from https://matplotlib.org/stable/objects.inv ... -WARNING: failed to reach any of the inventories with the following issues: -intersphinx inventory 'https://docs.python.org/3/objects.inv' not fetchable due to : HTTPSConnectionPool(host='docs.python.org', port=443): Max retries exceeded with url: /3/objects.inv (Caused by NameResolutionError(": Failed to resolve 'docs.python.org' ([Errno -3] Temporary failure in name resolution)")) -loading intersphinx inventory 'pandas' from https://pandas.pydata.org/pandas-docs/stable/objects.inv ... -WARNING: failed to reach any of the inventories with the following issues: -intersphinx inventory 'https://matplotlib.org/stable/objects.inv' not fetchable due to : HTTPSConnectionPool(host='matplotlib.org', port=443): Max retries exceeded with url: /stable/objects.inv (Caused by NameResolutionError(": Failed to resolve 'matplotlib.org' ([Errno -3] Temporary failure in name resolution)")) -WARNING: failed to reach any of the inventories with the following issues: -intersphinx inventory 'https://numpy.org/doc/stable/objects.inv' not fetchable due to : HTTPSConnectionPool(host='numpy.org', port=443): Max retries exceeded with url: /doc/stable/objects.inv (Caused by NameResolutionError(": Failed to resolve 'numpy.org' ([Errno -3] Temporary failure in name resolution)")) -WARNING: failed to reach any of the inventories with the following issues: -intersphinx inventory 'https://docs.scipy.org/doc/scipy/objects.inv' not fetchable due to : HTTPSConnectionPool(host='docs.scipy.org', port=443): Max retries exceeded with url: /doc/scipy/objects.inv (Caused by NameResolutionError(": Failed to resolve 'docs.scipy.org' ([Errno -3] Temporary failure in name resolution)")) -loading intersphinx inventory 'sympy' from https://docs.sympy.org/latest/objects.inv ... -WARNING: failed to reach any of the inventories with the following issues: -intersphinx inventory 'https://pandas.pydata.org/pandas-docs/stable/objects.inv' not fetchable due to : HTTPSConnectionPool(host='pandas.pydata.org', port=443): Max retries exceeded with url: /pandas-docs/stable/objects.inv (Caused by NameResolutionError(": Failed to resolve 'pandas.pydata.org' ([Errno -3] Temporary failure in name resolution)")) -WARNING: failed to reach any of the inventories with the following issues: -intersphinx inventory 'https://docs.sympy.org/latest/objects.inv' not fetchable due to : HTTPSConnectionPool(host='docs.sympy.org', port=443): Max retries exceeded with url: /latest/objects.inv (Caused by NameResolutionError(": Failed to resolve 'docs.sympy.org' ([Errno -3] Temporary failure in name resolution)")) -generating gallery... -generating gallery for examples... 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[100%] example_brute.py - -computation time summary: - - ../examples/example_brute.py: 36.25 sec 0.0 MB - - ../examples/example_confidence_interval.py: 18.97 sec 0.0 MB - - ../examples/example_basinhopping.py: 4.44 sec 0.0 MB - - ../examples/example_two_dimensional_peak.py: 3.25 sec 0.0 MB - - ../examples/example_sympy.py: 1.84 sec 0.0 MB - - ../examples/example_detect_outliers.py: 1.54 sec 0.0 MB - - ../examples/example_complex_resonator_model.py: 1.02 sec 0.0 MB - - ../examples/example_Model_interface.py: 0.70 sec 0.0 MB - - ../examples/example_reduce_fcn.py: 0.61 sec 0.0 MB - - ../examples/example_diffev.py: 0.54 sec 0.0 MB - - ../examples/example_fit_with_algebraic_constraint.py: 0.52 sec 0.0 MB - - ../examples/example_fit_with_inequality.py: 0.43 sec 0.0 MB - - ../examples/example_fit_with_derivfunc.py: 0.43 sec 0.0 MB - - ../examples/example_fit_with_bounds.py: 0.36 sec 0.0 MB - - ../examples/example_use_pandas.py: 0.34 sec 0.0 MB - - ../examples/example_fit_multi_datasets.py: 0.33 sec 0.0 MB - - ../examples/example_expression_model.py: 0.30 sec 0.0 MB - - ../examples/lmfit_emcee_model_selection.py: 0.00 sec 0.0 MB -building [mo]: targets for 0 po files that are out of date -writing output... -building [html]: targets for 14 source files that are out of date -updating environment: [new config] 33 added, 0 changed, 0 removed -reading sources... 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[100%] whatsnew - -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:27: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - from lmfit.models import LinearModel, LorentzianModel - - peak = LorentzianModel() - background = LinearModel() - model = peak + background [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:289: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit.models import ExpressionModel - - mod = ExpressionModel('off + amp * exp(-x/x0) * sin(x*phase)') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:303: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from numpy import exp, linspace, sin - - x = linspace(0, 10, 501) - params = mod.make_params(off=0.25, amp=1.0, x0=2.0, phase=0.04) - y = mod.eval(params, x=x) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:324: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - script = """ - def mycurve(x, amp, cen, sig): - loren = lorentzian(x, amplitude=amp, center=cen, sigma=sig) - gauss = gaussian(x, amplitude=amp, center=cen, sigma=sig) - return log(loren) * gradient(gauss) / gradient(x) - """ [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:335: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mod = ExpressionModel('mycurve(x, height, mid, wid)', init_script=script, - independent_vars=['x']) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:354: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - from numpy import loadtxt - - from lmfit.models import GaussianModel - - data = loadtxt('test_peak.dat') - x = data[:, 0] - y = data[:, 1] - - mod = GaussianModel() - - pars = mod.guess(y, x=x) - out = mod.fit(y, pars, x=x) - - print(out.fit_report(min_correl=0.25)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:374: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(out.fit_report(min_correl=0.25)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:385: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - import matplotlib as mpl - mpl.rcParams['figure.dpi'] = 150 - %matplotlib inline - %config InlineBackend.figure_format = 'svg' - - import matplotlib.pyplot as plt - plt.plot(x, y, '-') - plt.plot(x, out.best_fit, '-', label='Gaussian Model') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:406: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit.models import LorentzianModel - - mod = LorentzianModel() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:415: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - pars = mod.guess(y, x=x) - out = mod.fit(y, pars, x=x) - print(out.fit_report(min_correl=0.25)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:424: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y, '-') - plt.plot(x, out.best_fit, '-', label='Lorentzian Model') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:435: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit.models import VoigtModel - - mod = VoigtModel() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:443: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - pars = mod.guess(y, x=x) - out = mod.fit(y, pars, x=x) - print(out.fit_report(min_correl=0.25)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:454: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - fig, axes = plt.subplots(1, 2, figsize=(12.8, 4.8)) - axes[0].plot(x, y, '-') - axes[0].plot(x, out.best_fit, '-', label='Voigt Model\ngamma constrained') - axes[0].legend() - # free gamma parameter - pars['gamma'].set(value=0.7, vary=True, expr='') - out_gamma = mod.fit(y, pars, x=x) - axes[1].plot(x, y, '-') - axes[1].plot(x, out_gamma.best_fit, '-', label='Voigt Model\ngamma unconstrained') - axes[1].legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:485: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(out_gamma.fit_report(min_correl=0.25)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:522: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_builtinmodels_stepmodel.