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HDBSCAN throwing TypeError #263
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Hey @zoccoler, |
He used the code from scikit-learn-contrib/hdbscan#607 from sklearn.datasets import make_blobs By the way, I don't think napari is relevant to the type error. It is omitted from the "minimal example" from #607. Edit: The #607 TypeError occurs with pip as the installer. My pip version is |
@jkmackie thanks for the quick reply! Unfortunately I cannot reproduce the error using that code, so I'm guessing it has something to do with how hdbscan is installed. very weird... |
@jkmackie I also think napari is unrelated to this. But I have hdbscan installed via conda and I do get the error when running this piece of code. |
Just adding some local tests I ran with different napari versions. For me, in both cases I am getting an hdscan failed test because of the my environment with napari 0.4.18# packages in environment at C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-dev-18:
#
# Name Version Build Channel
aiofiles 22.1.0 pyhd8ed1ab_0 conda-forge
aiosqlite 0.19.0 pyhd8ed1ab_0 conda-forge
alabaster 0.7.13 pyhd8ed1ab_0 conda-forge
anyio 3.7.1 pyhd8ed1ab_0 conda-forge
aom 3.5.0 h63175ca_0 conda-forge
apoc-backend 0.12.0 pyhd8ed1ab_0 conda-forge
app-model 0.2.0 pyhd8ed1ab_0 conda-forge
appdirs 1.4.4 pyh9f0ad1d_0 conda-forge
argon2-cffi 21.3.0 pyhd8ed1ab_0 conda-forge
argon2-cffi-bindings 21.2.0 py39ha55989b_3 conda-forge
arrow 1.2.3 pyhd8ed1ab_0 conda-forge
asciitree 0.3.3 py_2 conda-forge
asttokens 2.2.1 pyhd8ed1ab_0 conda-forge
attrs 23.1.0 pyh71513ae_1 conda-forge
autopep8 2.0.2 pyhd8ed1ab_0 conda-forge
aws-c-auth 0.7.0 h6f3c987_2 conda-forge
aws-c-cal 0.6.0 h6ba3258_0 conda-forge
aws-c-common 0.8.23 hcfcfb64_0 conda-forge
aws-c-compression 0.2.17 h420beca_1 conda-forge
aws-c-event-stream 0.3.1 had47b81_1 conda-forge
aws-c-http 0.7.11 h72ba615_0 conda-forge
aws-c-io 0.13.28 ha35c040_0 conda-forge
aws-c-mqtt 0.8.14 h4941efa_2 conda-forge
aws-c-s3 0.3.13 he04eaa7_2 conda-forge
aws-c-sdkutils 0.1.11 h420beca_1 conda-forge
aws-checksums 0.1.16 h420beca_1 conda-forge
aws-crt-cpp 0.20.3 h247a981_4 conda-forge
aws-sdk-cpp 1.10.57 h1a0519f_17 conda-forge
babel 2.12.1 pyhd8ed1ab_1 conda-forge
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
backports 1.0 pyhd8ed1ab_3 conda-forge
backports.functools_lru_cache 1.6.5 pyhd8ed1ab_0 conda-forge
beautifulsoup4 4.12.2 pyha770c72_0 conda-forge
bleach 6.0.0 pyhd8ed1ab_0 conda-forge
blosc 1.21.4 hdccc3a2_0 conda-forge
bokeh 3.2.1 pyhd8ed1ab_0 conda-forge
brotli 1.0.9 hcfcfb64_9 conda-forge
brotli-bin 1.0.9 hcfcfb64_9 conda-forge
brotli-python 1.0.9 py39h99910a6_9 conda-forge
bzip2 1.0.8 h8ffe710_4 conda-forge
c-ares 1.19.1 hcfcfb64_0 conda-forge
c-blosc2 2.10.0 h183a6f4_0 conda-forge
ca-certificates 2023.7.22 h56e8100_0 conda-forge
cached-property 1.5.2 hd8ed1ab_1 conda-forge
cached_property 1.5.2 pyha770c72_1 conda-forge
cachey 0.2.1 pyh9f0ad1d_0 conda-forge
certifi 2023.7.22 pyhd8ed1ab_0 conda-forge
cffi 1.15.1 py39h68f70e3_3 conda-forge
cfitsio 4.2.0 h9ebe7e4_0 conda-forge
charls 2.3.4 h39d44d4_0 conda-forge
charset-normalizer 3.2.0 pyhd8ed1ab_0 conda-forge
click 8.1.6 win_pyh7428d3b_0 conda-forge
cloudpickle 2.2.1 pyhd8ed1ab_0 conda-forge
colorama 0.4.6 pyhd8ed1ab_0 conda-forge
comm 0.1.4 pyhd8ed1ab_0 conda-forge
contourpy 1.1.0 py39h1f6ef14_0 conda-forge
cycler 0.11.0 pyhd8ed1ab_0 conda-forge
cython 0.29.36 pypi_0 pypi
cytoolz 0.12.2 py39ha55989b_0 conda-forge
czifile 2019.7.2 pyh9f0ad1d_0 conda-forge
dask 2023.7.1 pyhd8ed1ab_0 conda-forge
dask-core 2023.7.1 pyhd8ed1ab_0 conda-forge
dav1d 1.2.1 hcfcfb64_0 conda-forge
debugpy 1.6.8 py39h99910a6_0 conda-forge
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge
deprecated 1.2.14 pyh1a96a4e_0 conda-forge
devbio-napari 0.10.1 win_h08f2357_0 conda-forge
distributed 2023.7.1 pyhd8ed1ab_0 conda-forge
docstring_parser 0.15 pyhd8ed1ab_0 conda-forge
docutils 0.17.1 py39hcbf5309_3 conda-forge
eigen 3.4.0 h91493d7_0 conda-forge
entrypoints 0.4 pyhd8ed1ab_0 conda-forge
exceptiongroup 1.1.2 pyhd8ed1ab_0 conda-forge
executing 1.2.0 pyhd8ed1ab_0 conda-forge
expat 2.5.0 h63175ca_1 conda-forge
fasteners 0.17.3 pyhd8ed1ab_0 conda-forge
ffmpeg 5.1.2 gpl_h5b1d025_107 conda-forge
fftw 3.3.10 nompi_h38027f0_108 conda-forge
flit-core 3.9.0 pyhd8ed1ab_0 conda-forge
font-ttf-dejavu-sans-mono 2.37 hab24e00_0 conda-forge
font-ttf-inconsolata 3.000 h77eed37_0 conda-forge
font-ttf-source-code-pro 2.038 h77eed37_0 conda-forge
font-ttf-ubuntu 0.83 hab24e00_0 conda-forge
fontconfig 2.14.2 hbde0cde_0 conda-forge
fonts-conda-ecosystem 1 0 conda-forge
fonts-conda-forge 1 0 conda-forge
fonttools 4.42.0 py39ha55989b_0 conda-forge
fqdn 1.5.1 pyhd8ed1ab_0 conda-forge
freetype 2.12.1 h546665d_1 conda-forge
freetype-py 2.4.0 pyhd8ed1ab_0 conda-forge
fsspec 2023.6.0 pyh1a96a4e_0 conda-forge
funcsigs 1.0.2 py_3 conda-forge
gettext 0.21.1 h5728263_0 conda-forge
giflib 5.2.1 h64bf75a_3 conda-forge
glib 2.76.4 h12be248_0 conda-forge
glib-tools 2.76.4 h12be248_0 conda-forge
gst-plugins-base 1.22.5 h001b923_0 conda-forge
gstreamer 1.22.5 hb4038d2_0 conda-forge
hdbscan 0.8.33 py39hbaa61f9_1 conda-forge
hdf5 1.12.2 nompi_h57737ce_101 conda-forge
heapdict 1.0.1 py_0 conda-forge
hsluv 5.0.2 pyh44b312d_0 conda-forge
icu 70.1 h0e60522_0 conda-forge
idna 3.4 pyhd8ed1ab_0 conda-forge
imagecodecs 2022.9.26 py39haf5b5c4_4 conda-forge
imagecodecs-lite 2019.12.3 py39hc266a54_6 conda-forge
imageio 2.31.1 pyh24c5eb1_0 conda-forge
imageio-ffmpeg 0.4.8 pyhd8ed1ab_0 conda-forge
imagesize 1.4.1 pyhd8ed1ab_0 conda-forge
importlib-metadata 6.8.0 pyha770c72_0 conda-forge
importlib-resources 6.0.0 pyhd8ed1ab_1 conda-forge
importlib_metadata 6.8.0 hd8ed1ab_0 conda-forge
