added ill_correction.py

macsima_pipeline.sh

@@ -0,0 +1,28 @@
+#!/usr/bin/bash
+#SBATCH --job-name=basicpy_test
+#SBATCH --time=12:00:00
+#SBATCH --nodes=1
+#SBATCH --ntasks=1
+#SBATCH --mem=16gb
+#SBATCH --array=1
+
+#INPUTS
+acquisitions=/hpc/scratch/hdd1/vp232003/tsvs/acquisitions.tsv
+staging_container=/hpc/scratch/hdd1/vp232003/containers/multiplex_macsima_v1.0.0.sif
+output_dir=/hpc/scratch/hdd1/vp232003/output/
+#END INPUTS
+
+sample=$(awk -v ArrayTaskID=$SLURM_ARRAY_TASK_ID '$1==ArrayTaskID {print $2}' $acquisitions)
+
+
+
+
+for cycle in $sample/*;
+do
+
+cycle_folder=$(basename "$cycle")
+sample_id=${SLURM_ARRAY_TASK_ID}
+sample_id+="_$(basename $sample)"
+singularity exec --bind $sample:/mnt,$output_dir:/media --no-home $staging_container python /staging/macsima2mc/macsima2mc.py -i /mnt/$cycle_folder -o /media/$sample_id
+done
+

scripts/ill_correction.py

@@ -0,0 +1,107 @@
+import tifffile as tifff
+import numpy as np
+import os
+from pathlib import Path
+import argparse
+import sys
+
+#---CLI-BLOCK---#
+def setup_cli():
+
+    parser=argparse.ArgumentParser()
+
+
+    parser.add_argument('-i',
+                    '--input',
+                    required=True,
+                    help='path to the image to be corrected'
+                    )
+
+    parser.add_argument('-o',
+                    '--output',
+                    required=True,
+                    help='Directory where the corrected image will be written'
+                    )
+
+    args=parser.parse_args()
+
+    return args
+
+#---END_CLI-BLOCK---#
+
+def args2dict():
+    args_dict={}
+    for index,element in enumerate(sys.argv):
+        if type(element)==str:
+            if element.startswith('-'):
+                args_dict[element]=sys.argv[index+1]
+    return args_dict
+
+
+
+def cast_canvas(img_path):
+    with tifff.TiffFile(img_path) as tif:
+        im=tif.series[0].asarray()
+        stack_len=len(tif.pages)
+        channels=int(stack_len/len(tif.series))
+        x_size=im.shape[2]
+        y_size=im.shape[1]
+    canvas_img=np.zeros( (stack_len,y_size,x_size) ,dtype='uint16')
+
+    return canvas_img,(stack_len,channels)
+
+def ill_profile(img_path):
+
+    file_name=img_path.stem
+    flat_field_path=img_path.parents[1] / 'illumination'  / '{x}-ffp.tiff'.format(x=file_name)
+
+    return flat_field_path
+
+def ill_correction(img_path,ffp_path):
+
+    ffp=tifff.imread( ffp_path )
+    canvas,(z_size,no_of_chan)=cast_canvas(img_path)
+
+    for ch in range(no_of_chan):
+        range_of_interest=range(ch,z_size,no_of_chan)
+        img=tifff.imread(img_path,key=range_of_interest)
+        ffp_tile=np.tile(ffp[:,:,ch],(img.shape[0],1,1))
+        img_corrected= img.astype(float) / ffp_tile
+
+        canvas[range_of_interest,:,:]=np.uint16(img_corrected)
+
+
+    return canvas
+
+def apply_correction(img_path,out_dir):
+
+    img_name=img_path.stem + img_path.suffix
+    img_corr=ill_correction(img_path,ill_profile(img_path))
+    output_img_path=out_dir / img_name
+    ome_metadata=tifff.tiffcomment(img_path)
+    tifff.imwrite( output_img_path ,img_corr )
+    tifff.tiffcomment(output_img_path,ome_metadata)
+
+    return
+
+
+
+def main(args_dict):
+    #read CLI arguments
+    img_path=Path(args_dict['-i'])
+    out_dir =Path(args_dict['-o'])
+    #apply correction to image and write result in out_dir
+    apply_correction(img_path,out_dir)
+
+
+
+if __name__=='__main__':
+    args=setup_cli()
+    main(args2dict())
+
+
+
+
+
+
+