scanpy
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Kernel dies when using batch in highly_variable_genes()
When I run:
sc.pp.highly_variable_genes(
adata,
flavor="seurat_v3",
batch_key="batch",
n_top_genes=2000,
subset=False,
)```
kernel dies in about 60-90 seconds. I have plenty of available memory, so don't see why, but happens again and again.
If I comment out batch:
```pytb
sc.pp.highly_variable_genes(
adata,
flavor="seurat_v3",
#batch_key="batch",
n_top_genes=2000,
subset=False,
)```
It finished in about 10 seconds.
#### Versions
<details>
-----
anndata 0.8.0
scanpy 1.10.0.dev57+g08be4e9
-----
PIL 9.4.0
aa8f2297d25b4dc6fd3d98411eb3ba53823c4f42 NA
absl NA
adjustText 0.8
anyio NA
arrow 1.2.3
arviz 0.15.0
asciitree NA
asttokens NA
astunparse 1.6.3
attr 22.2.0
babel 2.12.1
backcall 0.2.0
beta_ufunc NA
binom_ufunc NA
bokeh 2.4.3
brotli NA
captum 0.6.0
cellrank 1.5.1
certifi 2023.05.07
cffi 1.15.1
charset_normalizer 2.1.1
chex 0.1.6
cloudpickle 2.2.1
colorama 0.4.6
comm 0.1.2
contextlib2 NA
cycler 0.10.0
cython_runtime NA
cytoolz 0.12.0
dask 2023.3.0
dask_image 2022.09.0
dateutil 2.8.2
debugpy 1.6.6
decorator 5.1.1
decoupler 1.4.0
defusedxml 0.7.1
dill 0.3.6
docrep 0.3.2
dot_parser NA
entrypoints 0.4
executing 1.2.0
fasteners 0.17.3
fastjsonschema NA
flatbuffers 23.1.21
flax 0.5.0
fqdn NA
fsspec 2023.1.0
gast NA
google NA
gseapy 1.0.4
h5py 3.8.0
hypergeom_ufunc NA
idna 3.4
igraph 0.10.3
imagecodecs 2023.1.23
imageio 2.26.0
invgauss_ufunc NA
ipykernel 6.21.2
ipython_genutils 0.2.0
ipywidgets 8.0.4
isoduration NA
jax 0.4.10
jaxlib 0.4.10
jedi 0.18.2
jinja2 3.0.3
joblib 1.2.0
json5 NA
jsonpointer 2.3
jsonschema 4.17.3
jupyter_events 0.6.3
jupyter_server 2.3.0
jupyterlab_server 2.19.0
keras 2.11.0
kiwisolver 1.4.4
leidenalg 0.9.1
lightning_fabric 1.9.3
lightning_utilities 0.7.0
llvmlite 0.39.1
lz4 4.3.2
markupsafe 2.1.2
matplotlib 3.7.1
matplotlib_inline 0.1.6
matplotlib_scalebar 0.8.1
ml_collections NA
ml_dtypes 0.1.0
mpl_toolkits NA
msgpack 1.0.4
mudata 0.2.1
multigrate 0.0.2
multipledispatch 0.6.0
natsort 8.3.1
nbformat 5.7.3
nbinom_ufunc NA
ncf_ufunc NA
nct_ufunc NA
ncx2_ufunc NA
networkx 3.0
newick 1.0.0
numba 0.56.4
numcodecs 0.11.0
numpy 1.23.5
numpyro 0.11.0
opt_einsum v3.3.0
optax 0.1.4
packaging 23.0
pandas 1.5.3
parso 0.8.3
paste NA
patsy 0.5.3
petsc4py 3.19.0
pexpect 4.8.0
pickleshare 0.7.5
pkg_resources NA
platformdirs 3.0.0
progressbar 4.2.0
prometheus_client NA
prompt_toolkit 3.0.38
psutil 5.9.4
ptyprocess 0.7.0
pure_eval 0.2.2
pvectorc NA
pycparser 2.21
pydev_ipython NA
pydevconsole NA
pydevd 2.9.5
pydevd_file_utils NA
pydevd_plugins NA
pydevd_tracing NA
pydot 1.4.2
pygam 0.8.0
pygments 2.14.0
pygpcca 1.0.4
pyparsing 3.0.9
pyro 1.8.4+9ed468d
pyrsistent NA
python_utils NA
pythonjsonlogger NA
pytorch_lightning 1.9.3
pytz 2022.7.1
pywt 1.4.1
requests 2.28.2
rfc3339_validator 0.1.4
rfc3986_validator 0.1.1
rich NA
scHPL NA
scarches 0.5.7
sccoda 0.1.9
scipy 1.10.1
scvelo 0.2.5
scvi 0.20.1
seaborn 0.12.2
send2trash NA
session_info 1.0.0
setuptools 67.4.0
six 1.16.0
skewnorm_ufunc NA
skimage 0.19.3
sklearn 1.2.1
slepc4py 3.19.0
sniffio 1.3.0
socks 1.7.1
squidpy 1.2.2
stack_data 0.6.2
statsmodels 0.13.5
tblib 1.7.0
tcr_embedding NA
tensorboard 2.11.2
tensorflow 2.11.0
tensorflow_probability 0.19.0
termcolor NA
texttable 1.6.7
threadpoolctl 3.1.0
tifffile 2023.2.28
tlz 0.12.0
toolz 0.12.0
torch 1.13.1
torch_cluster 1.6.0
torch_geometric 2.2.0
torch_scatter 2.1.0
torch_sparse 0.6.15
torchmetrics 0.11.3
torchvision 0.14.1
tornado 6.2
tqdm 4.64.1
traitlets 5.9.0
tree 0.1.7
typing_extensions NA
unicodedata2 NA
uri_template NA
urllib3 1.26.14
validators 0.20.0
wcwidth 0.2.6
webcolors 1.11.1
websocket 1.5.1
wrapt 1.15.0
xarray 2023.2.0
xarray_einstats 0.5.1
yaml 6.0
zarr 2.13.6
zipp NA
zmq 25.0.0
zoneinfo NA
zope NA
-----
IPython 8.11.0
jupyter_client 8.0.3
jupyter_core 5.2.0
jupyterlab 3.6.1
notebook 6.5.2
-----
Python 3.10.9 | packaged by conda-forge | (main, Feb 2 2023, 20:20:04) [GCC 11.3.0]
Linux-3.10.0-1160.83.1.el7.x86_64-x86_64-with-glibc2.17
-----
Session information updated at 2023-05-26 01:06
</details>
Dear @joseph-siefert do you have an anndata object which can help us reproduce this, please?