importlib_resources 6.0.0 pyhd8ed1ab_1 conda-forge
in-n-out 0.1.8 pyhd8ed1ab_0 conda-forge
iniconfig 2.0.0 pyhd8ed1ab_0 conda-forge
intel-openmp 2023.2.0 h57928b3_49496 conda-forge
ipycanvas 0.13.1 pyhd8ed1ab_0 conda-forge
ipyevents 2.0.1 pyhd8ed1ab_0 conda-forge
ipykernel 6.25.0 pyh6817e22_0 conda-forge
ipython 8.14.0 pyh08f2357_0 conda-forge
ipython_genutils 0.2.0 py_1 conda-forge
ipywidgets 8.1.0 pyhd8ed1ab_0 conda-forge
isoduration 20.11.0 pyhd8ed1ab_0 conda-forge
jedi 0.19.0 pyhd8ed1ab_0 conda-forge
jinja2 3.1.2 pyhd8ed1ab_1 conda-forge
joblib 1.3.0 pyhd8ed1ab_1 conda-forge
jpeg 9e h8ffe710_2 conda-forge
json5 0.9.14 pyhd8ed1ab_0 conda-forge
jsonpointer 2.0 py_0 conda-forge
jsonschema 4.18.6 pyhd8ed1ab_0 conda-forge
jsonschema-specifications 2023.7.1 pyhd8ed1ab_0 conda-forge
jsonschema-with-format-nongpl 4.18.6 pyhd8ed1ab_0 conda-forge
jupyter 1.0.0 py39hcbf5309_8 conda-forge
jupyter_client 8.3.0 pyhd8ed1ab_0 conda-forge
jupyter_console 6.6.3 pyhd8ed1ab_0 conda-forge
jupyter_core 5.3.1 py39hcbf5309_0 conda-forge
jupyter_events 0.7.0 pyhd8ed1ab_1 conda-forge
jupyter_server 1.23.6 pyhd8ed1ab_0 conda-forge
jupyter_server_fileid 0.9.0 pyhd8ed1ab_0 conda-forge
jupyter_server_ydoc 0.8.0 pyhd8ed1ab_0 conda-forge
jupyter_ydoc 0.2.4 pyhd8ed1ab_0 conda-forge
jupyterlab 3.6.5 pyhd8ed1ab_0 conda-forge
jupyterlab_pygments 0.2.2 pyhd8ed1ab_0 conda-forge
jupyterlab_server 2.24.0 pyhd8ed1ab_0 conda-forge
jupyterlab_widgets 3.0.8 pyhd8ed1ab_0 conda-forge
jupytext 1.15.0 pyhcff175f_0 conda-forge
jxrlib 1.1 h8ffe710_2 conda-forge
khronos-opencl-icd-loader 2023.04.17 h64bf75a_0 conda-forge
kiwisolver 1.4.4 py39h1f6ef14_1 conda-forge
krb5 1.20.1 heb0366b_0 conda-forge
lazy_loader 0.2 pyhd8ed1ab_0 conda-forge
lcms2 2.14 h90d422f_0 conda-forge
lerc 4.0.0 h63175ca_0 conda-forge
libabseil 20230125.3 cxx17_h63175ca_0 conda-forge
libaec 1.0.6 h63175ca_1 conda-forge
libarrow 12.0.1 h0578746_5_cpu conda-forge
libavif 0.11.1 ha7b97ba_2 conda-forge
libblas 3.9.0 17_win64_mkl conda-forge
libbrotlicommon 1.0.9 hcfcfb64_9 conda-forge
libbrotlidec 1.0.9 hcfcfb64_9 conda-forge
libbrotlienc 1.0.9 hcfcfb64_9 conda-forge
libcblas 3.9.0 17_win64_mkl conda-forge
libclang 15.0.7 default_h77d9078_3 conda-forge
libclang13 15.0.7 default_h77d9078_3 conda-forge
libcrc32c 1.1.2 h0e60522_0 conda-forge
libcurl 8.1.2 h68f0423_0 conda-forge
libdeflate 1.14 hcfcfb64_0 conda-forge
libevent 2.1.12 h3671451_1 conda-forge
libexpat 2.5.0 h63175ca_1 conda-forge
libffi 3.4.2 h8ffe710_5 conda-forge
libglib 2.76.4 he8f3873_0 conda-forge
libgoogle-cloud 2.12.0 hbc1b25b_1 conda-forge
libgrpc 1.56.2 hea2d5f7_0 conda-forge
libhwloc 2.9.1 h51c2c0f_0 conda-forge
libiconv 1.17 h8ffe710_0 conda-forge
libitk 5.3.0 h6e1890f_0 conda-forge
libjpeg-turbo 2.1.4 hcfcfb64_0 conda-forge
liblapack 3.9.0 17_win64_mkl conda-forge
libogg 1.3.4 h8ffe710_1 conda-forge
libopus 1.3.1 h8ffe710_1 conda-forge
libpng 1.6.39 h19919ed_0 conda-forge
libprotobuf 4.23.3 h1975477_0 conda-forge
libsodium 1.0.18 h8d14728_1 conda-forge
libsqlite 3.42.0 hcfcfb64_0 conda-forge
libssh2 1.11.0 h7dfc565_0 conda-forge
libthrift 0.18.1 h06f6336_2 conda-forge
libtiff 4.4.0 hc4f729c_5 conda-forge
libutf8proc 2.8.0 h82a8f57_0 conda-forge
libvorbis 1.3.7 h0e60522_0 conda-forge
libwebp-base 1.3.1 hcfcfb64_0 conda-forge
libxcb 1.13 hcd874cb_1004 conda-forge
libxml2 2.10.4 hc3477c8_0 conda-forge
libzlib 1.2.13 hcfcfb64_5 conda-forge
libzopfli 1.0.3 h0e60522_0 conda-forge
llvmlite 0.40.1 py39hd28a505_0 conda-forge
locket 1.0.0 pyhd8ed1ab_0 conda-forge
loguru 0.7.0 py39hcbf5309_0 conda-forge
lz4 4.3.2 py39hf617134_0 conda-forge
lz4-c 1.9.4 hcfcfb64_0 conda-forge
m2w64-gcc-libgfortran 5.3.0 6 conda-forge
m2w64-gcc-libs 5.3.0 7 conda-forge
m2w64-gcc-libs-core 5.3.0 7 conda-forge
m2w64-gmp 6.1.0 2 conda-forge
m2w64-libwinpthread-git 5.0.0.4634.697f757 2 conda-forge
magicgui 0.7.2 pyhd8ed1ab_0 conda-forge
mako 1.2.4 pyhd8ed1ab_0 conda-forge
markdown-it-py 3.0.0 pyhd8ed1ab_0 conda-forge
markupsafe 2.1.3 py39ha55989b_0 conda-forge
matplotlib 3.7.2 py39hcbf5309_0 conda-forge
matplotlib-base 3.7.2 py39ha3e071c_0 conda-forge
matplotlib-inline 0.1.6 pyhd8ed1ab_0 conda-forge
mdit-py-plugins 0.4.0 pyhd8ed1ab_0 conda-forge
mdurl 0.1.0 pyhd8ed1ab_0 conda-forge
mistune 3.0.0 pyhd8ed1ab_0 conda-forge
mkl 2022.1.0 h6a75c08_874 conda-forge
msgpack-python 1.0.5 py39h1f6ef14_0 conda-forge
msys2-conda-epoch 20160418 1 conda-forge
munkres 1.1.4 pyh9f0ad1d_0 conda-forge
mypy_extensions 1.0.0 pyha770c72_0 conda-forge
napari 0.4.18 pyhd8ed1ab_2 conda-forge
napari-3d-ortho-viewer 0.0.1 pyhd8ed1ab_0 conda-forge
napari-accelerated-pixel-and-object-classification 0.12.3 pyhd8ed1ab_0 conda-forge
napari-animation 0.0.7 pyhd8ed1ab_0 conda-forge
napari-assistant 0.4.5 pyhd8ed1ab_0 conda-forge
napari-blob-detection 0.0.2 pyhd8ed1ab_0 conda-forge
napari-brightness-contrast 0.1.8 pyhd8ed1ab_0 conda-forge
napari-clusters-plotter 0.7.2 dev_0 <develop>
napari-console 0.0.8 pyhd8ed1ab_0 conda-forge
napari-crop 0.1.9 pyhd8ed1ab_0 conda-forge
napari-curtain 0.1.1 pyhd8ed1ab_0 conda-forge
napari-czifile2 0.2.7 pyhd8ed1ab_0 conda-forge
napari-folder-browser 0.1.3 pyhd8ed1ab_0 conda-forge
napari-layer-details-display 0.1.5 pyhd8ed1ab_0 conda-forge
napari-mouse-controls 0.1.3 pyhd8ed1ab_0 conda-forge
napari-plot-profile 0.2.2 pyhd8ed1ab_0 conda-forge
napari-plugin-engine 0.2.0 pyhd8ed1ab_2 conda-forge
napari-plugin-search 0.1.3 pyhd8ed1ab_0 conda-forge
napari-pyclesperanto-assistant 0.22.1 pyhd8ed1ab_0 conda-forge
napari-pystackreg 0.1.4 pyhd8ed1ab_0 conda-forge
napari-roi 0.1.8 pyhd8ed1ab_0 conda-forge
napari-segment-blobs-and-things-with-membranes 0.3.6 pyhd8ed1ab_0 conda-forge
napari-simpleitk-image-processing 0.4.5 pyhd8ed1ab_0 conda-forge
napari-skimage-regionprops 0.10.1 pyhd8ed1ab_0 conda-forge
