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View Code? Open in Web Editor NEWConditional Autoencoders for Multiplexed Pixel Analysis
Home Page: https://campa.readthedocs.io
License: BSD 3-Clause "New" or "Revised" License
Conditional Autoencoders for Multiplexed Pixel Analysis
Home Page: https://campa.readthedocs.io
License: BSD 3-Clause "New" or "Revised" License
List of things to test & document
Currently, we can only exclude channels by listing all the remaining channels. It might be easier to have an explicit argument for exclude_channels
.
Default logging by Keras produces one line per for each update of the progress bar. Could investigate if using tqdm.keras
fixes this.
Size of dots in -log(p-value)
. Edit legend to reflect that.
Its hard to understand what comparison you are looking at otherwise
Use spellchecking in documentation
Here are some comments after looking at the tutorials. What I did was: 1) follow the installation instructions in the CONTRIBUTING
file, 2) work through the tutorials, 3) quickly look through the other documentation. I did this all pretty quickly so I probably missed some things and I didn't cover any of the command line stuff other than campa setup
. Some of the comments are just ideas/suggestions/questions so don't feel like you have to do/respond to everything. Overall I think it's already really good but hopefully the comments are helpful.
campa setup
. I was able to run things anyway so I think it still worked by probably worth looking at.ERROR: None of [PosixPath('/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/campa.ini'), PosixPath('/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/config.ini'), PosixPath('/Users/luke.zappia/.config/campa/campa.ini')] exists. Please create a config with "python cli/setup.py"
experiment_dir not defined in [PosixPath('/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/campa.ini'), PosixPath('/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/config.ini'), PosixPath('/Users/luke.zappia/.config/campa/campa.ini')]
data_dir not defined in [PosixPath('/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/campa.ini'), PosixPath('/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/config.ini'), PosixPath('/Users/luke.zappia/.config/campa/campa.ini')]
co_occ_chunk_size not defined in [PosixPath('/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/campa.ini'), PosixPath('/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/config.ini'), PosixPath('/Users/luke.zappia/.config/campa/campa.ini')]
/Users/luke.zappia/Documents/Code/GitHub-theislab/campa/campa/campa.ini.example
No campa.ini found in /Users/luke.zappia/.config/campa/campa.ini. Creating default config file.
setting up ExampleData config
data_config
argument from "TestData"
to "exampledata"
subset_channels()
maybe it would be good to have an argument that lets you exclude things rather than having to list everything you want to keep?
"00_EU"
channel in this examplenormalize()
step the output list was empty, unlike what was in the docs (possibly my fault)subset
and subsample
functions (and when each should be used)get_object_img()
function for three channels?ModelComparator
class is cool! It's great to have inbuilt functionality for this. My output plots were different to what was in the docs though.plot_cluster_images()
('test/VAE/results_epoch020/val/clustering_annotation.csv' missing
). Maybe I missed something?TypeError: expected str, bytes or os.PathLike object, not NoneType
)extract_features()
step took 70 mins on my laptop. Possibly that has something to do with my setup but my laptop is more powerful than average. Everything else was really fast so would be good if this bit didn't take too long.extract_intensity_csv()
was created?-log(p-value)
rather than just p-values? If so I would update the legend title.I hope that helps. Please let me know if anything isn't clear. Congrats again on the package ๐ !
Dear Developers,
I am trying to install campa on my Apple M1 Max machine;
Please note that I get the same error regardless of whether tensorflow is installed in my conda environment.
