Build log for python-skbio (0.5.6-5) on armhf

python-skbio → 0.5.6-5 → armhf → 2021-10-18 09:01:25

sbuild (Debian sbuild) 0.72.0 (25 Oct 2016) on mb-lxc-02

+==============================================================================+
| python-skbio 0.5.6-5 (armhf)                 Mon, 18 Oct 2021 08:47:29 +0000 |
+==============================================================================+

Package: python-skbio
Version: 0.5.6-5
Source Version: 0.5.6-5
Distribution: bookworm-staging
Machine Architecture: armhf
Host Architecture: armhf
Build Architecture: armhf

I: NOTICE: Log filtering will replace 'var/lib/schroot/mount/bookworm-staging-armhf-sbuild-b8389cd7-8d9e-4db6-984b-999e98902778' with '<<CHROOT>>'

+------------------------------------------------------------------------------+
| Update chroot                                                                |
+------------------------------------------------------------------------------+

Get:1 http://172.17.0.1/private bookworm-staging InRelease [11.3 kB]
Get:2 http://172.17.0.1/private bookworm-staging/main Sources [12.4 MB]
Get:3 http://172.17.0.1/private bookworm-staging/main armhf Packages [13.4 MB]
Fetched 25.9 MB in 10s (2718 kB/s)
Reading package lists...
W: No sandbox user '_apt' on the system, can not drop privileges

+------------------------------------------------------------------------------+
| Fetch source files                                                           |
+------------------------------------------------------------------------------+


Check APT
---------

Checking available source versions...

Download source files with APT
------------------------------

Reading package lists...
NOTICE: 'python-skbio' packaging is maintained in the 'Git' version control system at:
https://salsa.debian.org/med-team/python-skbio.git
Please use:
git clone https://salsa.debian.org/med-team/python-skbio.git
to retrieve the latest (possibly unreleased) updates to the package.
Need to get 8380 kB of source archives.
Get:1 http://172.17.0.1/private bookworm-staging/main python-skbio 0.5.6-5 (dsc) [2837 B]
Get:2 http://172.17.0.1/private bookworm-staging/main python-skbio 0.5.6-5 (tar) [8366 kB]
Get:3 http://172.17.0.1/private bookworm-staging/main python-skbio 0.5.6-5 (diff) [11.4 kB]
Fetched 8380 kB in 1s (6635 kB/s)
Download complete and in download only mode
I: NOTICE: Log filtering will replace 'build/python-skbio-BwiGX3/python-skbio-0.5.6' with '<<PKGBUILDDIR>>'
I: NOTICE: Log filtering will replace 'build/python-skbio-BwiGX3' with '<<BUILDDIR>>'

+------------------------------------------------------------------------------+
| Install build-essential                                                      |
+------------------------------------------------------------------------------+


Setup apt archive
-----------------

Merged Build-Depends: build-essential, fakeroot
Filtered Build-Depends: build-essential, fakeroot
dpkg-deb: building package 'sbuild-build-depends-core-dummy' in '/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive/sbuild-build-depends-core-dummy.deb'.
dpkg-scanpackages: warning: Packages in archive but missing from override file:
dpkg-scanpackages: warning:   sbuild-build-depends-core-dummy
dpkg-scanpackages: info: Wrote 1 entries to output Packages file.
gpg: keybox '/<<BUILDDIR>>/resolver-J0DkFJ/gpg/pubring.kbx' created
gpg: /<<BUILDDIR>>/resolver-J0DkFJ/gpg/trustdb.gpg: trustdb created
gpg: key 37145E60F90AF620: public key "Sbuild Signer (Sbuild Build Dependency Archive Key) <buildd-tools-devel@lists.alioth.debian.org>" imported
gpg: Total number processed: 1
gpg:               imported: 1
gpg: key 37145E60F90AF620: "Sbuild Signer (Sbuild Build Dependency Archive Key) <buildd-tools-devel@lists.alioth.debian.org>" not changed
gpg: key 37145E60F90AF620: secret key imported
gpg: Total number processed: 1
gpg:              unchanged: 1
gpg:       secret keys read: 1
gpg:   secret keys imported: 1
gpg: using "Sbuild Signer" as default secret key for signing
Ign:1 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ InRelease
Get:2 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ Release [957 B]
Get:3 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ Release.gpg [370 B]
Get:4 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ Sources [349 B]
Get:5 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ Packages [433 B]
Fetched 2109 B in 0s (9706 B/s)
Reading package lists...
W: No sandbox user '_apt' on the system, can not drop privileges
Reading package lists...

Install core build dependencies (apt-based resolver)
----------------------------------------------------

Installing build dependencies
Reading package lists...
Building dependency tree...
Reading state information...
The following package was automatically installed and is no longer required:
  netbase
Use 'apt autoremove' to remove it.
The following NEW packages will be installed:
  sbuild-build-depends-core-dummy
0 upgraded, 1 newly installed, 0 to remove and 36 not upgraded.
Need to get 852 B of archives.
After this operation, 0 B of additional disk space will be used.
Get:1 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ sbuild-build-depends-core-dummy 0.invalid.0 [852 B]
debconf: delaying package configuration, since apt-utils is not installed
Fetched 852 B in 0s (62.4 kB/s)
Selecting previously unselected package sbuild-build-depends-core-dummy.
(Reading database ... 12484 files and directories currently installed.)
Preparing to unpack .../sbuild-build-depends-core-dummy_0.invalid.0_armhf.deb ...
Unpacking sbuild-build-depends-core-dummy (0.invalid.0) ...
Setting up sbuild-build-depends-core-dummy (0.invalid.0) ...
W: No sandbox user '_apt' on the system, can not drop privileges

+------------------------------------------------------------------------------+
| Check architectures                                                          |
+------------------------------------------------------------------------------+

Arch check ok (armhf included in any all)

+------------------------------------------------------------------------------+
| Install package build dependencies                                           |
+------------------------------------------------------------------------------+


Setup apt archive
-----------------

Merged Build-Depends: debhelper-compat (= 13), dh-python, python3-all-dev, python3-setuptools, python3-numpy (>= 1:1.9.2), python3-matplotlib, python3-cachecontrol, python3-decorator, python3-pandas (>= 0.19.2), python3-scipy (>= 1.3.3), python3-ipython, python3-hdmedians (>= 0.14.1), python3-sklearn, python3-natsort, libssw-dev, sphinx-common, libsimde-dev, python3-lockfile, python3-pytest
Filtered Build-Depends: debhelper-compat (= 13), dh-python, python3-all-dev, python3-setuptools, python3-numpy (>= 1:1.9.2), python3-matplotlib, python3-cachecontrol, python3-decorator, python3-pandas (>= 0.19.2), python3-scipy (>= 1.3.3), python3-ipython, python3-hdmedians (>= 0.14.1), python3-sklearn, python3-natsort, libssw-dev, sphinx-common, libsimde-dev, python3-lockfile, python3-pytest
dpkg-deb: building package 'sbuild-build-depends-python-skbio-dummy' in '/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive/sbuild-build-depends-python-skbio-dummy.deb'.
dpkg-scanpackages: warning: Packages in archive but missing from override file:
dpkg-scanpackages: warning:   sbuild-build-depends-core-dummy sbuild-build-depends-python-skbio-dummy
dpkg-scanpackages: info: Wrote 2 entries to output Packages file.
gpg: using "Sbuild Signer" as default secret key for signing
Ign:1 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ InRelease
Get:2 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ Release [963 B]
Get:3 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ Release.gpg [370 B]
Get:4 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ Sources [662 B]
Get:5 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ Packages [728 B]
Fetched 2723 B in 0s (12.4 kB/s)
Reading package lists...
W: No sandbox user '_apt' on the system, can not drop privileges
Reading package lists...

Install python-skbio build dependencies (apt-based resolver)
------------------------------------------------------------