napari-svg 0.1.10 pyhd8ed1ab_0 conda-forge
napari-tabu 0.1.5 pyhd8ed1ab_0 conda-forge
napari-time-slicer 0.4.9 pyhd8ed1ab_1 conda-forge
napari-tools-menu 0.1.19 pyhd8ed1ab_0 conda-forge
napari-workflow-inspector 0.2.2 pyhd8ed1ab_0 conda-forge
napari-workflow-optimizer 0.1.4 pyhd8ed1ab_0 conda-forge
napari-workflows 0.2.9 pyhd8ed1ab_0 conda-forge
nbclassic 1.0.0 pyhb4ecaf3_1 conda-forge
nbclient 0.8.0 pyhd8ed1ab_0 conda-forge
nbconvert 7.7.3 pyhd8ed1ab_0 conda-forge
nbconvert-core 7.7.3 pyhd8ed1ab_0 conda-forge
nbconvert-pandoc 7.7.3 pyhd8ed1ab_0 conda-forge
nbformat 5.9.2 pyhd8ed1ab_0 conda-forge
nest-asyncio 1.5.6 pyhd8ed1ab_0 conda-forge
networkx 3.1 pyhd8ed1ab_0 conda-forge
notebook 6.5.4 pyha770c72_0 conda-forge
notebook-shim 0.2.3 pyhd8ed1ab_0 conda-forge
npe2 0.6.2 pyhd8ed1ab_0 conda-forge
numba 0.57.1 py39hadaa1c4_0 conda-forge
numcodecs 0.11.0 py39h99910a6_1 conda-forge
numpy 1.23.5 py39hbccbffa_0 conda-forge
numpydoc 1.5.0 pyhd8ed1ab_0 conda-forge
openh264 2.3.1 h63175ca_2 conda-forge
openjpeg 2.5.0 hc9384bd_1 conda-forge
openssl 3.1.2 hcfcfb64_0 conda-forge
orc 1.9.0 hf2b8f0d_1 conda-forge
packaging 23.1 pyhd8ed1ab_0 conda-forge
pandas 2.0.3 py39h1679cfb_1 conda-forge
pandoc 3.1.3 h57928b3_0 conda-forge
pandocfilters 1.5.0 pyhd8ed1ab_0 conda-forge
parso 0.8.3 pyhd8ed1ab_0 conda-forge
partd 1.4.0 pyhd8ed1ab_0 conda-forge
patsy 0.5.3 pyhd8ed1ab_0 conda-forge
pcre2 10.40 h17e33f8_0 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pillow 9.2.0 py39h595c93f_3 conda-forge
pint 0.22 pyhd8ed1ab_1 conda-forge
pip 23.2.1 pyhd8ed1ab_0 conda-forge
pkgutil-resolve-name 1.3.10 pyhd8ed1ab_0 conda-forge
platformdirs 3.10.0 pyhd8ed1ab_0 conda-forge
platymatch 0.0.3 pyhd8ed1ab_0 conda-forge
pluggy 1.2.0 pyhd8ed1ab_0 conda-forge
ply 3.11 py_1 conda-forge
pooch 1.7.0 pyha770c72_3 conda-forge
prometheus_client 0.17.1 pyhd8ed1ab_0 conda-forge
prompt-toolkit 3.0.39 pyha770c72_0 conda-forge
prompt_toolkit 3.0.39 hd8ed1ab_0 conda-forge
psutil 5.9.5 py39ha55989b_0 conda-forge
psygnal 0.9.1 pyhd8ed1ab_0 conda-forge
pthread-stubs 0.4 hcd874cb_1001 conda-forge
pthreads-win32 2.9.1 hfa6e2cd_3 conda-forge
pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
pyarrow 12.0.1 py39hca4e8af_5_cpu conda-forge
pyclesperanto-prototype 0.24.1 pyhd8ed1ab_0 conda-forge
pycodestyle 2.11.0 pyhd8ed1ab_0 conda-forge
pycparser 2.21 pyhd8ed1ab_0 conda-forge
pydantic 1.10.12 py39ha55989b_1 conda-forge
pygments 2.15.1 pyhd8ed1ab_0 conda-forge
pynndescent 0.5.10 pyh1a96a4e_0 conda-forge
pyopencl 2023.1.1 py39h2ca6765_0 conda-forge
pyopengl 3.1.6 pyhd8ed1ab_1 conda-forge
pyparsing 3.0.9 pyhd8ed1ab_0 conda-forge
pyperclip 1.8.2 pyhd8ed1ab_2 conda-forge
pyproject_hooks 1.0.0 pyhd8ed1ab_0 conda-forge
pyqt 5.15.9 py39hb77abff_4 conda-forge
pyqt5-sip 12.12.2 py39h99910a6_4 conda-forge
pyqtgraph 0.13.3 pyhd8ed1ab_0 conda-forge
pyrsistent 0.19.3 py39ha55989b_0 conda-forge
pysocks 1.7.1 pyh0701188_6 conda-forge
pystackreg 0.2.7 py39h2ba5b7c_1 conda-forge
pytest 7.4.0 pyhd8ed1ab_0 conda-forge
pytest-qt 4.2.0 pypi_0 pypi
python 3.9.16 h4de0772_0_cpython conda-forge
python-build 0.10.0 pyhd8ed1ab_1 conda-forge
python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge
python-fastjsonschema 2.18.0 pyhd8ed1ab_0 conda-forge
python-json-logger 2.0.7 pyhd8ed1ab_0 conda-forge
python-tzdata 2023.3 pyhd8ed1ab_0 conda-forge
python_abi 3.9 3_cp39 conda-forge
pytomlpp 1.0.13 py39h1f6ef14_0 conda-forge
pytools 2023.1.1 pyhd8ed1ab_0 conda-forge
pytz 2023.3 pyhd8ed1ab_0 conda-forge
pywavelets 1.4.1 py39hc266a54_0 conda-forge
pywin32 304 py39h99910a6_2 conda-forge
pywinpty 2.0.11 py39h99910a6_0 conda-forge
pyyaml 6.0 py39ha55989b_5 conda-forge
pyzmq 25.1.0 py39hea35a22_0 conda-forge
qt-main 5.15.8 h720456b_6 conda-forge
qtconsole 5.4.3 pyhd8ed1ab_0 conda-forge
qtconsole-base 5.4.3 pyha770c72_0 conda-forge
qtpy 2.3.1 pyhd8ed1ab_0 conda-forge
re2 2023.03.02 hd4eee63_0 conda-forge
redlionfish 0.9 py39hcbf5309_2 conda-forge
referencing 0.30.0 pyhd8ed1ab_0 conda-forge
reikna 0.8.0 pyhd8ed1ab_0 conda-forge
requests 2.31.0 pyhd8ed1ab_0 conda-forge
rfc3339-validator 0.1.4 pyhd8ed1ab_0 conda-forge
rfc3986-validator 0.1.1 pyh9f0ad1d_0 conda-forge
rich 13.5.1 pyhd8ed1ab_0 conda-forge
rpds-py 0.9.2 py39hf21820d_0 conda-forge
scikit-image 0.21.0 py39h99910a6_0 conda-forge
scikit-learn 1.3.0 py39hfa9d973_0 conda-forge
scipy 1.11.1 py39hde5eda1_0 conda-forge
seaborn 0.12.2 hd8ed1ab_0 conda-forge
seaborn-base 0.12.2 pyhd8ed1ab_0 conda-forge
send2trash 1.8.2 pyh08f2357_0 conda-forge
setuptools 68.0.0 pyhd8ed1ab_0 conda-forge
shellingham 1.5.1 pyhd8ed1ab_0 conda-forge
simpleitk 2.2.1 py39h138a4a7_1 conda-forge
sip 6.7.11 py39h99910a6_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
snappy 1.1.10 hfb803bf_0 conda-forge
sniffio 1.3.0 pyhd8ed1ab_0 conda-forge
snowballstemmer 2.2.0 pyhd8ed1ab_0 conda-forge
sortedcontainers 2.4.0 pyhd8ed1ab_0 conda-forge
soupsieve 2.3.2.post1 pyhd8ed1ab_0 conda-forge
sphinx 4.5.0 pyh6c4a22f_0 conda-forge
sphinxcontrib-applehelp 1.0.4 pyhd8ed1ab_0 conda-forge
sphinxcontrib-devhelp 1.0.2 py_0 conda-forge
sphinxcontrib-htmlhelp 2.0.1 pyhd8ed1ab_0 conda-forge
sphinxcontrib-jsmath 1.0.1 py_0 conda-forge
sphinxcontrib-qthelp 1.0.3 py_0 conda-forge
sphinxcontrib-serializinghtml 1.1.5 pyhd8ed1ab_2 conda-forge
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
stackview 0.6.3 pyhd8ed1ab_0 conda-forge
statsmodels 0.14.0 py39hbaa61f9_1 conda-forge
superqt 0.4.1 pyhd8ed1ab_0 conda-forge
svt-av1 1.4.1 h63175ca_0 conda-forge
tbb 2021.9.0 h91493d7_0 conda-forge
tblib 1.7.0 pyhd8ed1ab_0 conda-forge
terminado 0.17.0 pyh08f2357_0 conda-forge
the-segmentation-game 0.2.0 pyhd8ed1ab_0 conda-forge
threadpoolctl 3.2.0 pyha21a80b_0 conda-forge
tifffile 2022.10.10 pyhd8ed1ab_0 conda-forge
tinycss2 1.2.1 pyhd8ed1ab_0 conda-forge