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:533: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(out.fit_report()) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:540: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y) - plt.plot(x, out.init_fit, '--', label='initial fit') - plt.plot(x, out.best_fit, '-', label='best fit') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:563: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_builtinmodels_nistgauss.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:579: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(out.fit_report()) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:590: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - fig, axes = plt.subplots(1, 2, figsize=(12.8, 4.8)) - axes[0].plot(x, y) - axes[0].plot(x, init, '--', label='initial fit') - axes[0].plot(x, out.best_fit, '-', label='best fit') - axes[0].legend() - - comps = out.eval_components(x=x) - axes[1].plot(x, y) - axes[1].plot(x, comps['g1_'], '--', label='Gaussian component 1') - axes[1].plot(x, comps['g2_'], '--', label='Gaussian component 2') - axes[1].plot(x, comps['exp_'], '--', label='Exponential component') - axes[1].legend() - - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:632: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_builtinmodels_nistgauss2.py - :hide-code: - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:638: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y) - plt.plot(x, out.init_fit, '--', label='initial fit') - plt.plot(x, out.best_fit, '-', label='best fit') - plt.legend() - - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:652: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(out.fit_report()) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:689: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - import numpy as np - import matplotlib.pyplot as plt - from lmfit.models import SplineModel, GaussianModel - - data = np.loadtxt('test_splinepeak.dat') - x = data[:, 0] - y = data[:, 1] - - plt.plot(x, y, label='data') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:706: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y, label='data') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:717: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - model = GaussianModel(prefix='peak_') - params = model.make_params(amplitude=8, center=16, sigma=1) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:731: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - knot_xvals = np.array([1, 3, 5, 7, 9, 11, 13, 19, 21, 23, 25]) - - bkg = SplineModel(prefix='bkg_', xknots=knot_xvals) - params.update(bkg.guess(y, x)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:751: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - model = model + bkg - - params['peak_amplitude'].min = 0 - params['peak_center'].min = 10 - params['peak_center'].max = 20 - - out = model.fit(y, params, x=x) - print(out.fit_report(min_correl=0.3)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:770: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(out.fit_report(min_correl=0.3)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:786: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - comps = out.eval_components() - plt.plot(x, out.best_fit, label='best fit') - plt.plot(x, comps['bkg_'], label='background') - plt.plot(x, comps['peak_'], label='peak') - plt.legend() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:797: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y, label='data') - plt.plot(x, out.best_fit, label='best fit') - plt.plot(x, comps['bkg_'], label='background') - plt.plot(x, comps['peak_'], label='peak') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:810: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - knot_yvals = np.array([o.value for o in out.params.values() if o.name.startswith('bkg')]) - plt.plot(knot_xvals, knot_yvals, 'o', color='black', label='spline knots values') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:818: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y, label='data') - plt.plot(x, out.best_fit, label='best fit') - plt.plot(x, comps['bkg_'], label='background') - plt.plot(x, comps['peak_'], label='peak') - knot_yvals = np.array([o.value for o in out.params.values() if o.name.startswith('bkg')]) - plt.plot(knot_xvals, knot_yvals, 'o', color='black', label='spline knots values') - - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:836: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - knot_xvals1 = np.array([1, 3, 5, 7, 9, 11, 13, 19, 21, 23, 25]) - knot_xvals2 = np.array([1, 3, 5, 7, 9, 11, 13, 16, 19, 21, 23, 25]) - knot_xvals3 = np.array([1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25]) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:877: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - plt.plot(x, y, 'o', label='data') - for nknots in (10, 15, 20, 25): - model = SplineModel(prefix='bkg_', xknots=np.linspace(0, 25, nknots)) - params = model.guess(y, x) - out = model.fit(y, params, x=x) - plt.plot(x, out.best_fit, label=f'best-fit ({nknots} knots)') - - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst:894: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y, 'o', label='data') - for nknots in (10, 15, 20, 25): - model = SplineModel(prefix='bkg_', xknots=np.linspace(0, 25, nknots)) - params = model.guess(y, x) - out = model.fit(y, params, x=x) - plt.plot(x, out.best_fit, label=f'best-fit ({nknots} knots)') - - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:47: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - import numpy as np - - import lmfit - - x = np.linspace(0.3, 10, 100) - np.random.seed(0) - y = 1/(0.1*x) + 2 + 0.1*np.random.randn(x.size) - pars = lmfit.Parameters() - pars.add_many(('a', 0.1), ('b', 1)) - - - def residual(p): - return 1/(p['a']*x) + p['b'] - y [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:68: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mini = lmfit.Minimizer(residual, pars) - result = mini.minimize() - - print(lmfit.fit_report(result.params)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:78: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - ci = lmfit.conf_interval(mini, result) - lmfit.printfuncs.report_ci(ci) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:105: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - for p in result.params: - result.params[p].stderr = abs(result.params[p].value * 0.1) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:144: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - # - import matplotlib.pyplot as plt - import numpy as np - - from lmfit import conf_interval, conf_interval2d, report_ci - from lmfit.lineshapes import gaussian - from lmfit.models import GaussianModel, LinearModel - - sigma_levels = [1, 2, 3] - - rng = np.random.default_rng(seed=102) - - ######################### - # set up data -- deliberately adding imperfections and - # a small amount of non-Gaussian noise - npts = 501 - x = np.linspace(1, 100, num=npts) - noise = rng.normal(scale=0.3, size=npts) + 0.2*rng.f(3, 9, size=npts) - y = (gaussian(x, amplitude=83, center=47., sigma=5.) - + 0.02*x + 4 + 0.25*np.cos((x-20)/8.0) + noise) - - mod = GaussianModel() + LinearModel() - params = mod.make_params(amplitude=100, center=50, sigma=5, - slope=0, intecept=2) - out = mod.fit(y, params, x=x) - print(out.fit_report()) - - ######################### - # run conf_intervale, print report - sigma_levels = [1, 2, 3] - ci = conf_interval(out, out, sigmas=sigma_levels) - - print("## Confidence Report:") - report_ci(ci) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:191: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - ######################### - # plot initial fit - colors = ('#2030b0', '#b02030', '#207070') - fig, axes = plt.subplots(2, 3, figsize=(15, 9.5)) - - axes[0, 0].plot(x, y, 'o', markersize=3, label='data', color=colors[0]) - axes[0, 0].plot(x, out.best_fit, label='fit', color=colors[1]) - axes[0, 0].set_xlabel('x') - axes[0, 0].set_ylabel('y') - axes[0, 0].legend() - - aix, aiy = 0, 0 - nsamples = 50 - explicitly_calculate_sigma = True - - for pairs in (('sigma', 'amplitude'), ('intercept', 'amplitude'), - ('slope', 'intercept'), ('slope', 'center'), ('sigma', 'center')): - - xpar, ypar = pairs - if explicitly_calculate_sigma: - print(f"Generating chi-square map for {pairs}") - c_x, c_y, chi2_mat = conf_interval2d(out, out, xpar, ypar, - nsamples, nsamples, nsigma=3.5, - chi2_out=True) - # explicitly calculate sigma matrix: sigma increases chi_square - # from chi_square_best - # to chi_square + sigma**2 * reduced_chi_square - # so: sigma = sqrt((chi2-chi2_best)/ reduced_chi_square) - chi2_min = chi2_mat.min() - sigma_mat = np.sqrt((chi2_mat-chi2_min)/out.redchi) - else: - print(f"Generating sigma map for {pairs}") - # or, you could just calculate the matrix of probabilities as: - c_x, c_y, sigma_mat = conf_interval2d(out, out, xpar, ypar, - nsamples, nsamples, nsigma=3.5) - - aix += 1 - if aix == 2: - aix = 0 - aiy += 1 - ax = axes[aix, aiy] - - cnt = ax.contour(c_x, c_y, sigma_mat, levels=sigma_levels, colors=colors, - linestyles='-') - ax.clabel(cnt, inline=True, fmt=r"$\sigma=%.0f$", fontsize=13) - - # draw boxes for estimated uncertaties: - # dotted : scaled stderr from initial fit - # dashed : values found from conf_interval() - xv = out.params[xpar].value - xs = out.params[xpar].stderr - yv = out.params[ypar].value - ys = out.params[ypar].stderr - - cix = ci[xpar] - ciy = ci[ypar] - nc = len(sigma_levels) - for i in sigma_levels: - # dotted line: scaled stderr - ax.plot((xv-i*xs, xv+i*xs, xv+i*xs, xv-i*xs, xv-i*xs), - (yv-i*ys, yv-i*ys, yv+i*ys, yv+i*ys, yv-i*ys), - linestyle='dotted', color=colors[i-1]) - - # dashed line: refined uncertainties from conf_interval - xsp, xsm = cix[nc+i][1], cix[nc-i][1] - ysp, ysm = ciy[nc+i][1], ciy[nc-i][1] - ax.plot((xsm, xsp, xsp, xsm, xsm), (ysm, ysm, ysp, ysp, ysm), - linestyle='dashed', color=colors[i-1]) - - ax.set_xlabel(xpar) - ax.set_ylabel(ypar) - ax.grid(True, color='#d0d0d0') - plt.show() - # [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:295: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - import warnings - warnings.filterwarnings(action="ignore") - import matplotlib as mpl - import matplotlib.pyplot as plt - mpl.rcParams['figure.dpi'] = 150 - %matplotlib inline - %config InlineBackend.figure_format = 'svg' [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:306: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_confidence_advanced.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:311: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - lmfit.report_fit(out2.params, min_correl=0.5) - print('') - lmfit.printfuncs.report_ci(ci) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:328: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - fig, axes = plt.subplots(1, 2, figsize=(12.8, 4.8)) - cx, cy, grid = lmfit.conf_interval2d(mini, out2, 'a1', 't2', 30, 30) - ctp = axes[0].contourf(cx, cy, grid, np.linspace(0, 1, 11)) - fig.colorbar(ctp, ax=axes[0]) - axes[0].set_xlabel('a1') - axes[0].set_ylabel('t2') - - cx, cy, grid = lmfit.conf_interval2d(mini, out2, 'a2', 't2', 30, 30) - ctp = axes[1].contourf(cx, cy, grid, np.linspace(0, 1, 11)) - fig.colorbar(ctp, ax=axes[1]) - axes[1].set_xlabel('a2') - axes[1].set_ylabel('t2') - - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:362: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - fig, axes = plt.subplots(1, 2, figsize=(12.8, 4.8)) - cx1, cy1, prob = trace['a1']['a1'], trace['a1']['t2'], trace['a1']['prob'] - cx2, cy2, prob2 = trace['t2']['t2'], trace['t2']['a1'], trace['t2']['prob'] - - axes[0].scatter(cx1, cy1, c=prob, s=30) - axes[0].set_xlabel('a1') - axes[0].set_ylabel('t2') - - axes[1].scatter(cx2, cy2, c=prob2, s=30) - axes[1].set_xlabel('t2') - axes[1].set_ylabel('a1') - - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst:381: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - fig, axes = plt.subplots(1, 2, figsize=(12.8, 4.8)) - cx1, cy1, prob = trace['a1']['a1'], trace['a1']['t2'], trace['a1']['prob'] - cx2, cy2, prob2 = trace['t2']['t2'], trace['t2']['a1'], trace['t2']['prob'] - axes[0].scatter(cx1, cy1, c=prob, s=30) - axes[0].set_xlabel('a1') - axes[0].set_ylabel('t2') - axes[1].scatter(cx2, cy2, c=prob2, s=30) - axes[1].set_xlabel('t2') - axes[1].set_ylabel('a1') - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:43: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit import Parameters - - pars = Parameters() - pars.add('frac_curve1', value=0.5, min=0, max=1) - pars.add('frac_curve2', expr='1-frac_curve1') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:85: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - pars = Parameters() - pars.add('amp_1', value=0.5, min=0, max=1) - pars.add('cen_1', value=2.2) - pars.add('wid_1', value=0.2) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:94: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - pars.add('amp_2', expr='(2.0 - amp_1**2)') - pars.add('wid_2', expr='sqrt(pi)*wid_1') - pars.add('cen_2', expr='cen_1 * wid_2 / max(wid_1, 0.001)') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:103: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - pars.add('param_a', value=1) - pars.add('param_b', value=2) - pars.add('test_val', value=100) - - pars.add('bounded', expr='param_a if test_val/2. > 100 else param_b') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:113: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - if pars['test_val'].value/2. > 100: - bounded = pars['param_a'].value - else: - bounded = pars['param_b'].value [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:132: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - pars = Parameters() - pars.add('x', value=5, vary=True) - pars.add('delta', value=5, max=10, vary=True) - pars.add('y', expr='delta-x') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:175: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - def mylorentzian(x, amp, cen, wid): - "lorentzian function: wid = half-width at half-max" - return (amp / (1 + ((x-cen) / wid)**2)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:185: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit import Parameters - - pars = Parameters() - pars._asteval.symtable['lorentzian'] = mylorentzian [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:194: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit import Minimizer - - - def userfcn(x, params): - pass - - - fitter = Minimizer(userfcn, pars) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst:209: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - pars = Parameters() - fitter = Minimizer(userfcn, pars) - fitter.params._asteval.symtable['lorentzian'] = mylorentzian [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/faq.rst:249: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - import numpy as np - - import lmfit - - - def quad_off(x, x0, a, b, c): - model = a + b * x**2 - model[np.where(x < x0)] = c - return model - - - x0 = 19 - b = 0.02 - a = 2.0 - xdat = np.linspace(0, 100, 101) - ydat = a + b * xdat**2 - ydat[np.where(xdat < x0)] = a + b * x0**2 - ydat += np.random.normal(scale=0.1, size=xdat.size) - - mod = lmfit.Model(quad_off) - pars = mod.make_params(x0=22, a=1, b=1, c=1) - - result = mod.fit(ydat, pars, x=xdat) - print(result.fit_report()) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/faq.rst:292: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - import numpy as np - from scipy.special import erf - - import lmfit - - - def quad_off(x, x0, a, b, c): - m1 = a + b * x**2 - m2 = c * np.ones(len(x)) - # step up from 0 to 1 at x0: (erf(x-x0)+1)/2 - # step down from 1 to 0 at x0: (1-erf(x-x0))/2 - model = m1 * (erf(x-x0)+1)/2 + m2 * (1-erf(x-x0))/2 - return model - - - x0 = 19 - b = 0.02 - a = 2.0 - xdat = np.linspace(0, 100, 101) - ydat = a + b * xdat**2 - ydat[np.where(xdat < x0)] = a + b * x0**2 - ydat += np.random.normal(scale=0.1, size=xdat.size) - - mod = lmfit.Model(quad_off) - pars = mod.make_params(x0=22, a=1, b=1, c=1) - - result = mod.fit(ydat, pars, x=xdat) - print(result.fit_report()) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:64: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from numpy import exp, sign, sin, pi - - - def residual(pars, x, data=None, eps=None): - # unpack parameters: extract .value attribute for each parameter - parvals = pars.valuesdict() - period = parvals['period'] - shift = parvals['shift'] - decay = parvals['decay'] - - if abs(shift) > pi/2: - shift = shift - sign(shift)*pi - - if abs(period) < 1.e-10: - period = sign(period)*1.e-10 - - model = parvals['amp'] * sin(shift + x/period) * exp(-x*x*decay*decay) - - if data is None: - return model - if eps is None: - return model - data - return (model-data) / eps [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:97: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - from lmfit import Parameter, Parameters - - params = Parameters() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:104: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - params['period'] = Parameter(name='period', value=2, min=1.e-10) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:110: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - period = 1 [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:115: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - if abs(period) < 1.e-10: - period = sign(period)*1.e-10 [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:521: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_fitting_withreport.