Metadata-Version: 2.1
Name: chemprobe
Version: 0.1.5
Summary: A package for chemprobe
Home-page: https://github.com/keiserlab/chemprobe
Author: William Connell
Author-email: connell@keiserlab.org
License: UNKNOWN
Description: # chemprobe
        
        ## installation
        Requires `python<=3.11`
        
        To access model & dataset modules:
        ```
        pip install chemprobe
        ```
        To access scripts for preprocessing/training/inference you must install from source:
        ```
        git clone https://github.com/keiserlab/chemprobe.git
        cd chemprobe
        # use a virutal env...
        # conda activate env
        pip install .
        ```
        
        ## download data
        Required to run inference
        ```
        bash download_data.sh
        ```
        
        ## preprocess
        Required to run inference
        ```
        python preprocess.py \
            --data_path ../data
        ```
        
        ## train
        ```
        python train.py \
            --name TEST \
            --exp film \
            --fold 0 \
            --n_blocks 4 \
            --data_path ../data/preprocessed \
            --batch_size 16384 \
            --gpus 0,1,2,3 \
            --num_workers 4 \
            --lr 1e-3
        ```
        
        permuted label model
        ```
        python train.py \
        --study_path /scratch/wconnell/danger/chemprobe/optuna/exp=film/fold=0/ \
        --data_path ../data/preprocessed \
        --name perm-fold=0 \
        --exp film \
        --fold 0 \
        --max_epochs 5 \
        --batch_size 16384 \
        --gpus 3, \
        --permute_labels
        ```
        
        ## optimize
        ```
        python optimize.py \
            --study_path /srv/danger/scratch/wconnell/chemprobe/optuna/ \
            --data_path ../data/preprocessed \
            --exp film \
            --fold 0 \
            --n_trials 20 \
            --prune \
            --batch_size 16384 \
            --gpus 1,
        ```
        
        ## predict
        ```
        python predict.py \
            --cpds neratinib \ # Do not specify to run on all compounds
            --data_path ../data/your_data/ \
            --attribute \ # optional to run attribution
            --batch_size 128 \
            --gpus 2,
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7,<=3.11.0
Description-Content-Type: text/markdown
