tigrlab / dmri-microstructure Goto Github PK

import pandas as pd
from nilearn import plotting
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subjects = pd.read_csv('/KIMEL/tigrlab/scratch/mjoseph/bids/TAY/code/subject_list.txt', header = None)
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PLOT_DIR=f"/KIMEL/tigrlab/scratch/edickie/TAY_DWI_QA/" 
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get_ipython().system(' mkdir -p {PLOT_DIR}')
get_ipython().system(' mkdir {PLOT_DIR}/ICVF')
get_ipython().system(' mkdir {PLOT_DIR}/ICVF_GM')
get_ipython().system(' mkdir {PLOT_DIR}/ICVF_WM')
get_ipython().system(' mkdir {PLOT_DIR}/ISOVF')
get_ipython().system(' mkdir {PLOT_DIR}/ISOVF_GM')
get_ipython().system(' mkdir {PLOT_DIR}/ISOVF_WM')
get_ipython().system(' mkdir {PLOT_DIR}/OD')
get_ipython().system(' mkdir {PLOT_DIR}/OD_GM')
get_ipython().system(' mkdir {PLOT_DIR}/OD_WM')
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# In[42]:
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from pathlib import Path
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# subject = subjects.loc[0,0]
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for subject in subjects.loc[:,0].to_list():
    
    AMICO_RESAMPLED_DIR=f"/KIMEL/tigrlab/scratch/fogunsanya/dmri-microstructure/amico_resampled_MNI152NLin6/{subject}/ses-01/dwi"
    FMRIPREP_DIR=f"/KIMEL/tigrlab/archive/data/TAY/pipelines/in_progress/baseline/fmriprep/{subject}/ses-01/anat"
    OUTPUT_DIR=f"/KIMEL/tigrlab/scratch/fogunsanya/dmri-microstructure/NODDI_volume_space_masked/{subject}/ses-01/dwi" 
    
    print(subject)
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    for noddi_type in ["ICVF", "ISOVF", "OD"]:
        noddi_img = f"{AMICO_RESAMPLED_DIR}/{subject}_ses-01_space-MNI152NLin6Asym_desc-{noddi_type}_NODDI.nii.gz"
        
        if Path(noddi_img).is_file():
            
            p1 = plotting.plot_img(noddi_img, cut_coords=[-26, -27, 0], title = f"{subject} {noddi_type}", colorbar = True)
            p1.savefig(f"{PLOT_DIR}/{noddi_type}/{subject}_{noddi_type}.png")
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            for mask_type in ["GM","WM"]:
                mask = f"{FMRIPREP_DIR}/{subject}_ses-01_space-MNI152NLin6Asym_label-{mask_type}_probseg.nii.gz"
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                fig = plotting.plot_anat(noddi_img, cut_coords=[-26, -27, 0], title = f"{subject} {noddi_type} {mask_type}")
                fig.add_contours(mask, filled = True, levels=[.6], alpha = 0.4, colors='y')
                fig.savefig(f"{PLOT_DIR}/{noddi_type}_{mask_type}/{subject}_{noddi_type}_{mask_type}.png")
        else: 
            print(f"{noddi_img} is missing")