Installing build dependencies
Reading package lists...
Building dependency tree...
Reading state information...
The following package was automatically installed and is no longer required:
  netbase
Use 'apt autoremove' to remove it.
The following additional packages will be installed:
  autoconf automake autopoint autotools-dev bsdextrautils ca-certificates
  cython3 debhelper dh-autoreconf dh-python dh-strip-nondeterminism dwz file
  fonts-lyx gcc-11-base gettext gettext-base groff-base intltool-debian
  libarchive-zip-perl libasan6 libatomic1 libblas3 libbrotli1 libbsd0 libcc1-0
  libdebhelper-perl libdeflate0 libelf1 libexpat1 libexpat1-dev libffi8
  libfile-stripnondeterminism-perl libfreetype6 libgcc-s1 libgfortran5
  libgomp1 libicu67 libimagequant0 libjbig0 libjpeg62-turbo libjs-jquery
  libjs-jquery-ui libjs-sphinxdoc libjs-underscore liblapack3 liblbfgsb0
  liblcms2-2 libmagic-mgc libmagic1 libmd0 libmpdec3 libncurses6 libpipeline1
  libpng16-16 libprocps8 libpython3-all-dev libpython3-dev libpython3-stdlib
  libpython3.9 libpython3.9-dev libpython3.9-minimal libpython3.9-stdlib
  libsigsegv2 libsimde-dev libssw-dev libssw0 libstdc++6 libsub-override-perl
  libtiff5 libtool libubsan1 libuchardet0 libwebp6 libwebpdemux2 libwebpmux3
  libxau6 libxcb1 libxdmcp6 libxml2 m4 mailcap man-db media-types mime-support
  openssl po-debconf procps python-matplotlib-data python3 python3-all
  python3-all-dev python3-attr python3-backcall python3-cachecontrol
  python3-certifi python3-chardet python3-cycler python3-dateutil
  python3-decorator python3-dev python3-distutils python3-hdmedians
  python3-idna python3-importlib-metadata python3-iniconfig python3-ipython
  python3-jedi python3-joblib python3-kiwisolver python3-lib2to3
  python3-lockfile python3-matplotlib python3-minimal python3-more-itertools
  python3-msgpack python3-natsort python3-numpy python3-packaging
  python3-pandas python3-pandas-lib python3-parso python3-pexpect
  python3-pickleshare python3-pil python3-pkg-resources python3-pluggy
  python3-prompt-toolkit python3-ptyprocess python3-py python3-pygments
  python3-pyparsing python3-pytest python3-requests python3-scipy
  python3-setuptools python3-six python3-sklearn python3-sklearn-lib
  python3-threadpoolctl python3-toml python3-traitlets python3-tz
  python3-urllib3 python3-wcwidth python3-zipp python3.9 python3.9-dev
  python3.9-minimal sensible-utils sphinx-common ttf-bitstream-vera zlib1g-dev
Suggested packages:
  autoconf-archive gnu-standards autoconf-doc cython-doc dh-make gettext-doc
  libasprintf-dev libgettextpo-dev groff libjs-jquery-ui-docs liblcms2-utils
  libtool-doc gfortran | fortran95-compiler gcj-jdk m4-doc apparmor less
  www-browser libmail-box-perl python3-doc python3-tk python3-venv
  python-attr-doc python-cycler-doc python-ipython-doc python-lockfile-doc
  dvipng ffmpeg ghostscript gir1.2-gtk-3.0 inkscape ipython3 librsvg2-common
  python-matplotlib-doc python3-cairocffi python3-gi python3-gi-cairo
  python3-gobject python3-nose python3-pyqt5 python3-sip python3-tornado
  texlive-extra-utils texlive-latex-extra ttf-staypuft python-natsort-doc
  gfortran python-numpy-doc python3-numpy-dbg python-pandas-doc
  python3-statsmodels python-pexpect-doc python-pil-doc python3-pil-dbg
  subversion python-pygments-doc python-pyparsing-doc python3-cryptography
  python3-openssl python3-socks python-requests-doc python-scipy-doc
  python-setuptools-doc python3-dap python-sklearn-doc python3.9-venv
  python3.9-doc binfmt-support
Recommended packages:
  curl | wget | lynx libarchive-cpio-perl javascript-common libgpm2
  libltdl-dev libmail-sendmail-perl psmisc python3-simplejson python3-psutil
  python3-tk python3-bottleneck python3-numexpr python3-odf python3-openpyxl
  python3-xlwt python3-bs4 python3-html5lib python3-lxml python3-tables
  python3-jinja2 python3-olefile python3-nose python3-sphinx
The following NEW packages will be installed:
  autoconf automake autopoint autotools-dev bsdextrautils ca-certificates
  cython3 debhelper dh-autoreconf dh-python dh-strip-nondeterminism dwz file
  fonts-lyx gettext gettext-base groff-base intltool-debian
  libarchive-zip-perl libblas3 libbrotli1 libbsd0 libdebhelper-perl
  libdeflate0 libelf1 libexpat1 libexpat1-dev libffi8
  libfile-stripnondeterminism-perl libfreetype6 libgfortran5 libicu67
  libimagequant0 libjbig0 libjpeg62-turbo libjs-jquery libjs-jquery-ui
  libjs-sphinxdoc libjs-underscore liblapack3 liblbfgsb0 liblcms2-2
  libmagic-mgc libmagic1 libmd0 libmpdec3 libncurses6 libpipeline1 libpng16-16
  libprocps8 libpython3-all-dev libpython3-dev libpython3-stdlib libpython3.9
  libpython3.9-dev libpython3.9-minimal libpython3.9-stdlib libsigsegv2
  libsimde-dev libssw-dev libssw0 libsub-override-perl libtiff5 libtool
  libuchardet0 libwebp6 libwebpdemux2 libwebpmux3 libxau6 libxcb1 libxdmcp6
  libxml2 m4 mailcap man-db media-types mime-support openssl po-debconf procps
  python-matplotlib-data python3 python3-all python3-all-dev python3-attr
  python3-backcall python3-cachecontrol python3-certifi python3-chardet
  python3-cycler python3-dateutil python3-decorator python3-dev
  python3-distutils python3-hdmedians python3-idna python3-importlib-metadata
  python3-iniconfig python3-ipython python3-jedi python3-joblib
  python3-kiwisolver python3-lib2to3 python3-lockfile python3-matplotlib
  python3-minimal python3-more-itertools python3-msgpack python3-natsort
  python3-numpy python3-packaging python3-pandas python3-pandas-lib
  python3-parso python3-pexpect python3-pickleshare python3-pil
  python3-pkg-resources python3-pluggy python3-prompt-toolkit
  python3-ptyprocess python3-py python3-pygments python3-pyparsing
  python3-pytest python3-requests python3-scipy python3-setuptools python3-six
  python3-sklearn python3-sklearn-lib python3-threadpoolctl python3-toml
  python3-traitlets python3-tz python3-urllib3 python3-wcwidth python3-zipp
  python3.9 python3.9-dev python3.9-minimal
  sbuild-build-depends-python-skbio-dummy sensible-utils sphinx-common
  ttf-bitstream-vera zlib1g-dev
The following packages will be upgraded:
  gcc-11-base libasan6 libatomic1 libcc1-0 libgcc-s1 libgomp1 libstdc++6
  libubsan1
8 upgraded, 146 newly installed, 0 to remove and 28 not upgraded.
Need to get 78.4 MB of archives.
After this operation, 305 MB of additional disk space will be used.
Get:1 copy:/<<BUILDDIR>>/resolver-J0DkFJ/apt_archive ./ sbuild-build-depends-python-skbio-dummy 0.invalid.0 [1008 B]
Get:2 http://172.17.0.1/private bookworm-staging/main armhf bsdextrautils armhf 2.37.2-3 [135 kB]
Get:3 http://172.17.0.1/private bookworm-staging/main armhf libasan6 armhf 11.2.0-8+rpi1 [1944 kB]
Get:4 http://172.17.0.1/private bookworm-staging/main armhf libubsan1 armhf 11.2.0-8+rpi1 [797 kB]
Get:5 http://172.17.0.1/private bookworm-staging/main armhf libgomp1 armhf 11.2.0-8+rpi1 [88.1 kB]
Get:6 http://172.17.0.1/private bookworm-staging/main armhf gcc-11-base armhf 11.2.0-8+rpi1 [205 kB]
Get:7 http://172.17.0.1/private bookworm-staging/main armhf libgcc-s1 armhf 11.2.0-8+rpi1 [36.1 kB]
Get:8 http://172.17.0.1/private bookworm-staging/main armhf libcc1-0 armhf 11.2.0-8+rpi1 [37.8 kB]
Get:9 http://172.17.0.1/private bookworm-staging/main armhf libatomic1 armhf 11.2.0-8+rpi1 [8196 B]
Get:10 http://172.17.0.1/private bookworm-staging/main armhf libstdc++6 armhf 11.2.0-8+rpi1 [466 kB]
Get:11 http://172.17.0.1/private bookworm-staging/main armhf libuchardet0 armhf 0.0.7-1 [65.0 kB]
Get:12 http://172.17.0.1/private bookworm-staging/main armhf groff-base armhf 1.22.4-7 [793 kB]
Get:13 http://172.17.0.1/private bookworm-staging/main armhf libpipeline1 armhf 1.5.3-1 [29.9 kB]
Get:14 http://172.17.0.1/private bookworm-staging/main armhf man-db armhf 2.9.4-2 [1307 kB]
Get:15 http://172.17.0.1/private bookworm-staging/main armhf libpython3.9-minimal armhf 3.9.7-4+rpi1 [794 kB]
Get:16 http://172.17.0.1/private bookworm-staging/main armhf libexpat1 armhf 2.4.1-2 [80.3 kB]
Get:17 http://172.17.0.1/private bookworm-staging/main armhf python3.9-minimal armhf 3.9.7-4+rpi1 [1632 kB]
Get:18 http://172.17.0.1/private bookworm-staging/main armhf python3-minimal armhf 3.9.2-3 [38.2 kB]
Get:19 http://172.17.0.1/private bookworm-staging/main armhf media-types all 4.0.0 [30.3 kB]
Get:20 http://172.17.0.1/private bookworm-staging/main armhf mailcap all 3.70 [31.8 kB]
Get:21 http://172.17.0.1/private bookworm-staging/main armhf mime-support all 3.66 [10.9 kB]
Get:22 http://172.17.0.1/private bookworm-staging/main armhf libffi8 armhf 3.4.2-3 [21.3 kB]
Get:23 http://172.17.0.1/private bookworm-staging/main armhf libmpdec3 armhf 2.5.1-2+rpi1 [73.5 kB]
Get:24 http://172.17.0.1/private bookworm-staging/main armhf libpython3.9-stdlib armhf 3.9.7-4+rpi1 [1618 kB]
Get:25 http://172.17.0.1/private bookworm-staging/main armhf python3.9 armhf 3.9.7-4+rpi1 [480 kB]
Get:26 http://172.17.0.1/private bookworm-staging/main armhf libpython3-stdlib armhf 3.9.2-3 [21.4 kB]
Get:27 http://172.17.0.1/private bookworm-staging/main armhf python3 armhf 3.9.2-3 [37.9 kB]
Get:28 http://172.17.0.1/private bookworm-staging/main armhf libncurses6 armhf 6.2+20201114-4 [79.7 kB]
Get:29 http://172.17.0.1/private bookworm-staging/main armhf libprocps8 armhf 2:3.3.17-5 [60.5 kB]
Get:30 http://172.17.0.1/private bookworm-staging/main armhf procps armhf 2:3.3.17-5 [475 kB]
Get:31 http://172.17.0.1/private bookworm-staging/main armhf sensible-utils all 0.0.17 [21.5 kB]
Get:32 http://172.17.0.1/private bookworm-staging/main armhf libmagic-mgc armhf 1:5.39-3 [273 kB]
Get:33 http://172.17.0.1/private bookworm-staging/main armhf libmagic1 armhf 1:5.39-3 [117 kB]
Get:34 http://172.17.0.1/private bookworm-staging/main armhf file armhf 1:5.39-3 [68.0 kB]
Get:35 http://172.17.0.1/private bookworm-staging/main armhf gettext-base armhf 0.21-4 [171 kB]
Get:36 http://172.17.0.1/private bookworm-staging/main armhf libsigsegv2 armhf 2.13-1 [34.3 kB]
Get:37 http://172.17.0.1/private bookworm-staging/main armhf m4 armhf 1.4.18-5 [186 kB]
Get:38 http://172.17.0.1/private bookworm-staging/main armhf autoconf all 2.71-2 [343 kB]
Get:39 http://172.17.0.1/private bookworm-staging/main armhf autotools-dev all 20180224.1+nmu1 [77.1 kB]
Get:40 http://172.17.0.1/private bookworm-staging/main armhf automake all 1:1.16.4-2 [819 kB]
Get:41 http://172.17.0.1/private bookworm-staging/main armhf autopoint all 0.21-4 [510 kB]
Get:42 http://172.17.0.1/private bookworm-staging/main armhf openssl armhf 1.1.1l-1 [815 kB]
Get:43 http://172.17.0.1/private bookworm-staging/main armhf ca-certificates all 20210119 [158 kB]
Get:44 http://172.17.0.1/private bookworm-staging/main armhf cython3 armhf 0.29.21-3+b1 [1234 kB]
Get:45 http://172.17.0.1/private bookworm-staging/main armhf libdebhelper-perl all 13.5.2 [192 kB]
Get:46 http://172.17.0.1/private bookworm-staging/main armhf libtool all 2.4.6-15 [513 kB]
Get:47 http://172.17.0.1/private bookworm-staging/main armhf dh-autoreconf all 20 [17.1 kB]
Get:48 http://172.17.0.1/private bookworm-staging/main armhf libarchive-zip-perl all 1.68-1 [104 kB]
Get:49 http://172.17.0.1/private bookworm-staging/main armhf libsub-override-perl all 0.09-2 [10.2 kB]
Get:50 http://172.17.0.1/private bookworm-staging/main armhf libfile-stripnondeterminism-perl all 1.12.0-1 [26.3 kB]
Get:51 http://172.17.0.1/private bookworm-staging/main armhf dh-strip-nondeterminism all 1.12.0-1 [15.4 kB]
Get:52 http://172.17.0.1/private bookworm-staging/main armhf libelf1 armhf 0.185-2 [168 kB]
Get:53 http://172.17.0.1/private bookworm-staging/main armhf dwz armhf 0.14-1 [83.0 kB]
Get:54 http://172.17.0.1/private bookworm-staging/main armhf libicu67 armhf 67.1-7 [8291 kB]
Get:55 http://172.17.0.1/private bookworm-staging/main armhf libxml2 armhf 2.9.12+dfsg-5 [584 kB]
Get:56 http://172.17.0.1/private bookworm-staging/main armhf gettext armhf 0.21-4 [1215 kB]
Get:57 http://172.17.0.1/private bookworm-staging/main armhf intltool-debian all 0.35.0+20060710.5 [26.8 kB]
Get:58 http://172.17.0.1/private bookworm-staging/main armhf po-debconf all 1.0.21+nmu1 [248 kB]
Get:59 http://172.17.0.1/private bookworm-staging/main armhf debhelper all 13.5.2 [1056 kB]
Get:60 http://172.17.0.1/private bookworm-staging/main armhf python3-lib2to3 all 3.9.7-1 [79.4 kB]
Get:61 http://172.17.0.1/private bookworm-staging/main armhf python3-distutils all 3.9.7-1 [146 kB]
Get:62 http://172.17.0.1/private bookworm-staging/main armhf dh-python all 4.20201102+nmu1 [99.4 kB]
Get:63 http://172.17.0.1/private bookworm-staging/main armhf fonts-lyx all 2.3.6-1 [205 kB]
Get:64 http://172.17.0.1/private bookworm-staging/main armhf libblas3 armhf 3.10.0-1 [108 kB]
Get:65 http://172.17.0.1/private bookworm-staging/main armhf libbrotli1 armhf 1.0.9-2+b1 [261 kB]
Get:66 http://172.17.0.1/private bookworm-staging/main armhf libmd0 armhf 1.0.4-1 [28.9 kB]
Get:67 http://172.17.0.1/private bookworm-staging/main armhf libbsd0 armhf 0.11.3-1 [103 kB]
Get:68 http://172.17.0.1/private bookworm-staging/main armhf libdeflate0 armhf 1.8-1 [44.1 kB]
Get:69 http://172.17.0.1/private bookworm-staging/main armhf libexpat1-dev armhf 2.4.1-2 [135 kB]
Get:70 http://172.17.0.1/private bookworm-staging/main armhf libpng16-16 armhf 1.6.37-3 [276 kB]
Get:71 http://172.17.0.1/private bookworm-staging/main armhf libfreetype6 armhf 2.10.4+dfsg-1 [353 kB]
Get:72 http://172.17.0.1/private bookworm-staging/main armhf libgfortran5 armhf 11.2.0-8+rpi1 [235 kB]
Get:73 http://172.17.0.1/private bookworm-staging/main armhf libimagequant0 armhf 2.12.2-1.1 [27.2 kB]
Get:74 http://172.17.0.1/private bookworm-staging/main armhf libjbig0 armhf 2.1-3.1+b2 [27.6 kB]
Get:75 http://172.17.0.1/private bookworm-staging/main armhf libjpeg62-turbo armhf 1:2.0.6-4 [122 kB]
Get:76 http://172.17.0.1/private bookworm-staging/main armhf libjs-jquery all 3.5.1+dfsg+~3.5.5-7 [315 kB]
Get:77 http://172.17.0.1/private bookworm-staging/main armhf libjs-jquery-ui all 1.12.1+dfsg-8 [232 kB]
Get:78 http://172.17.0.1/private bookworm-staging/main armhf libjs-underscore all 1.9.1~dfsg-4 [100 kB]
Get:79 http://172.17.0.1/private bookworm-staging/main armhf libjs-sphinxdoc all 4.2.0-4 [137 kB]
Get:80 http://172.17.0.1/private bookworm-staging/main armhf liblapack3 armhf 3.10.0-1 [1594 kB]
Get:81 http://172.17.0.1/private bookworm-staging/main armhf liblbfgsb0 armhf 3.0+dfsg.3-9 [24.6 kB]
Get:82 http://172.17.0.1/private bookworm-staging/main armhf liblcms2-2 armhf 2.12~rc1-2 [121 kB]
Get:83 http://172.17.0.1/private bookworm-staging/main armhf libpython3.9 armhf 3.9.7-4+rpi1 [1416 kB]
Get:84 http://172.17.0.1/private bookworm-staging/main armhf zlib1g-dev armhf 1:1.2.11.dfsg-2 [184 kB]
Get:85 http://172.17.0.1/private bookworm-staging/main armhf libpython3.9-dev armhf 3.9.7-4+rpi1 [3060 kB]
Get:86 http://172.17.0.1/private bookworm-staging/main armhf libpython3-dev armhf 3.9.2-3 [21.7 kB]
Get:87 http://172.17.0.1/private bookworm-staging/main armhf libpython3-all-dev armhf 3.9.2-3 [1068 B]
Get:88 http://172.17.0.1/private bookworm-staging/main armhf libsimde-dev all 0.7.2-5 [259 kB]
Get:89 http://172.17.0.1/private bookworm-staging/main armhf libssw0 armhf 1.1-13 [21.0 kB]
Get:90 http://172.17.0.1/private bookworm-staging/main armhf libssw-dev armhf 1.1-13 [24.0 kB]
Get:91 http://172.17.0.1/private bookworm-staging/main armhf libwebp6 armhf 0.6.1-2.1 [225 kB]
Get:92 http://172.17.0.1/private bookworm-staging/main armhf libtiff5 armhf 4.3.0-2 [272 kB]
Get:93 http://172.17.0.1/private bookworm-staging/main armhf libwebpdemux2 armhf 0.6.1-2.1 [86.8 kB]
Get:94 http://172.17.0.1/private bookworm-staging/main armhf libwebpmux3 armhf 0.6.1-2.1 [94.4 kB]
Get:95 http://172.17.0.1/private bookworm-staging/main armhf libxau6 armhf 1:1.0.9-1 [19.1 kB]
Get:96 http://172.17.0.1/private bookworm-staging/main armhf libxdmcp6 armhf 1:1.1.2-3 [25.0 kB]
Get:97 http://172.17.0.1/private bookworm-staging/main armhf libxcb1 armhf 1.14-3 [136 kB]
Get:98 http://172.17.0.1/private bookworm-staging/main armhf ttf-bitstream-vera all 1.10-8.1 [223 kB]
Get:99 http://172.17.0.1/private bookworm-staging/main armhf python-matplotlib-data all 3.3.4-2 [4154 kB]
Get:100 http://172.17.0.1/private bookworm-staging/main armhf python3-all armhf 3.9.2-3 [1056 B]
Get:101 http://172.17.0.1/private bookworm-staging/main armhf python3.9-dev armhf 3.9.7-4+rpi1 [501 kB]
Get:102 http://172.17.0.1/private bookworm-staging/main armhf python3-dev armhf 3.9.2-3 [24.8 kB]
Get:103 http://172.17.0.1/private bookworm-staging/main armhf python3-all-dev armhf 3.9.2-3 [1064 B]
Get:104 http://172.17.0.1/private bookworm-staging/main armhf python3-attr all 20.3.0-1 [52.9 kB]
Get:105 http://172.17.0.1/private bookworm-staging/main armhf python3-backcall all 0.2.0-2 [10.9 kB]
Get:106 http://172.17.0.1/private bookworm-staging/main armhf python3-certifi all 2020.6.20-1 [151 kB]
Get:107 http://172.17.0.1/private bookworm-staging/main armhf python3-pkg-resources all 58.2.0-1 [192 kB]
Get:108 http://172.17.0.1/private bookworm-staging/main armhf python3-chardet all 4.0.0-1 [99.0 kB]
Get:109 http://172.17.0.1/private bookworm-staging/main armhf python3-idna all 2.10-1 [37.4 kB]
Get:110 http://172.17.0.1/private bookworm-staging/main armhf python3-six all 1.16.0-2 [17.5 kB]
Get:111 http://172.17.0.1/private bookworm-staging/main armhf python3-urllib3 all 1.26.5-1~exp1 [114 kB]
Get:112 http://172.17.0.1/private bookworm-staging/main armhf python3-requests all 2.25.1+dfsg-2 [69.3 kB]
Get:113 http://172.17.0.1/private bookworm-staging/main armhf python3-msgpack armhf 1.0.2-2 [64.2 kB]
Get:114 http://172.17.0.1/private bookworm-staging/main armhf python3-cachecontrol all 0.12.6+ds-1 [16.7 kB]
Get:115 http://172.17.0.1/private bookworm-staging/main armhf python3-cycler all 0.10.0-3 [8084 B]
Get:116 http://172.17.0.1/private bookworm-staging/main armhf python3-dateutil all 2.8.1-6 [79.2 kB]
Get:117 http://172.17.0.1/private bookworm-staging/main armhf python3-decorator all 4.4.2-2 [15.8 kB]
Get:118 http://172.17.0.1/private bookworm-staging/main armhf python3-numpy armhf 1:1.19.5-1 [2930 kB]
Get:119 http://172.17.0.1/private bookworm-staging/main armhf python3-hdmedians armhf 0.14.2-1 [83.6 kB]
Get:120 http://172.17.0.1/private bookworm-staging/main armhf python3-more-itertools all 4.2.0-3 [42.7 kB]
Get:121 http://172.17.0.1/private bookworm-staging/main armhf python3-zipp all 1.0.0-3 [6060 B]
Get:122 http://172.17.0.1/private bookworm-staging/main armhf python3-importlib-metadata all 4.6.4-1 [22.5 kB]
Get:123 http://172.17.0.1/private bookworm-staging/main armhf python3-iniconfig all 1.1.1-1 [6308 B]
Get:124 http://172.17.0.1/private bookworm-staging/main armhf python3-parso all 0.8.1-1 [65.9 kB]
Get:125 http://172.17.0.1/private bookworm-staging/main armhf python3-jedi all 0.18.0-1 [620 kB]
Get:126 http://172.17.0.1/private bookworm-staging/main armhf python3-ptyprocess all 0.7.0-2 [13.7 kB]
Get:127 http://172.17.0.1/private bookworm-staging/main armhf python3-pexpect all 4.8.0-2 [54.9 kB]
Get:128 http://172.17.0.1/private bookworm-staging/main armhf python3-pickleshare all 0.7.5-4 [7636 B]
Get:129 http://172.17.0.1/private bookworm-staging/main armhf python3-wcwidth all 0.1.9+dfsg1-2 [18.2 kB]
Get:130 http://172.17.0.1/private bookworm-staging/main armhf python3-prompt-toolkit all 3.0.20-1 [265 kB]
Get:131 http://172.17.0.1/private bookworm-staging/main armhf python3-pygments all 2.7.1+dfsg-2.1 [657 kB]
Get:132 http://172.17.0.1/private bookworm-staging/main armhf python3-traitlets all 5.1.0-1 [86.5 kB]
Get:133 http://172.17.0.1/private bookworm-staging/main armhf python3-ipython all 7.22.0-1 [518 kB]
Get:134 http://172.17.0.1/private bookworm-staging/main armhf python3-joblib all 0.17.0-4 [213 kB]
Get:135 http://172.17.0.1/private bookworm-staging/main armhf python3-kiwisolver armhf 1.3.2-1 [45.8 kB]
Get:136 http://172.17.0.1/private bookworm-staging/main armhf python3-lockfile all 1:0.12.2-2.2 [17.3 kB]
Get:137 http://172.17.0.1/private bookworm-staging/main armhf python3-pyparsing all 2.4.7-1 [109 kB]
Get:138 http://172.17.0.1/private bookworm-staging/main armhf python3-pil armhf 8.1.2+dfsg-0.3 [410 kB]
Get:139 http://172.17.0.1/private bookworm-staging/main armhf python3-matplotlib armhf 3.3.4-2 [6035 kB]
Get:140 http://172.17.0.1/private bookworm-staging/main armhf python3-natsort all 7.1.0-1 [37.5 kB]
Get:141 http://172.17.0.1/private bookworm-staging/main armhf python3-packaging all 21.0-1 [33.5 kB]
Get:142 http://172.17.0.1/private bookworm-staging/main armhf python3-tz all 2021.3-1 [34.9 kB]
Get:143 http://172.17.0.1/private bookworm-staging/main armhf python3-pandas-lib armhf 1.1.5+dfsg-2 [2863 kB]
Get:144 http://172.17.0.1/private bookworm-staging/main armhf python3-pandas all 1.1.5+dfsg-2 [2096 kB]
Get:145 http://172.17.0.1/private bookworm-staging/main armhf python3-pluggy all 0.13.0-6 [22.3 kB]
Get:146 http://172.17.0.1/private bookworm-staging/main armhf python3-py all 1.10.0-1 [94.2 kB]
Get:147 http://172.17.0.1/private bookworm-staging/main armhf python3-toml all 0.10.2-1 [16.2 kB]
Get:148 http://172.17.0.1/private bookworm-staging/main armhf python3-pytest all 6.2.5-1 [218 kB]
Get:149 http://172.17.0.1/private bookworm-staging/main armhf python3-scipy armhf 1.6.0-2 [11.1 MB]
Get:150 http://172.17.0.1/private bookworm-staging/main armhf python3-setuptools all 58.2.0-1 [396 kB]
Get:151 http://172.17.0.1/private bookworm-staging/main armhf python3-sklearn-lib armhf 0.23.2-5 [1555 kB]
Get:152 http://172.17.0.1/private bookworm-staging/main armhf python3-threadpoolctl all 2.1.0-1 [15.3 kB]
Get:153 http://172.17.0.1/private bookworm-staging/main armhf python3-sklearn all 0.23.2-5 [1818 kB]
Get:154 http://172.17.0.1/private bookworm-staging/main armhf sphinx-common all 4.2.0-4 [622 kB]
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Setting up man-db (2.9.4-2) ...
Not building database; man-db/auto-update is not 'true'.
Setting up python3-tz (2021.3-1) ...
Setting up python3-natsort (7.1.0-1) ...
Setting up python3-six (1.16.0-2) ...
Setting up dh-autoreconf (20) ...
Setting up python3-pil:armhf (8.1.2+dfsg-0.3) ...
Setting up python3-decorator (4.4.2-2) ...
Setting up python3-wcwidth (0.1.9+dfsg1-2) ...
Setting up python3-pyparsing (2.4.7-1) ...
Setting up python3-certifi (2020.6.20-1) ...
Setting up sphinx-common (4.2.0-4) ...
Setting up python3-cycler (0.10.0-3) ...
Setting up python3-kiwisolver (1.3.2-1) ...
Setting up python3-idna (2.10-1) ...
Setting up cython3 (0.29.21-3+b1) ...
Setting up python3-pickleshare (0.7.5-4) ...
Setting up python3-toml (0.10.2-1) ...
Setting up python3-urllib3 (1.26.5-1~exp1) ...
Setting up python3.9-dev (3.9.7-4+rpi1) ...
Setting up python3-traitlets (5.1.0-1) ...
Setting up python3-dateutil (2.8.1-6) ...
Setting up python3-msgpack (1.0.2-2) ...
Setting up python3-lib2to3 (3.9.7-1) ...
Setting up python3-ptyprocess (0.7.0-2) ...
Setting up python3-pkg-resources (58.2.0-1) ...
Setting up python3-prompt-toolkit (3.0.20-1) ...
Setting up python3-distutils (3.9.7-1) ...
Setting up dh-python (4.20201102+nmu1) ...
Setting up python3-more-itertools (4.2.0-3) ...
Setting up python3-iniconfig (1.1.1-1) ...
Setting up python3-attr (20.3.0-1) ...
Setting up python3-lockfile (1:0.12.2-2.2) ...
Setting up libpython3-dev:armhf (3.9.2-3) ...
Setting up python3-setuptools (58.2.0-1) ...
Setting up python3-py (1.10.0-1) ...
Setting up python3-backcall (0.2.0-2) ...
Setting up python3-joblib (0.17.0-4) ...
Setting up python3-parso (0.8.1-1) ...
Setting up python3-threadpoolctl (2.1.0-1) ...
Setting up python3-all (3.9.2-3) ...
Setting up debhelper (13.5.2) ...
Setting up python3-zipp (1.0.0-3) ...
Setting up python3-pygments (2.7.1+dfsg-2.1) ...
Setting up python3-packaging (21.0-1) ...
Setting up python3-chardet (4.0.0-1) ...
Setting up libpython3-all-dev:armhf (3.9.2-3) ...
Setting up python3-pexpect (4.8.0-2) ...
Setting up python3-dev (3.9.2-3) ...
Setting up python3-requests (2.25.1+dfsg-2) ...
Setting up python3-numpy (1:1.19.5-1) ...
Setting up python3-hdmedians (0.14.2-1) ...
Setting up python3-cachecontrol (0.12.6+ds-1) ...
Setting up python3-all-dev (3.9.2-3) ...
Setting up python3-matplotlib (3.3.4-2) ...
Setting up python3-scipy (1.6.0-2) ...
Setting up python3-importlib-metadata (4.6.4-1) ...
Setting up python3-jedi (0.18.0-1) ...
Setting up python3-pandas-lib:armhf (1.1.5+dfsg-2) ...
Setting up python3-sklearn-lib:armhf (0.23.2-5) ...
Setting up python3-pandas (1.1.5+dfsg-2) ...
Setting up python3-ipython (7.22.0-1) ...
Setting up python3-sklearn (0.23.2-5) ...
Setting up python3-pluggy (0.13.0-6) ...
Setting up python3-pytest (6.2.5-1) ...
Setting up sbuild-build-depends-python-skbio-dummy (0.invalid.0) ...
Processing triggers for libc-bin (2.32-4+rpi1) ...
Processing triggers for ca-certificates (20210119) ...
Updating certificates in /etc/ssl/certs...
0 added, 0 removed; done.
Running hooks in /etc/ca-certificates/update.d...
done.
W: No sandbox user '_apt' on the system, can not drop privileges

+------------------------------------------------------------------------------+
| Build environment                                                            |
+------------------------------------------------------------------------------+

