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Main_train_test_chemprop_models_stratified_split.sh
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Main_train_test_chemprop_models_stratified_split.sh
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#!/bin/bash
#Created on Fri Jun 5 13:44:34 2020
#
#This code trains the following models and performs test set predictions:
# 1. DMPNN with Opt/cor/rdkit/morgancount/morgan/no features with and without HO.
# 2. Same for ffNN.
#chmod 700 Train_chemprop_models.sh
#@author: armi
#
#SBATCH -o chemprop_results/Results/Run_trains.log-%j
#SBATCH -c 20
#--gres=gpu:volta:1
source /etc/profile
module load anaconda/2020b
module load cuda/11.0
#source "/home/gridsan/tiihonen/.conda/envs/coe-dmpnn-tl/bin"
#conda init bash
#conda activate coe-dmpnn-tl
source activate coe-dmpnn-tl
#unset PYTHONPATH
#export PYTHONNOUSERSITE=True
run=21
task=0
numGpus=20 # number of available gpus
gpu=0 # gpu num to run on
numTestFolds=20
dataName="opt" # Input y file, same for all the files.
seed="3"
dataPathTrain="Data/Downselection_data_files/y_${dataName}_train_seed${seed}.csv"
dataPathTest="Data/Downselection_data_files/y_${dataName}_test_seed${seed}.csv"
dataPathNewdata="Data/Downselection_data_files/y_${dataName}_newdata.csv"
smilesColumn="smiles"
targetColumn="log2mic"
valFoldIndex=1
testFoldIndex=2
dataType=regression
# These need to be defined every time the fingerprint changes - or, in case of Opt. and Cor., every time that fingerprint or task changes.
featuresPathRdkit="--features_generator rdkit_2d_normalized --no_features_scaling"
featuresPathMorgan="--features_generator morgan"
featuresPathMorganCount="--features_generator morgan_count"
featuresPathDefault=""
# featuresPathOpt="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
# featuresPathCor="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
#########################################
modelName="DMPNN"
echo "DMPNN with Opt. features"
fingerprintName="opt"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPathOpt="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
featuresPath=$featuresPathOpt
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="DMPNN"
echo "DMPNN with Cor. features"
fingerprintName="cor"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="DMPNN"
echo "DMPNN on Biol."
fingerprintName="rdkit"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath=$featuresPathRdkit
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="DMPNN"
echo "DMPNN on Morgan"
fingerprintName="morgan"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath=$featuresPathMorgan
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="DMPNN"
echo "DMPNN on Morgancount"
fingerprintName="morgancount"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath=$featuresPathMorganCount
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="DMPNN"
echo "DMPNN with no extra features"
fingerprintName="no"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath=$featuresPathDefault
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#####################################################################################
#####################################################################################
#####################################################################################
#####################################################################################
#########################################
modelName="ffNN"
echo "ffNN with Opt. features"
fingerprintName="opt"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPathOpt="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
featuresPath=$featuresPathOpt
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="ffNN"
echo "ffNN with Cor. features"
fingerprintName="cor"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}_seed${seed}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
featuresPath="--features_path Data/Downselection_data_files/x_${fingerprintName}_${taskType}.csv"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="ffNN"
echo "ffNN on Biol."
fingerprintName="rdkit"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath=$featuresPathRdkit
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="ffNN"
echo "ffNN on Morgan"
fingerprintName="morgan"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath=$featuresPathMorgan
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################
#########################################
modelName="ffNN"
echo "ffNN on Morgancount"
fingerprintName="morgancount"
echo "No HO"
hyperOpt="standard"
configPath=""
taskType="train"
featuresPath=$featuresPathMorganCount
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "With HO"
hyperOpt="ho"
configPath="--config_path chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/ho.json"
taskType="train"
checkpointDir="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/checkpoints_${hyperOpt}"
for ((i=0;i<$numTestFolds;i++)); do
saveDir="${checkpointDir}/fold_${i}"
foldsFile="Data/Downselection_data_files/CV_splits/Seed${seed}/stratified_split_indices_cv${i}_train.pckl"
#gpu=$((($gpu + 1) % $numGpus))
CUDA_VISIBLE_DEVICES=$gpu python train.py --data_path ${dataPathTrain} --dataset_type $dataType ${featuresPath} --save_dir ${saveDir} --split_type predetermined --folds_file ${foldsFile} --val_fold_index $valFoldIndex --test_fold_index $testFoldIndex --smiles_column ${smilesColumn} --target_column ${targetColumn} --show_individual_scores --features_only --extra_metrics r2 ${configPath}&
done
wait
echo "Predict test set"
taskType="test"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathTest} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
echo "Predict new data"
taskType="newdata"
predsPath="chemprop_models_stratsplit/Models/${modelName}/${fingerprintName}features/preds_${hyperOpt}_${taskType}.csv"
python predict.py --test_path ${dataPathNewdata} --checkpoint_dir ${checkpointDir} --preds_path ${predsPath} ${featuresPath} --smiles_column ${smilesColumn}
#####################################################################################