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Merge pull request #2 from loucerac/develop
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Develop
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loucerac authored Oct 9, 2021
2 parents 03c9d7b + 61caa02 commit 8660dc3
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3 changes: 0 additions & 3 deletions .Rprofile

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13 changes: 13 additions & 0 deletions .gitignore
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*.pickle
*.pkl

## catboost
catboost_info

# Based on:
# https://github.com/github/gitignore/blob/master/R.gitignore

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.apdisk

notebooks/sandbox_20190416/hypmorf_fanconi_02_from_targets_to_pathways_global_explained_relevance\.tsv
notebooks/sandbox_gpu/*.jbl
notebooks/sandbox_gpu/*.txt
notebooks/sandbox_gpu/*.json
err.txt
out.txt
data/
err2.txt
out2.txt
*.err
*.out
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23 changes: 20 additions & 3 deletions .vscode/settings.json
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{
"python.pythonPath": "/home/cloucera/apps/miniconda3/envs/hord/bin/python",
"python.pythonPath": "${workspaceFolder}/.venv/bin/python",
"python.linting.pylintEnabled": true,
"python.dataScience.jupyterServerURI": "http://127.0.0.1:8890",
"autoDocstring.docstringFormat": "numpy",
"python.linting.enabled": true,
"terminal.integrated.fontSize": 13
"terminal.integrated.fontSize": 13,
"python.formatting.provider": "black",
"editor.rulers": [88],
"files.watcherExclude": {
"**/venvs": true,
"**/.venv": true,
"**/data": true
},
"files.exclude": {
"**/venvs": true,
"**/.venv": true,
"**/data": true
},
"search.exclude": {
"**/venvs": true,
"**/.venv": true,
"**/data": true
}
}

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10 changes: 6 additions & 4 deletions README.md
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# Holistic Rare Disease paper review March 2019
# Holistic Rare Disease

## Setup

In order to compute the SHAP explanations with a CUDA-enabled GPU install the `shap` change the `CUDAHOME` environment variable. Note that the `CUDAHOME` variable has already been specified in the conda environment file, see the conda version requirement.

The GPU version has been tested on GNU/Linux x64 4.15 with cuda 10.2 and conda >= 4.3 . Use the following command in order to create the python environment needed to run the experiments.

```
mv example.env .env
conda env create -p ./.venv -f environment.yml
```