Kernel: Linux 4.15.0-76-generic armhf (armv8l)
Toolchain package versions: binutils_2.37-5+rpi1 dpkg-dev_1.20.9+rpi1 g++-10_10.3.0-9+rpi1 gcc-10_10.3.0-9+rpi1 libc6-dev_2.32-4+rpi1 libstdc++-10-dev_10.3.0-9+rpi1 libstdc++6_11.2.0-8+rpi1 linux-libc-dev_5.10.46-4+rpi1
Package versions: adduser_3.118 apt_2.3.9 autoconf_2.71-2 automake_1:1.16.4-2 autopoint_0.21-4 autotools-dev_20180224.1+nmu1 base-files_12+rpi1 base-passwd_3.5.51 bash_5.1-3 binutils_2.37-5+rpi1 binutils-arm-linux-gnueabihf_2.37-5+rpi1 binutils-common_2.37-5+rpi1 bsdextrautils_2.37.2-3 bsdutils_1:2.37.2-1 build-essential_12.9 bzip2_1.0.8-4 ca-certificates_20210119 coreutils_8.32-4 cpp_4:10.2.1-1+rpi1 cpp-10_10.3.0-9+rpi1 cython3_0.29.21-3+b1 dash_0.5.11+git20210120+802ebd4-1 debconf_1.5.77 debhelper_13.5.2 debianutils_4.11.2 dh-autoreconf_20 dh-python_4.20201102+nmu1 dh-strip-nondeterminism_1.12.0-1 diffutils_1:3.7-5 dirmngr_2.2.27-2 dpkg_1.20.9+rpi1 dpkg-dev_1.20.9+rpi1 dwz_0.14-1 e2fsprogs_1.46.4-1 fakeroot_1.25.3-1.1 file_1:5.39-3 findutils_4.8.0-1 fonts-lyx_2.3.6-1 g++_4:10.2.1-1+rpi1 g++-10_10.3.0-9+rpi1 gcc_4:10.2.1-1+rpi1 gcc-10_10.3.0-9+rpi1 gcc-10-base_10.3.0-9+rpi1 gcc-11-base_11.2.0-8+rpi1 gcc-7-base_7.5.0-6+rpi1+b2 gcc-8-base_8.4.0-7+rpi1 gcc-9-base_9.4.0-2+rpi1 gettext_0.21-4 gettext-base_0.21-4 gnupg_2.2.27-2 gnupg-l10n_2.2.27-2 gnupg-utils_2.2.27-2 gpg_2.2.27-2 gpg-agent_2.2.27-2 gpg-wks-client_2.2.27-2 gpg-wks-server_2.2.27-2 gpgconf_2.2.27-2 gpgsm_2.2.27-2 gpgv_2.2.27-2 grep_3.7-1 groff-base_1.22.4-7 gzip_1.10-4 hostname_3.23 init-system-helpers_1.60 intltool-debian_0.35.0+20060710.5 libacl1_2.3.1-1 libapt-pkg6.0_2.3.9 libarchive-zip-perl_1.68-1 libasan6_11.2.0-8+rpi1 libassuan0_2.5.5-1 libatomic1_11.2.0-8+rpi1 libattr1_1:2.5.1-1 libaudit-common_1:3.0.5-1 libaudit1_1:3.0.5-1 libbinutils_2.37-5+rpi1 libblas3_3.10.0-1 libblkid1_2.37.2-1 libbrotli1_1.0.9-2+b1 libbsd0_0.11.3-1 libbz2-1.0_1.0.8-4 libc-bin_2.32-4+rpi1 libc-dev-bin_2.32-4+rpi1 libc6_2.32-4+rpi1 libc6-dev_2.32-4+rpi1 libcap-ng0_0.7.9-2.2+b1 libcc1-0_11.2.0-8+rpi1 libcom-err2_1.46.4-1 libcrypt-dev_1:4.4.25-2 libcrypt1_1:4.4.25-2 libctf-nobfd0_2.37-5+rpi1 libctf0_2.37-5+rpi1 libdb5.3_5.3.28+dfsg1-0.8 libdebconfclient0_0.260 libdebhelper-perl_13.5.2 libdeflate0_1.8-1 libdpkg-perl_1.20.9+rpi1 libelf1_0.185-2 libexpat1_2.4.1-2 libexpat1-dev_2.4.1-2 libext2fs2_1.46.4-1 libfakeroot_1.25.3-1.1 libffi7_3.3-6 libffi8_3.4.2-3 libfile-stripnondeterminism-perl_1.12.0-1 libfreetype6_2.10.4+dfsg-1 libgcc-10-dev_10.3.0-9+rpi1 libgcc-s1_11.2.0-8+rpi1 libgcrypt20_1.9.4-3 libgdbm-compat4_1.21-1 libgdbm6_1.21-1 libgfortran5_11.2.0-8+rpi1 libgmp10_2:6.2.1+dfsg-2 libgnutls30_3.7.2-2 libgomp1_11.2.0-8+rpi1 libgpg-error0_1.42-3 libgssapi-krb5-2_1.18.3-7 libhogweed6_3.7.3-1 libicu67_67.1-7 libidn2-0_2.3.2-2 libimagequant0_2.12.2-1.1 libisl23_0.23-1 libjbig0_2.1-3.1+b2 libjpeg62-turbo_1:2.0.6-4 libjs-jquery_3.5.1+dfsg+~3.5.5-7 libjs-jquery-ui_1.12.1+dfsg-8 libjs-sphinxdoc_4.2.0-4 libjs-underscore_1.9.1~dfsg-4 libk5crypto3_1.18.3-7 libkeyutils1_1.6.1-2 libkrb5-3_1.18.3-7 libkrb5support0_1.18.3-7 libksba8_1.6.0-2 liblapack3_3.10.0-1 liblbfgsb0_3.0+dfsg.3-9 liblcms2-2_2.12~rc1-2 libldap-2.4-2_2.4.59+dfsg-1 liblocale-gettext-perl_1.07-4+b1 liblz4-1_1.9.3-2 liblzma5_5.2.5-2 libmagic-mgc_1:5.39-3 libmagic1_1:5.39-3 libmd0_1.0.4-1 libmount1_2.37.2-1 libmpc3_1.2.0-1 libmpdec3_2.5.1-2+rpi1 libmpfr6_4.1.0-3 libncurses6_6.2+20201114-4 libncursesw6_6.2+20201114-4 libnettle8_3.7.3-1 libnpth0_1.6-3 libnsl-dev_1.3.0-2 libnsl2_1.3.0-2 libp11-kit0_0.24.0-2 libpam-modules_1.4.0-10 libpam-modules-bin_1.4.0-10 libpam-runtime_1.4.0-10 libpam0g_1.4.0-10 libpcre2-8-0_10.36-2 libpcre3_2:8.39-13 libperl5.32_5.32.1-5 libpipeline1_1.5.3-1 libpng16-16_1.6.37-3 libprocps8_2:3.3.17-5 libpython3-all-dev_3.9.2-3 libpython3-dev_3.9.2-3 libpython3-stdlib_3.9.2-3 libpython3.9_3.9.7-4+rpi1 libpython3.9-dev_3.9.7-4+rpi1 libpython3.9-minimal_3.9.7-4+rpi1 libpython3.9-stdlib_3.9.7-4+rpi1 libreadline8_8.1-2 libsasl2-2_2.1.27+dfsg-2.1 libsasl2-modules-db_2.1.27+dfsg-2.1 libseccomp2_2.5.1-1+rpi1 libselinux1_3.1-3 libsemanage-common_3.1-1 libsemanage1_3.1-1+b1 libsepol1_3.1-1 libsigsegv2_2.13-1 libsimde-dev_0.7.2-5 libsmartcols1_2.37.2-1 libsqlite3-0_3.36.0-2 libss2_1.46.4-1 libssl1.1_1.1.1l-1 libssw-dev_1.1-13 libssw0_1.1-13 libstdc++-10-dev_10.3.0-9+rpi1 libstdc++6_11.2.0-8+rpi1 libsub-override-perl_0.09-2 libsystemd0_247.9-1+rpi1 libtasn1-6_4.17.0-2 libtext-charwidth-perl_0.04-10+b1 libtext-iconv-perl_1.7-7+b1 libtiff5_4.3.0-2 libtinfo6_6.2+20201114-4 libtirpc-common_1.3.2-2 libtirpc-dev_1.3.2-2 libtirpc3_1.3.2-2 libtool_2.4.6-15 libubsan1_11.2.0-8+rpi1 libuchardet0_0.0.7-1 libudev1_247.9-1+rpi1 libunistring2_0.9.10-6 libuuid1_2.37.2-1 libwebp6_0.6.1-2.1 libwebpdemux2_0.6.1-2.1 libwebpmux3_0.6.1-2.1 libxau6_1:1.0.9-1 libxcb1_1.14-3 libxdmcp6_1:1.1.2-3 libxml2_2.9.12+dfsg-5 libxxhash0_0.8.0-2+rpi1 libzstd1_1.4.8+dfsg-2.1+rpi1 linux-libc-dev_5.10.46-4+rpi1 login_1:4.8.1-1 logsave_1.46.4-1 lsb-base_11.1.0+rpi1 m4_1.4.18-5 mailcap_3.70 make_4.3-4.1 man-db_2.9.4-2 mawk_1.3.4.20200120-2 media-types_4.0.0 mime-support_3.66 mount_2.37.2-1 ncurses-base_6.2+20201114-4 ncurses-bin_6.2+20201114-4 netbase_6.3 openssl_1.1.1l-1 passwd_1:4.8.1-1 patch_2.7.6-7 perl_5.32.1-5 perl-base_5.32.1-5 perl-modules-5.32_5.32.1-5 pinentry-curses_1.1.0-4 po-debconf_1.0.21+nmu1 procps_2:3.3.17-5 python-matplotlib-data_3.3.4-2 python3_3.9.2-3 python3-all_3.9.2-3 python3-all-dev_3.9.2-3 python3-attr_20.3.0-1 python3-backcall_0.2.0-2 python3-cachecontrol_0.12.6+ds-1 python3-certifi_2020.6.20-1 python3-chardet_4.0.0-1 python3-cycler_0.10.0-3 python3-dateutil_2.8.1-6 python3-decorator_4.4.2-2 python3-dev_3.9.2-3 python3-distutils_3.9.7-1 python3-hdmedians_0.14.2-1 python3-idna_2.10-1 python3-importlib-metadata_4.6.4-1 python3-iniconfig_1.1.1-1 python3-ipython_7.22.0-1 python3-jedi_0.18.0-1 python3-joblib_0.17.0-4 python3-kiwisolver_1.3.2-1 python3-lib2to3_3.9.7-1 python3-lockfile_1:0.12.2-2.2 python3-matplotlib_3.3.4-2 python3-minimal_3.9.2-3 python3-more-itertools_4.2.0-3 python3-msgpack_1.0.2-2 python3-natsort_7.1.0-1 python3-numpy_1:1.19.5-1 python3-packaging_21.0-1 python3-pandas_1.1.5+dfsg-2 python3-pandas-lib_1.1.5+dfsg-2 python3-parso_0.8.1-1 python3-pexpect_4.8.0-2 python3-pickleshare_0.7.5-4 python3-pil_8.1.2+dfsg-0.3 python3-pkg-resources_58.2.0-1 python3-pluggy_0.13.0-6 python3-prompt-toolkit_3.0.20-1 python3-ptyprocess_0.7.0-2 python3-py_1.10.0-1 python3-pygments_2.7.1+dfsg-2.1 python3-pyparsing_2.4.7-1 python3-pytest_6.2.5-1 python3-requests_2.25.1+dfsg-2 python3-scipy_1.6.0-2 python3-setuptools_58.2.0-1 python3-six_1.16.0-2 python3-sklearn_0.23.2-5 python3-sklearn-lib_0.23.2-5 python3-threadpoolctl_2.1.0-1 python3-toml_0.10.2-1 python3-traitlets_5.1.0-1 python3-tz_2021.3-1 python3-urllib3_1.26.5-1~exp1 python3-wcwidth_0.1.9+dfsg1-2 python3-zipp_1.0.0-3 python3.9_3.9.7-4+rpi1 python3.9-dev_3.9.7-4+rpi1 python3.9-minimal_3.9.7-4+rpi1 raspbian-archive-keyring_20120528.2 readline-common_8.1-2 rpcsvc-proto_1.4.2-4 sbuild-build-depends-core-dummy_0.invalid.0 sbuild-build-depends-python-skbio-dummy_0.invalid.0 sed_4.8-1 sensible-utils_0.0.17 sphinx-common_4.2.0-4 sysvinit-utils_3.00-1 tar_1.34+dfsg-1 ttf-bitstream-vera_1.10-8.1 tzdata_2021a-1 util-linux_2.37.2-1 xz-utils_5.2.5-2 zlib1g_1:1.2.11.dfsg-2 zlib1g-dev_1:1.2.11.dfsg-2

+------------------------------------------------------------------------------+
| Build                                                                        |
+------------------------------------------------------------------------------+


Unpack source
-------------

gpgv: unknown type of key resource 'trustedkeys.kbx'
gpgv: keyblock resource '/tmp/dpkg-verify-sig.uXaIawJp/trustedkeys.kbx': General error
gpgv: Signature made Wed Oct 13 07:24:25 2021 UTC
gpgv:                using RSA key F1F007320A035541F0A663CA578A0494D1C646D1
gpgv:                issuer "tille@debian.org"
gpgv: Can't check signature: No public key
dpkg-source: warning: failed to verify signature on ./python-skbio_0.5.6-5.dsc
dpkg-source: info: extracting python-skbio in /<<PKGBUILDDIR>>
dpkg-source: info: unpacking python-skbio_0.5.6.orig.tar.gz
dpkg-source: info: unpacking python-skbio_0.5.6-5.debian.tar.xz
dpkg-source: info: using patch list from debian/patches/series
dpkg-source: info: applying mathjax-path
dpkg-source: info: applying 0002-use-libsww-as-library-not-embedded-src.patch
dpkg-source: info: applying no_privacy_breach_logo.patch
dpkg-source: info: applying simde
dpkg-source: info: applying soften_test
dpkg-source: info: applying pandas1.1-ordination-fix.patch
dpkg-source: info: applying pandas1.1-valueerror.patch
dpkg-source: info: applying local_inventory
dpkg-source: info: applying sphinx_add_javascript.patch
dpkg-source: info: applying skip_tests_failung_due_to_scipy.patch

Check disk space
----------------

Sufficient free space for build

User Environment
----------------

APT_CONFIG=/var/lib/sbuild/apt.conf
DEB_BUILD_OPTIONS=parallel=4
HOME=/sbuild-nonexistent
LC_ALL=POSIX
LOGNAME=buildd
PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games
SCHROOT_ALIAS_NAME=bookworm-staging-armhf-sbuild
SCHROOT_CHROOT_NAME=bookworm-staging-armhf-sbuild
SCHROOT_COMMAND=env
SCHROOT_GID=112
SCHROOT_GROUP=buildd
SCHROOT_SESSION_ID=bookworm-staging-armhf-sbuild-b8389cd7-8d9e-4db6-984b-999e98902778
SCHROOT_UID=107
SCHROOT_USER=buildd
SHELL=/bin/sh
USER=buildd

dpkg-buildpackage
-----------------

dpkg-buildpackage: info: source package python-skbio
dpkg-buildpackage: info: source version 0.5.6-5
dpkg-buildpackage: info: source distribution unstable
 dpkg-source --before-build .
dpkg-buildpackage: info: host architecture armhf
 debian/rules clean
dh clean --with python3,sphinxdoc --buildsystem=pybuild
   debian/rules override_dh_auto_clean
make[1]: Entering directory '/<<PKGBUILDDIR>>'
if [ "`find . -name "*.pyo"`" = "" ] ; then echo no need to clean up ; else dh_auto_clean; fi
no need to clean up
make[1]: Leaving directory '/<<PKGBUILDDIR>>'
   dh_autoreconf_clean -O--buildsystem=pybuild
   debian/rules override_dh_clean
make[1]: Entering directory '/<<PKGBUILDDIR>>'
dh_clean
find ./skbio -name '*.so' -delete
find ./skbio -name '*.o' -delete
rm -rf doc/build build doc/source/generated
find doc -name *.doctree -delete
rm -rf .pybuild
rm -f scikit_bio.egg-info/PKG-INFO scikit_bio.egg-info/SOURCES.txt scikit_bio.egg-info/dependency_links.txt scikit_bio.egg-info/requires.txt scikit_bio.egg-info/top_level.txt
make[1]: Leaving directory '/<<PKGBUILDDIR>>'
 debian/rules binary-arch
dh binary-arch --with python3,sphinxdoc --buildsystem=pybuild
   dh_update_autotools_config -a -O--buildsystem=pybuild
   dh_autoreconf -a -O--buildsystem=pybuild
   dh_auto_configure -a -O--buildsystem=pybuild
I: pybuild base:232: python3.9 setup.py config 
/usr/lib/python3/dist-packages/setuptools/dist.py:717: UserWarning: Usage of dash-separated 'build-lib' will not be supported in future versions. Please use the underscore name 'build_lib' instead
  warnings.warn(
/usr/lib/python3/dist-packages/setuptools/dist.py:717: UserWarning: Usage of dash-separated 'install-layout' will not be supported in future versions. Please use the underscore name 'install_layout' instead
  warnings.warn(
/usr/lib/python3/dist-packages/setuptools/dist.py:717: UserWarning: Usage of dash-separated 'install-scripts' will not be supported in future versions. Please use the underscore name 'install_scripts' instead
  warnings.warn(
/usr/lib/python3/dist-packages/setuptools/dist.py:717: UserWarning: Usage of dash-separated 'install-lib' will not be supported in future versions. Please use the underscore name 'install_lib' instead
  warnings.warn(
running config
   debian/rules override_dh_auto_build-arch
make[1]: Entering directory '/<<PKGBUILDDIR>>'
dh_auto_build
I: pybuild base:232: /usr/bin/python3 setup.py build 
/usr/lib/python3/dist-packages/setuptools/dist.py:717: UserWarning: Usage of dash-separated 'build-lib' will not be supported in future versions. Please use the underscore name 'build_lib' instead
  warnings.warn(
/usr/lib/python3/dist-packages/setuptools/dist.py:717: UserWarning: Usage of dash-separated 'install-layout' will not be supported in future versions. Please use the underscore name 'install_layout' instead
  warnings.warn(
/usr/lib/python3/dist-packages/setuptools/dist.py:717: UserWarning: Usage of dash-separated 'install-scripts' will not be supported in future versions. Please use the underscore name 'install_scripts' instead
  warnings.warn(
/usr/lib/python3/dist-packages/setuptools/dist.py:717: UserWarning: Usage of dash-separated 'install-lib' will not be supported in future versions. Please use the underscore name 'install_lib' instead
  warnings.warn(
running build
running build_py
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/benchmarks
copying benchmarks/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/benchmarks
copying benchmarks/benchmarks.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/benchmarks
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio
copying skbio/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio
copying skbio/_base.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio
copying skbio/test.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio
copying skbio/workflow.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment
copying skbio/alignment/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment
copying skbio/alignment/_indexing.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment
copying skbio/alignment/_pairwise.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment
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copying skbio/stats/tests/data/gr_wo_msg_raw -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/tests/data
copying skbio/stats/tests/data/vr_out -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/tests/data
copying skbio/stats/tests/data/vr_raw -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/tests/data
copying skbio/stats/tests/data/vr_real_out -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/tests/data
copying skbio/stats/tests/data/vr_real_raw -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/tests/data
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/bioenv_df_vegan.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/bioenv_dm_vegan.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/bioenv_exp_results_vegan.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/df.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/df_extra_column.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/dm.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/dm2.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/dm3.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/dm4.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/dm_reordered.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/exp_results.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/exp_results_different_column_order.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/exp_results_single_column.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/mantel_env_dm_vegan.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/mantel_veg_dm_vegan.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/moving_pictures_dm.tsv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/moving_pictures_mf.tsv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/pwmantel_exp_results_all_dms.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/pwmantel_exp_results_dm_dm2.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/pwmantel_exp_results_duplicate_dms.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/pwmantel_exp_results_minimal.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/pwmantel_exp_results_minimal_with_labels.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/pwmantel_exp_results_na_p_value.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
copying skbio/stats/distance/tests/data/pwmantel_exp_results_reordered_distance_matrices.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/data
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/L&L_CA_data -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_biplot_descriptors -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_biplot_projected_descriptors -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_sample_data -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_sample_data_12dim -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_sample_data_2 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_sample_data_3 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_sample_data_3_eigh_ref_3dim -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_sample_data_3_fsvd_ref_3dim -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/PCoA_skbio -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_X -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_Y -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_biplot_scaling1 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_biplot_scaling2 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_sample_constraints_scaling1 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_sample_constraints_scaling2 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_site_scaling1_from_vegan -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_site_scaling2_from_vegan -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_species_scaling1_from_vegan -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example2_species_scaling2_from_vegan -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_X -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_Y -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_biplot_scaling1 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_biplot_scaling2 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_sample_constraints_scaling1 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_sample_constraints_scaling2 -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_site_scaling1_from_vegan -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_site_scaling2_from_vegan -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_species_scaling1_from_vegan -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/example3_species_scaling2_from_vegan -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/exp_PCoAEigenResults_site -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/exp_PCoAzeros_site -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/vare_rda_biplot_from_vegan.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/vare_rda_constraints_from_vegan.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/vare_rda_eigvals_from_vegan.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/vare_rda_propexpl_from_vegan.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/vare_rda_sites_from_vegan.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/vare_rda_species_from_vegan.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/varechem.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
copying skbio/stats/ordination/tests/data/varespec.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/data
running build_ext
building 'skbio.metadata._intersection' extension
creating build
creating build/temp.linux-armhf-3.9
creating build/temp.linux-armhf-3.9/skbio
creating build/temp.linux-armhf-3.9/skbio/metadata
arm-linux-gnueabihf-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -O2 -ffile-prefix-map=/<<PKGBUILDDIR>>=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/lib/python3/dist-packages/numpy/core/include -I/usr/include/python3.9 -c skbio/metadata/_intersection.c -o build/temp.linux-armhf-3.9/skbio/metadata/_intersection.o -DSIMDE_ENABLE_OPENMP -fopenmp-simd -O3
skbio/metadata/_intersection.c: In function '__Pyx_ParseOptionalKeywords':
skbio/metadata/_intersection.c:11013:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
11013 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11013:21: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
11013 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11013:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
11013 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11013:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
11013 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11013:21: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
11013 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11013:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
11013 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11029:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
11029 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11029:25: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
11029 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11029:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
11029 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11029:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
11029 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11029:25: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
11029 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/metadata/_intersection.c:11029:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
11029 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/metadata/_intersection.c:17:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
arm-linux-gnueabihf-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -ffile-prefix-map=/<<PKGBUILDDIR>>=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-armhf-3.9/skbio/metadata/_intersection.o -o /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/metadata/_intersection.cpython-39-arm-linux-gnueabihf.so
building 'skbio.stats.__subsample' extension
creating build/temp.linux-armhf-3.9/skbio/stats
arm-linux-gnueabihf-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -O2 -ffile-prefix-map=/<<PKGBUILDDIR>>=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/lib/python3/dist-packages/numpy/core/include -I/usr/lib/python3/dist-packages/numpy/core/include -I/usr/include/python3.9 -c skbio/stats/__subsample.c -o build/temp.linux-armhf-3.9/skbio/stats/__subsample.o -DSIMDE_ENABLE_OPENMP -fopenmp-simd -O3
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1822,
                 from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
                 from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
                 from skbio/stats/__subsample.c:617:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
   17 | #warning "Using deprecated NumPy API, disable it with " \
      |  ^~~~~~~
skbio/stats/__subsample.c: In function '__Pyx_ParseOptionalKeywords':
skbio/stats/__subsample.c:5377:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 5377 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5377:21: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
 5377 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5377:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 5377 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5377:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 5377 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5377:21: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
 5377 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5377:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 5377 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5393:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 5393 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5393:25: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
 5393 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5393:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 5393 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5393:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 5393 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5393:25: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
 5393 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/stats/__subsample.c:5393:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 5393 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/stats/__subsample.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
arm-linux-gnueabihf-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -ffile-prefix-map=/<<PKGBUILDDIR>>=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-armhf-3.9/skbio/stats/__subsample.o -o /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/__subsample.cpython-39-arm-linux-gnueabihf.so
building 'skbio.alignment._ssw_wrapper' extension
creating build/temp.linux-armhf-3.9/skbio/alignment
arm-linux-gnueabihf-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -O2 -ffile-prefix-map=/<<PKGBUILDDIR>>=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/lib/python3/dist-packages/numpy/core/include -I/usr/lib/python3/dist-packages/numpy/core/include -I/usr/include/python3.9 -c skbio/alignment/_ssw_wrapper.c -o build/temp.linux-armhf-3.9/skbio/alignment/_ssw_wrapper.o -DSIMDE_ENABLE_OPENMP -fopenmp-simd -O3
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1822,
                 from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
                 from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
                 from skbio/alignment/_ssw_wrapper.c:624:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
   17 | #warning "Using deprecated NumPy API, disable it with " \
      |  ^~~~~~~
skbio/alignment/_ssw_wrapper.c: In function '__Pyx_ParseOptionalKeywords':
skbio/alignment/_ssw_wrapper.c:12453:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
12453 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12453:21: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
12453 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12453:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
12453 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12453:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
12453 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12453:21: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
12453 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12453:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
12453 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12469:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
12469 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12469:25: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
12469 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12469:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
12469 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12469:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
12469 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12469:25: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
12469 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/alignment/_ssw_wrapper.c:12469:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
12469 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/alignment/_ssw_wrapper.c:29:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
arm-linux-gnueabihf-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -ffile-prefix-map=/<<PKGBUILDDIR>>=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-armhf-3.9/skbio/alignment/_ssw_wrapper.o -lssw -o /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment/_ssw_wrapper.cpython-39-arm-linux-gnueabihf.so
building 'skbio.diversity._phylogenetic' extension
creating build/temp.linux-armhf-3.9/skbio/diversity
arm-linux-gnueabihf-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -g -fwrapv -O2 -g -O2 -ffile-prefix-map=/<<PKGBUILDDIR>>=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/lib/python3/dist-packages/numpy/core/include -I/usr/lib/python3/dist-packages/numpy/core/include -I/usr/include/python3.9 -c skbio/diversity/_phylogenetic.c -o build/temp.linux-armhf-3.9/skbio/diversity/_phylogenetic.o -DSIMDE_ENABLE_OPENMP -fopenmp-simd -O3
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1822,
                 from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
                 from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
                 from skbio/diversity/_phylogenetic.c:617:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
   17 | #warning "Using deprecated NumPy API, disable it with " \
      |  ^~~~~~~
skbio/diversity/_phylogenetic.c: In function '__Pyx_ParseOptionalKeywords':
skbio/diversity/_phylogenetic.c:6462:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 6462 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6462:21: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
 6462 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6462:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 6462 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6462:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 6462 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6462:21: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
 6462 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6462:21: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 6462 |                     (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                     ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6478:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 6478 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6478:25: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
 6478 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6478:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 6478 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6478:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 6478 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6478:25: warning: 'PyUnicode_AsUnicode' is deprecated [-Wdeprecated-declarations]
 6478 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:580:45: note: declared here
  580 | Py_DEPRECATED(3.3) PyAPI_FUNC(Py_UNICODE *) PyUnicode_AsUnicode(
      |                                             ^~~~~~~~~~~~~~~~~~~
skbio/diversity/_phylogenetic.c:6478:25: warning: '_PyUnicode_get_wstr_length' is deprecated [-Wdeprecated-declarations]
 6478 |                         (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
      |                         ^
In file included from /usr/include/python3.9/unicodeobject.h:1026,
                 from /usr/include/python3.9/Python.h:106,
                 from skbio/diversity/_phylogenetic.c:23:
/usr/include/python3.9/cpython/unicodeobject.h:446:26: note: declared here
  446 | static inline Py_ssize_t _PyUnicode_get_wstr_length(PyObject *op) {
      |                          ^~~~~~~~~~~~~~~~~~~~~~~~~~
arm-linux-gnueabihf-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -ffile-prefix-map=/<<PKGBUILDDIR>>=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-armhf-3.9/skbio/diversity/_phylogenetic.o -o /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/diversity/_phylogenetic.cpython-39-arm-linux-gnueabihf.so
make[1]: Leaving directory '/<<PKGBUILDDIR>>'
   dh_auto_test -a -O--buildsystem=pybuild
I: pybuild base:232: cd /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build; python3.9 -m pytest 
============================= test session starts ==============================
platform linux -- Python 3.9.7, pytest-6.2.5, py-1.10.0, pluggy-0.13.0
rootdir: /<<PKGBUILDDIR>>
collected 2348 items

