Diff of the two buildlogs:
--
--- b1/build.log 2025-04-03 10:02:48.537538157 +0000
+++ b2/build.log 2025-04-03 10:41:13.798534751 +0000
@@ -1,6 +1,6 @@
I: pbuilder: network access will be disabled during build
-I: Current time: Wed May 6 04:20:39 -12 2026
-I: pbuilder-time-stamp: 1778084439
+I: Current time: Fri Apr 4 00:02:51 +14 2025
+I: pbuilder-time-stamp: 1743674571
I: Building the build Environment
I: extracting base tarball [/var/cache/pbuilder/unstable-reproducible-base.tgz]
I: copying local configuration
@@ -26,52 +26,84 @@
dpkg-source: info: applying exclude_test_for_32bit.patch
I: Not using root during the build.
I: Installing the build-deps
-I: user script /srv/workspace/pbuilder/269231/tmp/hooks/D02_print_environment starting
+I: user script /srv/workspace/pbuilder/2303067/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 Apr 3 10:03 /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/2303067/tmp/hooks/D01_modify_environment finished
+I: user script /srv/workspace/pbuilder/2303067/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='80c9b69e54b2437382476fbf70d3ad13'
- 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='269231'
- PS1='# '
- PS2='> '
+ INVOCATION_ID=030bd3e2763940a799e66483321365d3
+ 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=2303067
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.WshGpeY4/pbuilderrc_hY5f --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.WshGpeY4/b1 --logfile b1/build.log lmfit-py_1.3.3-1.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.WshGpeY4/pbuilderrc_XmRi --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.WshGpeY4/b2 --logfile b2/build.log lmfit-py_1.3.3-1.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 6.12.12+bpo-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.12.12-1~bpo12+1 (2025-02-23) x86_64 GNU/Linux
+ Linux i-capture-the-hostname 6.1.0-32-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.129-1 (2025-03-06) x86_64 GNU/Linux
I: ls -l /bin
- lrwxrwxrwx 1 root root 7 Mar 4 2025 /bin -> usr/bin
-I: user script /srv/workspace/pbuilder/269231/tmp/hooks/D02_print_environment finished
+ lrwxrwxrwx 1 root root 7 Mar 4 11:20 /bin -> usr/bin
+I: user script /srv/workspace/pbuilder/2303067/tmp/hooks/D02_print_environment finished
-> Attempting to satisfy build-dependencies
-> Creating pbuilder-satisfydepends-dummy package
Package: pbuilder-satisfydepends-dummy
@@ -382,7 +414,7 @@
Get: 231 http://deb.debian.org/debian unstable/main amd64 python3-setuptools-scm all 8.2.1-1 [41.2 kB]
Get: 232 http://deb.debian.org/debian unstable/main amd64 python3-sphinx-gallery all 0.17.1-1 [401 kB]
Get: 233 http://deb.debian.org/debian unstable/main amd64 python3-uncertainties all 3.2.2-1 [54.7 kB]
-Fetched 129 MB in 1s (112 MB/s)
+Fetched 129 MB in 10s (13.4 MB/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 ... 19810 files and directories currently installed.)
@@ -1132,8 +1164,8 @@
Setting up tzdata (2025b-1) ...
Current default time zone: 'Etc/UTC'
-Local time is now: Wed May 6 16:21:22 UTC 2026.
-Universal Time is now: Wed May 6 16:21:22 UTC 2026.
+Local time is now: Thu Apr 3 10:06:46 UTC 2025.
+Universal Time is now: Thu Apr 3 10:06:46 UTC 2025.
Run 'dpkg-reconfigure tzdata' if you wish to change it.
Setting up unicode-data (15.1.0-1) ...
@@ -1356,7 +1388,11 @@
Building tag database...
