Bootstrap: docker
From: continuumio/miniconda3:latest

%files

	

%post

	export PATH=/opt/conda/bin:$PATH

	mkdir -p /opt/scripts
	mkdir /opt/src/
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/entrypoint.sh -O /opt/scripts/entrypoint.sh
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/setup.py -O /opt/src/setup.py
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/pyproject.toml -O /opt/src/pyproject.toml
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/predict_age_sing.py -O /opt/scripts/predict_age_sing.py

	mkdir -p /opt/masks
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/masks/brainmask_12.8.nii -O /opt/masks/brainmask_12.8.nii

	mkdir -p /opt/trained_models 
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/trained_models/brainageR_S4_R4.gauss.models -O /opt/trained_models/brainageR.S4_R4.gauss.models
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/trained_models/brainageR_S4_R4_pca.gauss.models -O /opt/trained_models/brainageR.S4_R4_pca.gauss.models
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/trained_models/4sites.S0_R4.lasso.models -O /opt/trained_models/4sites.S0_R4.lasso.models
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/trained_models/4sites.S4_R4.gauss.models -O /opt/trained_models/4sites.S4_R4.gauss.models
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/trained_models/4sites.S4_R4_pca.gauss.models -O /opt/trained_models/4sites.S4_R4_pca.gauss.models
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/trained_models/9datasets.S4_R4.gauss.models -O /opt/trained_models/9datasets.S4_R4.gauss.models
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/trained_models/9datasets.S4_R4_pca.gauss.models -O /opt/trained_models/9datasets.S4_R4_pca.gauss.models


	mkdir /opt/src/brainage/
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/brainage/__init__.py -O /opt/src/brainage/__init__.py
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/brainage/calculate_features.py -O /opt/src/brainage/calculate_features.py
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/brainage/create_splits.py -O /opt/src/brainage/create_splits.py
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/brainage/define_models.py -O /opt/src/brainage/define_models.py
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/brainage/performance_metric.py -O /opt/src/brainage/performance_metric.py
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/brainage/read_data.py -O /opt/src/brainage/read_data.py
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/brainage/xgboost_adapted.py -O /opt/src/brainage/xgboost_adapted.py
	wget https://gin.g-node.org/juaml/brainage/raw/master/More/brainage/zscore.py -O /opt/src/brainage/zscore.py

	
	chmod 777 /tmp/
    chmod 777 /opt/scripts/entrypoint.sh
	chmod 777 /opt/scripts/predict_age_sing.py
	chmod 777 /opt/masks/brainmask_12.8.nii
	
	apt-get update --allow-releaseinfo-change
    apt-get install -y --fix-missing libgomp1 wget dpkg 

    
	NOW=`date`
	
    # Initialize conda
    conda --version

	conda create --name BA_env -c conda-forge python=3.9.1 numpy==1.22.3 matplotlib==3.5.1 nibabel==3.2.2 nilearn==0.9.1 pandas==1.4.2 scipy==1.8.0 seaborn==0.11.2 xgboost==1.6.1 scikit-learn==1.0.2 glmnet
	. /opt/conda/etc/profile.d/conda.sh
 	conda activate BA_env
	pip install "julearn==0.2.5"
	pip install git+https://github.com/JamesRitchie/scikit-rvm.git@master
	cd /opt/src && pip install -e .

%environment
    export PYTHONPATH=/opt/src

%runscript
    echo "Container was created $NOW"
    echo "Arguments received: $*"

    # Activate environment
    conda init
    . /opt/conda/etc/profile.d/conda.sh
    conda activate BA_env

    # Running entrypoint.sh
    /opt/scripts/entrypoint.sh "$1" "$2" "$3" "$4" "$5" "$6" "$7" "$8"
    echo "Computation finished!"