tk 8.6.12 h8ffe710_0 conda-forge
toml 0.10.2 pyhd8ed1ab_0 conda-forge
tomli 2.0.1 pyhd8ed1ab_0 conda-forge
tomli-w 1.0.0 pyhd8ed1ab_0 conda-forge
toolz 0.12.0 pyhd8ed1ab_0 conda-forge
tornado 6.3.2 py39ha55989b_0 conda-forge
tqdm 4.65.0 pyhd8ed1ab_1 conda-forge
traitlets 5.9.0 pyhd8ed1ab_0 conda-forge
transforms3d 0.4.1 pyhd8ed1ab_0 conda-forge
typer 0.9.0 pyhd8ed1ab_0 conda-forge
typing-extensions 4.7.1 hd8ed1ab_0 conda-forge
typing_extensions 4.7.1 pyha770c72_0 conda-forge
tzdata 2023c h71feb2d_0 conda-forge
ucrt 10.0.22621.0 h57928b3_0 conda-forge
umap-learn 0.5.3 py39hcbf5309_1 conda-forge
unicodedata2 15.0.0 py39ha55989b_0 conda-forge
uri-template 1.3.0 pyhd8ed1ab_0 conda-forge
urllib3 2.0.4 pyhd8ed1ab_0 conda-forge
vc 14.3 h64f974e_17 conda-forge
vc14_runtime 14.36.32532 hfdfe4a8_17 conda-forge
vispy 0.12.2 py39hc266a54_0 conda-forge
vs2015_runtime 14.36.32532 h05e6639_17 conda-forge
wcwidth 0.2.6 pyhd8ed1ab_0 conda-forge
webcolors 1.13 pyhd8ed1ab_0 conda-forge
webencodings 0.5.1 py_1 conda-forge
websocket-client 1.6.1 pyhd8ed1ab_0 conda-forge
wheel 0.41.0 pyhd8ed1ab_0 conda-forge
widgetsnbextension 4.0.8 pyhd8ed1ab_0 conda-forge
win32_setctime 1.1.0 pyhd8ed1ab_0 conda-forge
win_inet_pton 1.1.0 pyhd8ed1ab_6 conda-forge
winpty 0.4.3 4 conda-forge
wrapt 1.15.0 py39ha55989b_0 conda-forge
x264 1!164.3095 h8ffe710_2 conda-forge
x265 3.5 h2d74725_3 conda-forge
xorg-libxau 1.0.11 hcd874cb_0 conda-forge
xorg-libxdmcp 1.1.3 hcd874cb_0 conda-forge
xyzservices 2023.7.0 pyhd8ed1ab_0 conda-forge
xz 5.2.6 h8d14728_0 conda-forge
y-py 0.5.9 py39hf21820d_0 conda-forge
yaml 0.2.5 h8ffe710_2 conda-forge
ypy-websocket 0.8.2 pyhd8ed1ab_0 conda-forge
zarr 2.16.0 pyhd8ed1ab_0 conda-forge
zeromq 4.3.4 h0e60522_1 conda-forge
zfp 1.0.0 h63175ca_3 conda-forge
zict 3.0.0 pyhd8ed1ab_0 conda-forge
zipp 3.16.2 pyhd8ed1ab_0 conda-forge
zlib-ng 2.0.7 hcfcfb64_0 conda-forge
zstd 1.5.2 h12be248_7 conda-forge my pytest local results with napari 0.4.18================================================= test session starts =================================================
platform win32 -- Python 3.9.16, pytest-7.4.0, pluggy-1.2.0
PyQt5 5.15.9 -- Qt runtime 5.15.8 -- Qt compiled 5.15.8
rootdir: C:\Users\mazo260d\Documents\GitHub\napari-clusters-plotter
plugins: anyio-3.7.1, napari-0.4.18, napari-plugin-engine-0.2.0, npe2-0.6.2, qt-4.2.0
collected 23 items
napari_clusters_plotter\_tests\test_clustering.py .KMEANS predictions finished.
.F... [ 26%]
napari_clusters_plotter\_tests\test_dimension_reduction.py .E.E..... [ 56%]
napari_clusters_plotter\_tests\test_dock_widget.py ... [ 69%]
napari_clusters_plotter\_tests\test_plotter.py .... [ 86%]
napari_clusters_plotter\_tests\test_utils.py ... [100%]
======================================================= ERRORS ========================================================
_____________________________________ ERROR at teardown of test_clustering_widget _____________________________________
qtbot = <pytestqt.qtbot.QtBot object at 0x000001C651DE9310>
request = <SubRequest 'make_napari_viewer' for <Function test_clustering_widget>>
napari_plugin_manager = <napari.plugins._plugin_manager.NapariPluginManager object at 0x000001C651DE9BB0>
monkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x000001C651DE91C0>, clean_themes = None
@pytest.fixture
def make_napari_viewer(
qtbot,
request: 'FixtureRequest',
napari_plugin_manager,
monkeypatch,
clean_themes,
):
"""A fixture function that creates a napari viewer for use in testing.
Use this fixture as a function in your tests:
viewer = make_napari_viewer()
It accepts all the same arguments as napari.Viewer, plus the following
test-related paramaters:
ViewerClass : Type[napari.Viewer], optional
Override the viewer class being used. By default, will
use napari.viewer.Viewer
strict_qt : bool or str, optional
If True, a check will be performed after test cleanup to make sure that
no top level widgets were created and *not* cleaned up during the
test. If the string "raise" is provided, an AssertionError will be
raised. Otherwise a warning is emitted.
By default, this is False unless the test is being performed within
the napari package.
This can be made globally true by setting the 'NAPARI_STRICT_QT'
environment variable.
block_plugin_discovery : bool, optional
Block discovery of non-builtin plugins. Note: plugins can still be
manually registered by using the 'napari_plugin_manager' fixture and
the `napari_plugin_manager.register()` method. By default, True.
Examples
--------
>>> def test_adding_shapes(make_napari_viewer):
... viewer = make_napari_viewer()
... viewer.add_shapes()
... assert len(viewer.layers) == 1
>>> def test_something_with_plugins(make_napari_viewer):
... viewer = make_napari_viewer(block_plugin_discovery=False)
>>> def test_something_with_strict_qt_tests(make_napari_viewer):
... viewer = make_napari_viewer(strict_qt=True)
"""
from qtpy.QtWidgets import QApplication
from napari import Viewer
from napari._qt.qt_viewer import QtViewer
from napari.settings import get_settings
global GCPASS
GCPASS += 1
if GCPASS % 50 == 0:
gc.collect()
else:
gc.collect(1)
_do_not_inline_below = len(QtViewer._instances)
# # do not inline to avoid pytest trying to compute repr of expression.
# # it fails if C++ object gone but not Python object.
if request.config.getoption(_SAVE_GRAPH_OPNAME):
fail_obj_graph(QtViewer)
QtViewer._instances.clear()
assert _do_not_inline_below == 0, (
"Some instance of QtViewer is not properly cleaned in one of previous test. For easier debug one may "
f"use {_SAVE_GRAPH_OPNAME} flag for pytest to get graph of leaked objects. If you use qtbot (from pytest-qt)"
" to clean Qt objects after test you may need to switch to manual clean using "
"`deleteLater()` and `qtbot.wait(50)` later."