-> Finished parsing the build-deps
I: Building the package
-I: Running cd /build/reproducible-path/lmfit-py-1.3.3/ && 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_1.3.3-1_source.changes
+I: user script /srv/workspace/pbuilder/2303067/tmp/hooks/A99_set_merged_usr starting
+Not re-configuring usrmerge for unstable
+I: user script /srv/workspace/pbuilder/2303067/tmp/hooks/A99_set_merged_usr finished
+hostname: Name or service not known
+I: Running cd /build/reproducible-path/lmfit-py-1.3.3/ && 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_1.3.3-1_source.changes
dpkg-buildpackage: info: source package lmfit-py
dpkg-buildpackage: info: source version 1.3.3-1
dpkg-buildpackage: info: source distribution unstable
@@ -1408,17 +1444,17 @@
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
@@ -1433,22 +1469,22 @@
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-1.3.3.egg-info
running install_scripts
creating build/bdist.linux-x86_64/wheel/lmfit-1.3.3.dist-info/WHEEL
-creating '/build/reproducible-path/lmfit-py-1.3.3/.pybuild/cpython3_3.13_lmfit/.tmp-izziwspu/lmfit-1.3.3-py3-none-any.whl' and adding 'build/bdist.linux-x86_64/wheel' to it
+creating '/build/reproducible-path/lmfit-py-1.3.3/.pybuild/cpython3_3.13_lmfit/.tmp-o1r8l0pm/lmfit-1.3.3-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'
@@ -1477,7 +1513,7 @@
platform linux -- Python 3.13.2, pytest-8.3.5, pluggy-1.5.0
rootdir: /build/reproducible-path/lmfit-py-1.3.3/.pybuild/cpython3_3.13_lmfit/build
configfile: pyproject.toml
-plugins: typeguard-4.4.2, cov-5.0.0
+plugins: cov-5.0.0, typeguard-4.4.2
collected 671 items
tests/test_1variable.py . [ 0%]
@@ -1501,7 +1537,7 @@
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%]
@@ -1519,8 +1555,35 @@
tests/test_params_uvars.py .... [ 93%]
tests/test_printfuncs.py ............................s...... [ 98%]
tests/test_shgo.py ...... [ 99%]
-tests/test_stepmodel.py .... [100%]
+tests/test_stepmodel.py ..../usr/lib/python3/dist-packages/coverage/data.py:180: CoverageWarning: Data file '/build/reproducible-path/lmfit-py-1.3.3/.pybuild/cpython3_3.13_lmfit/build/.coverage.i-capture-the-hostname.2439871.XuHrbmMx' doesn't seem to be a coverage data file:
+ data._warn(str(exc))
+ [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 (1743675591.214749 - 1743675589.9164617) < 0.5
+
+tests/test_manypeaks_speed.py:33: AssertionError
=============================== warnings summary ===============================
tests/test_manypeaks_speed.py:15
/build/reproducible-path/lmfit-py-1.3.3/.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
@@ -1595,2038 +1658,26 @@
---------- coverage: platform linux, python 3.13.2-final-0 -----------
Coverage HTML written to dir htmlcov
-=========== 659 passed, 12 skipped, 17 warnings in 130.05s (0:02:10) ===========
-I: pybuild pybuild:334: rm -fr /build/reproducible-path/lmfit-py-1.3.3/.pybuild/cpython3_3.13_lmfit/build/NIST_STRD /build/reproducible-path/lmfit-py-1.3.3/.pybuild/cpython3_3.13_lmfit/build/examples; find /build/reproducible-path/lmfit-py-1.3.3/.pybuild/cpython3_3.13_lmfit/build -name "*.sav" -delete
- rm -fr -- /tmp/dh-xdg-rundir-tTmd5Tt9
- 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-1.3.3/debian/tmp
- pybuild --install -i python{version} -p 3.13 --dest-dir=/build/reproducible-path/lmfit-py-1.3.3/debian/tmp
-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-1.3.3'
-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 ...
-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://docs.scipy.org/doc/scipy/objects.inv' not fetchable due to <class 'requests.exceptions.ConnectionError'>: HTTPSConnectionPool(host='docs.scipy.org', port=443): Max retries exceeded with url: /doc/scipy/objects.inv (Caused by NameResolutionError("<urllib3.connection.HTTPSConnection object at 0x7f668413c050>: Failed to resolve 'docs.scipy.org' ([Errno -3] Temporary failure in name resolution)"))
-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 <class 'requests.exceptions.ConnectionError'>: HTTPSConnectionPool(host='docs.python.org', port=443): Max retries exceeded with url: /3/objects.inv (Caused by NameResolutionError("<urllib3.connection.HTTPSConnection object at 0x7f668429ee40>: Failed to resolve 'docs.python.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 <class 'requests.exceptions.ConnectionError'>: HTTPSConnectionPool(host='pandas.pydata.org', port=443): Max retries exceeded with url: /pandas-docs/stable/objects.inv (Caused by NameResolutionError("<urllib3.connection.HTTPSConnection object at 0x7f668413f390>: 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://numpy.org/doc/stable/objects.inv' not fetchable due to <class 'requests.exceptions.ConnectionError'>: HTTPSConnectionPool(host='numpy.org', port=443): Max retries exceeded with url: /doc/stable/objects.inv (Caused by NameResolutionError("<urllib3.connection.HTTPSConnection object at 0x7f668413fc50>: 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://matplotlib.org/stable/objects.inv' not fetchable due to <class 'requests.exceptions.ConnectionError'>: HTTPSConnectionPool(host='matplotlib.org', port=443): Max retries exceeded with url: /stable/objects.inv (Caused by NameResolutionError("<urllib3.connection.HTTPSConnection object at 0x7f668413fd90>: 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://docs.sympy.org/latest/objects.inv' not fetchable due to <class 'requests.exceptions.ConnectionError'>: HTTPSConnectionPool(host='docs.sympy.org', port=443): Max retries exceeded with url: /latest/objects.inv (Caused by NameResolutionError("<urllib3.connection.HTTPSConnection object at 0x7f668419c410>: Failed to resolve 'docs.sympy.org' ([Errno -3] Temporary failure in name resolution)"))
-generating gallery...