skbio/alignment/tests/test_pairwise.py .........................         [  1%]
skbio/alignment/tests/test_ssw.py ...........................            [  2%]
skbio/alignment/tests/test_tabular_msa.py .............................. [  3%]
..............F......................................................... [  6%]
........................................................................ [  9%]
................................F....................................... [ 12%]
........................................................................ [ 15%]
........................................................................ [ 18%]
............                                                             [ 19%]
skbio/diversity/alpha/tests/test_ace.py ..                               [ 19%]
skbio/diversity/alpha/tests/test_base.py ..............F.........        [ 20%]
skbio/diversity/alpha/tests/test_chao1.py ...                            [ 20%]
skbio/diversity/alpha/tests/test_faith_pd.py FFF.FFFF                    [ 20%]
skbio/diversity/alpha/tests/test_gini.py ...                             [ 21%]
skbio/diversity/alpha/tests/test_lladser.py ..FF.....F..                 [ 21%]
skbio/diversity/beta/tests/test_unifrac.py .FFFFFFF.FFFFFFFF.FFFFF.FFFF  [ 22%]
skbio/diversity/tests/test_block.py F..........                          [ 23%]
skbio/diversity/tests/test_driver.py FFFF...FFF....F...FFF.......F...FF  [ 24%]
skbio/diversity/tests/test_util.py .........F                            [ 25%]
skbio/io/format/tests/test_base.py ................................      [ 26%]
skbio/io/format/tests/test_blast6.py ...........                         [ 26%]
skbio/io/format/tests/test_blast7.py ..............                      [ 27%]
skbio/io/format/tests/test_clustal.py .............                      [ 28%]
skbio/io/format/tests/test_embl.py ...............................       [ 29%]
skbio/io/format/tests/test_emptyfile.py ..                               [ 29%]
skbio/io/format/tests/test_fasta.py .F..............                     [ 30%]
skbio/io/format/tests/test_fastq.py ...............                      [ 30%]
skbio/io/format/tests/test_genbank.py .....................              [ 31%]
skbio/io/format/tests/test_gff3.py ........................              [ 32%]
skbio/io/format/tests/test_lsmat.py .......                              [ 33%]
skbio/io/format/tests/test_newick.py .......                             [ 33%]
skbio/io/format/tests/test_ordination.py .....                           [ 33%]
skbio/io/format/tests/test_phylip.py .......                             [ 33%]
skbio/io/format/tests/test_qseq.py ......                                [ 34%]
skbio/io/format/tests/test_sequence_feature_vocabulary.py ....           [ 34%]
skbio/io/format/tests/test_stockholm.py ................................ [ 35%]
...........................................                              [ 37%]
skbio/io/tests/test_iosources.py ..........                              [ 37%]
skbio/io/tests/test_registry.py ........................................ [ 39%]
......................................................                   [ 41%]
skbio/io/tests/test_util.py .........................................sss [ 43%]
sssssssssssssssssssssssssss............................................. [ 46%]
........................................................................ [ 49%]
................................                                         [ 51%]
skbio/metadata/tests/test_intersection.py ...............                [ 51%]
skbio/metadata/tests/test_interval.py .................................. [ 53%]
.....................................                                    [ 54%]
skbio/metadata/tests/test_mixin.py ..................................... [ 56%]
.......F.....................................................            [ 59%]
skbio/sequence/tests/test_distance.py ..........................         [ 60%]
skbio/sequence/tests/test_dna.py ....                                    [ 60%]
skbio/sequence/tests/test_genetic_code.py ..........................     [ 61%]
skbio/sequence/tests/test_grammared_sequence.py .....F.................. [ 62%]
...................                                                      [ 63%]
skbio/sequence/tests/test_nucleotide_sequences.py ...................... [ 64%]
.......                                                                  [ 64%]
skbio/sequence/tests/test_protein.py ..........                          [ 64%]
skbio/sequence/tests/test_rna.py ....                                    [ 65%]
skbio/sequence/tests/test_sequence.py .................................. [ 66%]
..........F............................................................. [ 69%]
....................F...................F...F..F.F.F...F.........F...... [ 72%]
....F........................................................F...F...... [ 75%]
.......                                                                  [ 76%]
skbio/stats/distance/tests/test_anosim.py ....                           [ 76%]
skbio/stats/distance/tests/test_base.py ................................ [ 77%]
...............................................................          [ 80%]
skbio/stats/distance/tests/test_bioenv.py FFF.........FF...              [ 81%]
skbio/stats/distance/tests/test_mantel.py ................F.FFFFF.FFF... [ 82%]
.........                                                                [ 82%]
skbio/stats/distance/tests/test_permanova.py ....                        [ 82%]
skbio/stats/distance/tests/test_permdisp.py ........                     [ 83%]
skbio/stats/evolve/tests/test_hommola.py ............                    [ 83%]
skbio/stats/ordination/tests/test_canonical_correspondence_analysis.py . [ 83%]
.....                                                                    [ 83%]
skbio/stats/ordination/tests/test_correspondence_analysis.py ........    [ 84%]
skbio/stats/ordination/tests/test_ordination_results.py ................ [ 84%]
                                                                         [ 84%]
skbio/stats/ordination/tests/test_principal_coordinate_analysis.py ..... [ 85%]
......                                                                   [ 85%]
skbio/stats/ordination/tests/test_redundancy_analysis.py ....            [ 85%]
skbio/stats/ordination/tests/test_util.py .........                      [ 85%]
skbio/stats/tests/test_composition.py .................................. [ 87%]
........................                                                 [ 88%]
skbio/stats/tests/test_gradient.py ..........................            [ 89%]
skbio/stats/tests/test_misc.py ...                                       [ 89%]
skbio/stats/tests/test_power.py ........................................ [ 91%]
...                                                                      [ 91%]
skbio/stats/tests/test_subsample.py .F..F.F...FF                         [ 92%]
skbio/tests/test_base.py .....                                           [ 92%]
skbio/tests/test_workflow.py .................                           [ 92%]
skbio/tree/tests/test_majority_rule.py ......                            [ 93%]
skbio/tree/tests/test_nj.py ...........                                  [ 93%]
skbio/tree/tests/test_tree.py .......................................... [ 95%]
.................................................                        [ 97%]
skbio/util/tests/test_decorator.py .......................               [ 98%]
skbio/util/tests/test_misc.py ...................                        [ 99%]
skbio/util/tests/test_testing.py ...............                         [100%]

=================================== FAILURES ===================================
________ TestTabularMSAPositionalMetadata.test_eq_from_different_source ________

self = <skbio.alignment.tests.test_tabular_msa.TestTabularMSAPositionalMetadata testMethod=test_eq_from_different_source>

    def test_eq_from_different_source(self):
        obj1 = self._positional_metadata_constructor_(
            3, positional_metadata={'foo': np.array([1, 2, 3])})
        obj2 = self._positional_metadata_constructor_(
            3, positional_metadata=pd.DataFrame({'foo': [1, 2, 3]},
                                                index=['foo', 'bar', 'baz']))
>       self.assertReallyEqual(obj1, obj2)

skbio/metadata/_testing.py:464: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/util/_testing.py:31: in assertReallyEqual
    self.assertEqual(a, b)
E   AssertionError: Tabul[75 chars]: int32>
E   Stats:
E       sequence count: 1
E       posi[38 chars]-
E   AAA != Tabul[75 chars]: int64>
E   Stats:
E       sequence count: 1
E       posi[38 chars]-
E   AAA
____________________ TestILoc.test_fancy_empty_second_axis _____________________

self = <skbio.alignment.tests.test_tabular_msa.TestILoc testMethod=test_fancy_empty_second_axis>

    def test_fancy_empty_second_axis(self):
        a = DNA("ACGT", metadata={0: 0}, positional_metadata={0: [1, 2, 3, 4]})
        b = DNA("ACGT", metadata={1: 1}, positional_metadata={1: [1, 2, 3, 4]})
        c = DNA("ACGT", metadata={2: 2}, positional_metadata={2: [1, 2, 3, 4]})
    
        msa = TabularMSA([a, b, c], metadata={3: 3},
                         positional_metadata={3: [1, 2, 3, 4]})
    
>       self.assertEqual(self.get(msa, (Ellipsis, [])),
                         TabularMSA([a[0:0], b[0:0], c[0:0]],
                                    metadata={3: 3},
                                    positional_metadata={3: np.array(
                                        [], dtype=int)}))
E       AssertionError: Tabul[86 chars]: int64>
E       Stats:
E           sequence count: 3
E           posi[30 chars]----- != Tabul[86 chars]: int32>
E       Stats:
E           sequence count: 3
E           posi[30 chars]-----

skbio/alignment/tests/test_tabular_msa.py:1659: AssertionError
_____________________ BaseTests.test_michaelis_menten_fit ______________________

self = <skbio.diversity.alpha.tests.test_base.BaseTests testMethod=test_michaelis_menten_fit>

    def test_michaelis_menten_fit(self):
>       obs = michaelis_menten_fit([22])

skbio/diversity/alpha/tests/test_base.py:176: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_base.py:687: in michaelis_menten_fit
    ymtx[i] = np.asarray([observed_otus(subsample_counts(counts, n))
skbio/diversity/alpha/_base.py:687: in <listcomp>
    ymtx[i] = np.asarray([observed_otus(subsample_counts(counts, n))
skbio/stats/_subsample.py:246: in subsample_counts
    result = _subsample_counts_without_replacement(counts, n,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'int64_t' but got 'long'

skbio/stats/__subsample.pyx:13: ValueError
__________________________ FaithPDTests.test_faith_pd __________________________

self = <skbio.diversity.alpha.tests.test_faith_pd.FaithPDTests testMethod=test_faith_pd>

    def test_faith_pd(self):
        # expected results derived from QIIME 1.9.1, which
        # is a completely different implementation skbio's initial
        # phylogenetic diversity implementation
>       actual = faith_pd(self.b1[0], self.oids1, self.t1)

skbio/diversity/alpha/tests/test_faith_pd.py:65: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_faith_pd.py:122: in faith_pd
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
___________________ FaithPDTests.test_faith_pd_all_observed ____________________

self = <skbio.diversity.alpha.tests.test_faith_pd.FaithPDTests testMethod=test_faith_pd_all_observed>

    def test_faith_pd_all_observed(self):
>       actual = faith_pd([1, 1, 1, 1, 1], self.oids1, self.t1)

skbio/diversity/alpha/tests/test_faith_pd.py:51: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_faith_pd.py:122: in faith_pd
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
____________________ FaithPDTests.test_faith_pd_extra_tips _____________________

self = <skbio.diversity.alpha.tests.test_faith_pd.FaithPDTests testMethod=test_faith_pd_extra_tips>

    def test_faith_pd_extra_tips(self):
        # results are the same despite presences of unobserved tips in tree
>       actual = faith_pd(self.b1[0], self.oids1, self.t1_w_extra_tips)

skbio/diversity/alpha/tests/test_faith_pd.py:80: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_faith_pd.py:122: in faith_pd
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
______________________ FaithPDTests.test_faith_pd_minimal ______________________

self = <skbio.diversity.alpha.tests.test_faith_pd.FaithPDTests testMethod=test_faith_pd_minimal>

    def test_faith_pd_minimal(self):
        # two tips
        tree = TreeNode.read(StringIO('(OTU1:0.25, OTU2:0.25)root;'))
>       actual = faith_pd([1, 0], ['OTU1', 'OTU2'], tree)

skbio/diversity/alpha/tests/test_faith_pd.py:96: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_faith_pd.py:122: in faith_pd
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
___________________ FaithPDTests.test_faith_pd_none_observed ___________________

self = <skbio.diversity.alpha.tests.test_faith_pd.FaithPDTests testMethod=test_faith_pd_none_observed>

    def test_faith_pd_none_observed(self):
>       actual = faith_pd(np.array([], dtype=int),
                          np.array([], dtype=int),
                          self.t1)

skbio/diversity/alpha/tests/test_faith_pd.py:41: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_faith_pd.py:122: in faith_pd
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
__________________ FaithPDTests.test_faith_pd_qiime_tiny_test __________________

self = <skbio.diversity.alpha.tests.test_faith_pd.FaithPDTests testMethod=test_faith_pd_qiime_tiny_test>

    def test_faith_pd_qiime_tiny_test(self):
        # the following table and tree are derived from the QIIME 1.9.1
        # "tiny-test" data
        tt_table_fp = get_data_path(
            os.path.join('qiime-191-tt', 'otu-table.tsv'), 'data')
        tt_tree_fp = get_data_path(
            os.path.join('qiime-191-tt', 'tree.nwk'), 'data')
    
        self.q_table = pd.read_csv(tt_table_fp, sep='\t', skiprows=1,
                                   index_col=0)
        self.q_tree = TreeNode.read(tt_tree_fp)
    
        expected_fp = get_data_path(
            os.path.join('qiime-191-tt', 'faith-pd.txt'), 'data')
        expected = pd.read_csv(expected_fp, sep='\t', index_col=0)
        for sid in self.q_table.columns:
>           actual = faith_pd(self.q_table[sid],
                              otu_ids=self.q_table.index,
                              tree=self.q_tree)

skbio/diversity/alpha/tests/test_faith_pd.py:116: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_faith_pd.py:122: in faith_pd
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________________ FaithPDTests.test_faith_pd_root_not_observed _________________

self = <skbio.diversity.alpha.tests.test_faith_pd.FaithPDTests testMethod=test_faith_pd_root_not_observed>

    def test_faith_pd_root_not_observed(self):
        # expected values computed by hand
        tree = TreeNode.read(
            StringIO('((OTU1:0.1, OTU2:0.2):0.3, (OTU3:0.5, OTU4:0.7):1.1)'
                     'root;'))
        otu_ids = ['OTU%d' % i for i in range(1, 5)]
        # root node not observed, but branch between (OTU1, OTU2) and root
        # is considered observed
>       actual = faith_pd([1, 1, 0, 0], otu_ids, tree)

skbio/diversity/alpha/tests/test_faith_pd.py:129: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_faith_pd.py:122: in faith_pd
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________________________ LladserTests.test_lladser_ci _________________________

self = <skbio.diversity.alpha.tests.test_lladser.LladserTests testMethod=test_lladser_ci>

    def test_lladser_ci(self):
        """lladser_ci estimate using defaults contains p with 95% prob"""
        np.random.seed(12345678)
        reps = 100
        sum = 0
        for i in range(reps):
>           fake_obs, exp_p = create_fake_observation()

skbio/diversity/alpha/tests/test_lladser.py:69: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/tests/test_lladser.py:31: in create_fake_observation
    fake_obs = subsample_counts(counts, 1000)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

counts = array([9000,    1,    1, ...,    1,    1,    1], dtype=int64), n = 1000
replace = False

    @experimental(as_of="0.4.0")
    def subsample_counts(counts, n, replace=False):
        """Randomly subsample from a vector of counts, with or without replacement.
    
        Parameters
        ----------
        counts : 1-D array_like
            Vector of counts (integers) to randomly subsample from.
        n : int
            Number of items to subsample from `counts`. Must be less than or equal
            to the sum of `counts`.
        replace : bool, optional
            If ``True``, subsample with replacement. If ``False`` (the default),
            subsample without replacement.
    
        Returns
        -------
        subsampled : ndarray
            Subsampled vector of counts where the sum of the elements equals `n`
            (i.e., ``subsampled.sum() == n``). Will have the same shape as
            `counts`.
    
        Raises
        ------
        TypeError
            If `counts` cannot be safely converted to an integer datatype.
        ValueError
            If `n` is less than zero or greater than the sum of `counts`
            when `replace=False`.
        EfficiencyWarning
            If the accelerated code isn't present or hasn't been compiled.
    
        See Also
        --------
        isubsample
        skbio.diversity.alpha
    
        Notes
        -----
        If subsampling is performed without replacement (``replace=False``), a copy
        of `counts` is returned if `n` is equal to the number of items in `counts`,
        as all items will be chosen from the original vector.
    
        If subsampling is performed with replacement (``replace=True``) and `n` is
        equal to the number of items in `counts`, the subsampled vector that is
        returned may not necessarily be the same vector as `counts`.
    
        Examples
        --------
        Subsample 4 items (without replacement) from a vector of counts:
    
        >>> import numpy as np
        >>> from skbio.stats import subsample_counts
        >>> a = np.array([4, 5, 0, 2, 1])
        >>> sub = subsample_counts(a, 4)
        >>> sub.sum()
        4
        >>> sub.shape
        (5,)
    
        Trying to subsample an equal number of items (without replacement) results
        in the same vector as our input:
    
        >>> subsample_counts([0, 3, 0, 1], 4)
        array([0, 3, 0, 1])
    
        Subsample 5 items (with replacement):
    
        >>> sub = subsample_counts([1, 0, 1, 2, 2, 3, 0, 1], 5, replace=True)
        >>> sub.sum()
        5
        >>> sub.shape
        (8,)
    
        """
        if n < 0:
            raise ValueError("n cannot be negative.")
    
        counts = np.asarray(counts)
>       counts = counts.astype(int, casting='safe')
E       TypeError: Cannot cast array data from dtype('int64') to dtype('int32') according to the rule 'safe'

skbio/stats/_subsample.py:229: TypeError
_______________________ LladserTests.test_lladser_ci_f3 ________________________

self = <skbio.diversity.alpha.tests.test_lladser.LladserTests testMethod=test_lladser_ci_f3>

    def test_lladser_ci_f3(self):
        """lladser_ci estimate using f=3 contains p with 95% prob"""
    
        # Test different values of f=3 and r=14, which lie exactly on the
        # 95% interval line. For 100 reps using simple cumulative binomial
        # probs we expect to have more than 5 misses of the interval in 38%
        # of all test runs. To make this test pass reliable we thus have to
        # set a defined seed
        np.random.seed(12345678)
        reps = 100
        sum = 0
        for i in range(reps):
            # re-create the obs for every estimate, such that they are truly
            # independent events
>           fake_obs, exp_p = create_fake_observation()

skbio/diversity/alpha/tests/test_lladser.py:90: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/tests/test_lladser.py:31: in create_fake_observation
    fake_obs = subsample_counts(counts, 1000)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

counts = array([9000,    1,    1, ...,    1,    1,    1], dtype=int64), n = 1000
replace = False

    @experimental(as_of="0.4.0")
    def subsample_counts(counts, n, replace=False):
        """Randomly subsample from a vector of counts, with or without replacement.
    
        Parameters
        ----------
        counts : 1-D array_like
            Vector of counts (integers) to randomly subsample from.
        n : int
            Number of items to subsample from `counts`. Must be less than or equal
            to the sum of `counts`.
        replace : bool, optional
            If ``True``, subsample with replacement. If ``False`` (the default),
            subsample without replacement.
    
        Returns
        -------
        subsampled : ndarray
            Subsampled vector of counts where the sum of the elements equals `n`
            (i.e., ``subsampled.sum() == n``). Will have the same shape as
            `counts`.
    
        Raises
        ------
        TypeError
            If `counts` cannot be safely converted to an integer datatype.
        ValueError
            If `n` is less than zero or greater than the sum of `counts`
            when `replace=False`.
        EfficiencyWarning
            If the accelerated code isn't present or hasn't been compiled.
    
        See Also
        --------
        isubsample
        skbio.diversity.alpha
    
        Notes
        -----
        If subsampling is performed without replacement (``replace=False``), a copy
        of `counts` is returned if `n` is equal to the number of items in `counts`,
        as all items will be chosen from the original vector.
    
        If subsampling is performed with replacement (``replace=True``) and `n` is
        equal to the number of items in `counts`, the subsampled vector that is
        returned may not necessarily be the same vector as `counts`.
    