)
settings = get_settings()
settings.reset()
viewers: WeakSet[Viewer] = WeakSet()
# may be overridden by using `make_napari_viewer(strict=True)`
_strict = False
initial = QApplication.topLevelWidgets()
prior_exception = getattr(sys, 'last_value', None)
is_internal_test = request.module.__name__.startswith("napari.")
# disable throttling cursor event in tests
monkeypatch.setattr(
"napari._qt.qt_main_window._QtMainWindow._throttle_cursor_to_status_connection",
_empty,
)
def actual_factory(
*model_args,
ViewerClass=Viewer,
strict_qt=None,
block_plugin_discovery=True,
**model_kwargs,
):
if strict_qt is None:
strict_qt = is_internal_test or os.getenv("NAPARI_STRICT_QT")
nonlocal _strict
_strict = strict_qt
if not block_plugin_discovery:
napari_plugin_manager.discovery_blocker.stop()
should_show = request.config.getoption("--show-napari-viewer")
model_kwargs['show'] = model_kwargs.pop('show', should_show)
viewer = ViewerClass(*model_args, **model_kwargs)
viewers.add(viewer)
return viewer
yield actual_factory
# Some tests might have the viewer closed, so this call will not be able
# to access the window.
with suppress(AttributeError):
get_settings().reset()
# close viewers, but don't saving window settings while closing
for viewer in viewers:
if hasattr(viewer.window, '_qt_window'):
with patch.object(
viewer.window._qt_window, '_save_current_window_settings'
):
viewer.close()
else:
viewer.close()
if GCPASS % 50 == 0 or len(QtViewer._instances):
gc.collect()
else:
gc.collect(1)
if request.config.getoption(_SAVE_GRAPH_OPNAME):
fail_obj_graph(QtViewer)
if request.node.rep_call.failed:
# IF test failed do not check for leaks
QtViewer._instances.clear()
_do_not_inline_below = len(QtViewer._instances)
QtViewer._instances.clear() # clear to prevent fail of next test
# do not inline to avoid pytest trying to compute repr of expression.
# it fails if C++ object gone but not Python object.
assert _do_not_inline_below == 0
# only check for leaked widgets if an exception was raised during the test,
# or "strict" mode was used.
if _strict and getattr(sys, 'last_value', None) is prior_exception:
QApplication.processEvents()
leak = set(QApplication.topLevelWidgets()).difference(initial)
# still not sure how to clean up some of the remaining vispy
# vispy.app.backends._qt.CanvasBackendDesktop widgets...
if any(n.__class__.__name__ != 'CanvasBackendDesktop' for n in leak):
# just a warning... but this can be converted to test errors
# in pytest with `-W error`
msg = f"""The following Widgets leaked!: {leak}.
Note: If other tests are failing it is likely that widgets will leak
as they will be (indirectly) attached to the tracebacks of previous failures.
Please only consider this an error if all other tests are passing.
"""
# Explanation notes on the above: While we are indeed looking at the
# difference in sets of widgets between before and after, new object can
# still not be garbage collected because of it.
# in particular with VisPyCanvas, it looks like if a traceback keeps
# contains the type, then instances are still attached to the type.
# I'm not too sure why this is the case though.
if _strict:
> raise AssertionError(msg)
E AssertionError: The following Widgets leaked!: {<napari_clusters_plotter._clustering.ClusteringWidget object at 0x000001C64E60B820>, <PyQt5.QtWidgets.QFrame object at 0x000001C65061A550>, <PyQt5.QtWidgets.QFrame object at 0x000001C65061A790>}.
E
E Note: If other tests are failing it is likely that widgets will leak
E as they will be (indirectly) attached to the tracebacks of previous failures.
E Please only consider this an error if all other tests are passing.
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\napari\utils\_testsupport.py:303: AssertionError
_____________________________________ ERROR at teardown of test_bad_measurements ______________________________________
qtbot = <pytestqt.qtbot.QtBot object at 0x000001C64F908D90>
request = <SubRequest 'make_napari_viewer' for <Function test_bad_measurements>>
napari_plugin_manager = <napari.plugins._plugin_manager.NapariPluginManager object at 0x000001C64F908460>
monkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x000001C64F908850>, clean_themes = None
@pytest.fixture
def make_napari_viewer(
qtbot,
request: 'FixtureRequest',
napari_plugin_manager,
monkeypatch,
clean_themes,
):
"""A fixture function that creates a napari viewer for use in testing.
Use this fixture as a function in your tests:
viewer = make_napari_viewer()
It accepts all the same arguments as napari.Viewer, plus the following
test-related paramaters:
ViewerClass : Type[napari.Viewer], optional
Override the viewer class being used. By default, will
use napari.viewer.Viewer
strict_qt : bool or str, optional
If True, a check will be performed after test cleanup to make sure that
no top level widgets were created and *not* cleaned up during the
test. If the string "raise" is provided, an AssertionError will be
raised. Otherwise a warning is emitted.
By default, this is False unless the test is being performed within
the napari package.
This can be made globally true by setting the 'NAPARI_STRICT_QT'
environment variable.
block_plugin_discovery : bool, optional
Block discovery of non-builtin plugins. Note: plugins can still be
manually registered by using the 'napari_plugin_manager' fixture and
the `napari_plugin_manager.register()` method. By default, True.
Examples
--------
>>> def test_adding_shapes(make_napari_viewer):
... viewer = make_napari_viewer()
... viewer.add_shapes()
... assert len(viewer.layers) == 1
>>> def test_something_with_plugins(make_napari_viewer):
... viewer = make_napari_viewer(block_plugin_discovery=False)
>>> def test_something_with_strict_qt_tests(make_napari_viewer):
... viewer = make_napari_viewer(strict_qt=True)
"""
from qtpy.QtWidgets import QApplication
from napari import Viewer
from napari._qt.qt_viewer import QtViewer
from napari.settings import get_settings
global GCPASS
GCPASS += 1
if GCPASS % 50 == 0:
gc.collect()
else:
gc.collect(1)
_do_not_inline_below = len(QtViewer._instances)
# # do not inline to avoid pytest trying to compute repr of expression.
# # it fails if C++ object gone but not Python object.
if request.config.getoption(_SAVE_GRAPH_OPNAME):
fail_obj_graph(QtViewer)
QtViewer._instances.clear()
assert _do_not_inline_below == 0, (
"Some instance of QtViewer is not properly cleaned in one of previous test. For easier debug one may "
f"use {_SAVE_GRAPH_OPNAME} flag for pytest to get graph of leaked objects. If you use qtbot (from pytest-qt)"
" to clean Qt objects after test you may need to switch to manual clean using "
"`deleteLater()` and `qtbot.wait(50)` later."
)
settings = get_settings()
settings.reset()
viewers: WeakSet[Viewer] = WeakSet()
# may be overridden by using `make_napari_viewer(strict=True)`
_strict = False
initial = QApplication.topLevelWidgets()
prior_exception = getattr(sys, 'last_value', None)
is_internal_test = request.module.__name__.startswith("napari.")
# disable throttling cursor event in tests
monkeypatch.setattr(
"napari._qt.qt_main_window._QtMainWindow._throttle_cursor_to_status_connection",
_empty,
)
def actual_factory(
*model_args,
ViewerClass=Viewer,
strict_qt=None,
block_plugin_discovery=True,
**model_kwargs,
):
if strict_qt is None:
strict_qt = is_internal_test or os.getenv("NAPARI_STRICT_QT")
nonlocal _strict
_strict = strict_qt
if not block_plugin_discovery:
napari_plugin_manager.discovery_blocker.stop()
should_show = request.config.getoption("--show-napari-viewer")
model_kwargs['show'] = model_kwargs.pop('show', should_show)
viewer = ViewerClass(*model_args, **model_kwargs)
viewers.add(viewer)
return viewer
yield actual_factory
# Some tests might have the viewer closed, so this call will not be able
# to access the window.
with suppress(AttributeError):
get_settings().reset()
# close viewers, but don't saving window settings while closing
for viewer in viewers:
if hasattr(viewer.window, '_qt_window'):
with patch.object(
viewer.window._qt_window, '_save_current_window_settings'
):
viewer.close()
else:
viewer.close()
if GCPASS % 50 == 0 or len(QtViewer._instances):
gc.collect()
else:
gc.collect(1)
if request.config.getoption(_SAVE_GRAPH_OPNAME):
fail_obj_graph(QtViewer)
if request.node.rep_call.failed:
# IF test failed do not check for leaks
QtViewer._instances.clear()
_do_not_inline_below = len(QtViewer._instances)
QtViewer._instances.clear() # clear to prevent fail of next test
# do not inline to avoid pytest trying to compute repr of expression.
# it fails if C++ object gone but not Python object.
assert _do_not_inline_below == 0
# only check for leaked widgets if an exception was raised during the test,
# or "strict" mode was used.
if _strict and getattr(sys, 'last_value', None) is prior_exception:
QApplication.processEvents()
leak = set(QApplication.topLevelWidgets()).difference(initial)
# still not sure how to clean up some of the remaining vispy
# vispy.app.backends._qt.CanvasBackendDesktop widgets...
if any(n.__class__.__name__ != 'CanvasBackendDesktop' for n in leak):
# just a warning... but this can be converted to test errors
# in pytest with `-W error`
msg = f"""The following Widgets leaked!: {leak}.