-generating gallery for examples... [ 5%] example_use_pandas.py
-generating gallery for examples... [ 10%] example_expression_model.py
-generating gallery for examples... [ 14%] example_fit_with_inequality.py
-generating gallery for examples... [ 19%] example_diffev.py
-generating gallery for examples... [ 24%] example_fit_with_bounds.py
-generating gallery for examples... [ 29%] example_fit_with_algebraic_constraint.py
-generating gallery for examples... [ 33%] example_reduce_fcn.py
-generating gallery for examples... [ 38%] example_sympy.py
-generating gallery for examples... [ 43%] example_basinhopping.py
-generating gallery for examples... [ 48%] example_fit_multi_datasets.py
-generating gallery for examples... [ 52%] example_fit_multi_datasets_Model-interface.py
-generating gallery for examples... [ 57%] example_Model_interface.py
-generating gallery for examples... [ 62%] example_fit_with_derivfunc.py
-generating gallery for examples... [ 67%] example_detect_outliers.py
-generating gallery for examples... [ 71%] example_uncertainties_y_and_x.py
-generating gallery for examples... [ 76%] example_complex_resonator_model.py
-generating gallery for examples... [ 81%] lmfit_emcee_model_selection.py
-generating gallery for examples... [ 86%] example_fit_jacobian_benchmark.py
-generating gallery for examples... [ 90%] example_confidence_interval.py
-generating gallery for examples... [ 95%] example_two_dimensional_peak.py
-generating gallery for examples... [100%] example_brute.py
-
-computation time summary:
- - ../examples/example_brute.py: 24.22 sec 0.0 MB
- - ../examples/example_confidence_interval.py: 17.68 sec 0.0 MB
- - ../examples/example_basinhopping.py: 3.91 sec 0.0 MB
- - ../examples/example_two_dimensional_peak.py: 3.41 sec 0.0 MB
- - ../examples/example_fit_jacobian_benchmark.py: 1.64 sec 0.0 MB
- - ../examples/example_detect_outliers.py: 1.25 sec 0.0 MB
- - ../examples/example_sympy.py: 1.21 sec 0.0 MB
- - ../examples/example_complex_resonator_model.py: 0.82 sec 0.0 MB
- - ../examples/example_diffev.py: 0.52 sec 0.0 MB
- - ../examples/example_Model_interface.py: 0.45 sec 0.0 MB
- - ../examples/example_fit_multi_datasets_Model-interface.py: 0.37 sec 0.0 MB
- - ../examples/example_reduce_fcn.py: 0.36 sec 0.0 MB
- - ../examples/example_use_pandas.py: 0.32 sec 0.0 MB
- - ../examples/example_fit_with_algebraic_constraint.py: 0.32 sec 0.0 MB
- - ../examples/example_fit_with_bounds.py: 0.31 sec 0.0 MB
- - ../examples/example_fit_multi_datasets.py: 0.30 sec 0.0 MB
- - ../examples/example_uncertainties_y_and_x.py: 0.29 sec 0.0 MB
- - ../examples/example_fit_with_inequality.py: 0.29 sec 0.0 MB
- - ../examples/example_expression_model.py: 0.29 sec 0.0 MB
- - ../examples/example_fit_with_derivfunc.py: 0.29 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] 36 added, 0 changed, 0 removed
-reading sources... [ 3%] bounds
-reading sources... [ 6%] builtin_models
-reading sources... [ 8%] confidence
-reading sources... [ 11%] constraints
-reading sources... [ 14%] contents
-reading sources... [ 17%] examples/example_Model_interface
-reading sources... [ 19%] examples/example_basinhopping
-reading sources... [ 22%] examples/example_brute
-reading sources... [ 25%] examples/example_complex_resonator_model
-reading sources... [ 28%] examples/example_confidence_interval
-reading sources... [ 31%] examples/example_detect_outliers
-reading sources... [ 33%] examples/example_diffev
-reading sources... [ 36%] examples/example_expression_model
-reading sources... [ 39%] examples/example_fit_jacobian_benchmark
-reading sources... [ 42%] examples/example_fit_multi_datasets
-reading sources... [ 44%] examples/example_fit_multi_datasets_Model-interface
-reading sources... [ 47%] examples/example_fit_with_algebraic_constraint
-reading sources... [ 50%] examples/example_fit_with_bounds
-reading sources... [ 53%] examples/example_fit_with_derivfunc
-reading sources... [ 56%] examples/example_fit_with_inequality
-reading sources... [ 58%] examples/example_reduce_fcn
-reading sources... [ 61%] examples/example_sympy
-reading sources... [ 64%] examples/example_two_dimensional_peak
-reading sources... [ 67%] examples/example_uncertainties_y_and_x
-reading sources... [ 69%] examples/example_use_pandas
-reading sources... [ 72%] examples/index
-reading sources... [ 75%] examples/lmfit_emcee_model_selection
-reading sources... [ 78%] faq
-reading sources... [ 81%] fitting
-reading sources... [ 83%] index
-reading sources... [ 86%] installation
-reading sources... [ 89%] intro