        Examples
        --------
        Subsample 4 items (without replacement) from a vector of counts:
    
        >>> import numpy as np
        >>> from skbio.stats import subsample_counts
        >>> a = np.array([4, 5, 0, 2, 1])
        >>> sub = subsample_counts(a, 4)
        >>> sub.sum()
        4
        >>> sub.shape
        (5,)
    
        Trying to subsample an equal number of items (without replacement) results
        in the same vector as our input:
    
        >>> subsample_counts([0, 3, 0, 1], 4)
        array([0, 3, 0, 1])
    
        Subsample 5 items (with replacement):
    
        >>> sub = subsample_counts([1, 0, 1, 2, 2, 3, 0, 1], 5, replace=True)
        >>> sub.sum()
        5
        >>> sub.shape
        (8,)
    
        """
        if n < 0:
            raise ValueError("n cannot be negative.")
    
        counts = np.asarray(counts)
>       counts = counts.astype(int, casting='safe')
E       TypeError: Cannot cast array data from dtype('int64') to dtype('int32') according to the rule 'safe'

skbio/stats/_subsample.py:229: TypeError
_________________________ LladserTests.test_lladser_pe _________________________

self = <skbio.diversity.alpha.tests.test_lladser.LladserTests testMethod=test_lladser_pe>

    def test_lladser_pe(self):
        """lladser_pe returns point estimates within the expected variance"""
    
        obs = lladser_pe([3], r=4)
        self.assertTrue(np.isnan(obs))
    
        np.random.seed(123456789)
>       fake_obs, exp_p = create_fake_observation()

skbio/diversity/alpha/tests/test_lladser.py:45: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/tests/test_lladser.py:31: in create_fake_observation
    fake_obs = subsample_counts(counts, 1000)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

counts = array([9000,    1,    1, ...,    1,    1,    1], dtype=int64), n = 1000
replace = False

    @experimental(as_of="0.4.0")
    def subsample_counts(counts, n, replace=False):
        """Randomly subsample from a vector of counts, with or without replacement.
    
        Parameters
        ----------
        counts : 1-D array_like
            Vector of counts (integers) to randomly subsample from.
        n : int
            Number of items to subsample from `counts`. Must be less than or equal
            to the sum of `counts`.
        replace : bool, optional
            If ``True``, subsample with replacement. If ``False`` (the default),
            subsample without replacement.
    
        Returns
        -------
        subsampled : ndarray
            Subsampled vector of counts where the sum of the elements equals `n`
            (i.e., ``subsampled.sum() == n``). Will have the same shape as
            `counts`.
    
        Raises
        ------
        TypeError
            If `counts` cannot be safely converted to an integer datatype.
        ValueError
            If `n` is less than zero or greater than the sum of `counts`
            when `replace=False`.
        EfficiencyWarning
            If the accelerated code isn't present or hasn't been compiled.
    
        See Also
        --------
        isubsample
        skbio.diversity.alpha
    
        Notes
        -----
        If subsampling is performed without replacement (``replace=False``), a copy
        of `counts` is returned if `n` is equal to the number of items in `counts`,
        as all items will be chosen from the original vector.
    
        If subsampling is performed with replacement (``replace=True``) and `n` is
        equal to the number of items in `counts`, the subsampled vector that is
        returned may not necessarily be the same vector as `counts`.
    
        Examples
        --------
        Subsample 4 items (without replacement) from a vector of counts:
    
        >>> import numpy as np
        >>> from skbio.stats import subsample_counts
        >>> a = np.array([4, 5, 0, 2, 1])
        >>> sub = subsample_counts(a, 4)
        >>> sub.sum()
        4
        >>> sub.shape
        (5,)
    
        Trying to subsample an equal number of items (without replacement) results
        in the same vector as our input:
    
        >>> subsample_counts([0, 3, 0, 1], 4)
        array([0, 3, 0, 1])
    
        Subsample 5 items (with replacement):
    
        >>> sub = subsample_counts([1, 0, 1, 2, 2, 3, 0, 1], 5, replace=True)
        >>> sub.sum()
        5
        >>> sub.shape
        (8,)
    
        """
        if n < 0:
            raise ValueError("n cannot be negative.")
    
        counts = np.asarray(counts)
>       counts = counts.astype(int, casting='safe')
E       TypeError: Cannot cast array data from dtype('int64') to dtype('int32') according to the rule 'safe'

skbio/stats/_subsample.py:229: TypeError
___________________ UnifracTests.test_unweighted_extra_tips ____________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_extra_tips>

    def test_unweighted_extra_tips(self):
        # UniFrac values are the same despite unobserved tips in the tree
        for i in range(len(self.b1)):
            for j in range(len(self.b1)):
>               actual = unweighted_unifrac(
                    self.b1[i], self.b1[j], self.oids1, self.t1_w_extra_tips)

skbio/diversity/beta/tests/test_unifrac.py:85: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
__________________ UnifracTests.test_unweighted_minimal_trees __________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_minimal_trees>

    def test_unweighted_minimal_trees(self):
        # two tips
        tree = TreeNode.read(StringIO('(OTU1:0.25, OTU2:0.25)root;'))
>       actual = unweighted_unifrac([1, 0], [0, 0], ['OTU1', 'OTU2'],
                                    tree)

skbio/diversity/beta/tests/test_unifrac.py:104: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________________ UnifracTests.test_unweighted_otus_out_of_order ________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_otus_out_of_order>

    def test_unweighted_otus_out_of_order(self):
        # UniFrac API does not assert the observations are in tip order of the
        # input tree
        shuffled_ids = self.oids1[:]
        shuffled_b1 = self.b1.copy()
    
        shuffled_ids[0], shuffled_ids[-1] = shuffled_ids[-1], shuffled_ids[0]
        shuffled_b1[:, [0, -1]] = shuffled_b1[:, [-1, 0]]
    
        for i in range(len(self.b1)):
            for j in range(len(self.b1)):
>               actual = unweighted_unifrac(
                    self.b1[i], self.b1[j], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:58: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________________ UnifracTests.test_unweighted_root_not_observed ________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_root_not_observed>

    def test_unweighted_root_not_observed(self):
        # expected values computed with QIIME 1.9.1 and by hand
        # root node not observed, but branch between (OTU1, OTU2) and root
        # is considered shared
>       actual = unweighted_unifrac([1, 1, 0, 0], [1, 0, 0, 0],
                                    self.oids2, self.t2)

skbio/diversity/beta/tests/test_unifrac.py:120: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_____________________ UnifracTests.test_unweighted_unifrac _____________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_unifrac>

    def test_unweighted_unifrac(self):
        # expected results derived from QIIME 1.9.1, which
        # is a completely different implementation skbio's initial
        # unweighted unifrac implementation
        # sample A versus all
>       actual = unweighted_unifrac(
            self.b1[0], self.b1[1], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:338: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________________ UnifracTests.test_unweighted_unifrac_identity _________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_unifrac_identity>

    def test_unweighted_unifrac_identity(self):
        for i in range(len(self.b1)):
>           actual = unweighted_unifrac(
                self.b1[i], self.b1[i], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:174: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_____________ UnifracTests.test_unweighted_unifrac_non_overlapping _____________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_unifrac_non_overlapping>

    def test_unweighted_unifrac_non_overlapping(self):
        # these communities only share the root node
>       actual = unweighted_unifrac(
            self.b1[4], self.b1[5], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:310: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________________ UnifracTests.test_unweighted_unifrac_symmetry _________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_unifrac_symmetry>

    def test_unweighted_unifrac_symmetry(self):
        for i in range(len(self.b1)):
            for j in range(len(self.b1)):
>               actual = unweighted_unifrac(
                    self.b1[i], self.b1[j], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:182: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_______________ UnifracTests.test_unweighted_unifrac_zero_counts _______________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_unweighted_unifrac_zero_counts>

    def test_unweighted_unifrac_zero_counts(self):
>       actual = unweighted_unifrac(
            [1, 1, 1, 0, 0], [0, 0, 0, 0, 0], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:320: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:146: in unweighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
____________________ UnifracTests.test_weighted_extra_tips _____________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_extra_tips>

    def test_weighted_extra_tips(self):
        # UniFrac values are the same despite unobserved tips in the tree
        for i in range(len(self.b1)):
            for j in range(len(self.b1)):
>               actual = weighted_unifrac(
                    self.b1[i], self.b1[j], self.oids1, self.t1_w_extra_tips)

skbio/diversity/beta/tests/test_unifrac.py:95: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
___________________ UnifracTests.test_weighted_minimal_trees ___________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_minimal_trees>

    def test_weighted_minimal_trees(self):
        # two tips
        tree = TreeNode.read(StringIO('(OTU1:0.25, OTU2:0.25)root;'))
>       actual = weighted_unifrac([1, 0], [0, 0], ['OTU1', 'OTU2'], tree)

skbio/diversity/beta/tests/test_unifrac.py:112: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
___________ UnifracTests.test_weighted_normalized_root_not_observed ____________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_normalized_root_not_observed>

    def test_weighted_normalized_root_not_observed(self):
        # expected values computed by hand, these disagree with QIIME 1.9.1
        # root node not observed, but branch between (OTU1, OTU2) and root
        # is considered shared
>       actual = weighted_unifrac([1, 0, 0, 0], [1, 1, 0, 0],
                                  self.oids2, self.t2, normalized=True)

skbio/diversity/beta/tests/test_unifrac.py:160: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________________ UnifracTests.test_weighted_otus_out_of_order _________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_otus_out_of_order>

    def test_weighted_otus_out_of_order(self):
        # UniFrac API does not assert the observations are in tip order of the
        # input tree
        shuffled_ids = self.oids1[:]
        shuffled_b1 = self.b1.copy()
    
        shuffled_ids[0], shuffled_ids[-1] = shuffled_ids[-1], shuffled_ids[0]
        shuffled_b1[:, [0, -1]] = shuffled_b1[:, [-1, 0]]
    
        for i in range(len(self.b1)):
            for j in range(len(self.b1)):
>               actual = weighted_unifrac(
                    self.b1[i], self.b1[j], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:75: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________________ UnifracTests.test_weighted_root_not_observed _________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_root_not_observed>

    def test_weighted_root_not_observed(self):
        # expected values computed by hand, these disagree with QIIME 1.9.1
        # root node not observed, but branch between (OTU1, OTU2) and root
        # is considered shared
>       actual = weighted_unifrac([1, 0, 0, 0], [1, 1, 0, 0],
                                  self.oids2, self.t2)

skbio/diversity/beta/tests/test_unifrac.py:144: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
______________________ UnifracTests.test_weighted_unifrac ______________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac>

    def test_weighted_unifrac(self):
        # expected results derived from QIIME 1.9.1, which
        # is a completely different implementation skbio's initial
        # weighted unifrac implementation
>       actual = weighted_unifrac(
            self.b1[0], self.b1[1], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:450: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________________ UnifracTests.test_weighted_unifrac_identity __________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_identity>

    def test_weighted_unifrac_identity(self):
        for i in range(len(self.b1)):
>           actual = weighted_unifrac(
                self.b1[i], self.b1[i], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:405: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
____________ UnifracTests.test_weighted_unifrac_identity_normalized ____________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_identity_normalized>

    def test_weighted_unifrac_identity_normalized(self):
        for i in range(len(self.b1)):
>           actual = weighted_unifrac(
                self.b1[i], self.b1[i], self.oids1, self.t1, normalized=True)

skbio/diversity/beta/tests/test_unifrac.py:517: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
______________ UnifracTests.test_weighted_unifrac_non_overlapping ______________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_non_overlapping>

    def test_weighted_unifrac_non_overlapping(self):
        # expected results derived from QIIME 1.9.1, which
        # is a completely different implementation skbio's initial
        # weighted unifrac implementation
        # these communities only share the root node
>       actual = weighted_unifrac(
            self.b1[4], self.b1[5], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:424: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________ UnifracTests.test_weighted_unifrac_non_overlapping_normalized _________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_non_overlapping_normalized>

    def test_weighted_unifrac_non_overlapping_normalized(self):
        # these communities only share the root node
>       actual = weighted_unifrac(
            self.b1[4], self.b1[5], self.oids1, self.t1, normalized=True)

skbio/diversity/beta/tests/test_unifrac.py:535: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________________ UnifracTests.test_weighted_unifrac_normalized _________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_normalized>

    def test_weighted_unifrac_normalized(self):
        # expected results derived from QIIME 1.9.1, which
        # is a completely different implementation skbio's initial
        # weighted unifrac implementation
>       actual = weighted_unifrac(
            self.b1[0], self.b1[1], self.oids1, self.t1, normalized=True)

skbio/diversity/beta/tests/test_unifrac.py:568: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________________ UnifracTests.test_weighted_unifrac_symmetry __________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_symmetry>

    def test_weighted_unifrac_symmetry(self):
        for i in range(len(self.b1)):
            for j in range(len(self.b1)):
>               actual = weighted_unifrac(
                    self.b1[i], self.b1[j], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:413: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
____________ UnifracTests.test_weighted_unifrac_symmetry_normalized ____________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_symmetry_normalized>

    def test_weighted_unifrac_symmetry_normalized(self):
        for i in range(len(self.b1)):
            for j in range(len(self.b1)):
>               actual = weighted_unifrac(
                    self.b1[i], self.b1[j], self.oids1, self.t1,
                    normalized=True)

skbio/diversity/beta/tests/test_unifrac.py:525: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________________ UnifracTests.test_weighted_unifrac_zero_counts ________________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_zero_counts>

    def test_weighted_unifrac_zero_counts(self):
>       actual = weighted_unifrac(
            [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], self.oids1, self.t1)

skbio/diversity/beta/tests/test_unifrac.py:430: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
__________ UnifracTests.test_weighted_unifrac_zero_counts_normalized ___________

self = <skbio.diversity.beta.tests.test_unifrac.UnifracTests testMethod=test_weighted_unifrac_zero_counts_normalized>

    def test_weighted_unifrac_zero_counts_normalized(self):
        # expected results derived from QIIME 1.9.1, which
        # is a completely different implementation skbio's initial
        # weighted unifrac implementation
>       actual = weighted_unifrac(
            [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], self.oids1, self.t1,
            normalized=True)

skbio/diversity/beta/tests/test_unifrac.py:549: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/beta/_unifrac.py:280: in weighted_unifrac
    _setup_pairwise_unifrac(u_counts, v_counts, otu_ids, tree, validate,
skbio/diversity/beta/_unifrac.py:315: in _setup_pairwise_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_______________ ParallelBetaDiversity.test_block_beta_diversity ________________

self = <skbio.diversity.tests.test_block.ParallelBetaDiversity testMethod=test_block_beta_diversity>

    def test_block_beta_diversity(self):
>       exp = beta_diversity('unweighted_unifrac', self.table1, self.sids1,
                             tree=self.tree1, otu_ids=self.oids1)

skbio/diversity/tests/test_block.py:118: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:354: in beta_diversity
    metric, counts_by_node = _setup_multiple_unweighted_unifrac(
skbio/diversity/beta/_unifrac.py:485: in _setup_multiple_unweighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________________________ AlphaDiversityTests.test_empty ________________________

self = <skbio.diversity.tests.test_driver.AlphaDiversityTests testMethod=test_empty>

    def test_empty(self):
        # empty vector
        actual = alpha_diversity('observed_otus', np.array([], dtype=np.int64))
        expected = pd.Series([0])
        assert_series_almost_equal(actual, expected)
    
        # array of empty vector
        actual = alpha_diversity('observed_otus',
                                 np.array([[]], dtype=np.int64))
        expected = pd.Series([0])
        assert_series_almost_equal(actual, expected)
    
        # array of empty vectors
        actual = alpha_diversity('observed_otus',
                                 np.array([[], []], dtype=np.int64))
        expected = pd.Series([0, 0])
        assert_series_almost_equal(actual, expected)
    
        # empty vector
>       actual = alpha_diversity('faith_pd', np.array([], dtype=np.int64),
                                 tree=self.tree1, otu_ids=[])

skbio/diversity/tests/test_driver.py:175: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:169: in alpha_diversity
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
______________________ AlphaDiversityTests.test_faith_pd _______________________

self = <skbio.diversity.tests.test_driver.AlphaDiversityTests testMethod=test_faith_pd>

    def test_faith_pd(self):
        # calling faith_pd through alpha_diversity gives same results as
        # calling it directly
        expected = []
        for e in self.table1:
>           expected.append(faith_pd(e, tree=self.tree1, otu_ids=self.oids1))

skbio/diversity/tests/test_driver.py:235: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/alpha/_faith_pd.py:122: in faith_pd
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_____________________ AlphaDiversityTests.test_input_types _____________________

self = <skbio.diversity.tests.test_driver.AlphaDiversityTests testMethod=test_input_types>

    def test_input_types(self):
        list_result = alpha_diversity('observed_otus', [1, 3, 0, 1, 0])
        array_result = alpha_diversity('observed_otus',
                                       np.array([1, 3, 0, 1, 0]))
        self.assertAlmostEqual(list_result[0], 3)
        assert_series_almost_equal(list_result, array_result)
    
>       list_result = alpha_diversity('faith_pd', [1, 3, 0, 1, 0],
                                      tree=self.tree1, otu_ids=self.oids1)

skbio/diversity/tests/test_driver.py:210: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:169: in alpha_diversity
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
____________________ AlphaDiversityTests.test_invalid_input ____________________

self = <skbio.diversity.tests.test_driver.AlphaDiversityTests testMethod=test_invalid_input>

    def test_invalid_input(self):
        # number of ids doesn't match the number of samples
        self.assertRaises(ValueError, alpha_diversity, 'observed_otus',
                          self.table1, list('ABC'))
    
        # unknown metric provided
        self.assertRaises(ValueError, alpha_diversity, 'not-a-metric',
                          self.table1)
    
        # 3-D list provided as input
        self.assertRaises(ValueError, alpha_diversity, 'observed_otus',
                          [[[43]]])
    
        # negative counts
        self.assertRaises(ValueError, alpha_diversity, 'observed_otus',
                          [0, 3, -12, 42])
    
        # additional kwargs
        self.assertRaises(TypeError, alpha_diversity, 'observed_otus',
                          [0, 1], not_a_real_kwarg=42.0)
>       self.assertRaises(TypeError, alpha_diversity, 'faith_pd',
                          [0, 1], tree=self.tree1, otu_ids=['OTU1', 'OTU2'],
                          not_a_real_kwarg=42.0)

skbio/diversity/tests/test_driver.py:68: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:169: in alpha_diversity
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
______________________ AlphaDiversityTests.test_optimized ______________________

self = <skbio.diversity.tests.test_driver.AlphaDiversityTests testMethod=test_optimized>

    def test_optimized(self):
        # calling optimized faith_pd gives same results as calling unoptimized
        # version
>       optimized = alpha_diversity('faith_pd', self.table1, tree=self.tree1,
                                    otu_ids=self.oids1)

skbio/diversity/tests/test_driver.py:259: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:169: in alpha_diversity
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________________ AlphaDiversityTests.test_single_count_vector _________________

self = <skbio.diversity.tests.test_driver.AlphaDiversityTests testMethod=test_single_count_vector>

    def test_single_count_vector(self):
        actual = alpha_diversity('observed_otus', np.array([1, 0, 2]))
        expected = pd.Series([2])
        assert_series_almost_equal(actual, expected)
    
>       actual = alpha_diversity('faith_pd', np.array([1, 3, 0, 1, 0]),
                                 tree=self.tree1, otu_ids=self.oids1)

skbio/diversity/tests/test_driver.py:199: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:169: in alpha_diversity
    counts_by_node, branch_lengths = _setup_faith_pd(
skbio/diversity/alpha/_faith_pd.py:139: in _setup_faith_pd
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
__________________ BetaDiversityTests.test_alt_pairwise_func ___________________

self = <skbio.diversity.tests.test_driver.BetaDiversityTests testMethod=test_alt_pairwise_func>

    def test_alt_pairwise_func(self):
        # confirm that pairwise_func is actually being used
        def not_a_real_pdist(counts, metric):
            return [[0.0, 42.0], [42.0, 0.0]]
>       dm1 = beta_diversity('unweighted_unifrac', self.table1,
                             otu_ids=self.oids1, tree=self.tree1,
                             pairwise_func=not_a_real_pdist)

skbio/diversity/tests/test_driver.py:601: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:354: in beta_diversity
    metric, counts_by_node = _setup_multiple_unweighted_unifrac(
skbio/diversity/beta/_unifrac.py:485: in _setup_multiple_unweighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
____________________ BetaDiversityTests.test_invalid_input _____________________

self = <skbio.diversity.tests.test_driver.BetaDiversityTests testMethod=test_invalid_input>

    def test_invalid_input(self):
        # number of ids doesn't match the number of samples
        error_msg = (r"Number of rows")
        with self.assertRaisesRegex(ValueError, error_msg):
            beta_diversity(self.table1, list('AB'), 'euclidean')
    
        # unknown metric provided
        error_msg = r"not-a-metric"
        with self.assertRaisesRegex(ValueError, error_msg):
            beta_diversity('not-a-metric', self.table1)
    
        # 3-D list provided as input
        error_msg = (r"Only 1-D and 2-D")
        with self.assertRaisesRegex(ValueError, error_msg):
            beta_diversity('euclidean', [[[43]]])
    
        # negative counts
        error_msg = r"negative values."
        with self.assertRaisesRegex(ValueError, error_msg):
            beta_diversity('euclidean', [[0, 1, 3, 4], [0, 3, -12, 42]])
        with self.assertRaisesRegex(ValueError, error_msg):
            beta_diversity('euclidean', [[0, 1, 3, -4], [0, 3, 12, 42]])
    
