Description
openedon Sep 26, 2021
I installed scCODA (pip install sccoda) without any problem/warning and performed the basic analysis following the getting started tutorial, until the model setup and inference. Unfortunately I cannot import sccoda.util.comp_ana function into python. Following the tutorial:
from sccoda.util import cell_composition_data as dat
from sccoda.util import data_visualization as viz
from sccoda.util.comp_ana import comp_ana as mod
doesn't work for my python installation (conda, python 3.9), thus I used
import sccoda.util.cell_composition_data as dat
import sccoda.util.data_visualization as viz
successfully. When I try to import comp_ana using:
import sccoda.util.comp_ana as mod
The kernel crushes. If I import sccoda separately;
import sccoda
And look for the possible functions, but I only can see cell_composition_data and data_visualization, but not comp_ana
comp_ana.py is under the sccoda/util folder where it is supposed to be. I am not sure what exactly the problem is, but somehow comp_ana is 'invisible'.
I have a Macbook pro M1 with 8-core, my environment details are:
anndata 0.7.6
scanpy 1.8.1
sinfo 0.3.4
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PIL 8.2.0
anyio NA
appnope 0.1.2
argon2 20.1.0
attr 21.2.0
babel 2.9.1
backcall 0.2.0
brotli NA
cairo 1.19.1
certifi 2021.05.30
cffi 1.14.5
chardet 4.0.0
cloudpickle 1.6.0
cycler 0.10.0
cython_runtime NA
dask 2021.06.0
dateutil 2.8.1
decorator 4.4.2
fsspec 2021.06.0
google NA
h5py 3.1.0
idna 2.10
igraph 0.9.6
ipykernel 5.5.5
ipython_genutils 0.2.0
jedi 0.18.0
jinja2 3.0.1
joblib 1.0.1
json5 NA
jsonschema 3.2.0
jupyter_server 1.8.0
jupyterlab_server 2.6.0
kiwisolver 1.3.1
leidenalg 0.8.4
llvmlite 0.36.0
markupsafe 2.0.1
matplotlib 3.4.2
mpl_toolkits NA
natsort 7.1.1
nbclassic NA
nbformat 5.1.3
numba 0.53.1
numexpr 2.7.3
numpy 1.19.5
packaging 20.9
pandas 1.2.4
parso 0.8.2
pexpect 4.8.0
pickleshare 0.7.5
pkg_resources NA
prometheus_client NA
prompt_toolkit 3.0.18
psutil 5.8.0
ptyprocess 0.7.0
pvectorc NA
pyexpat NA
pygments 2.9.0
pyparsing 2.4.7
pyrsistent NA
pytz 2021.1
requests 2.25.1
sccoda 0.1.4
scipy 1.6.2
seaborn 0.11.1
send2trash NA
six 1.15.0
sklearn 0.24.2
sniffio 1.2.0
socks 1.7.1
sparse 0.12.0
statsmodels 0.12.2
storemagic NA
tables 3.6.1
tblib 1.7.0
terminado 0.10.1
texttable 1.6.3
tlz 0.11.1
toolz 0.11.1
tornado 6.1
traitlets 5.0.5
typing_extensions NA
urllib3 1.26.5
wcwidth 0.2.5
websocket 0.57.0
yaml 5.4.1
zipp NA
zmq 22.1.0
-----
IPython 7.24.1
jupyter_client 6.1.12
jupyter_core 4.7.1
jupyterlab 3.0.16
notebook 6.4.0
-----
Python 3.9.4 | packaged by conda-forge | (default, May 10 2021, 22:13:15) [Clang 11.1.0 ]
macOS-11.2.3-x86_64-i386-64bit
8 logical CPU cores, i386
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Session information updated at 2021-09-26 14:07
I have tried this on a linux server as well with identical results.
Thanks for the time