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:526: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(fit_report(out)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:535: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - print('-------------------------------') - print('Parameter Value Stderr') - for name, param in out.params.items(): - print(f'{name:7s} {param.value:11.5f} {param.stderr:11.5f}') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:643: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - import warnings - warnings.filterwarnings(action="ignore") - - import matplotlib as mpl - import matplotlib.pyplot as plt - mpl.rcParams['figure.dpi'] = 150 - %matplotlib inline - %config InlineBackend.figure_format = 'svg' [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:656: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - import matplotlib.pyplot as plt - import numpy as np - - import lmfit - - x = np.linspace(1, 10, 250) - np.random.seed(0) - y = 3.0 * np.exp(-x / 2) - 5.0 * np.exp(-(x - 0.1) / 10.) + 0.1 * np.random.randn(x.size) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:669: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - p = lmfit.Parameters() - p.add_many(('a1', 4.), ('a2', 4.), ('t1', 3.), ('t2', 3., True)) - - def residual(p): - v = p.valuesdict() - return v['a1'] * np.exp(-x / v['t1']) + v['a2'] * np.exp(-(x - 0.1) / v['t2']) - y [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:683: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mi = lmfit.minimize(residual, p, method='nelder', nan_policy='omit') - lmfit.printfuncs.report_fit(mi.params, min_correl=0.5) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:690: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - plt.plot(x, y, 'o') - plt.plot(x, residual(mi.params) + y, label='best fit') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:717: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mi.params.add('__lnsigma', value=np.log(0.1), min=np.log(0.001), max=np.log(2)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:724: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - res = lmfit.minimize(residual, method='emcee', nan_policy='omit', burn=300, steps=1000, thin=20, - params=mi.params, is_weighted=False, progress=False) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:743: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - plt.plot(res.acceptance_fraction, 'o') - plt.xlabel('walker') - plt.ylabel('acceptance fraction') - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:753: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - import corner - - emcee_plot = corner.corner(res.flatchain, labels=res.var_names, - truths=list(res.params.valuesdict().values())) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:765: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - print('median of posterior probability distribution') - print('--------------------------------------------') - lmfit.report_fit(res.params) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:786: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - highest_prob = np.argmax(res.lnprob) - hp_loc = np.unravel_index(highest_prob, res.lnprob.shape) - mle_soln = res.chain[hp_loc] - for i, par in enumerate(p): - p[par].value = mle_soln[i] - - - print('\nMaximum Likelihood Estimation from emcee ') - print('-------------------------------------------------') - print('Parameter MLE Value Median Value Uncertainty') - fmt = ' {:5s} {:11.5f} {:11.5f} {:11.5f}'.format - for name, param in p.items(): - print(fmt(name, param.value, res.params[name].value, - res.params[name].stderr)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst:810: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - print('\nError estimates from emcee:') - print('------------------------------------------------------') - print('Parameter -2sigma -1sigma median +1sigma +2sigma') - - for name in p.keys(): - quantiles = np.percentile(res.flatchain[name], - [2.275, 15.865, 50, 84.135, 97.275]) - median = quantiles[2] - err_m2 = quantiles[0] - median - err_m1 = quantiles[1] - median - err_p1 = quantiles[3] - median - err_p2 = quantiles[4] - median - fmt = ' {:5s} {:8.4f} {:8.4f} {:8.4f} {:8.4f} {:8.4f}'.format - print(fmt(name, err_m2, err_m1, median, err_p1, err_p2)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/intro.rst:43: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from numpy import exp, sin - - def residual(variables, x, data, uncertainty): - """Model a decaying sine wave and subtract data.""" - amp = variables[0] - phaseshift = variables[1] - freq = variables[2] - decay = variables[3] - - model = amp * sin(x*freq + phaseshift) * exp(-x*x*decay) - - return (data-model) / uncertainty [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/intro.rst:60: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from numpy import linspace, random - from scipy.optimize import leastsq - - # generate synthetic data with noise - x = linspace(0, 100) - noise = random.normal(size=x.size, scale=0.2) - data = 7.5 * sin(x*0.22 + 2.5) * exp(-x*x*0.01) + noise - - # generate experimental uncertainties - uncertainty = abs(0.16 + random.normal(size=x.size, scale=0.05)) - - variables = [10.0, 0.2, 3.0, 0.007] - out = leastsq(residual, variables, args=(x, data, uncertainty)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/intro.rst:123: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from numpy import exp, sin - - from lmfit import minimize, Parameters - - - def residual(params, x, data, uncertainty): - amp = params['amp'] - phaseshift = params['phase'] - freq = params['frequency'] - decay = params['decay'] - - model = amp * sin(x*freq + phaseshift) * exp(-x*x*decay) - - return (data-model) / uncertainty - - - params = Parameters() - params.add('amp', value=10) - params.add('decay', value=0.007) - params.add('phase', value=0.2) - params.add('frequency', value=3.0) - - out = minimize(residual, params, args=(x, data, uncertainty)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/intro.rst:158: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit import create_params - - params = create_params(amp=10, decay=0.007, phase=0.2, frequency=3.0) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/intro.rst:176: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - params = Parameters() - params.add('amp', value=10, vary=False) - params.add('decay', value=0.007, min=0.0) - params.add('phase', value=0.2) - params.add('frequency', value=3.0, max=10) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/intro.rst:192: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - params = create_params(amp={'value': 10, 'vary': False}, - decay={'value': 0.007, 'min': 0}, - phase=0.2, - frequency={'value': 3.0, 'max':10}) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/intro.rst:201: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - params['amp'].vary = False - params['decay'].min = 0.10 [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:49: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - import matplotlib as mpl - mpl.rcParams['figure.dpi'] = 150 - %matplotlib inline - %config InlineBackend.figure_format = 'svg' [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:57: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from numpy import exp, linspace, random - - - def gaussian(x, amp, cen, wid): - return amp * exp(-(x-cen)**2 / wid) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:69: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - from scipy.optimize import curve_fit - - x = linspace(-10, 10, 101) - y = gaussian(x, 2.33, 0.21, 1.51) + random.normal(0, 0.2, x.size) - - init_vals = [1, 0, 1] # for [amp, cen, wid] - best_vals, covar = curve_fit(gaussian, x, y, p0=init_vals) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:90: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit import Model - - gmodel = Model(gaussian) - print(f'parameter names: {gmodel.param_names}') - print(f'independent variables: {gmodel.independent_vars}') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:120: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - params = gmodel.make_params() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:130: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - params = gmodel.make_params(cen=0.3, amp=3, wid=1.25) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:144: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - x_eval = linspace(0, 10, 201) - y_eval = gmodel.eval(params, x=x_eval) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:151: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - y_eval = gmodel.eval(x=x_eval, cen=6.5, amp=100, wid=2.0) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:160: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - result = gmodel.fit(y, params, x=x) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:166: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - result = gmodel.fit(y, x=x, cen=0.5, amp=10, wid=2.0) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:173: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_gaussian.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:180: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(result.fit_report()) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:190: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y, 'o') - plt.plot(x, result.init_fit, '--', label='initial fit') - plt.plot(x, result.best_fit, '-', label='best fit') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:204: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - gmodel = Model(gaussian) - result = gmodel.fit(y, params, x=x, amp=5, cen=5, wid=1) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:350: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - import numpy as np - from lmfit import Model - - - def decay(t, tau, N): - return N*np.exp(-t/tau) - - - decay_model = Model(decay) - print(f'independent variables: {decay_model.independent_vars}') - - params = decay_model.make_params() - print('\nParameters:') - for pname, par in params.items(): - print(pname, par) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:375: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - decay_model = Model(decay, independent_vars=['tau']) - print(f'independent variables: {decay_model.independent_vars}') - - params = decay_model.make_params() - print('\nParameters:') - for pname, par in params.items(): - print(pname, par) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:407: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - def decay2(t, tau, N=10, check_positive=False): - if check_positive: - arg = abs(t)/max(1.e-9, abs(tau)) - else: - arg = t/tau - return N*np.exp(arg) - - - mod = Model(decay2) - print(f'independent variables: {mod.independent_vars}') - - params = mod.make_params() - print('Parameters:') - for pname, par in params.items(): - print(pname, par) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:440: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - - def voigt(x, amplitude=1.0, center=0.0, sigma=1.0, gamma=None): - """Return a 1-dimensional Voigt function. - ... - """ - if gamma is None: - gamma = sigma - z = (x-center + 1j*gamma) / max(tiny, (sigma*s2)) - return amplitude*real(wofz(z)) / max(tiny, (sigma*s2pi)) - - mod = Model(voigt) - print(f'independent variables: {mod.independent_vars}') - - params = mod.make_params(amplitude=10, center=5, sigma=2) - - # or - params2 = mod.make_params(amplitude=10, center=5, sigma=2, gamma=1.5) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:483: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - def myfunc(x, amplitude=1, center=0, sigma=1): - # function definition, for now just ``pass`` - pass - - - mod = Model(myfunc, prefix='f1_') - params = mod.make_params() - print('Parameters:') - for pname, par in params.items(): - print(pname, par) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:530: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - def myfunc(x, a=1, b=0): - return a*x + 10*a - b [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:537: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - def myfunc(x, a, b): - return a*x + 10*a - b [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:556: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mod = Model(myfunc) - - # simply supply initial values - pars = mod.make_params(a=3, b=0.5) - - # supply initial values, attributes for bounds, etcetera: - pars_bounded = mod.make_params(a=dict(value=3, min=0), - b=dict(value=0.5, vary=False)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:576: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - from lmfit import create_params - - mod = Model(myfunc) - - # simply supply initial values - pars = create_params(a=3, b=0.5) - - # supply initial values and attributes for bounds, etc: - pars_bounded = create_params(a=dict(value=3, min=0), - b=dict(value=0.5, vary=False)) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:600: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - x = linspace(0, 10, 100) - y_eval = mod.eval(x=x, a=7.0, b=-2.0) - y_sim = y_eval + random.normal(0, 0.2, x.size) - out = mod.fit(y_sim, pars, x=x, a=3.0, b=0.0) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:631: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mod = Model(myfunc) - mod.set_param_hint('bounded_parameter', min=0, max=1.0) - pars = mod.make_params() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:643: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - print('Parameter hints:') - for pname, par in mod.param_hints.items(): - print(pname, par) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:658: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mod = Model(gaussian) - mod.set_param_hint('wid', min=0) - mod.set_param_hint('fwhm', expr='2.3548*wid') - params = mod.make_params(amp={'value': 10, 'min':0.1, 'max':2000}, - cen=5.5, wid=1.25) - params.pretty_print() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:775: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_savemodel.py [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:779: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_loadmodel.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1077: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_gaussian.py - :hide-output: - :hide-code: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1081: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - dely = result.eval_uncertainty(sigma=3) - plt.fill_between(x, result.best_fit-dely, result.best_fit+dely, color="#ABABAB", - label=r'3-$\sigma$ uncertainty band') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1092: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - plt.plot(x, y, 'o') - plt.plot(x, result.init_fit, '--', label='initial fit') - plt.plot(x, result.best_fit, '-', label='best fit') - plt.fill_between(x, result.best_fit-dely, result.best_fit+dely, color="#ABABAB", - label=r'3-$\sigma$ uncertainty band') - plt.legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1116: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_uncertainty2.py [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1126: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_uncertainty_pred.py [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1169: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_uvars_params.py [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1201: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_savemodelresult.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1206: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_loadmodelresult.