        # additional kwargs
        error_msg = r"keyword argument"
        with self.assertRaisesRegex(TypeError, error_msg):
            beta_diversity('euclidean', [[0, 1, 3], [0, 3, 12]],
                           not_a_real_kwarg=42.0)
        with self.assertRaisesRegex(TypeError, error_msg):
>           beta_diversity('unweighted_unifrac', [[0, 1, 3], [0, 3, 12]],
                           not_a_real_kwarg=42.0, tree=self.tree1,
                           otu_ids=['O1', 'O2', 'O3'])

skbio/diversity/tests/test_driver.py:323: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:354: in beta_diversity
    metric, counts_by_node = _setup_multiple_unweighted_unifrac(
skbio/diversity/beta/_unifrac.py:485: in _setup_multiple_unweighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
__________________ BetaDiversityTests.test_unweighted_unifrac __________________

self = <skbio.diversity.tests.test_driver.BetaDiversityTests testMethod=test_unweighted_unifrac>

    def test_unweighted_unifrac(self):
        # TODO: update npt.assert_almost_equal calls to use DistanceMatrix
        # near-equality testing when that support is available
        # expected values calculated by hand
>       dm1 = beta_diversity('unweighted_unifrac', self.table1, self.sids1,
                             otu_ids=self.oids1, tree=self.tree1)

skbio/diversity/tests/test_driver.py:528: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:354: in beta_diversity
    metric, counts_by_node = _setup_multiple_unweighted_unifrac(
skbio/diversity/beta/_unifrac.py:485: in _setup_multiple_unweighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
___________________ BetaDiversityTests.test_weighted_unifrac ___________________

self = <skbio.diversity.tests.test_driver.BetaDiversityTests testMethod=test_weighted_unifrac>

    def test_weighted_unifrac(self):
        # TODO: update npt.assert_almost_equal calls to use DistanceMatrix
        # near-equality testing when that support is available
        # expected values calculated by hand
>       dm1 = beta_diversity('weighted_unifrac', self.table1, self.sids1,
                             otu_ids=self.oids1, tree=self.tree1)

skbio/diversity/tests/test_driver.py:547: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:363: in beta_diversity
    metric, counts_by_node = _setup_multiple_weighted_unifrac(
skbio/diversity/beta/_unifrac.py:521: in _setup_multiple_weighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_____________ BetaDiversityTests.test_weighted_unifrac_normalized ______________

self = <skbio.diversity.tests.test_driver.BetaDiversityTests testMethod=test_weighted_unifrac_normalized>

    def test_weighted_unifrac_normalized(self):
        # TODO: update npt.assert_almost_equal calls to use DistanceMatrix
        # near-equality testing when that support is available
        # expected values calculated by hand
>       dm1 = beta_diversity('weighted_unifrac', self.table1, self.sids1,
                             otu_ids=self.oids1, tree=self.tree1,
                             normalized=True)

skbio/diversity/tests/test_driver.py:567: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_driver.py:363: in beta_diversity
    metric, counts_by_node = _setup_multiple_weighted_unifrac(
skbio/diversity/beta/_unifrac.py:521: in _setup_multiple_weighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
______________ TestPartialBetaDiversity.test_id_pairs_as_iterable ______________

self = <skbio.diversity.tests.test_driver.TestPartialBetaDiversity testMethod=test_id_pairs_as_iterable>

    def test_id_pairs_as_iterable(self):
        id_pairs = iter([('B', 'C'), ])
>       dm = partial_beta_diversity('unweighted_unifrac', self.table1,
                                    self.sids1, otu_ids=self.oids1,
                                    tree=self.tree1, id_pairs=id_pairs)

skbio/diversity/tests/test_driver.py:670: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
<decorator-gen-112>:2: in partial_beta_diversity
    ???
skbio/util/_decorator.py:260: in wrapped_f
    return func(*args[1:], **kwargs)
skbio/diversity/_driver.py:250: in partial_beta_diversity
    metric, counts_by_node = _setup_multiple_unweighted_unifrac(
skbio/diversity/beta/_unifrac.py:485: in _setup_multiple_unweighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
___________ TestPartialBetaDiversity.test_unweighted_unifrac_partial ___________

self = <skbio.diversity.tests.test_driver.TestPartialBetaDiversity testMethod=test_unweighted_unifrac_partial>

    def test_unweighted_unifrac_partial(self):
        # TODO: update npt.assert_almost_equal calls to use DistanceMatrix
        # near-equality testing when that support is available
        # expected values calculated by hand
>       dm = partial_beta_diversity('unweighted_unifrac', self.table1,
                                    self.sids1, otu_ids=self.oids1,
                                    tree=self.tree1, id_pairs=[('B', 'C'), ])

skbio/diversity/tests/test_driver.py:689: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
<decorator-gen-112>:2: in partial_beta_diversity
    ???
skbio/util/_decorator.py:260: in wrapped_f
    return func(*args[1:], **kwargs)
skbio/diversity/_driver.py:250: in partial_beta_diversity
    metric, counts_by_node = _setup_multiple_unweighted_unifrac(
skbio/diversity/beta/_unifrac.py:485: in _setup_multiple_unweighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________ TestPartialBetaDiversity.test_weighted_unifrac_partial_full __________

self = <skbio.diversity.tests.test_driver.TestPartialBetaDiversity testMethod=test_weighted_unifrac_partial_full>

    def test_weighted_unifrac_partial_full(self):
        # TODO: update npt.assert_almost_equal calls to use DistanceMatrix
        # near-equality testing when that support is available
        # expected values calculated by hand
>       dm1 = partial_beta_diversity('weighted_unifrac', self.table1,
                                     self.sids1, otu_ids=self.oids1,
                                     tree=self.tree1, id_pairs=[('A', 'B'),
                                                                ('A', 'C'),
                                                                ('B', 'C')])

skbio/diversity/tests/test_driver.py:706: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
<decorator-gen-112>:2: in partial_beta_diversity
    ???
skbio/util/_decorator.py:260: in wrapped_f
    return func(*args[1:], **kwargs)
skbio/diversity/_driver.py:259: in partial_beta_diversity
    metric, counts_by_node = _setup_multiple_weighted_unifrac(
skbio/diversity/beta/_unifrac.py:521: in _setup_multiple_weighted_unifrac
    _setup_multiple_unifrac(counts, otu_ids, tree, validate)
skbio/diversity/beta/_unifrac.py:452: in _setup_multiple_unifrac
    _vectorize_counts_and_tree(counts, otu_ids, tree)
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
________________ ValidationTests.test_vectorize_counts_and_tree ________________

self = <skbio.diversity.tests.test_util.ValidationTests testMethod=test_vectorize_counts_and_tree>

    def test_vectorize_counts_and_tree(self):
        t = TreeNode.read(io.StringIO("((a:1, b:2)c:3)root;"))
        counts = np.array([[0, 1], [1, 5], [10, 1]])
        count_array, indexed, branch_lengths = \
>           _vectorize_counts_and_tree(counts, np.array(['a', 'b']), t)

skbio/diversity/tests/test_util.py:249: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/diversity/_util.py:126: in _vectorize_counts_and_tree
    counts_by_node = _nodes_by_counts(counts, otu_ids, tree_index)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'DTYPE_t' but got 'int'

skbio/diversity/_phylogenetic.pyx:184: ValueError
_________________________ SnifferTests.test_positives __________________________

self = <skbio.io.format.tests.test_fasta.SnifferTests testMethod=test_positives>

    def test_positives(self):
        for fp in self.positive_fps:
>           self.assertEqual(_fasta_sniffer(fp), (True, {}))
E           AssertionError: Tuples differ: (False, {}) != (True, {})
E           
E           First differing element 0:
E           False
E           True
E           
E           - (False, {})
E           + (True, {})

skbio/io/format/tests/test_fasta.py:153: AssertionError
__________ TestPositionalMetadataMixin.test_eq_from_different_source ___________

self = <skbio.metadata.tests.test_mixin.TestPositionalMetadataMixin testMethod=test_eq_from_different_source>

    def test_eq_from_different_source(self):
        obj1 = self._positional_metadata_constructor_(
            3, positional_metadata={'foo': np.array([1, 2, 3])})
        obj2 = self._positional_metadata_constructor_(
            3, positional_metadata=pd.DataFrame({'foo': [1, 2, 3]},
                                                index=['foo', 'bar', 'baz']))
>       self.assertReallyEqual(obj1, obj2)

skbio/metadata/_testing.py:464: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/util/_testing.py:31: in assertReallyEqual
    self.assertEqual(a, b)
E   AssertionError: <skbi[60 chars]p.<locals>.ExamplePositionalMetadataMixin object at 0xeea333e8> != <skbi[60 chars]p.<locals>.ExamplePositionalMetadataMixin object at 0xeea4f718>
_______________________ TestGrammaredSequence.test_degap _______________________

self = <skbio.sequence.tests.test_grammared_sequence.TestGrammaredSequence testMethod=test_degap>

    def test_degap(self):
        kw = {
            'metadata': {
                'id': 'some_id',
                'description': 'some description',
            },
        }
    
        self.assertEqual(
            ExampleGrammaredSequence(
                "", positional_metadata={'qual': []}, **kw).degap(),
            ExampleGrammaredSequence(
                "", positional_metadata={'qual': []}, **kw))
    
        self.assertEqual(
            ExampleGrammaredSequence(
                "ABCXYZ",
                positional_metadata={'qual': np.arange(6)},
                **kw).degap(),
            ExampleGrammaredSequence(
                "ABCXYZ",
                positional_metadata={'qual': np.arange(6)},
                **kw))
    
>       self.assertEqual(
            ExampleGrammaredSequence(
                "ABC-XYZ",
                positional_metadata={'qual': np.arange(7)},
                **kw).degap(),
            ExampleGrammaredSequence(
                "ABCXYZ",
                positional_metadata={'qual': [0, 1, 2, 4, 5, 6]},
                **kw))
E       AssertionError: Examp[165 chars]: int32>
E       Stats:
E           length: 6
E           has gaps: Fa[95 chars]BCXYZ != Examp[165 chars]: int64>
E       Stats:
E           length: 6
E           has gaps: Fa[95 chars]BCXYZ

skbio/sequence/tests/test_grammared_sequence.py:525: AssertionError
_________ TestSequencePositionalMetadata.test_eq_from_different_source _________

self = <skbio.sequence.tests.test_sequence.TestSequencePositionalMetadata testMethod=test_eq_from_different_source>

    def test_eq_from_different_source(self):
        obj1 = self._positional_metadata_constructor_(
            3, positional_metadata={'foo': np.array([1, 2, 3])})
        obj2 = self._positional_metadata_constructor_(
            3, positional_metadata=pd.DataFrame({'foo': [1, 2, 3]},
                                                index=['foo', 'bar', 'baz']))
>       self.assertReallyEqual(obj1, obj2)

skbio/metadata/_testing.py:464: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/util/_testing.py:31: in assertReallyEqual
    self.assertEqual(a, b)
E   AssertionError: Seque[66 chars]pe: int32>
E   Stats:
E       length: 3
E   -------------------------
E   0 ZZZ != Seque[66 chars]pe: int64>
E   Stats:
E       length: 3
E   -------------------------
E   0 ZZZ
_____ TestSequence.test_eq_sequences_from_different_sources_compare_equal ______

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_eq_sequences_from_different_sources_compare_equal>

    def test_eq_sequences_from_different_sources_compare_equal(self):
        # sequences that have the same data but are constructed from different
        # types of data should compare equal
        im = IntervalMetadata(4)
        im.add([(0, 2)], metadata={'gene': 'sagB'})
        seq1 = Sequence('ACGT', metadata={'id': 'foo', 'desc': 'abc'},
                        positional_metadata={'quality': (1, 2, 3, 4)},
                        interval_metadata=im)
        seq2 = Sequence(np.array([65, 67, 71, 84], dtype=np.uint8),
                        metadata={'id': 'foo', 'desc': 'abc'},
                        positional_metadata={'quality': np.array([1, 2, 3,
                                                                  4])},
                        interval_metadata=im)
>       self.assertTrue(seq1 == seq2)
E       AssertionError: False is not true

skbio/sequence/tests/test_sequence.py:622: AssertionError
____________ TestSequence.test_getitem_with_boolean_vector_has_qual ____________

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_getitem_with_boolean_vector_has_qual>

    def test_getitem_with_boolean_vector_has_qual(self):
        s = "0123456789abcdef"
        length = len(s)
        seq = Sequence(s, metadata={'id': 'id11', 'description': 'dsc11'},
                       positional_metadata={'quality': np.arange(length)})
    
        eseq = Sequence("13579bdf",
                        metadata={'id': 'id11', 'description': 'dsc11'},
                        positional_metadata={'quality': [1, 3, 5, 7, 9, 11,
                                                         13, 15]})
    
>       self.assertEqual(seq[np.array([False, True] * 8)], eseq)
E       AssertionError: Seque[130 chars]: int32>
E       Stats:
E           length: 8
E       ----------------[19 chars]79bdf != Seque[130 chars]: int64>
E       Stats:
E           length: 8
E       ----------------[19 chars]79bdf

skbio/sequence/tests/test_sequence.py:932: AssertionError
__________ TestSequence.test_getitem_with_int_has_positional_metadata __________

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_getitem_with_int_has_positional_metadata>

    def test_getitem_with_int_has_positional_metadata(self):
        s = "Sequence string !1@2#3?.,"
        length = len(s)
        seq = Sequence(s, metadata={'id': 'id', 'description': 'dsc'},
                       positional_metadata={'quality': np.arange(length)})
    
        eseq = Sequence("S", {'id': 'id', 'description': 'dsc'},
                        positional_metadata={'quality': np.array([0])})
        self.assertEqual(seq[0], eseq)
    
        eseq = Sequence(",", metadata={'id': 'id', 'description': 'dsc'},
                        positional_metadata={'quality':
                                             np.array([len(seq) - 1])})
        self.assertEqual(seq[len(seq) - 1], eseq)
    
        eseq = Sequence("t", metadata={'id': 'id', 'description': 'dsc'},
                        positional_metadata={'quality': [10]})
>       self.assertEqual(seq[10], eseq)
E       AssertionError: Seque[126 chars]: int32>
E       Stats:
E           length: 1
E       -----------------------------
E       0 t != Seque[126 chars]: int64>
E       Stats:
E           length: 1
E       -----------------------------
E       0 t

skbio/sequence/tests/test_sequence.py:689: AssertionError
___ TestSequence.test_getitem_with_iterable_of_mixed_has_positional_metadata ___

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_getitem_with_iterable_of_mixed_has_positional_metadata>

    def test_getitem_with_iterable_of_mixed_has_positional_metadata(self):
        s = "0123456789abcdef"
        length = len(s)
        seq = Sequence(s, metadata={'id': 'id7', 'description': 'dsc7'},
                       positional_metadata={'quality': np.arange(length)})
    
        def generator():
            yield slice(0, 4)
            yield slice(200, 400)
            yield -1
            yield slice(-2, -4, -1)
            yield 9
    
        eseq = Sequence("0123fed9",
                        metadata={'id': 'id7', 'description': 'dsc7'},
                        positional_metadata={'quality': [0, 1, 2, 3, 15, 14,
                                                         13, 9]})
>       self.assertEqual(seq[[0, 1, 2, 3, 15, 14, 13, 9]], eseq)
E       AssertionError: Seque[128 chars]: int32>
E       Stats:
E           length: 8
E       ----------------[19 chars]3fed9 != Seque[128 chars]: int64>
E       Stats:
E           length: 8
E       ----------------[19 chars]3fed9

skbio/sequence/tests/test_sequence.py:853: AssertionError
______ TestSequence.test_getitem_with_numpy_index_has_positional_metadata ______

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_getitem_with_numpy_index_has_positional_metadata>

    def test_getitem_with_numpy_index_has_positional_metadata(self):
        s = "0123456789abcdef"
        length = len(s)
        seq = Sequence(s, metadata={'id': 'id9', 'description': 'dsc9'},
                       positional_metadata={'quality': np.arange(length)})
    
        eseq = Sequence("0123fed9",
                        metadata={'id': 'id9', 'description': 'dsc9'},
                        positional_metadata={'quality': [0, 1, 2, 3, 15, 14,
                                                         13, 9]})
>       self.assertEqual(seq[np.array([0, 1, 2, 3, 15, 14, 13, 9])], eseq)
E       AssertionError: Seque[128 chars]: int32>
E       Stats:
E           length: 8
E       ----------------[19 chars]3fed9 != Seque[128 chars]: int64>
E       Stats:
E           length: 8
E       ----------------[19 chars]3fed9

skbio/sequence/tests/test_sequence.py:887: AssertionError
_________ TestSequence.test_getitem_with_slice_has_positional_metadata _________

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_getitem_with_slice_has_positional_metadata>

    def test_getitem_with_slice_has_positional_metadata(self):
        s = "0123456789abcdef"
        length = len(s)
        seq = Sequence(s, metadata={'id': 'id3', 'description': 'dsc3'},
                       positional_metadata={'quality': np.arange(length)})
    
        eseq = Sequence("012", metadata={'id': 'id3', 'description': 'dsc3'},
                        positional_metadata={'quality': np.arange(3)})
        self.assertEqual(seq[0:3], eseq)
        self.assertEqual(seq[:3], eseq)
        self.assertEqual(seq[:3:1], eseq)
    
        eseq = Sequence("def", metadata={'id': 'id3', 'description': 'dsc3'},
                        positional_metadata={'quality': [13, 14, 15]})
>       self.assertEqual(seq[-3:], eseq)
E       AssertionError: Seque[128 chars]: int32>
E       Stats:
E           length: 3
E       ----------------[14 chars]0 def != Seque[128 chars]: int64>
E       Stats:
E           length: 3
E       ----------------[14 chars]0 def

skbio/sequence/tests/test_sequence.py:747: AssertionError
____ TestSequence.test_getitem_with_tuple_of_mixed_with_positional_metadata ____

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_getitem_with_tuple_of_mixed_with_positional_metadata>

    def test_getitem_with_tuple_of_mixed_with_positional_metadata(self):
        s = "0123456789abcdef"
        length = len(s)
        seq = Sequence(s, metadata={'id': 'id5', 'description': 'dsc5'},
                       positional_metadata={'quality': np.arange(length)})
    
        eseq = Sequence("00000", metadata={'id': 'id5', 'description': 'dsc5'},
                        positional_metadata={'quality': [0, 0, 0, 0, 0]})
>       self.assertEqual(seq[0, 0, 0, 0, 0], eseq)
E       AssertionError: Seque[128 chars]: int32>
E       Stats:
E           length: 5
E       ----------------[16 chars]00000 != Seque[128 chars]: int64>
E       Stats:
E           length: 5
E       ----------------[16 chars]00000

skbio/sequence/tests/test_sequence.py:803: AssertionError
___________________ TestSequence.test_init_invalid_sequence ____________________
TypeError: Can cannot create a sequence with 'int32'

During handling of the above exception, another exception occurred:

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_init_invalid_sequence>

    def test_init_invalid_sequence(self):
        # invalid dtype (numpy.ndarray input)
        with self.assertRaises(TypeError):
            # int64
            Sequence(np.array([1, 2, 3]))
        with self.assertRaises(TypeError):
            # |S21
            Sequence(np.array([1, "23", 3]))
        with self.assertRaises(TypeError):
            # object
            Sequence(np.array([1, {}, ()]))
    
        # invalid input type (non-numpy.ndarray input)
        with self.assertRaisesRegex(TypeError, r'tuple'):
            Sequence(('a', 'b', 'c'))
        with self.assertRaisesRegex(TypeError, r'list'):
            Sequence(['a', 'b', 'c'])
        with self.assertRaisesRegex(TypeError, r'set'):
            Sequence({'a', 'b', 'c'})
        with self.assertRaisesRegex(TypeError, r'dict'):
            Sequence({'a': 42, 'b': 43, 'c': 44})
        with self.assertRaisesRegex(TypeError, r'int'):
            Sequence(42)
        with self.assertRaisesRegex(TypeError, r'float'):
            Sequence(4.2)
        with self.assertRaisesRegex(TypeError, r'int64'):
>           Sequence(np.int_(50))
E           AssertionError: "int64" does not match "Can cannot create a sequence with 'int32'"

skbio/sequence/tests/test_sequence.py:477: AssertionError
________________ TestSequence.test_iter_has_positional_metadata ________________

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_iter_has_positional_metadata>

    def test_iter_has_positional_metadata(self):
        tested = False
        seq = Sequence("0123456789", metadata={'id': 'a', 'desc': 'b'},
                       positional_metadata={'qual': np.arange(10)})
        for i, s in enumerate(seq):
            tested = True
>           self.assertEqual(s, Sequence(str(i),
                                         metadata={'id': 'a', 'desc': 'b'},
                                         positional_metadata={'qual': [i]}))
E           AssertionError: Seque[107 chars]ype: int32>
E           Stats:
E               length: 1
E           --------------------------
E           0 0 != Seque[107 chars]ype: int64>
E           Stats:
E               length: 1
E           --------------------------
E           0 0

skbio/sequence/tests/test_sequence.py:1036: AssertionError
______________ TestSequence.test_reversed_has_positional_metadata ______________

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_reversed_has_positional_metadata>

    def test_reversed_has_positional_metadata(self):
        tested = False
        seq = Sequence("0123456789", metadata={'id': 'a', 'desc': 'b'},
                       positional_metadata={'qual': np.arange(10)})
        for i, s in enumerate(reversed(seq)):
            tested = True
>           self.assertEqual(s, Sequence(str(9 - i),
                                         metadata={'id': 'a', 'desc': 'b'},
                                         positional_metadata={'qual':
                                                              [9 - i]}))
E           AssertionError: Seque[107 chars]ype: int32>
E           Stats:
E               length: 1
E           --------------------------
E           0 9 != Seque[107 chars]ype: int64>
E           Stats:
E               length: 1
E           --------------------------
E           0 9

skbio/sequence/tests/test_sequence.py:1056: AssertionError
_________________ TestSequence.test_slice_positional_metadata __________________

self = <skbio.sequence.tests.test_sequence.TestSequence testMethod=test_slice_positional_metadata>

    def test_slice_positional_metadata(self):
        seq = Sequence('ABCDEFGHIJ',
                       positional_metadata={'foo': np.arange(10),
                                            'bar': np.arange(100, 110)})
>       self.assertTrue(pd.DataFrame({'foo': [0], 'bar': [100]}).equals(
                        seq._slice_positional_metadata(0)))
E       AssertionError: False is not true

skbio/sequence/tests/test_sequence.py:715: AssertionError
_________________ BIOENVTests.test_bioenv_all_columns_explicit _________________

self = <skbio.stats.distance.tests.test_bioenv.BIOENVTests testMethod=test_bioenv_all_columns_explicit>

    def test_bioenv_all_columns_explicit(self):
        # Test with all columns being specified.
        obs = bioenv(self.dm, self.df, columns=self.cols)
>       assert_data_frame_almost_equal(obs, self.exp_results)

skbio/stats/distance/tests/test_bioenv.py:102: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =                                                     size  correlation
vars                                            ...LAY, ELEVATION, SOIL_MOISTU...    10     0.607143
TOT_ORG_CARB, SILT_CLAY, ELEVATION, SOIL_MOISTU...    11     0.539286
right =                                                     size  correlation
vars                                            ...LAY, ELEVATION, SOIL_MOISTU...    10     0.607143
TOT_ORG_CARB, SILT_CLAY, ELEVATION, SOIL_MOISTU...    11     0.539286