-reading sources... [ 92%] model
-reading sources... [ 94%] parameters
-reading sources... [ 97%] support
-reading sources... [100%] whatsnew
-
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/confidence.rst:144: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
-
- # <examples/doc_confidence_chi2_maps.py>
- 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-1.3.3/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()
- # <end examples/doc_confidence_chi2_maps.py> [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/faq.rst:239: 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-1.3.3/doc/faq.rst:282: 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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/fitting.rst:110: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
- :hide-code:
-
- period = 1 [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/doc/fitting.rst:526: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
- :hide-code:
-
- print(fit_report(out)) [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/model.rst:120: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
-
- params = gmodel.make_params() [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/model.rst:180: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
- :hide-code:
-
- print(result.fit_report()) [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/model.rst:775: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute:: ../examples/doc_model_savemodel.py [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/model.rst:1116: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute:: ../examples/doc_model_uncertainty2.py [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/doc/model.rst:1126: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute:: ../examples/doc_model_uncertainty_pred.py [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/doc/model.rst:1169: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute:: ../examples/doc_parameters_uvars.py [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/model.rst:1239: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
-
- mod = Model(gaussian_plus_line) [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/doc/model.rst:1259: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
-
- mod = Model(gaussian) + Model(line) [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/doc/model.rst:1270: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
- :hide-code:
-
- print(result.fit_report()) [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/model.rst:1387: ERROR: Unknown directive type "jupyter-execute".
-
-.. jupyter-execute::
- :hide-code:
-
- print(result.fit_report()) [docutils]
-/build/reproducible-path/lmfit-py-1.3.3/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-1.3.3/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-1.3.3/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-1.3.3/doc/bounds.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- bounds
-/build/reproducible-path/lmfit-py-1.3.3/doc/builtin_models.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- builtin_models
-/build/reproducible-path/lmfit-py-1.3.3/doc/confidence.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- confidence
-/build/reproducible-path/lmfit-py-1.3.3/doc/constraints.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- constraints
-/build/reproducible-path/lmfit-py-1.3.3/doc/examples/index.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- examples/index
-/build/reproducible-path/lmfit-py-1.3.3/doc/faq.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- faq
-/build/reproducible-path/lmfit-py-1.3.3/doc/fitting.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- fitting
-/build/reproducible-path/lmfit-py-1.3.3/doc/installation.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- installation
-/build/reproducible-path/lmfit-py-1.3.3/doc/intro.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- intro
-/build/reproducible-path/lmfit-py-1.3.3/doc/model.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- model
-/build/reproducible-path/lmfit-py-1.3.3/doc/parameters.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- parameters
-/build/reproducible-path/lmfit-py-1.3.3/doc/support.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- support
-/build/reproducible-path/lmfit-py-1.3.3/doc/whatsnew.rst: document is referenced in multiple toctrees: ['contents', 'index'], selecting: index <- whatsnew
-done
-preparing documents... done
-copying assets...