Edit `.env` as desired.
172 changes: 27 additions & 145 deletions environment.yml
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name: hord
name: panrd
channels:
- intel
- defaults
- conda-forge
- defaults
dependencies:
- gpflow=1.3.0=py36_0
- python-dotenv=0.10.1=py_0
- absl-py=0.7.0=py36_0
- astor=0.7.1=py36_0
- atomicwrites=1.3.0=py_0
- attrs=18.2.0=py36h28b3542_0
- c-ares=1.15.0=h7b6447c_1
- click=7.0=py36_0
- gast=0.2.2=py36_0
- grpcio=1.14.1=py36h9ba97e2_0
- h5py=2.8.0=py36h989c5e5_3
- jupyterlab=0.35.3=py36_0
- jupyterlab_server=0.2.0=py36_0
- keras-applications=1.0.6=py36_0
- keras-preprocessing=1.0.5=py36_0
- libgcc-ng=8.2.0=hdf63c60_1
- libprotobuf=3.6.1=hd408876_0
- libstdcxx-ng=8.2.0=hdf63c60_1
- markdown=3.0.1=py36_0
- more-itertools=5.0.0=py36_0
- multipledispatch=0.6.0=py36_0
- pluggy=0.9.0=py36_0
- protobuf=3.6.1=py36he6710b0_0
- py=1.8.0=py36_0
- pytest=3.9.1=py36_0
- tensorboard=1.12.2=py36he6710b0_0
- termcolor=1.1.0=py36_1
- asn1crypto=0.24.0=py36_3
- backcall=0.1.0=py36_2
- backports=1.0=py36_9
- bleach=2.1.3=py36_2
- bzip2=1.0.6=17
- certifi=2018.1.18=py36_2
- cffi=1.11.5=py36_3
- chardet=3.0.4=py36_3
- cryptography=2.3=py36_0
- cycler=0.10.0=py36_7
- cython=0.28.5=py36h1aa3f02_0
- daal=2019.2=intel_187
- daal4py=0.2019.1=py36_1
- decorator=4.3.0=py36_3
- entrypoints=0.2.3=py36_2
- freetype=2.9=3
- get_terminal_size=1.0.0=py36_7
- hdf5=1.10.2=2
- html5lib=1.0.1=py36_4
- icc_rt=2019.2=intel_187
- idna=2.6=py36_3
- impi_rt=2019.2=intel_187
- intel-openmp=2019.2=intel_187
- intelpython=2019.1=0
- intelpython3_core=2019.1=1
- intelpython3_full=2019.1=1
- ipp=2019.2=intel_187
- ipykernel=4.6.1=py36_2
- ipyparallel=6.0.2=py36_2
- ipython=6.3.1=py36_3
- ipython_genutils=0.2.0=py36_2
- ipywidgets=7.0.0=py36_2
- jedi=0.12.0=py36_2
- jinja2=2.9.6=py36_2
- jsonschema=2.6.0=py36_2
- jupyter=1.0.0=py36_7
- jupyter_client=5.1.0=py36_5
- jupyter_console=5.1.0=py36_2
- jupyter_core=4.4.0=py36_6
- kiwisolver=1.0.1=py36_2
- libffi=3.2.1=11
- libpng=1.6.35=0
- libsodium=1.0.16=3
- llvmlite=0.25.0=py36_2
- markupsafe=1.0=py36_3
- matplotlib=2.2.3=py36_0
- mistune=0.8.3=py36_2
- mkl=2019.2=intel_187
- mkl-service=1.0.0=py36_6
- mkl_fft=1.0.6=py36_1
- mkl_random=1.0.1=py36_9
- mpi4py=3.0.0=py36_3
- mpmath=1.0.0=py36_2
- nbconvert=5.2.1=py36_2
- nbformat=4.4.0=py36_2
- nose=1.3.7=py36_18
- notebook=5.2.2=py36_1
- numba=0.40.0=np115py36_2
- numexpr=2.6.8=py36_0
- numpy=1.15.4=py36_2
- numpy-base=1.15.4=py36_2
- openssl=1.0.2p=0
- pandas=0.23.4=py36_1
- pandocfilters=1.4.1=py36_2
- parso=0.2.0=py36_2
- path.py=11.0.1=py36_2
- pexpect=4.2.1=py36_4
- pickleshare=0.7.4=py36_3
- pip=9.0.3=py36_1
- prompt_toolkit=1.0.15=py36_2
- ptyprocess=0.5.2=py36_2
- pycparser=2.18=py36_2
- pyeditline=2.0.0=py36_0
- pygments=2.2.0=py36_5
- pyopenssl=17.5.0=py36_2
- pyparsing=2.2.0=py36_2
- pysocks=1.6.7=py36_1
- pytables=3.4.3=np115py36_3
- python=3.6.5=11
- python-dateutil=2.6.0=py36_12
- pytz=2018.4=py36_3
- pyyaml=4.1=py36_2
- pyzmq=16.0.2=py36_6
- requests=2.19.1=py36_0
- scikit-learn=0.20.0=py36_13
- scipy=1.1.0=np115py36_6
- setuptools=39.0.1=py36_0
- simplegeneric=0.8.1=py36_7
- six=1.11.0=py36_3
- smp=0.1.4=py36_0
- sqlite=3.23.1=1
- sympy=1.3=py36_1
- tbb=2019.3=intel_0
- tbb4py=2019.3=py36_intel_0
- tcl=8.6.4=20
- tensorflow=1.12.0=py36_0
- terminado=0.8.1=py36_2
- testpath=0.3.1=py36_2
- tk=8.6.4=28
- tornado=4.5.2=py36_5
- traitlets=4.3.2=py36_3
- urllib3=1.22=py36_2
- wcwidth=0.1.7=py36_6
- webencodings=0.5.1=py36_0
- werkzeug=0.14.1=py36_0
- wheel=0.31.0=py36_3
- widgetsnbextension=3.2.0=py36_1
- xgboost=0.7=py36_0
- xz=5.2.3=2
- yaml=0.1.7=2
- zeromq=4.2.3=2
- zlib=1.2.11=5
- _libgcc_mutex=0.1
- _openmp_mutex=4.5
- ca-certificates=2020.12.5
- certifi=2020.12.5
- ld_impl_linux-64=2.35.1
- libffi=3.3
- libgcc-ng=9.3.0
- libgomp=9.3.0
- libstdcxx-ng=9.3.0
- ncurses=6.2
- openssl=1.1.1i
- pip=20.3.3
- python=3.8.6
- python_abi=3.8
- readline=8.0
- setuptools=49.6.0
- sqlite=3.34.0
- tk=8.6.10
- wheel=0.36.2
- xz=5.2.5
- zlib=1.2.11
- git
- pip:
- backports.shutil-get-terminal-size==1.0.0
- tables==3.4.3

- -r file:requirements.txt
variables:
CUDAHOME: /usr/local/cuda-10.2/
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