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 0] (column name="size") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
_________________ BIOENVTests.test_bioenv_all_columns_implicit _________________

self = <skbio.stats.distance.tests.test_bioenv.BIOENVTests testMethod=test_bioenv_all_columns_implicit>

    def test_bioenv_all_columns_implicit(self):
        # Test with all columns in data frame (implicitly).
        obs = bioenv(self.dm, self.df)
>       assert_data_frame_almost_equal(obs, self.exp_results)

skbio/stats/distance/tests/test_bioenv.py:92: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =                                                     size  correlation
vars                                            ...LAY, ELEVATION, SOIL_MOISTU...    10     0.607143
TOT_ORG_CARB, SILT_CLAY, ELEVATION, SOIL_MOISTU...    11     0.539286
right =                                                     size  correlation
vars                                            ...LAY, ELEVATION, SOIL_MOISTU...    10     0.607143
TOT_ORG_CARB, SILT_CLAY, ELEVATION, SOIL_MOISTU...    11     0.539286

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 0] (column name="size") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
________________ BIOENVTests.test_bioenv_different_column_order ________________

self = <skbio.stats.distance.tests.test_bioenv.BIOENVTests testMethod=test_bioenv_different_column_order>

    def test_bioenv_different_column_order(self):
        # Specifying columns in a different order will change the row labels in
        # the results data frame as the column subsets will be reordered, but
        # the actual results (e.g., correlation coefficients) shouldn't change.
        obs = bioenv(self.dm, self.df, columns=self.cols[::-1])
>       assert_data_frame_almost_equal(
            obs,
            self.exp_results_different_column_order)

skbio/stats/distance/tests/test_bioenv.py:119: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =                                                     size  correlation
vars                                            ... PH, ANNUAL_SEASON_PRECPT, ...    10     0.607143
LATITUDE, LONGITUDE, CMIN_RATE, PH, ANNUAL_SEAS...    11     0.539286
right =                                                     size  correlation
vars                                            ... PH, ANNUAL_SEASON_PRECPT, ...    10     0.607143
LATITUDE, LONGITUDE, CMIN_RATE, PH, ANNUAL_SEAS...    11     0.539286

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 0] (column name="size") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
____________________ BIOENVTests.test_bioenv_single_column _____________________

self = <skbio.stats.distance.tests.test_bioenv.BIOENVTests testMethod=test_bioenv_single_column>

    def test_bioenv_single_column(self):
        obs = bioenv(self.dm, self.df, columns=['PH'])
>       assert_data_frame_almost_equal(obs, self.exp_results_single_column)

skbio/stats/distance/tests/test_bioenv.py:112: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =       size  correlation
vars                   
PH       1         0.75
right =       size  correlation
vars                   
PH       1         0.75

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 0] (column name="size") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
____________________ BIOENVTests.test_bioenv_vegan_example _____________________

self = <skbio.stats.distance.tests.test_bioenv.BIOENVTests testMethod=test_bioenv_vegan_example>

    def test_bioenv_vegan_example(self):
        # The correlation coefficient in the first row of the
        # results (rho=0.2516) is different from the correlation coefficient
        # computed by vegan (rho=0.2513). This seems to occur due to
        # differences in numerical precision when calculating the Euclidean
        # distances, which affects the rank calculations in Spearman
        # (specifically, dealing with ties). The ranked distances end up being
        # slightly different between vegan and our implementation because some
        # distances are treated as ties in vegan but treated as distinct values
        # in our implementation. This explains the difference in rho values. I
        # verified that using Pearson correlation instead of Spearman on the
        # same distances yields *very* similar results. Thus, the discrepancy
        # seems to stem from differences when computing ranks/ties.
        obs = bioenv(self.dm_vegan, self.df_vegan)
>       assert_data_frame_almost_equal(obs, self.exp_results_vegan)

skbio/stats/distance/tests/test_bioenv.py:149: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =                           size  correlation
vars                                       
P                            1...l                4     0.361875
log(N), P, Ca, pH, Al        5     0.321552
log(N), P, K, Ca, pH, Al     6     0.282181
right =                           size  correlation
vars                                       
P                            1...l                4     0.361875
log(N), P, Ca, pH, Al        5     0.321552
log(N), P, K, Ca, pH, Al     6     0.282181

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 0] (column name="size") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
____________________ PairwiseMantelTests.test_duplicate_dms ____________________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_duplicate_dms>

    def test_duplicate_dms(self):
        obs = pwmantel((self.minx_dm, self.minx_dm, self.minx_dm),
                       alternative='less')
>       assert_data_frame_almost_equal(obs, self.exp_results_duplicate_dms)

skbio/stats/distance/tests/test_mantel.py:376: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...   1.0      1.0  3  pearson           999        less
1   2          1.0      1.0  3  pearson           999        less
right =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...   1.0      1.0  3  pearson           999        less
1   2          1.0      1.0  3  pearson           999        less

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
_________________ PairwiseMantelTests.test_filepaths_as_input __________________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_filepaths_as_input>

    def test_filepaths_as_input(self):
        dms = [
            get_data_path('dm.txt'),
            get_data_path('dm2.txt'),
        ]
        np.random.seed(0)
    
        obs = pwmantel(dms)
>       assert_data_frame_almost_equal(obs, self.exp_results_dm_dm2)

skbio/stats/distance/tests/test_mantel.py:465: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                                          
0   1     0.702031    0.001  6  pearson           999   two-sided
right =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                                          
0   1     0.702031    0.001  6  pearson           999   two-sided

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
______________________ PairwiseMantelTests.test_id_lookup ______________________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_id_lookup>

    def test_id_lookup(self):
        # Matrices have mismatched IDs but a lookup is provided.
        self.minx_dm_extra.ids = ['a', 'b', 'c', 'foo']
        self.minz_dm_extra.ids = ['d', 'e', 'f', 'bar']
        lookup = {'a': '0', 'b': '1', 'c': '2', 'foo': 'foo',
                  'd': '0', 'e': '1', 'f': '2', 'bar': 'bar',
                  '0': '0', '1': '1', '2': '2'}
    
        x = self.minx_dm_extra.filter(['b', 'a', 'foo', 'c'])
        y = self.miny_dm.filter(['0', '2', '1'])
        z = self.minz_dm_extra.filter(['bar', 'e', 'f', 'd'])
    
        x_copy = x.copy()
        y_copy = y.copy()
        z_copy = z.copy()
    
        np.random.seed(0)
    
        obs = pwmantel((x, y, z), alternative='greater', strict=False,
                       lookup=lookup)
>       assert_data_frame_almost_equal(
            obs,
            self.exp_results_reordered_distance_matrices)

skbio/stats/distance/tests/test_mantel.py:431: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...989743    1.000  3  pearson           999     greater
1   2    -0.841698    0.822  3  pearson           999     greater
right =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...989743    1.000  3  pearson           999     greater
1   2    -0.841698    0.822  3  pearson           999     greater

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
_______________ PairwiseMantelTests.test_many_filepaths_as_input _______________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_many_filepaths_as_input>

    def test_many_filepaths_as_input(self):
        dms = [
            get_data_path('dm2.txt'),
            get_data_path('dm.txt'),
            get_data_path('dm4.txt'),
            get_data_path('dm3.txt')
        ]
        np.random.seed(0)
    
        obs = pwmantel(dms)
>       assert_data_frame_almost_equal(obs, self.exp_results_all_dms)

skbio/stats/distance/tests/test_mantel.py:477: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...920688    0.004  6  pearson           999   two-sided
2   3     0.717297    0.003  6  pearson           999   two-sided
right =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...920688    0.004  6  pearson           999   two-sided
2   3     0.717297    0.003  6  pearson           999   two-sided

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
______________ PairwiseMantelTests.test_minimal_compatible_input _______________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_minimal_compatible_input>

    def test_minimal_compatible_input(self):
        # Matrices are already in the correct order and have matching IDs.
        np.random.seed(0)
    
        # input as DistanceMatrix instances
        obs = pwmantel(self.min_dms, alternative='greater')
>       assert_data_frame_almost_equal(obs, self.exp_results_minimal)

skbio/stats/distance/tests/test_mantel.py:355: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...989743    1.000  3  pearson           999     greater
1   2    -0.841698    0.835  3  pearson           999     greater
right =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...989743    1.000  3  pearson           999     greater
1   2    -0.841698    0.835  3  pearson           999     greater

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
________ PairwiseMantelTests.test_minimal_compatible_input_with_labels _________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_minimal_compatible_input_with_labels>

    def test_minimal_compatible_input_with_labels(self):
        np.random.seed(0)
    
        obs = pwmantel(self.min_dms, alternative='greater',
                       labels=('minx', 'miny', 'minz'))
>       assert_data_frame_almost_equal(
            obs,
            self.exp_results_minimal_with_labels)

skbio/stats/distance/tests/test_mantel.py:369: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =            statistic  p-value  n   method  permutations alternative
dm1  dm2                                          ...9743    1.000  3  pearson           999     greater
miny minz  -0.841698    0.835  3  pearson           999     greater
right =            statistic  p-value  n   method  permutations alternative
dm1  dm2                                          ...9743    1.000  3  pearson           999     greater
miny minz  -0.841698    0.835  3  pearson           999     greater

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
_____________________ PairwiseMantelTests.test_na_p_value ______________________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_na_p_value>

    def test_na_p_value(self):
        obs = pwmantel((self.miny_dm, self.minx_dm), method='spearman',
                       permutations=0)
>       assert_data_frame_almost_equal(obs, self.exp_results_na_p_value)

skbio/stats/distance/tests/test_mantel.py:381: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =          statistic  p-value  n    method  permutations alternative
dm1 dm2                                                           
0   1          0.5      NaN  3  spearman             0   two-sided
right =          statistic  p-value  n    method  permutations alternative
dm1 dm2                                                           
0   1          0.5      NaN  3  spearman             0   two-sided

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
_____________ PairwiseMantelTests.test_reordered_distance_matrices _____________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_reordered_distance_matrices>

    def test_reordered_distance_matrices(self):
        # Matrices have matching IDs but they all have different ordering.
        x = self.minx_dm.filter(['1', '0', '2'])
        y = self.miny_dm.filter(['0', '2', '1'])
        z = self.minz_dm.filter(['1', '2', '0'])
    
        np.random.seed(0)
    
        obs = pwmantel((x, y, z), alternative='greater')
>       assert_data_frame_almost_equal(
            obs,
            self.exp_results_reordered_distance_matrices)

skbio/stats/distance/tests/test_mantel.py:392: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...989743    1.000  3  pearson           999     greater
1   2    -0.841698    0.822  3  pearson           999     greater
right =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...989743    1.000  3  pearson           999     greater
1   2    -0.841698    0.822  3  pearson           999     greater

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
_______________________ PairwiseMantelTests.test_strict ________________________

self = <skbio.stats.distance.tests.test_mantel.PairwiseMantelTests testMethod=test_strict>

    def test_strict(self):
        # Matrices have some matching and nonmatching IDs, with different
        # ordering.
        x = self.minx_dm_extra.filter(['1', '0', 'foo', '2'])
        y = self.miny_dm.filter(['0', '2', '1'])
        z = self.minz_dm_extra.filter(['bar', '1', '2', '0'])
    
        np.random.seed(0)
    
        # strict=False should discard IDs that aren't found in both matrices
        obs = pwmantel((x, y, z), alternative='greater', strict=False)
>       assert_data_frame_almost_equal(
            obs,
            self.exp_results_reordered_distance_matrices)

skbio/stats/distance/tests/test_mantel.py:407: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

left =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...989743    1.000  3  pearson           999     greater
1   2    -0.841698    0.822  3  pearson           999     greater
right =          statistic  p-value  n   method  permutations alternative
dm1 dm2                                             ...989743    1.000  3  pearson           999     greater
1   2    -0.841698    0.822  3  pearson           999     greater

    @experimental(as_of="0.4.0")
    def assert_data_frame_almost_equal(left, right):
        """Raise AssertionError if ``pd.DataFrame`` objects are not "almost equal".
    
        Wrapper of ``pd.util.testing.assert_frame_equal``. Floating point values
        are considered "almost equal" if they are within a threshold defined by
        ``assert_frame_equal``. This wrapper uses a number of
        checks that are turned off by default in ``assert_frame_equal`` in order to
        perform stricter comparisons (for example, ensuring the index and column
        types are the same). It also does not consider empty ``pd.DataFrame``
        objects equal if they have a different index.
    
        Other notes:
    
        * Index (row) and column ordering must be the same for objects to be equal.
        * NaNs (``np.nan``) in the same locations are considered equal.
    
        This is a helper function intended to be used in unit tests that need to
        compare ``pd.DataFrame`` objects.
    
        Parameters
        ----------
        left, right : pd.DataFrame
            ``pd.DataFrame`` objects to compare.
    
        Raises
        ------
        AssertionError
            If `left` and `right` are not "almost equal".
    
        See Also
        --------
        pandas.util.testing.assert_frame_equal
    
        """
        # pass all kwargs to ensure this function has consistent behavior even if
        # `assert_frame_equal`'s defaults change
>       pdt.assert_frame_equal(left, right,
                               check_dtype=True,
                               check_index_type=True,
                               check_column_type=True,
                               check_frame_type=True,
                               check_less_precise=False,
                               check_names=True,
                               by_blocks=False,
                               check_exact=False)
E       AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="n") are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

skbio/util/_testing.py:304: AssertionError
_____________ SubsampleCountsTests.test_subsample_counts_nonrandom _____________

self = <skbio.stats.tests.test_subsample.SubsampleCountsTests testMethod=test_subsample_counts_nonrandom>

    def test_subsample_counts_nonrandom(self):
        a = np.array([0, 5, 0])
    
        # Subsample same number of items that are in input (without
        # replacement).
        npt.assert_equal(subsample_counts(a, 5), a)
    
        # Can only choose from one bin.
        exp = np.array([0, 2, 0])
>       npt.assert_equal(subsample_counts(a, 2), exp)

skbio/stats/tests/test_subsample.py:38: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/stats/_subsample.py:246: in subsample_counts
    result = _subsample_counts_without_replacement(counts, n,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'int64_t' but got 'long'

skbio/stats/__subsample.pyx:13: ValueError
________ SubsampleCountsTests.test_subsample_counts_without_replacement ________

self = <skbio.stats.tests.test_subsample.SubsampleCountsTests testMethod=test_subsample_counts_without_replacement>

    def test_subsample_counts_without_replacement(self):
        # Selecting 2 counts from the vector 1000 times yields each of the two
        # possible results at least once each.
        a = np.array([2, 0, 1])
        actual = set()
        for i in range(1000):
>           obs = subsample_counts(a, 2)

skbio/stats/tests/test_subsample.py:54: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
skbio/stats/_subsample.py:246: in subsample_counts
    result = _subsample_counts_without_replacement(counts, n,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: Buffer dtype mismatch, expected 'int64_t' but got 'long'

skbio/stats/__subsample.pyx:13: ValueError
____________________ ISubsampleTests.test_isubsample_simple ____________________

self = <skbio.stats.tests.test_subsample.ISubsampleTests testMethod=test_isubsample_simple>

    def test_isubsample_simple(self):
        maximum = 10
    
        def bin_f(x):
            return x['SequenceID'].rsplit('_', 1)[0]
    
        # note, the result here is sorted by sequence_id but is in heap order
        # by the random values associated to each sequence
        exp = sorted([('a', {'SequenceID': 'a_5', 'Sequence': 'AATTGGCC-a5'}),
                      ('a', {'SequenceID': 'a_1', 'Sequence': 'AATTGGCC-a1'}),
                      ('a', {'SequenceID': 'a_4', 'Sequence': 'AATTGGCC-a4'}),
                      ('a', {'SequenceID': 'a_3', 'Sequence': 'AATTGGCC-a3'}),
                      ('a', {'SequenceID': 'a_2', 'Sequence': 'AATTGGCC-a2'}),
                      ('b', {'SequenceID': 'b_2', 'Sequence': 'AATTGGCC-b2'}),
                      ('b', {'SequenceID': 'b_1', 'Sequence': 'AATTGGCC-b1'}),
                      ('c', {'SequenceID': 'c_3', 'Sequence': 'AATTGGCC-c3'}),
                      ('c', {'SequenceID': 'c_2', 'Sequence': 'AATTGGCC-c2'}),
                      ('c', {'SequenceID': 'c_1', 'Sequence': 'AATTGGCC-c1'})],
                     key=lambda x: x[0])
        obs = isubsample(self.mock_sequence_iter(self.sequences), maximum,
                         bin_f=bin_f)
>       self.assertEqual(sorted(obs, key=lambda x: x[0]), exp)
E       AssertionError: Lists differ: [('a'[15 chars]: 'a_3', 'Sequence': 'AATTGGCC-a3'}), ('a', {'[499 chars]3'})] != [('a'[15 chars]: 'a_5', 'Sequence': 'AATTGGCC-a5'}), ('a', {'[499 chars]1'})]
E       
E       First differing element 0:
E       ('a', {'SequenceID': 'a_3', 'Sequence': 'AATTGGCC-a3'})
E       ('a', {'SequenceID': 'a_5', 'Sequence': 'AATTGGCC-a5'})
E       
E       Diff is 1356 characters long. Set self.maxDiff to None to see it.

skbio/stats/tests/test_subsample.py:158: AssertionError
______________ ISubsampleTests.test_per_sample_sequences_complex _______________

self = <skbio.stats.tests.test_subsample.ISubsampleTests testMethod=test_per_sample_sequences_complex>

    def test_per_sample_sequences_complex(self):
        maximum = 2
    
        def bin_f(x):
            return x['SequenceID'].rsplit('_', 1)[0]
    
        exp = sorted([('a', {'SequenceID': 'a_2', 'Sequence': 'AATTGGCC-a2'}),
                      ('a', {'SequenceID': 'a_3', 'Sequence': 'AATTGGCC-a3'}),
                      ('b', {'SequenceID': 'b_2', 'Sequence': 'AATTGGCC-b2'}),
                      ('b', {'SequenceID': 'b_1', 'Sequence': 'AATTGGCC-b1'}),
                      ('c', {'SequenceID': 'c_1', 'Sequence': 'AATTGGCC-c1'}),
                      ('c', {'SequenceID': 'c_2', 'Sequence': 'AATTGGCC-c2'})],
                     key=lambda x: x[0])
        obs = isubsample(self.mock_sequence_iter(self.sequences), maximum,
                         bin_f=bin_f, buf_size=1)
>       self.assertEqual(sorted(obs, key=lambda x: x[0]), exp)
E       AssertionError: Lists differ: [('a'[15 chars]: 'a_5', 'Sequence': 'AATTGGCC-a5'}), ('a', {'[271 chars]3'})] != [('a'[15 chars]: 'a_2', 'Sequence': 'AATTGGCC-a2'}), ('a', {'[271 chars]2'})]
E       
E       First differing element 0:
E       ('a', {'SequenceID': 'a_5', 'Sequence': 'AATTGGCC-a5'})
E       ('a', {'SequenceID': 'a_2', 'Sequence': 'AATTGGCC-a2'})
E       
E       Diff is 1124 characters long. Set self.maxDiff to None to see it.

skbio/stats/tests/test_subsample.py:197: AssertionError
______________ ISubsampleTests.test_per_sample_sequences_min_seqs ______________

self = <skbio.stats.tests.test_subsample.ISubsampleTests testMethod=test_per_sample_sequences_min_seqs>

    def test_per_sample_sequences_min_seqs(self):
        maximum = 10
        minimum = 3
    
        def bin_f(x):
            return x['SequenceID'].rsplit('_', 1)[0]
    
        # note, the result here is sorted by sequence_id but is in heap order
        # by the random values associated to each sequence
        exp = sorted([('a', {'SequenceID': 'a_5', 'Sequence': 'AATTGGCC-a5'}),
                      ('a', {'SequenceID': 'a_1', 'Sequence': 'AATTGGCC-a1'}),
                      ('a', {'SequenceID': 'a_4', 'Sequence': 'AATTGGCC-a4'}),
                      ('a', {'SequenceID': 'a_3', 'Sequence': 'AATTGGCC-a3'}),
                      ('a', {'SequenceID': 'a_2', 'Sequence': 'AATTGGCC-a2'}),
                      ('c', {'SequenceID': 'c_3', 'Sequence': 'AATTGGCC-c3'}),
                      ('c', {'SequenceID': 'c_2', 'Sequence': 'AATTGGCC-c2'}),
                      ('c', {'SequenceID': 'c_1', 'Sequence': 'AATTGGCC-c1'})],
                     key=lambda x: x[0])
        obs = isubsample(self.mock_sequence_iter(self.sequences), maximum,
                         minimum, bin_f=bin_f)
>       self.assertEqual(sorted(obs, key=lambda x: x[0]), exp)
E       AssertionError: Lists differ: [('a'[15 chars]: 'a_3', 'Sequence': 'AATTGGCC-a3'}), ('a', {'[385 chars]3'})] != [('a'[15 chars]: 'a_5', 'Sequence': 'AATTGGCC-a5'}), ('a', {'[385 chars]1'})]
E       
E       First differing element 0:
E       ('a', {'SequenceID': 'a_3', 'Sequence': 'AATTGGCC-a3'})
E       ('a', {'SequenceID': 'a_5', 'Sequence': 'AATTGGCC-a5'})
E       
E       Diff is 1062 characters long. Set self.maxDiff to None to see it.