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1228: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - def gaussian_plus_line(x, amp, cen, wid, slope, intercept): - """line + 1-d gaussian""" - - gauss = (amp / (sqrt(2*pi) * wid)) * exp(-(x-cen)**2 / (2*wid**2)) - line = slope*x + intercept - return gauss + line [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1239: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mod = Model(gaussian_plus_line) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1251: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - def line(x, slope, intercept): - """a line""" - return slope*x + intercept [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1259: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mod = Model(gaussian) + Model(line) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1265: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_two_components.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1270: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(result.fit_report()) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1277: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - fig, axes = plt.subplots(1, 2, figsize=(12.8, 4.8)) - axes[0].plot(x, y, 'o') - axes[0].plot(x, result.init_fit, '--', label='initial fit') - axes[0].plot(x, result.best_fit, '-', label='best fit') - axes[0].legend() - - comps = result.eval_components() - axes[1].plot(x, y, 'o') - axes[1].plot(x, comps['gaussian'], '--', label='Gaussian component') - axes[1].plot(x, comps['line'], '--', label='Line component') - axes[1].legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1299: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-output: - - comps = result.eval_components() - plt.plot(x, y, 'o') - plt.plot(x, comps['gaussian'], '--', label='Gaussian component') - plt.plot(x, comps['line'], '--', label='Line component') [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1321: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - xwide = linspace(-5, 25, 3001) - predicted = mod.eval(result.params, x=xwide) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1338: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - def fcn1(x, a): - pass - - def fcn2(x, b): - pass - - def fcn3(x, c): - pass [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1350: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - mod = Model(fcn1) + Model(fcn2) * Model(fcn3) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1364: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - import numpy as np - - def convolve(dat, kernel): - """simple convolution of two arrays""" - npts = min(len(dat), len(kernel)) - pad = np.ones(npts) - tmp = np.concatenate((pad*dat[0], dat, pad*dat[-1])) - out = np.convolve(tmp, kernel, mode='valid') - noff = int((len(out) - npts) / 2) - return (out[noff:])[:npts] [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1382: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_model_composite.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1387: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - print(result.fit_report()) [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst:1394: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - :hide-code: - - fig, axes = plt.subplots(1, 2, figsize=(12.8, 4.8)) - axes[0].plot(x, y, 'o') - axes[0].plot(x, result.init_fit, '--', label='initial fit') - axes[0].plot(x, result.best_fit, '-', label='best fit') - axes[0].legend() - axes[1].plot(x, y, 'o') - axes[1].plot(x, 10*comps['jump'], '--', label='Jump component') - axes[1].plot(x, 10*comps['gaussian'], '-', label='Gaussian component') - axes[1].legend() - plt.show() [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/parameters.rst:117: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: ../examples/doc_parameters_basic.py - :hide-output: [docutils] -/build/reproducible-path/lmfit-py-1.3.2/doc/parameters.rst:125: ERROR: Unknown directive type "jupyter-execute". - -.. jupyter-execute:: - - def fcn2min(params, x, data): - """Model a decaying sine wave and subtract data.""" - v = params.valuesdict() - - model = v['amp'] * np.sin(x*v['omega'] + v['shift']) * np.exp(-x*x*v['decay']) - return model - data [docutils] -looking for now-outdated files... none found -pickling environment... done -checking consistency... /build/reproducible-path/lmfit-py-1.3.2/doc/bounds.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- bounds -/build/reproducible-path/lmfit-py-1.3.2/doc/builtin_models.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- builtin_models -/build/reproducible-path/lmfit-py-1.3.2/doc/confidence.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- confidence -/build/reproducible-path/lmfit-py-1.3.2/doc/constraints.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- constraints -/build/reproducible-path/lmfit-py-1.3.2/doc/examples/index.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- examples/index -/build/reproducible-path/lmfit-py-1.3.2/doc/faq.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- faq -/build/reproducible-path/lmfit-py-1.3.2/doc/fitting.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- fitting -/build/reproducible-path/lmfit-py-1.3.2/doc/installation.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- installation -/build/reproducible-path/lmfit-py-1.3.2/doc/intro.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- intro -/build/reproducible-path/lmfit-py-1.3.2/doc/model.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- model -/build/reproducible-path/lmfit-py-1.3.2/doc/parameters.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- parameters -/build/reproducible-path/lmfit-py-1.3.2/doc/support.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- support -/build/reproducible-path/lmfit-py-1.3.2/doc/whatsnew.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- whatsnew -done -preparing documents... done -copying assets... -copying downloadable files... 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dh_installsystemduser -O--buildsystem=pybuild - dh_perl -O--buildsystem=pybuild - dh_link -O--buildsystem=pybuild - rm -f debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/searchtools.js - ln -s ../../../../javascript/sphinxdoc/1.0/searchtools.js debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/searchtools.js - rm -f debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/language_data.js - ln -s ../../../../javascript/sphinxdoc/1.0/language_data.js debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/language_data.js - rm -f debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/doctools.js - ln -s ../../../../javascript/sphinxdoc/1.0/doctools.js debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/doctools.js - rm -f debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/sphinx_highlight.js - ln -s ../../../../javascript/sphinxdoc/1.0/sphinx_highlight.js debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/sphinx_highlight.js - dh_strip_nondeterminism -O--buildsystem=pybuild - Using 1739226326 as canonical time - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_detect_outliers_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_003_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_inequality_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_sympy_002.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_confidence_interval_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_complex_resonator_model_003.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_003_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_expression_model_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_004.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_multi_datasets_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_002_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_detect_outliers_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_algebraic_constraint_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_Model_interface_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_complex_resonator_model_002.