Normal installation of tensorflow does not work in my machine, so I had to do following to install tensorflow:
conda install -c apple tensorflow-deps==2.7.0
python -m pip install tensorflow-macos==2.7.0
python -m pip install tensorflow-metal
After installing tensorflow, I can see below:
More details of pip freeze;
absl-py==1.1.0
appnope==0.1.3
argon2-cffi==21.3.0
argon2-cffi-bindings==21.2.0
asttokens==2.0.5
astunparse==1.6.3
attrs==21.4.0
backcall==0.2.0
beautifulsoup4==4.11.1
bleach==5.0.0
brotlipy @ file:///Users/runner/miniforge3/conda-bld/brotlipy_1648854242877/work
cached-property @ file:///home/conda/feedstock_root/build_artifacts/cached_property_1615209429212/work
cachetools==5.2.0
certifi==2022.6.15
cffi @ file:///Users/runner/miniforge3/conda-bld/cffi_1636046173594/work
charset-normalizer @ file:///home/conda/feedstock_root/build_artifacts/charset-normalizer_1644853463426/work
colorama @ file:///home/conda/feedstock_root/build_artifacts/colorama_1602866480661/work
conda-package-handling @ file:///Users/runner/miniforge3/conda-bld/conda-package-handling_1649385125392/work
cryptography @ file:///Users/runner/miniforge3/conda-bld/cryptography_1652967108255/work
cycler==0.11.0
czifile==2019.7.2
debugpy==1.6.0
decorator==5.1.1
defusedxml==0.7.1
entrypoints==0.4
executing==0.8.3
fastjsonschema==2.15.3
flatbuffers==1.12
fonttools==4.33.3
gast==0.4.0
google-auth==2.8.0
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio @ file:///Users/runner/miniforge3/conda-bld/grpc-split_1655728648515/work
h5py @ file:///Users/runner/miniforge3/conda-bld/h5py_1637964045648/work
idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1642433548627/work
imageio==2.19.3
importlib-metadata==4.11.4
ipykernel==6.15.0
ipython==8.4.0
ipython-genutils==0.2.0
ipywidgets==7.7.1
jedi==0.18.1
Jinja2==3.1.2
joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1633637554808/work
jsonschema==4.6.0
jupyter==1.0.0
jupyter-client==7.3.4
jupyter-console==6.4.4
jupyter-core==4.10.0
jupyterlab-pygments==0.2.2
jupyterlab-widgets==1.1.1
keras==2.9.0
Keras-Preprocessing==1.1.2
kiwisolver==1.4.3
libclang==14.0.1
libmambapy @ file:///Users/runner/miniforge3/conda-bld/mamba-split_1649138467459/work/libmambapy
llvmlite==0.38.1
Markdown==3.3.7
MarkupSafe==2.1.1
matplotlib==3.5.2
matplotlib-inline==0.1.3
mistune==0.8.4
nbclient==0.6.4
nbconvert==6.5.0
nbformat==5.4.0
nest-asyncio==1.5.5
networkx==2.8.4
notebook==6.4.12
numba==0.55.2
numpy @ file:///Users/runner/miniforge3/conda-bld/numpy_1653325964689/work
oauthlib==3.2.0
opencv-python==4.6.0.66
opt-einsum==3.3.0
packaging==21.3
pandas==1.4.2
pandocfilters==1.5.0
parso==0.8.3
pexpect==4.8.0
pickleshare==0.7.5
Pillow==9.1.1
prometheus-client==0.14.1
prompt-toolkit==3.0.29
protobuf==3.19.4
psutil==5.9.1
ptyprocess==0.7.0
pure-eval==0.2.2
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycosat @ file:///Users/runner/miniforge3/conda-bld/pycosat_1649384941891/work
pycparser @ file:///home/conda/feedstock_root/build_artifacts/pycparser_1636257122734/work
Pygments==2.12.0
pynndescent==0.5.7
pyOpenSSL @ file:///home/conda/feedstock_root/build_artifacts/pyopenssl_1643496850550/work
pyparsing==3.0.9
pyrsistent==0.18.1
PySocks @ file:///Users/runner/miniforge3/conda-bld/pysocks_1648857374584/work
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1626286286081/work
pytz @ file:///home/conda/feedstock_root/build_artifacts/pytz_1647961439546/work
PyWavelets==1.3.0
pyzmq==23.2.0
qtconsole==5.3.1
QtPy==2.1.0
requests @ file:///home/conda/feedstock_root/build_artifacts/requests_1641580202195/work
requests-oauthlib==1.3.1
rsa==4.8
ruamel-yaml-conda @ file:///Users/runner/miniforge3/conda-bld/ruamel_yaml_1653464548430/work
scikit-image==0.19.3
scikit-learn @ file:///Users/runner/miniforge3/conda-bld/scikit-learn_1652976950430/work
scipy @ file:///Users/runner/miniforge3/conda-bld/scipy_1653074075583/work
seaborn==0.11.2
Send2Trash==1.8.0
six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
soupsieve==2.3.2.post1
stack-data==0.3.0
tensorboard==2.9.1
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow-estimator==2.9.0
tensorflow-macos==2.9.2
tensorflow-metal==0.5.0
termcolor==1.1.0
terminado==0.15.0
threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1643647933166/work
tifffile==2022.5.4
tinycss2==1.1.1
tornado==6.1
tqdm @ file:///home/conda/feedstock_root/build_artifacts/tqdm_1649051611147/work
traitlets==5.3.0
typing_extensions==4.2.0
umap-learn==0.5.3
urllib3 @ file:///home/conda/feedstock_root/build_artifacts/urllib3_1647489083693/work
wcwidth==0.2.5
webencodings==0.5.1
Werkzeug==2.1.2
widgetsnbextension==3.6.1
wrapt==1.14.1
zipp==3.8.0
Dear Professor,
I am a first-year Ph.D. student, I read your paper "Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps" carefully. But my research direction is not protein, but spatial transcriptomics with subcellular resolution, and I wonder if I can use your tool on my data.
Spatial transcriptomics with subcellular resolution such as Stereo-seq, uses barcodes to represent spatial location information, it also contains expression quantity.
Looking forward to your reply! : )
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