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- Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_detect_outliers_thumb.png using File::StripNondeterminism::handlers::png
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- 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_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_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_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_fit_jacobian_benchmark_thumb.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_jacobian_benchmark_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_004_3_00x.png using File::StripNondeterminism::handlers::png
- Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_images/sphx_glr_example_fit_multi_datasets_Model-interface_thumb.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_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_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_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_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_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_uncertainties_y_and_x_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_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_fit_multi_datasets_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_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_fit_multi_datasets_Model-interface_001.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/4b0b2bd3ab5ac85a687b73fdf77c10e8/example_fit_with_algebraic_constraint.zip using File::StripNondeterminism::handlers::zip
- Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/906b26cb632f958951ad30391cca03c2/example_fit_multi_datasets_Model-interface.zip using File::StripNondeterminism::handlers::zip
- Normalizing debian/python-lmfit-doc/usr/share/doc/python3-lmfit/html/_downloads/60ed202e1a46df18e620e4db6b68bc5b/example_uncertainties_y_and_x.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/_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/9a2c85e37f5bf773d8457e3313adec9d/example_fit_jacobian_benchmark.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/dbec5987901e14219cbb0374bcb09f84/example_Model_interface.zip using File::StripNondeterminism::handlers::zip
- 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/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/_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/42b143772ac94b1e24f82c78c37f8727/example_fit_jacobian_benchmark.py usr/share/doc/python3-lmfit/html/_downloads/6069607ae016c4f4f055d1c8dfd4bfa7/example_sympy.ipynb usr/share/doc/python3-lmfit/html/_downloads/6bd1774e2b7de7f7c5a9bb78e91a173a/example_fit_multi_datasets_Model-interface.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/9db45352ed3b7a40b0471b4137f67079/example_fit_jacobian_benchmark.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-1.3.3'
- 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/42b143772ac94b1e24f82c78c37f8727/example_fit_jacobian_benchmark.py usr/share/doc/python3-lmfit/html/_downloads/6069607ae016c4f4f055d1c8dfd4bfa7/example_sympy.ipynb usr/share/doc/python3-lmfit/html/_downloads/6bd1774e2b7de7f7c5a9bb78e91a173a/example_fit_multi_datasets_Model-interface.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/9db45352ed3b7a40b0471b4137f67079/example_fit_jacobian_benchmark.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-1.3.3'
- 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
-Possible precedence issue with control flow operator (return) at /usr/bin/dh_numpy3 line 57.
- 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/python-lmfit-doc/DEBIAN/control
- chmod 0644 -- debian/python3-lmfit/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_1.3.3-1_all.deb'.
-dpkg-deb: building package 'python-lmfit-doc' in '../python-lmfit-doc_1.3.3-1_all.deb'.
- dpkg-genbuildinfo --build=binary -O../lmfit-py_1.3.3-1_amd64.buildinfo
- dpkg-genchanges --build=binary -O../lmfit-py_1.3.3-1_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: including full source code in upload
+=========================== short test summary info ============================
+FAILED tests/test_manypeaks_speed.py::test_manypeaks_speed - assert (17436755...
+===== 1 failed, 658 passed, 12 skipped, 17 warnings in 1595.06s (0:26:35) ======
+E: pybuild pybuild:389: test: plugin pyproject failed with: exit code=1: cd /build/reproducible-path/lmfit-py-1.3.3/.pybuild/cpython3_3.13_lmfit/build; python3.13 -m pytest tests
+ rm -fr -- /tmp/dh-xdg-rundir-31jq5DoW
+dh_auto_test: error: pybuild --test --test-pytest -i python{version} -p 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/2303067/tmp/hooks/C01_cleanup starting
+debug output: disk usage on i-capture-the-hostname at Thu Apr 3 10:41:06 UTC 2025
+Filesystem Size Used Avail Use% Mounted on
+tmpfs 40G 0 40G 0% /dev/shm
+
+I: user script /srv/workspace/pbuilder/2303067/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/269231 and its subdirectories
-I: Current time: Wed May 6 04:25:47 -12 2026
-I: pbuilder-time-stamp: 1778084747
+I: removing directory /srv/workspace/pbuilder/2303067 and its subdirectories