skbio/stats/tests/test_subsample.py:180: AssertionError
=============================== warnings summary ===============================
skbio/util/_testing.py:15
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_testing.py:15: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.
    import pandas.util.testing as pdt

skbio/sequence/_sequence.py:28
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/_sequence.py:28: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
    collections.Sequence, SkbioObject):

skbio/io/format/gff3.py:217
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/io/format/gff3.py:217: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
    from collections import Iterable

skbio/util/_exception.py:10
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_exception.py:10: PytestCollectionWarning: cannot collect test class 'TestingUtilError' because it has a __init__ constructor (from: .pybuild/cpython3_3.9_skbio/build/skbio/io/tests/test_registry.py)
    class TestingUtilError(Exception):

skbio/sequence/tests/test_sequence.py:14
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py:14: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
    from collections import Hashable

.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_ssw.py: 18 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py: 5606 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_base.py: 14 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_clustal.py: 57 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_embl.py: 40 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fasta.py: 1632 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fastq.py: 652 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_genbank.py: 34 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_gff3.py: 6 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_phylip.py: 55 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_qseq.py: 108 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_stockholm.py: 58 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/tests/test_registry.py: 6 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_distance.py: 251 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_dna.py: 29 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_genetic_code.py: 1818 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py: 102 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_nucleotide_sequences.py: 264 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_protein.py: 6 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_rna.py: 29 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py: 1297 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/_sequence.py:427: DeprecationWarning: tostring() is deprecated. Use tobytes() instead.
    return self._bytes.tostring()

.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_ssw.py: 6 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py: 3712 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_clustal.py: 18 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fasta.py: 30 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fastq.py: 83 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_phylip.py: 34 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_stockholm.py: 79 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment/_tabular_msa.py:784: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
    self._seqs = pd.Series([])

.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py: 498 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_clustal.py: 1 warning
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fasta.py: 9 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fastq.py: 12 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_phylip.py: 2 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_stockholm.py: 47 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment/_tabular_msa.py:1991: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
    self._seqs = pd.Series(sequences, index=index)

.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py: 26 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_blast6.py: 6 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_blast7.py: 8 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/metadata/tests/test_mixin.py: 22 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py: 2 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py: 29 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py: 3 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_bioenv.py: 8 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_mantel.py: 9 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/stats/tests/test_composition.py: 21 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/stats/tests/test_gradient.py: 4 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/util/tests/test_testing.py: 2 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_testing.py:304: FutureWarning: The 'check_less_precise' keyword in testing.assert_*_equal is deprecated and will be removed in a future version. You can stop passing 'check_less_precise' to silence this warning.
    pdt.assert_frame_equal(left, right,

.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py::TestLoc::test_multiindex_complicated_axis
.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py::TestLoc::test_multiindex_complicated_axis_empty_selection
.pybuild/cpython3_3.9_skbio/build/skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_invalid_input
.pybuild/cpython3_3.9_skbio/build/skbio/diversity/tests/test_util.py::ValidationTests::test_validate_counts_matrix_unequal_lengths
  /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
    return array(a, dtype, copy=False, order=order)

.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py::TestExtend::test_non_empty_msa_empty_iterable
.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py::TestExtend::test_reset_index_non_empty_msa_empty_iterable
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment/_tabular_msa.py:1986: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
    self._seqs = self._seqs.append(pd.Series(sequences, index=index))

.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py: 62 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_embl.py: 14 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py: 18 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/_sequence.py:1815: DeprecationWarning: tostring() is deprecated. Use tobytes() instead.
    chars = indices.astype(np.uint8).tostring().decode('ascii')

.pybuild/cpython3_3.9_skbio/build/skbio/alignment/tests/test_tabular_msa.py::TestGapFrequencies::test_no_positions_relative
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/alignment/_tabular_msa.py:1653: RuntimeWarning: invalid value encountered in true_divide
    gap_freqs /= length

.pybuild/cpython3_3.9_skbio/build/skbio/diversity/alpha/tests/test_base.py::BaseTests::test_pielou_e
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/diversity/alpha/_base.py:793: RuntimeWarning: invalid value encountered in double_scalars
    return shannon(counts, base=np.e) / np.log(observed_otus(counts))

.pybuild/cpython3_3.9_skbio/build/skbio/diversity/alpha/tests/test_base.py::BaseTests::test_pielou_e
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/diversity/alpha/_base.py:869: RuntimeWarning: invalid value encountered in true_divide
    freqs = counts / counts.sum()

.pybuild/cpython3_3.9_skbio/build/skbio/diversity/alpha/tests/test_base.py::BaseTests::test_pielou_e
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/diversity/alpha/_base.py:793: RuntimeWarning: divide by zero encountered in log
    return shannon(counts, base=np.e) / np.log(observed_otus(counts))

.pybuild/cpython3_3.9_skbio/build/skbio/diversity/tests/test_block.py: 1 warning
.pybuild/cpython3_3.9_skbio/build/skbio/diversity/tests/test_driver.py: 9 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_decorator.py:254: DeprecationWarning: partial_beta_diversity is deprecated as of scikit-bio version 0.5.0, and will be removed in version 0.6.0. The return type is unstable. Developer caution is advised. The resulting DistanceMatrix object will include zeros when distance has not been calculated, and therefore can be misleading.
    warnings.warn('%s is deprecated as of scikit-bio version %s, and '

.pybuild/cpython3_3.9_skbio/build/skbio/diversity/tests/test_driver.py: 5 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py: 4 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/util/tests/test_testing.py: 2 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_testing.py:322: FutureWarning: The 'check_less_precise' keyword in testing.assert_*_equal is deprecated and will be removed in a future version. You can stop passing 'check_less_precise' to silence this warning.
    pdt.assert_series_equal(left, right,

.pybuild/cpython3_3.9_skbio/build/skbio/diversity/tests/test_driver.py::BetaDiversityTests::test_qualitative_bug_issue_1549
  /usr/lib/python3/dist-packages/sklearn/metrics/pairwise.py:1765: DataConversionWarning: Data was converted to boolean for metric jaccard
    warnings.warn(msg, DataConversionWarning)

.pybuild/cpython3_3.9_skbio/build/skbio/diversity/tests/test_util.py::ValidationTests::test_validate_counts_vector_invalid_input
  /usr/lib/python3/dist-packages/numpy/lib/type_check.py:276: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
    return imag(x) == 0

.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fasta.py::SnifferTests::test_positives
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/io/registry.py:918: FormatIdentificationWarning: '_fasta_sniffer' has encountered a problem.
  Please send the following to our issue tracker at
  https://github.com/biocore/scikit-bio/issues
  
  Traceback (most recent call last):
    File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/io/registry.py", line 914, in wrapped_sniffer
      return sniffer(fh)
    File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/io/format/fasta.py", line 648, in _fasta_sniffer
      for _ in zip(range(num_records), parser):
    File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/io/format/fasta.py", line 868, in _parse_fasta_raw
      yield data_parser(data_chunks), id_, desc
    File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/io/format/fasta.py", line 662, in _sniffer_data_parser
      _parse_quality_scores(chunks)
    File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/io/format/fasta.py", line 883, in _parse_quality_scores
      quality = np.asarray(qual_str.split(), dtype=int)
    File "/usr/lib/python3/dist-packages/numpy/core/_asarray.py", line 83, in asarray
      return array(a, dtype, copy=False, order=order)
  OverflowError: Python int too large to convert to C long
  
    warn("'%s' has encountered a problem.\nPlease"

.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fasta.py: 52 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/io/format/tests/test_fastq.py: 75 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py: 3 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/_sequence.py:1308: DeprecationWarning: tostring() is deprecated. Use tobytes() instead.
    return str(outbytes.tostring().decode('ascii'))

.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_has_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_has_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_has_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_has_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_has_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_has_nondegenerates
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_decorator.py:254: DeprecationWarning: has_nondegenerates is deprecated as of scikit-bio version 0.5.0, and will be removed in version 0.6.0. Renamed to has_definites
    warnings.warn('%s is deprecated as of scikit-bio version %s, and '

.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py: 19 warnings
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py: 2 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/_grammared_sequence.py:348: DeprecationWarning: tostring() is deprecated. Use tobytes() instead.
    [str(b.tostring().decode("ascii")) for b in bad] if

.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerate_chars
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerate_chars
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerate_chars
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_nucleotide_sequences.py::TestNucleotideSequence::test_nondegenerate_chars
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_nucleotide_sequences.py::TestNucleotideSequence::test_nondegenerate_chars
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_nucleotide_sequences.py::TestNucleotideSequence::test_nondegenerate_chars
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_nucleotide_sequences.py::TestNucleotideSequence::test_nondegenerate_chars
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_protein.py::TestProtein::test_nondegenerate_chars
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_protein.py::TestProtein::test_nondegenerate_chars
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_decorator.py:254: DeprecationWarning: nondegenerate_chars is deprecated as of scikit-bio version 0.5.0, and will be removed in version 0.6.0. Renamed to definite_chars
    warnings.warn('%s is deprecated as of scikit-bio version %s, and '

.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerates
.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_nondegenerates
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_decorator.py:254: DeprecationWarning: nondegenerates is deprecated as of scikit-bio version 0.5.0, and will be removed in version 0.6.0. Renamed to definites
    warnings.warn('%s is deprecated as of scikit-bio version %s, and '

.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py::TestSequence::test_frequencies_empty_sequence
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/_sequence.py:1819: RuntimeWarning: invalid value encountered in true_divide
    obs_counts = obs_counts / len(self)

.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py::TestSequence::test_init_invalid_sequence
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py:461: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
    Sequence(np.array([1, {}, ()]))

.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py::TestSequence::test_munge_to_index_array_valid_iterable
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/sequence/tests/test_sequence.py:2214: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
    for c in (lambda x: x, list, tuple, lambda x: np.array(tuple(x)),

.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py::DissimilarityMatrixTests::test_subset_to_dataframe
.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py::DissimilarityMatrixTests::test_subset_to_dataframe
.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py::DissimilarityMatrixTests::test_subset_to_dataframe
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/_base.py:550: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
    i = pd.Series(i, name='i')

.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py::DissimilarityMatrixTests::test_subset_to_dataframe
.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py::DissimilarityMatrixTests::test_subset_to_dataframe
.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py::DissimilarityMatrixTests::test_subset_to_dataframe
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/_base.py:551: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
    j = pd.Series(j, name='j')

.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py::DistanceMatrixTests::test_to_series_1x1
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_base.py:938: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
    exp = pd.Series([], index=[])

.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_mantel.py::MantelTests::test_no_variation_pearson
  /usr/lib/python3/dist-packages/scipy/stats/stats.py:3913: PearsonRConstantInputWarning: An input array is constant; the correlation coefficent is not defined.
    warnings.warn(PearsonRConstantInputWarning())

.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_mantel.py::MantelTests::test_no_variation_spearman
  /usr/lib/python3/dist-packages/scipy/stats/stats.py:4264: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficent is not defined.
    warnings.warn(SpearmanRConstantInputWarning())

.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_permdisp.py::testPERMDISP::test_confirm_betadispr_results
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/_principal_coordinate_analysis.py:143: RuntimeWarning: The result contains negative eigenvalues. Please compare their magnitude with the magnitude of some of the largest positive eigenvalues. If the negative ones are smaller, it's probably safe to ignore them, but if they are large in magnitude, the results won't be useful. See the Notes section for more details. The smallest eigenvalue is -0.007758325147780715 and the largest is 2.707792948946925.
    warn(

.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_permdisp.py::testPERMDISP::test_no_permuations
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/_principal_coordinate_analysis.py:143: RuntimeWarning: The result contains negative eigenvalues. Please compare their magnitude with the magnitude of some of the largest positive eigenvalues. If the negative ones are smaller, it's probably safe to ignore them, but if they are large in magnitude, the results won't be useful. See the Notes section for more details. The smallest eigenvalue is -13.541846544269625 and the largest is 16.5872013747859.
    warn(

.pybuild/cpython3_3.9_skbio/build/skbio/stats/distance/tests/test_permdisp.py::testPERMDISP::test_not_distance_matrix
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/_principal_coordinate_analysis.py:188: RuntimeWarning: invalid value encountered in true_divide
    proportion_explained = eigvals / sum_eigenvalues

.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/test_ordination_results.py::TestOrdinationResults::test_plot_no_metadata
.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/test_ordination_results.py::TestOrdinationResults::test_plot_with_categorical_metadata_and_plot_options
.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/test_ordination_results.py::TestOrdinationResults::test_plot_with_numeric_metadata_and_plot_options
.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/test_ordination_results.py::TestOrdinationResults::test_png
.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/test_ordination_results.py::TestOrdinationResults::test_repr_png
.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/test_ordination_results.py::TestOrdinationResults::test_repr_svg
.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/tests/test_ordination_results.py::TestOrdinationResults::test_svg
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/stats/ordination/_ordination_results.py:285: UserWarning: Tight layout not applied. The left and right margins cannot be made large enough to accommodate all axes decorations. 
    fig.tight_layout()

.pybuild/cpython3_3.9_skbio/build/skbio/stats/tests/test_composition.py::AncomTests::test_ancom_no_signal
  /usr/lib/python3/dist-packages/scipy/stats/stats.py:3709: F_onewayConstantInputWarning: Each of the input arrays is constant;the F statistic is not defined or infinite
    warnings.warn(F_onewayConstantInputWarning())

.pybuild/cpython3_3.9_skbio/build/skbio/util/tests/test_decorator.py::TestDeprecated::test_function_output
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/_decorator.py:254: DeprecationWarning: f is deprecated as of scikit-bio version 0.1.0, and will be removed in version 0.1.4. You should now use skbio.g().
    warnings.warn('%s is deprecated as of scikit-bio version %s, and '

.pybuild/cpython3_3.9_skbio/build/skbio/util/tests/test_testing.py::TestAssertSeriesAlmostEqual::test_equal
.pybuild/cpython3_3.9_skbio/build/skbio/util/tests/test_testing.py::TestAssertSeriesAlmostEqual::test_not_equal
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build/skbio/util/tests/test_testing.py:231: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
    pd.Series(),

-- Docs: https://docs.pytest.org/en/stable/warnings.html
=========================== short test summary info ============================
FAILED skbio/alignment/tests/test_tabular_msa.py::TestTabularMSAPositionalMetadata::test_eq_from_different_source
FAILED skbio/alignment/tests/test_tabular_msa.py::TestILoc::test_fancy_empty_second_axis
FAILED skbio/diversity/alpha/tests/test_base.py::BaseTests::test_michaelis_menten_fit
FAILED skbio/diversity/alpha/tests/test_faith_pd.py::FaithPDTests::test_faith_pd
FAILED skbio/diversity/alpha/tests/test_faith_pd.py::FaithPDTests::test_faith_pd_all_observed
FAILED skbio/diversity/alpha/tests/test_faith_pd.py::FaithPDTests::test_faith_pd_extra_tips
FAILED skbio/diversity/alpha/tests/test_faith_pd.py::FaithPDTests::test_faith_pd_minimal
FAILED skbio/diversity/alpha/tests/test_faith_pd.py::FaithPDTests::test_faith_pd_none_observed
FAILED skbio/diversity/alpha/tests/test_faith_pd.py::FaithPDTests::test_faith_pd_qiime_tiny_test
FAILED skbio/diversity/alpha/tests/test_faith_pd.py::FaithPDTests::test_faith_pd_root_not_observed
FAILED skbio/diversity/alpha/tests/test_lladser.py::LladserTests::test_lladser_ci
FAILED skbio/diversity/alpha/tests/test_lladser.py::LladserTests::test_lladser_ci_f3
FAILED skbio/diversity/alpha/tests/test_lladser.py::LladserTests::test_lladser_pe
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_extra_tips
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_minimal_trees
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_otus_out_of_order
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_root_not_observed
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_unifrac
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_unifrac_identity
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_unifrac_non_overlapping
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_unifrac_symmetry
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_unweighted_unifrac_zero_counts
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_extra_tips
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_minimal_trees
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_normalized_root_not_observed
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_otus_out_of_order
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_root_not_observed
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_identity
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_identity_normalized
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_non_overlapping
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_non_overlapping_normalized
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_normalized
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_symmetry
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_symmetry_normalized
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_zero_counts
FAILED skbio/diversity/beta/tests/test_unifrac.py::UnifracTests::test_weighted_unifrac_zero_counts_normalized
FAILED skbio/diversity/tests/test_block.py::ParallelBetaDiversity::test_block_beta_diversity
FAILED skbio/diversity/tests/test_driver.py::AlphaDiversityTests::test_empty
FAILED skbio/diversity/tests/test_driver.py::AlphaDiversityTests::test_faith_pd
FAILED skbio/diversity/tests/test_driver.py::AlphaDiversityTests::test_input_types
FAILED skbio/diversity/tests/test_driver.py::AlphaDiversityTests::test_invalid_input
FAILED skbio/diversity/tests/test_driver.py::AlphaDiversityTests::test_optimized
FAILED skbio/diversity/tests/test_driver.py::AlphaDiversityTests::test_single_count_vector
FAILED skbio/diversity/tests/test_driver.py::BetaDiversityTests::test_alt_pairwise_func
FAILED skbio/diversity/tests/test_driver.py::BetaDiversityTests::test_invalid_input
FAILED skbio/diversity/tests/test_driver.py::BetaDiversityTests::test_unweighted_unifrac
FAILED skbio/diversity/tests/test_driver.py::BetaDiversityTests::test_weighted_unifrac
FAILED skbio/diversity/tests/test_driver.py::BetaDiversityTests::test_weighted_unifrac_normalized
FAILED skbio/diversity/tests/test_driver.py::TestPartialBetaDiversity::test_id_pairs_as_iterable
FAILED skbio/diversity/tests/test_driver.py::TestPartialBetaDiversity::test_unweighted_unifrac_partial
FAILED skbio/diversity/tests/test_driver.py::TestPartialBetaDiversity::test_weighted_unifrac_partial_full
FAILED skbio/diversity/tests/test_util.py::ValidationTests::test_vectorize_counts_and_tree
FAILED skbio/io/format/tests/test_fasta.py::SnifferTests::test_positives - As...
FAILED skbio/metadata/tests/test_mixin.py::TestPositionalMetadataMixin::test_eq_from_different_source
FAILED skbio/sequence/tests/test_grammared_sequence.py::TestGrammaredSequence::test_degap
FAILED skbio/sequence/tests/test_sequence.py::TestSequencePositionalMetadata::test_eq_from_different_source
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_eq_sequences_from_different_sources_compare_equal
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_getitem_with_boolean_vector_has_qual
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_getitem_with_int_has_positional_metadata
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_getitem_with_iterable_of_mixed_has_positional_metadata
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_getitem_with_numpy_index_has_positional_metadata
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_getitem_with_slice_has_positional_metadata
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_getitem_with_tuple_of_mixed_with_positional_metadata
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_init_invalid_sequence
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_iter_has_positional_metadata
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_reversed_has_positional_metadata
FAILED skbio/sequence/tests/test_sequence.py::TestSequence::test_slice_positional_metadata
FAILED skbio/stats/distance/tests/test_bioenv.py::BIOENVTests::test_bioenv_all_columns_explicit
FAILED skbio/stats/distance/tests/test_bioenv.py::BIOENVTests::test_bioenv_all_columns_implicit
FAILED skbio/stats/distance/tests/test_bioenv.py::BIOENVTests::test_bioenv_different_column_order
FAILED skbio/stats/distance/tests/test_bioenv.py::BIOENVTests::test_bioenv_single_column
FAILED skbio/stats/distance/tests/test_bioenv.py::BIOENVTests::test_bioenv_vegan_example
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_duplicate_dms
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_filepaths_as_input
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_id_lookup
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_many_filepaths_as_input
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_minimal_compatible_input
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_minimal_compatible_input_with_labels
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_na_p_value
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_reordered_distance_matrices
FAILED skbio/stats/distance/tests/test_mantel.py::PairwiseMantelTests::test_strict
FAILED skbio/stats/tests/test_subsample.py::SubsampleCountsTests::test_subsample_counts_nonrandom
FAILED skbio/stats/tests/test_subsample.py::SubsampleCountsTests::test_subsample_counts_without_replacement
FAILED skbio/stats/tests/test_subsample.py::ISubsampleTests::test_isubsample_simple
FAILED skbio/stats/tests/test_subsample.py::ISubsampleTests::test_per_sample_sequences_complex
FAILED skbio/stats/tests/test_subsample.py::ISubsampleTests::test_per_sample_sequences_min_seqs
=== 87 failed, 2231 passed, 30 skipped, 17085 warnings in 243.15s (0:04:03) ====
E: pybuild pybuild:353: test: plugin distutils failed with: exit code=1: cd /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_skbio/build; python3.9 -m pytest 
dh_auto_test: error: pybuild --test --test-pytest -i python{version} -p 3.9 returned exit code 13
make: *** [debian/rules:13: binary-arch] Error 25
dpkg-buildpackage: error: debian/rules binary-arch subprocess returned exit status 2
--------------------------------------------------------------------------------
Build finished at 2021-10-18T09:01:23Z

Finished
--------


+------------------------------------------------------------------------------+
| Cleanup                                                                      |
+------------------------------------------------------------------------------+

Purging /<<BUILDDIR>>
Not cleaning session: cloned chroot in use
E: Build failure (dpkg-buildpackage died)

+------------------------------------------------------------------------------+
| Summary                                                                      |
+------------------------------------------------------------------------------+

Build Architecture: armhf
Build-Space: 30520
Build-Time: 291
Distribution: bookworm-staging
Fail-Stage: build
Host Architecture: armhf
Install-Time: 524
Job: python-skbio_0.5.6-5
Machine Architecture: armhf
Package: python-skbio
Package-Time: 834
Source-Version: 0.5.6-5
Space: 30520
Status: attempted
Version: 0.5.6-5
--------------------------------------------------------------------------------
Finished at 2021-10-18T09:01:23Z
Build needed 00:13:54, 30520k disk space
Raspbian Package Auto-Building

Build log for python-skbio (0.5.6-5) on armhf