Note: If other tests are failing it is likely that widgets will leak
as they will be (indirectly) attached to the tracebacks of previous failures.
Please only consider this an error if all other tests are passing.
"""
# Explanation notes on the above: While we are indeed looking at the
# difference in sets of widgets between before and after, new object can
# still not be garbage collected because of it.
# in particular with VisPyCanvas, it looks like if a traceback keeps
# contains the type, then instances are still attached to the type.
# I'm not too sure why this is the case though.
if _strict:
> raise AssertionError(msg)
E AssertionError: The following Widgets leaked!: {<PyQt5.QtWidgets.QFrame object at 0x000001C64E5F74C0>, <PyQt5.QtWidgets.QFrame object at 0x000001C64F778700>, <napari_clusters_plotter._dimensionality_reduction.DimensionalityReductionWidget object at 0x000001C650618940>}.
E
E Note: If other tests are failing it is likely that widgets will leak
E as they will be (indirectly) attached to the tracebacks of previous failures.
E Please only consider this an error if all other tests are passing.
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\napari\utils\_testsupport.py:303: AssertionError
------------------------------------------------ Captured stdout call -------------------------------------------------
Selected labels layer: label
Selected measurements: ['label', 'area', 'perimeter']
UMAP(n_neighbors=2, random_state=133, verbose=True)
Fri Aug 11 08:24:22 2023 Construct fuzzy simplicial set
Fri Aug 11 08:24:22 2023 Finding Nearest Neighbors
Fri Aug 11 08:24:25 2023 Finished Nearest Neighbor Search
Fri Aug 11 08:24:27 2023 Construct embedding
Fri Aug 11 08:24:28 2023 Finished embedding
Napari status bar display of label properties disabled because https://github.com/napari/napari/issues/5417 and https://github.com/napari/napari/issues/4342
Dimensionality reduction finished
------------------------------------------------ Captured stderr call -------------------------------------------------
Dimensionality reduction progress: 100%| ██████████ 500/500 [00:00]
====================================================== FAILURES =======================================================
_______________________________________________ test_hdbscan_clustering _______________________________________________
def test_hdbscan_clustering():
# create an example dataset
n_samples = 100
data = datasets.make_moons(n_samples=n_samples, random_state=1, noise=0.05)
true_class = data[1]
measurements = data[0]
from napari_clusters_plotter._clustering import hdbscan_clustering
min_cluster_size = 5
min_samples = 2 # number of samples that should be included in one cluster
# hdbscan_clustering returns (str, np.ndarray), where the first item is algorithm name
> result = hdbscan_clustering(
measurements,
min_cluster_size=min_cluster_size,
min_samples=min_samples,
)
napari_clusters_plotter\_tests\test_clustering.py:129:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
napari_clusters_plotter\_utilities.py:159: in wrapper
embedded = func(*new_args, **kwargs)
napari_clusters_plotter\_clustering.py:559: in hdbscan_clustering
return "HDBSCAN", clustering_hdbscan.fit_predict(reg_props)
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\hdbscan\hdbscan_.py:1243: in fit_predict
self.fit(X)
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\hdbscan\hdbscan_.py:1205: in fit
) = hdbscan(clean_data, **kwargs)
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\hdbscan\hdbscan_.py:884: in hdbscan
_tree_to_labels(
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\hdbscan\hdbscan_.py:80: in _tree_to_labels
labels, probabilities, stabilities = get_clusters(
hdbscan\\_hdbscan_tree.pyx:659: in hdbscan._hdbscan_tree.get_clusters
???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> ???
E TypeError: 'numpy.float64' object cannot be interpreted as an integer
hdbscan\\_hdbscan_tree.pyx:733: TypeError
================================================== warnings summary ===================================================
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\imageio_ffmpeg\_utils.py:6
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\imageio_ffmpeg\_utils.py:6: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html
from pkg_resources import resource_filename
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\pkg_resources\__init__.py:2871
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\pkg_resources\__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('mpl_toolkits')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\pkg_resources\__init__.py:2871
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\pkg_resources\__init__.py:2871
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\pkg_resources\__init__.py:2871
..\..\..\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\pkg_resources\__init__.py:2871
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\pkg_resources\__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('sphinxcontrib')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
napari_clusters_plotter/_tests/test_clustering.py::test_kmeans_clustering
napari_clusters_plotter/_tests/test_clustering.py::test_kmeans_clustering
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\sklearn\cluster\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning
super()._check_params_vs_input(X, default_n_init=10)
napari_clusters_plotter/_tests/test_clustering.py::test_kmeans_clustering
napari_clusters_plotter/_tests/test_clustering.py::test_gaussian_mixture_model
napari_clusters_plotter/_tests/test_clustering.py::test_gaussian_mixture_model
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\sklearn\cluster\_kmeans.py:1436: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.
warnings.warn(
napari_clusters_plotter/_tests/test_clustering.py::test_agglomerative_clustering
napari_clusters_plotter/_tests/test_clustering.py::test_agglomerative_clustering
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\sklearn\cluster\_agglomerative.py:303: UserWarning: the number of connected components of the connectivity matrix is 3 > 1. Completing it to avoid stopping the tree early.
connectivity, n_connected_components = _fix_connectivity(
napari_clusters_plotter/_tests/test_dimension_reduction.py::test_mds
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-dev-18\lib\site-packages\sklearn\manifold\_mds.py:298: FutureWarning: The default value of `normalized_stress` will change to `'auto'` in version 1.4. To suppress this warning, manually set the value of `normalized_stress`.
warnings.warn(
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
=============================================== short test summary info ===============================================
FAILED napari_clusters_plotter/_tests/test_clustering.py::test_hdbscan_clustering - TypeError: 'numpy.float64' object cannot be interpreted as an integer
ERROR napari_clusters_plotter/_tests/test_dimension_reduction.py::test_clustering_widget - AssertionError: The following Widgets leaked!: {<napari_clusters_plotter._clustering.ClusteringWidget object at 0x0...
ERROR napari_clusters_plotter/_tests/test_dimension_reduction.py::test_bad_measurements - AssertionError: The following Widgets leaked!: {<PyQt5.QtWidgets.QFrame object at 0x000001C64E5F74C0>, <PyQt5.QtWid...