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_sympy_002_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_algebraic_constraint_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_derivfunc_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_derivfunc_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_diffev_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_detect_outliers_003.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_002_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_basinhopping_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_complex_resonator_model_002_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_detect_outliers_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_basinhopping_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_inequality_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_bounds_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_003.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_detect_outliers_002.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_bounds_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_multi_datasets_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_derivfunc_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_002.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_confidence_interval_002_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_expression_model_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_004.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_diffev_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_diffev_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_Model_interface_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_algebraic_constraint_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_bounds_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_sympy_003_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_004_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_sympy_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_basinhopping_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_sympy_003.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_detect_outliers_002_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_003.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_use_pandas_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_confidence_interval_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_use_pandas_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_reduce_fcn_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_complex_resonator_model_003_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_complex_resonator_model_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_002.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_Model_interface_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_complex_resonator_model_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_reduce_fcn_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_with_inequality_001.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_two_dimensional_peak_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_use_pandas_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_sympy_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_multi_datasets_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_confidence_interval_002.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_detect_outliers_003_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_004_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_sympy_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_confidence_interval_001_3_00x.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_complex_resonator_model_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_expression_model_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_brute_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_reduce_fcn_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_lmfit_emcee_model_selection_thumb.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/71e355b3b30ce74828ca4cf53539dee9/example_confidence_interval.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/f81f821349f6ac014b70d7d599914cf0/example_expression_model.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/cb0c48698554996e8733a1803c042898/lmfit_emcee_model_selection.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/headerbg.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/lmfitheader.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/footerbg.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/relbg.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/listitem.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/broken_example.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/minus.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/bodybg.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/plus.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/file.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/dbec5987901e14219cbb0374bcb09f84/example_Model_interface.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/9896395df97ee7377a6f37d810ed61b7/example_fit_with_inequality.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/94d199f783ca5474abd6b2528828a3da/example_reduce_fcn.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/4b0b2bd3ab5ac85a687b73fdf77c10e8/example_fit_with_algebraic_constraint.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/83c1efe92ae9450e505c8e1a6f140c89/example_diffev.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/570649c46ce3ba7d3aa57423dbdf4bfc/example_detect_outliers.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/00134ee71b9a3140093a2c880ffc05b2/example_two_dimensional_peak.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/699f40a9aaadc3e2940695c56ce1a766/example_complex_resonator_model.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/43307aed08caee4fd5f81b541b305e07/example_fit_with_derivfunc.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/1e1423cf629493dec61889ad589cc4ee/example_sympy.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/9525432cdc678720dba934ae8fde54b3/example_brute.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_static/no_image.png using File::StripNondeterminism::handlers::png - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/d91d8231a4fc8b35dce7ae4cca7141a1/example_use_pandas.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/8bc8bf935cb55b846fb887ae67119e73/example_fit_with_bounds.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/a77b5add2eaa4ab07fa4f0e915c3066a/example_basinhopping.zip using File::StripNondeterminism::handlers::zip - Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/fe2af31b7b0cbda8b83cc55e6a993962/example_fit_multi_datasets.zip using File::StripNondeterminism::handlers::zip - dh_compress -O--buildsystem=pybuild - cd debian/python3-lmfit - cd debian/python-lmfit-doc - chmod a-x usr/share/doc/python3-lmfit/changelog.Debian - gzip -9nf usr/share/doc/python3-lmfit/changelog.Debian - chmod a-x usr/share/doc/python-lmfit-doc/changelog.Debian usr/share/doc/python3-lmfit/html/_downloads/2c0316848a8a5e58fdf5c1bd1978018e/example_confidence_interval.ipynb usr/share/doc/python3-lmfit/html/_downloads/3805fc8171e8a0686d5cf65be55085ee/example_complex_resonator_model.py usr/share/doc/python3-lmfit/html/_downloads/3dcc7459227dbd4ba1982949be8491e1/example_complex_resonator_model.ipynb usr/share/doc/python3-lmfit/html/_downloads/6069607ae016c4f4f055d1c8dfd4bfa7/example_sympy.ipynb usr/share/doc/python3-lmfit/html/_downloads/87be2ee5d3294a608face2290f955fe3/example_two_dimensional_peak.py usr/share/doc/python3-lmfit/html/_downloads/8b2fe0a32f4790de5b0465c00682a37b/example_Model_interface.py usr/share/doc/python3-lmfit/html/_downloads/9074bca346e91d4783f1ebfda08595dd/lmfit_emcee_model_selection.ipynb usr/share/doc/python3-lmfit/html/_downloads/9254f2af7eef00978dc5823dc5418985/example_brute.ipynb usr/share/doc/python3-lmfit/html/_downloads/a48b6f5c2c4202cb67d15a117c5eb6bc/example_fit_with_derivfunc.ipynb usr/share/doc/python3-lmfit/html/_downloads/a4a9bd70fc277eac0b5a505f48c84a99/example_detect_outliers.ipynb usr/share/doc/python3-lmfit/html/_downloads/a69966d88009a9341e88bfe1935158a7/example_Model_interface.ipynb usr/share/doc/python3-lmfit/html/_downloads/b6a243851aa5b1d7362705005c5ed3b1/example_confidence_interval.py