#!/bin/bash
# Example script for the INF pipeline

CORES=12

OUTFOLDER=results
DATAFOLDER=data
DATASET=tcga_aml
LAYER1=gene
LAYER2=meth
LAYER3=mirna
TARGET=OS
MODEL=randomForest
N_SPLITS_START=0
N_SPLITS_END=10

RANDOM_LABELS=false

snakefile=Snakefile_full

if [[ $1 = accelerated ]]
then
    snakefile=Snakefile_accelerated
fi

# go!

for (( i=$N_SPLITS_START; i<$N_SPLITS_END; i++ ))
do
    snakemake -s $snakefile --cores $CORES --config datafolder=$DATAFOLDER outfolder=$OUTFOLDER dataset=$DATASET target=$TARGET layer1=$LAYER1 layer2=$LAYER2 layer3=$LAYER3 model=$MODEL random=$RANDOM_LABELS split_id=$i  -p --dryrun
done

if [ $RANDOM_LABELS = true ]
then 
    TARGET+='_random'
fi

for MODE in juxt rSNF rSNFi single
do
    python postprocessing/compute_all_metrics.py --outfolder $OUTFOLDER --dataset $DATASET --target $TARGET --layers $LAYER1 $LAYER2 $LAYER3 --model $MODEL --n_splits_end $N_SPLITS_END --n_splits_start $N_SPLITS_START --mode $MODE
done


for MODE in juxt rSNF 
do
    python postprocessing/borda_global_juxt_rSNF.py --datafolder $DATAFOLDER --outfolder $OUTFOLDER --dataset $DATASET --target $TARGET --layers $LAYER1 $LAYER2 $LAYER3 --model $MODEL --n_splits_end $N_SPLITS_END --n_splits_start $N_SPLITS_START --mode $MODE
done

python postprocessing/borda_global_rSNFi.py --datafolder $DATAFOLDER --outfolder $OUTFOLDER --dataset $DATASET --target $TARGET --layers $LAYER1 $LAYER2 $LAYER3 --model $MODEL --n_splits_end $N_SPLITS_END --n_splits_start $N_SPLITS_START --mode rSNFi