================================ 1 failed, 22 passed, 14 warnings, 2 errors in 45.18s ================================= my environment with napari 0.4.17# packages in environment at C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17:
#
# Name Version Build Channel
aiofiles 22.1.0 pyhd8ed1ab_0 conda-forge
aiosqlite 0.19.0 pyhd8ed1ab_0 conda-forge
alabaster 0.7.13 pyhd8ed1ab_0 conda-forge
anyio 3.7.1 pyhd8ed1ab_0 conda-forge
aom 3.5.0 h63175ca_0 conda-forge
apoc-backend 0.12.0 pyhd8ed1ab_0 conda-forge
app-model 0.2.0 pyhd8ed1ab_0 conda-forge
appdirs 1.4.4 pyh9f0ad1d_0 conda-forge
argon2-cffi 21.3.0 pyhd8ed1ab_0 conda-forge
argon2-cffi-bindings 21.2.0 py310h8d17308_3 conda-forge
arrow 1.2.3 pyhd8ed1ab_0 conda-forge
asciitree 0.3.3 py_2 conda-forge
asttokens 2.2.1 pyhd8ed1ab_0 conda-forge
attrs 23.1.0 pyh71513ae_1 conda-forge
autopep8 2.0.2 pyhd8ed1ab_0 conda-forge
aws-c-auth 0.7.0 h6f3c987_2 conda-forge
aws-c-cal 0.6.0 h6ba3258_0 conda-forge
aws-c-common 0.8.23 hcfcfb64_0 conda-forge
aws-c-compression 0.2.17 h420beca_1 conda-forge
aws-c-event-stream 0.3.1 had47b81_1 conda-forge
aws-c-http 0.7.11 h72ba615_0 conda-forge
aws-c-io 0.13.28 ha35c040_0 conda-forge
aws-c-mqtt 0.8.14 h4941efa_2 conda-forge
aws-c-s3 0.3.13 he04eaa7_2 conda-forge
aws-c-sdkutils 0.1.11 h420beca_1 conda-forge
aws-checksums 0.1.16 h420beca_1 conda-forge
aws-crt-cpp 0.20.3 h247a981_4 conda-forge
aws-sdk-cpp 1.10.57 h1a0519f_17 conda-forge
babel 2.12.1 pyhd8ed1ab_1 conda-forge
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
backports 1.0 pyhd8ed1ab_3 conda-forge
backports.functools_lru_cache 1.6.5 pyhd8ed1ab_0 conda-forge
beautifulsoup4 4.12.2 pyha770c72_0 conda-forge
bleach 6.0.0 pyhd8ed1ab_0 conda-forge
blosc 1.21.4 hdccc3a2_0 conda-forge
bokeh 3.2.1 pyhd8ed1ab_0 conda-forge
brotli 1.0.9 hcfcfb64_9 conda-forge
brotli-bin 1.0.9 hcfcfb64_9 conda-forge
brotli-python 1.0.9 py310h00ffb61_9 conda-forge
bzip2 1.0.8 h8ffe710_4 conda-forge
c-ares 1.19.1 hcfcfb64_0 conda-forge
c-blosc2 2.10.0 h183a6f4_0 conda-forge
ca-certificates 2023.7.22 h56e8100_0 conda-forge
cached-property 1.5.2 hd8ed1ab_1 conda-forge
cached_property 1.5.2 pyha770c72_1 conda-forge
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charls 2.3.4 h39d44d4_0 conda-forge
charset-normalizer 3.2.0 pyhd8ed1ab_0 conda-forge
click 8.1.6 win_pyh7428d3b_0 conda-forge
cloudpickle 2.2.1 pyhd8ed1ab_0 conda-forge
colorama 0.4.6 pyhd8ed1ab_0 conda-forge
comm 0.1.4 pyhd8ed1ab_0 conda-forge
contourpy 1.1.0 py310h232114e_0 conda-forge
cycler 0.11.0 pyhd8ed1ab_0 conda-forge
cython 0.29.36 pypi_0 pypi
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dask 2023.8.0 pyhd8ed1ab_0 conda-forge
dask-core 2023.8.0 pyhd8ed1ab_0 conda-forge
dav1d 1.2.0 hcfcfb64_0 conda-forge
debugpy 1.6.8 py310h00ffb61_0 conda-forge
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
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deprecated 1.2.14 pyh1a96a4e_0 conda-forge
devbio-napari 0.10.1 win_h08f2357_0 conda-forge
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fontconfig 2.14.2 hbde0cde_0 conda-forge
fonts-conda-ecosystem 1 0 conda-forge
fonts-conda-forge 1 0 conda-forge
fonttools 4.42.0 py310h8d17308_0 conda-forge
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freetype 2.12.1 h546665d_1 conda-forge
freetype-py 2.4.0 pyhd8ed1ab_0 conda-forge
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idna 3.4 pyhd8ed1ab_0 conda-forge
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imageio-ffmpeg 0.4.8 pyhd8ed1ab_0 conda-forge
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intel-openmp 2023.2.0 h57928b3_49496 conda-forge
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joblib 1.3.2 pyhd8ed1ab_0 conda-forge
jpeg 9e hcfcfb64_3 conda-forge
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napari-pystackreg 0.1.4 pyhd8ed1ab_0 conda-forge
napari-roi 0.1.8 pyhd8ed1ab_0 conda-forge
napari-segment-blobs-and-things-with-membranes 0.3.6 pyhd8ed1ab_0 conda-forge
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napari-svg 0.1.10 pyhd8ed1ab_0 conda-forge
napari-tabu 0.1.5 pyhd8ed1ab_0 conda-forge
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nbclassic 1.0.0 pyhb4ecaf3_1 conda-forge
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nest-asyncio 1.5.6 pyhd8ed1ab_0 conda-forge
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python 3.10.12 h4de0772_0_cpython conda-forge
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pytomlpp 1.0.13 py310h232114e_0 conda-forge
pytools 2023.1.1 pyhd8ed1ab_0 conda-forge
pytz 2023.3 pyhd8ed1ab_0 conda-forge
pywavelets 1.4.1 py310h9b08ddd_0 conda-forge
pywin32 304 py310h00ffb61_2 conda-forge
pywinpty 2.0.11 py310h00ffb61_0 conda-forge
pyyaml 6.0 py310h8d17308_5 conda-forge
pyzmq 24.0.1 py310hcd737a0_1 conda-forge
qt-main 5.15.8 h720456b_6 conda-forge
qtconsole 5.4.3 pyhd8ed1ab_0 conda-forge
qtconsole-base 5.4.3 pyha770c72_0 conda-forge
qtpy 2.3.1 pyhd8ed1ab_0 conda-forge
re2 2023.03.02 hd4eee63_0 conda-forge
redlionfish 0.9 py310h5588dad_2 conda-forge
referencing 0.30.2 pyhd8ed1ab_0 conda-forge
reikna 0.8.0 pyhd8ed1ab_0 conda-forge
requests 2.31.0 pyhd8ed1ab_0 conda-forge
rfc3339-validator 0.1.4 pyhd8ed1ab_0 conda-forge
rfc3986-validator 0.1.1 pyh9f0ad1d_0 conda-forge
rich 13.5.1 pyhd8ed1ab_0 conda-forge
rpds-py 0.9.2 py310h87d50f1_0 conda-forge
scikit-image 0.21.0 py310h00ffb61_0 conda-forge
scikit-learn 1.3.0 py310hd266714_0 conda-forge
scipy 1.11.1 py310h578b7cb_0 conda-forge
seaborn 0.12.2 hd8ed1ab_0 conda-forge
seaborn-base 0.12.2 pyhd8ed1ab_0 conda-forge
send2trash 1.8.2 pyh08f2357_0 conda-forge
setuptools 68.0.0 pyhd8ed1ab_0 conda-forge
shellingham 1.5.1 pyhd8ed1ab_0 conda-forge
simpleitk 2.2.1 py310hcf936e6_1 conda-forge
sip 6.7.11 py310h00ffb61_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
snappy 1.1.10 hfb803bf_0 conda-forge
sniffio 1.3.0 pyhd8ed1ab_0 conda-forge
snowballstemmer 2.2.0 pyhd8ed1ab_0 conda-forge
sortedcontainers 2.4.0 pyhd8ed1ab_0 conda-forge
soupsieve 2.3.2.post1 pyhd8ed1ab_0 conda-forge
sphinx 4.5.0 pyh6c4a22f_0 conda-forge
sphinxcontrib-applehelp 1.0.4 pyhd8ed1ab_0 conda-forge
sphinxcontrib-devhelp 1.0.2 py_0 conda-forge
sphinxcontrib-htmlhelp 2.0.1 pyhd8ed1ab_0 conda-forge
sphinxcontrib-jsmath 1.0.1 pyhd8ed1ab_0 conda-forge
sphinxcontrib-qthelp 1.0.3 py_0 conda-forge
sphinxcontrib-serializinghtml 1.1.5 pyhd8ed1ab_2 conda-forge
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
stackview 0.6.3 pyhd8ed1ab_0 conda-forge
statsmodels 0.14.0 py310h9b08ddd_1 conda-forge
superqt 0.5.0 pyh9208f05_0 conda-forge
svt-av1 1.5.0 h63175ca_0 conda-forge
tbb 2021.9.0 h91493d7_0 conda-forge
tblib 1.7.0 pyhd8ed1ab_0 conda-forge
terminado 0.17.0 pyh08f2357_0 conda-forge
the-segmentation-game 0.2.0 pyhd8ed1ab_0 conda-forge
threadpoolctl 3.2.0 pyha21a80b_0 conda-forge
tifffile 2022.10.10 pyhd8ed1ab_0 conda-forge
tinycss2 1.2.1 pyhd8ed1ab_0 conda-forge
tk 8.6.12 h8ffe710_0 conda-forge
toml 0.10.2 pyhd8ed1ab_0 conda-forge
tomli 2.0.1 pyhd8ed1ab_0 conda-forge
toolz 0.12.0 pyhd8ed1ab_0 conda-forge
tornado 6.3.2 py310h8d17308_0 conda-forge
tqdm 4.66.0 pyhd8ed1ab_0 conda-forge
traitlets 5.9.0 pyhd8ed1ab_0 conda-forge
transforms3d 0.4.1 pyhd8ed1ab_0 conda-forge
typer 0.9.0 pyhd8ed1ab_0 conda-forge
typing-extensions 4.7.1 hd8ed1ab_0 conda-forge
typing_extensions 4.7.1 pyha770c72_0 conda-forge
tzdata 2023c h71feb2d_0 conda-forge
ucrt 10.0.22621.0 h57928b3_0 conda-forge
umap-learn 0.5.3 py310h5588dad_1 conda-forge
unicodedata2 15.0.0 py310h8d17308_0 conda-forge
uri-template 1.3.0 pyhd8ed1ab_0 conda-forge
urllib3 2.0.4 pyhd8ed1ab_0 conda-forge
vc 14.3 h64f974e_17 conda-forge
vc14_runtime 14.36.32532 hfdfe4a8_17 conda-forge
vispy 0.11.0 py310h9b08ddd_1 conda-forge
vs2015_runtime 14.36.32532 h05e6639_17 conda-forge
wcwidth 0.2.6 pyhd8ed1ab_0 conda-forge
webcolors 1.13 pyhd8ed1ab_0 conda-forge
webencodings 0.5.1 py_1 conda-forge
websocket-client 1.6.1 pyhd8ed1ab_0 conda-forge
wheel 0.41.1 pyhd8ed1ab_0 conda-forge
widgetsnbextension 4.0.8 pyhd8ed1ab_0 conda-forge
win32_setctime 1.1.0 pyhd8ed1ab_0 conda-forge