usr/share/doc/python3-lmfit/html/_downloads/c004866ac6395edd2609ff96cecdc255/example_brute.py usr/share/doc/python3-lmfit/html/_downloads/c5b1d1ce60f76e20b3312a2697eca7f1/lmfit_emcee_model_selection.py usr/share/doc/python3-lmfit/html/_downloads/e9797dfaa256c029a43c2a364328ed36/example_fit_multi_datasets.ipynb usr/share/doc/python3-lmfit/html/_downloads/ee6bdfefbd3fee18a7b2cb99c291f27e/example_two_dimensional_peak.ipynb - cd '/build/reproducible-path/lmfit-py-1.3.2' - gzip -9nf usr/share/doc/python-lmfit-doc/changelog.Debian usr/share/doc/python3-lmfit/html/_downloads/2c0316848a8a5e58fdf5c1bd1978018e/example_confidence_interval.ipynb usr/share/doc/python3-lmfit/html/_downloads/3805fc8171e8a0686d5cf65be55085ee/example_complex_resonator_model.py usr/share/doc/python3-lmfit/html/_downloads/3dcc7459227dbd4ba1982949be8491e1/example_complex_resonator_model.ipynb usr/share/doc/python3-lmfit/html/_downloads/6069607ae016c4f4f055d1c8dfd4bfa7/example_sympy.ipynb usr/share/doc/python3-lmfit/html/_downloads/87be2ee5d3294a608face2290f955fe3/example_two_dimensional_peak.py usr/share/doc/python3-lmfit/html/_downloads/8b2fe0a32f4790de5b0465c00682a37b/example_Model_interface.py usr/share/doc/python3-lmfit/html/_downloads/9074bca346e91d4783f1ebfda08595dd/lmfit_emcee_model_selection.ipynb usr/share/doc/python3-lmfit/html/_downloads/9254f2af7eef00978dc5823dc5418985/example_brute.ipynb usr/share/doc/python3-lmfit/html/_downloads/a48b6f5c2c4202cb67d15a117c5eb6bc/example_fit_with_derivfunc.ipynb usr/share/doc/python3-lmfit/html/_downloads/a4a9bd70fc277eac0b5a505f48c84a99/example_detect_outliers.ipynb usr/share/doc/python3-lmfit/html/_downloads/a69966d88009a9341e88bfe1935158a7/example_Model_interface.ipynb usr/share/doc/python3-lmfit/html/_downloads/b6a243851aa5b1d7362705005c5ed3b1/example_confidence_interval.py usr/share/doc/python3-lmfit/html/_downloads/c004866ac6395edd2609ff96cecdc255/example_brute.py usr/share/doc/python3-lmfit/html/_downloads/c5b1d1ce60f76e20b3312a2697eca7f1/lmfit_emcee_model_selection.py usr/share/doc/python3-lmfit/html/_downloads/e9797dfaa256c029a43c2a364328ed36/example_fit_multi_datasets.ipynb usr/share/doc/python3-lmfit/html/_downloads/ee6bdfefbd3fee18a7b2cb99c291f27e/example_two_dimensional_peak.ipynb - cd '/build/reproducible-path/lmfit-py-1.3.2' - dh_fixperms -O--buildsystem=pybuild - find debian/python3-lmfit ! -type l -a -true -a -true -print0 2>/dev/null | xargs -0r chmod go=rX,u+rw,a-s - find debian/python-lmfit-doc ! -type l -a -true -a -true -print0 2>/dev/null | xargs -0r chmod go=rX,u+rw,a-s - find debian/python3-lmfit/usr/share/doc -type f -a -true -a ! -regex 'debian/python3-lmfit/usr/share/doc/[^/]*/examples/.*' -print0 2>/dev/null | xargs -0r chmod 0644 - find debian/python-lmfit-doc/usr/share/doc -type f -a -true -a ! -regex 'debian/python-lmfit-doc/usr/share/doc/[^/]*/examples/.*' -print0 2>/dev/null | xargs -0r chmod 0644 - find debian/python3-lmfit/usr/share/doc -type d -a -true -a -true -print0 2>/dev/null | xargs -0r chmod 0755 - find debian/python3-lmfit -type f \( -name '*.so.*' -o -name '*.so' -o -name '*.la' -o -name '*.a' -o -name '*.js' -o -name '*.css' -o -name '*.scss' -o -name '*.sass' -o -name '*.jpeg' -o -name '*.jpg' -o -name '*.png' -o -name '*.gif' -o -name '*.cmxs' -o -name '*.node' \) -a -true -a -true -print0 2>/dev/null | xargs -0r chmod 0644 - find debian/python-lmfit-doc/usr/share/doc -type d -a -true -a -true -print0 2>/dev/null | xargs -0r chmod 0755 - find debian/python3-lmfit/usr/lib -type f -name '*.ali' -a -true -a -true -print0 2>/dev/null | xargs -0r chmod uga-w - find debian/python-lmfit-doc -type f \( -name '*.so.*' -o -name '*.so' -o -name '*.la' -o -name '*.a' -o -name '*.js' -o -name '*.css' -o -name '*.scss' -o -name '*.sass' -o -name '*.jpeg' -o -name '*.jpg' -o -name '*.png' -o -name '*.gif' -o -name '*.cmxs' -o -name '*.node' \) -a -true -a -true -print0 2>/dev/null | xargs -0r chmod 0644 - dh_missing -O--buildsystem=pybuild - dh_installdeb -O--buildsystem=pybuild - install -m0755 -d debian/python3-lmfit/DEBIAN - printf '#!/bin/sh\nset -e\n' > debian/python3-lmfit/DEBIAN/postinst - cat debian/python3-lmfit.postinst.debhelper >> debian/python3-lmfit/DEBIAN/postinst - chmod 0755 -- debian/python3-lmfit/DEBIAN/postinst - printf '#!/bin/sh\nset -e\n' > debian/python3-lmfit/DEBIAN/prerm - cat debian/python3-lmfit.prerm.debhelper >> debian/python3-lmfit/DEBIAN/prerm - chmod 0755 -- debian/python3-lmfit/DEBIAN/prerm - install -m0755 -d debian/python-lmfit-doc/DEBIAN - dh_numpy3 -O--buildsystem=pybuild - mv debian/python3-lmfit.substvars.new debian/python3-lmfit.substvars - mv debian/python-lmfit-doc.substvars.new debian/python-lmfit-doc.substvars - dh_gencontrol -O--buildsystem=pybuild - install -m0755 -d debian/python3-lmfit/DEBIAN - echo misc:Depends= >> debian/python3-lmfit.substvars - echo misc:Pre-Depends= >> debian/python3-lmfit.substvars - dpkg-gencontrol -ppython3-lmfit -ldebian/changelog -Tdebian/python3-lmfit.substvars -cdebian/control -Pdebian/python3-lmfit - install -m0755 -d debian/python-lmfit-doc/DEBIAN - echo misc:Depends= >> debian/python-lmfit-doc.substvars - echo misc:Pre-Depends= >> debian/python-lmfit-doc.substvars - dpkg-gencontrol -ppython-lmfit-doc -ldebian/changelog -Tdebian/python-lmfit-doc.substvars -cdebian/control -Pdebian/python-lmfit-doc - chmod 0644 -- debian/python3-lmfit/DEBIAN/control -dpkg-gencontrol: warning: package python-lmfit-doc: substitution variable ${python3:Depends} unused, but is defined - chmod 0644 -- debian/python-lmfit-doc/DEBIAN/control - dh_md5sums -O--buildsystem=pybuild - install -m0755 -d debian/python3-lmfit/DEBIAN - install -m0755 -d debian/python-lmfit-doc/DEBIAN - cd debian/python3-lmfit >/dev/null && xargs -r0 md5sum | perl -pe 'if (s@^\\@@) { s/\\\\/\\/g; }' > DEBIAN/md5sums - cd debian/python-lmfit-doc >/dev/null && xargs -r0 md5sum | perl -pe 'if (s@^\\@@) { s/\\\\/\\/g; }' > DEBIAN/md5sums - chmod 0644 -- debian/python3-lmfit/DEBIAN/md5sums - chmod 0644 -- debian/python-lmfit-doc/DEBIAN/md5sums - dh_builddeb -O--buildsystem=pybuild - dpkg-deb --root-owner-group --build debian/python3-lmfit .. - dpkg-deb --root-owner-group --build debian/python-lmfit-doc .. -dpkg-deb: building package 'python3-lmfit' in '../python3-lmfit_1.3.2-2_all.deb'. -dpkg-deb: building package 'python-lmfit-doc' in '../python-lmfit-doc_1.3.2-2_all.deb'. - dpkg-genbuildinfo --build=binary -O../lmfit-py_1.3.2-2_amd64.buildinfo - dpkg-genchanges --build=binary -O../lmfit-py_1.3.2-2_amd64.changes -dpkg-genchanges: info: binary-only upload (no source code included) - dpkg-source --after-build . -dpkg-buildpackage: info: binary-only upload (no source included) -dpkg-genchanges: info: not including original source code in upload +=========================== short test summary info ============================ +FAILED tests/test_manypeaks_speed.py::test_manypeaks_speed - assert (17403464... +===== 1 failed, 649 passed, 12 skipped, 19 warnings in 1844.47s (0:30:44) ====== +E: pybuild pybuild:389: test: plugin pyproject failed with: exit code=1: cd /build/reproducible-path/lmfit-py-1.3.2/.pybuild/cpython3_3.13_lmfit/build; python3.13 -m pytest tests + rm -fr -- /tmp/dh-xdg-rundir-MMwPnUEj +dh_auto_test: error: pybuild --test --test-pytest -i python{version} -p "3.12 3.13" returned exit code 13 +make: *** [debian/rules:15: binary] Error 25 +dpkg-buildpackage: error: debian/rules binary subprocess returned exit status 2 I: copying local configuration +E: Failed autobuilding of package +I: user script /srv/workspace/pbuilder/356560/tmp/hooks/C01_cleanup starting +debug output: disk usage on i-capture-the-hostname at Sun Feb 23 22:01:36 UTC 2025 +Filesystem Size Used Avail Use% Mounted on +tmpfs 40G 0 40G 0% /dev/shm + +I: user script /srv/workspace/pbuilder/356560/tmp/hooks/C01_cleanup finished I: unmounting dev/ptmx filesystem I: unmounting dev/pts filesystem I: unmounting dev/shm filesystem I: unmounting proc filesystem I: unmounting sys filesystem I: cleaning the build env -I: removing directory /srv/workspace/pbuilder/2093964 and its subdirectories -I: Current time: Sat Mar 28 15:24:00 -12 2026 -I: pbuilder-time-stamp: 1774754640 +I: removing directory /srv/workspace/pbuilder/356560 and its subdirectories