--- a
+++ b/tests/pipeline_test.sh
@@ -0,0 +1,121 @@
+#!/usr/bin/env bash
+
+# ================================
+SCRIPT=$(readlink -m $(type -p $0))
+SCRIPTDIR=$(dirname $SCRIPT)
+testDataDir=$SCRIPTDIR/data
+prismaDir=$SCRIPTDIR/data/Prisma
+testDir=$SCRIPTDIR/
+zipFile=dtitest_Siemens_SC.zip
+
+# ================================
+echo Downloading Prisma data
+
+if [ ! -f $testDataDir/$zipFile ]
+then
+    wget http://people.cas.sc.edu/rorden/SW/dcm2niix/$zipFile -P $testDataDir
+else
+    echo $testDataDir/$zipFile exists, unzipping $zipFile
+fi
+
+rm -rf $prismaDir
+unzip -o -d $testDataDir $testDataDir/$zipFile
+
+
+pushd .
+cd $prismaDir
+dcm2niix -o . -f %z -z y .
+
+IMAGELIST=$testDataDir/imagelist.txt
+MASKLIST=$testDataDir/masklist.txt
+B0LIST=$testDataDir/b0list.txt
+WarpedB0LIST=$testDataDir/warped_b0list.txt
+WarpedMASKLIST=$testDataDir/warped_masklist.txt
+CASELIST=$testDataDir/caselist.txt
+
+if [ -f $IMAGELIST ]
+then
+    rm $IMAGELIST $MASKLIST $B0LIST $WarpedB0LIST $WarpedMASKLIST $CASELIST
+fi
+
+
+echo 'Generating b0 image and corresponding brain mask for test data ...'
+for i in `ls *.nii.gz`
+do
+    IFS=., read -r prefix _ _ <<< $i
+    if [ -f $prefix.bval ] && [ -f $prefix.bvec ]
+    then
+        echo $i
+        
+        b0=${prefix}_b0.nii.gz
+        mask=${prefix}
+        
+        fslroi $i $b0 0 1
+        bet $b0 $mask -m -n       
+        
+        echo `pwd`/$i >> $IMAGELIST
+        echo `pwd`/${prefix}_mask.nii.gz >> $MASKLIST
+        echo `pwd`/${prefix}_b0.nii.gz >> $B0LIST
+        echo `pwd`/${prefix}_b0-Warped.nii.gz >> $WarpedB0LIST
+        echo `pwd`/${prefix}_b0-Warped-mask.nii.gz >> $WarpedMASKLIST
+        echo $prefix >> $CASELIST
+    fi
+done
+popd
+
+
+# ================================
+
+
+# prediction based on provided model
+../pipeline/dwi_masking.py -i $IMAGELIST -nproc 5 -f ../model_folder/
+../pipeline/dwi_masking.py -i $IMAGELIST -nproc 5 -f ../model_folder/ -filter scipy
+../pipeline/dwi_masking.py -i $B0LIST -nproc 5 -f ../model_folder/
+
+# ================================
+
+
+# training
+../src/registration.py -b0 $B0LIST -mask $MASKLIST -ref ../model_folder/IITmean_b0_256.nii.gz
+../src/preprocess_b0.py -i $WarpedB0LIST
+../src/preprocess_mask.py -i $WarpedMASKLIST
+
+
+echo -e "
+[COMMON]
+save_model_dir = \"$testDataDir/model_folder_test\"
+log_dir = \"$testDataDir/log_dir\"
+
+[DATA]
+data_dir = \"$prismaDir\"
+train_data_file = \"sagittal-traindata-dwi.npy\"
+train_label_file = \"sagittal-traindata-mask.npy\"
+
+[TRAINING]
+principal_axis = \"sagittal\"
+learning_rate = 1e-3
+train_batch_size = 4
+validation_split = 0.2
+num_epochs = 1
+shuffle_data = \"True\"
+" > $testDataDir/settings.ini
+
+
+export COMPNET_CONFIG=$testDataDir/settings.ini
+../src/train.py
+
+sed -i "s/sagittal/coronal/g" $testDataDir/settings.ini
+../src/train.py
+
+sed -i "s/coronal/axial/g" $testDataDir/settings.ini
+../src/train.py
+
+
+# ================================
+
+
+# prediction based on trained model
+cp ../model_folder/IITmean_b0_256.nii.gz $testDataDir/model_folder_test/
+../pipeline/dwi_masking.py -i $IMAGELIST -nproc 5 -f $testDataDir/model_folder_test/
+
+