win_inet_pton 1.1.0 pyhd8ed1ab_6 conda-forge
winpty 0.4.3 4 conda-forge
wrapt 1.15.0 py310h8d17308_0 conda-forge
x264 1!164.3095 h8ffe710_2 conda-forge
x265 3.5 h2d74725_3 conda-forge
xorg-libxau 1.0.11 hcd874cb_0 conda-forge
xorg-libxdmcp 1.1.3 hcd874cb_0 conda-forge
xyzservices 2023.7.0 pyhd8ed1ab_0 conda-forge
xz 5.2.6 h8d14728_0 conda-forge
y-py 0.5.5 py310h87d50f1_2 conda-forge
yaml 0.2.5 h8ffe710_2 conda-forge
ypy-websocket 0.8.2 pyhd8ed1ab_0 conda-forge
zarr 2.16.0 pyhd8ed1ab_0 conda-forge
zeromq 4.3.4 h0e60522_1 conda-forge
zfp 1.0.0 h63175ca_3 conda-forge
zict 3.0.0 pyhd8ed1ab_0 conda-forge
zipp 3.16.2 pyhd8ed1ab_0 conda-forge
zlib-ng 2.0.7 hcfcfb64_0 conda-forge
zstd 1.5.2 h12be248_7 conda-forge my local test results with napari 0.4.17platform win32 -- Python 3.10.12, pytest-7.4.0, pluggy-1.2.0
PyQt5 5.15.9 -- Qt runtime 5.15.8 -- Qt compiled 5.15.8
rootdir: C:\Users\mazo260d\Documents\GitHub\napari-clusters-plotter
plugins: anyio-3.7.1, napari-0.4.17, napari-plugin-engine-0.2.0, npe2-0.6.2, qt-4.2.0
collected 23 items
napari_clusters_plotter\_tests\test_clustering.py .KMEANS predictions finished.
.F... [ 26%]
napari_clusters_plotter\_tests\test_dimension_reduction.py ....... [ 56%]
napari_clusters_plotter\_tests\test_dock_widget.py ... [ 69%]
napari_clusters_plotter\_tests\test_plotter.py .... [ 86%]
napari_clusters_plotter\_tests\test_utils.py ... [100%]
====================================================== FAILURES =======================================================
_______________________________________________ test_hdbscan_clustering _______________________________________________
def test_hdbscan_clustering():
# create an example dataset
n_samples = 100
data = datasets.make_moons(n_samples=n_samples, random_state=1, noise=0.05)
true_class = data[1]
measurements = data[0]
from napari_clusters_plotter._clustering import hdbscan_clustering
min_cluster_size = 5
min_samples = 2 # number of samples that should be included in one cluster
# hdbscan_clustering returns (str, np.ndarray), where the first item is algorithm name
> result = hdbscan_clustering(
measurements,
min_cluster_size=min_cluster_size,
min_samples=min_samples,
)
napari_clusters_plotter\_tests\test_clustering.py:129:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
napari_clusters_plotter\_utilities.py:159: in wrapper
embedded = func(*new_args, **kwargs)
napari_clusters_plotter\_clustering.py:559: in hdbscan_clustering
return "HDBSCAN", clustering_hdbscan.fit_predict(reg_props)
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\hdbscan\hdbscan_.py:1243: in fit_predict
self.fit(X)
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\hdbscan\hdbscan_.py:1205: in fit
) = hdbscan(clean_data, **kwargs)
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\hdbscan\hdbscan_.py:884: in hdbscan
_tree_to_labels(
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\hdbscan\hdbscan_.py:80: in _tree_to_labels
labels, probabilities, stabilities = get_clusters(
hdbscan\\_hdbscan_tree.pyx:659: in hdbscan._hdbscan_tree.get_clusters
???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> ???
E TypeError: 'numpy.float64' object cannot be interpreted as an integer
hdbscan\\_hdbscan_tree.pyx:733: TypeError
================================================== warnings summary ===================================================
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\imageio_ffmpeg\_utils.py:6
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\imageio_ffmpeg\_utils.py:6: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html
from pkg_resources import resource_filename
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\pkg_resources\__init__.py:2871
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\pkg_resources\__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('mpl_toolkits')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\pkg_resources\__init__.py:2871
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\pkg_resources\__init__.py:2871
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\pkg_resources\__init__.py:2871
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\pkg_resources\__init__.py:2871
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\pkg_resources\__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('sphinxcontrib')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\vispy\app\backends\_qt.py:93
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\vispy\app\backends\_qt.py:93: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
if LooseVersion(QT_VERSION_STR) >= '5.4.0':
..\..\..\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\setuptools\_distutils\version.py:345
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\setuptools\_distutils\version.py:345: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
other = LooseVersion(other)
napari_clusters_plotter/_tests/test_clustering.py::test_kmeans_clustering
napari_clusters_plotter/_tests/test_clustering.py::test_kmeans_clustering
napari_clusters_plotter/_tests/test_clustering.py::test_kmeans_clustering
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\sklearn\cluster\_kmeans.py:1412: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning
super()._check_params_vs_input(X, default_n_init=10)
napari_clusters_plotter/_tests/test_clustering.py::test_kmeans_clustering
napari_clusters_plotter/_tests/test_clustering.py::test_kmeans_clustering
napari_clusters_plotter/_tests/test_clustering.py::test_gaussian_mixture_model
napari_clusters_plotter/_tests/test_clustering.py::test_gaussian_mixture_model
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\sklearn\cluster\_kmeans.py:1436: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.
warnings.warn(
napari_clusters_plotter/_tests/test_clustering.py::test_agglomerative_clustering
napari_clusters_plotter/_tests/test_clustering.py::test_agglomerative_clustering
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\sklearn\cluster\_agglomerative.py:303: UserWarning: the number of connected components of the connectivity matrix is 3 > 1. Completing it to avoid stopping the tree early.
connectivity, n_connected_components = _fix_connectivity(
napari_clusters_plotter/_tests/test_dimension_reduction.py::test_bad_measurements
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\napari\utils\_testsupport.py:261: UserWarning: The following Widgets leaked!: {<PyQt5.QtWidgets.QFrame object at 0x0000021C4CCDE050>, <napari_clusters_plotter._dimensionality_reduction.DimensionalityReductionWidget object at 0x0000021C51D71BD0>, <PyQt5.QtWidgets.QFrame object at 0x0000021C513BC9D0>}.
Note: If other tests are failing it is likely that widgets will leak
as they will be (indirectly) attached to the tracebacks of previous failures.
Please only consider this an error if all other tests are passing.
warnings.warn(msg)
napari_clusters_plotter/_tests/test_dimension_reduction.py::test_mds
C:\Users\mazo260d\mambaforge\envs\napari-clusters-plotter-env-17\lib\site-packages\sklearn\manifold\_mds.py:298: FutureWarning: The default value of `normalized_stress` will change to `'auto'` in version 1.4. To suppress this warning, manually set the value of `normalized_stress`.
warnings.warn(
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
=============================================== short test summary info ===============================================
FAILED napari_clusters_plotter/_tests/test_clustering.py::test_hdbscan_clustering - TypeError: 'numpy.float64' object cannot be interpreted as an integer
===================================== 1 failed, 22 passed, 19 warnings in 37.83s ====================================== |
Even with napari 0.4.17, hdbscan gives me errors:
It can be related to this thread: scikit-learn-contrib/hdbscan#607
For example, running this:
also throws the error.
Some relevant package versions:
Maybe installation with
pip
works, as suggested in the thread mentioned above, but I cannot install hdbscan with pip right now.The text was updated successfully, but these errors were encountered: