[ENH] add MEG support

handler/Dockerfile

@@ -10,7 +10,7 @@ RUN apt update && \
 RUN apt install -y parallel python3 python3-pip tree curl unzip git jq python libgl-dev python-numpy
 
 RUN pip3 install numpy==1.23.0 nibabel==4.0.0 pandas==1.0.1 matplotlib pyyaml==5.4.1 pydicom==2.3.1 natsort pydeface && \
-    pip3 install quickshear pypet2bids
+    pip3 install quickshear pypet2bids mne mne-bids
 
 RUN apt-get install -y build-essential pkg-config cmake git pigz rename zstd libopenjp2-7 libgdcm-tools wget libopenblas-dev && \
     apt-get clean -y && apt-get autoclean -y && apt-get autoremove -y

handler/bids.sh

@@ -16,6 +16,10 @@ rootDir="$root/bids/$datasetName"
 #clean up from previous run
 rm -rf $root/bids
 
+# run MEG BIDS conversion if relevant data found
+echo "converting MEG data (if present)"
+./convert_meg.py $root/finalized.json $rootDir
+
 echo "converting output to bids"
 ./convert.js $root
 

handler/convert_meg.py

@@ -0,0 +1,93 @@
+#!/usr/bin/env python3
+
+"""
+Takes the ezBIDS data (finalized.json) and uses MNE-BIDS to perform the BIDS conversion for this
+specific modality data.
+"""
+
+import sys
+import json
+from mne.io import read_raw
+from mne_bids import (BIDSPath, write_raw_bids)
+
+# Begin:
+finalized_json_data = json.load(open(sys.argv[1]), strict=False)
+bids_root_dir = sys.argv[2]
+
+# subjects = finalized_json_data["subjects"]  # Is this the final say?
+subjects = [x["_entities"]["subject"] for x in finalized_json_data["objects"]]
+
+# Let's see how many MEG objects there are
+for obj in finalized_json_data["objects"]:
+    obj_type = obj["_type"]
+    if "meg" in obj_type:
+        datatype = "meg"
+        img_data = obj["_SeriesDescription"]
+
+        raw = read_raw(img_data, verbose=0)
+
+        # Get entity information
+        entities = obj["_entities"]
+        sub_idx = obj["subject_idx"]
+        ses_idx = obj["session_idx"]
+
+        # sub
+        sub = subjects[sub_idx]["subject"]
+
+        # ses
+        ses = subjects[sub_idx]["sessions"][ses_idx]
+        if ses["session"] == "" or ses["exclude"] is True:
+            ses = None
+
+        # task
+        task = entities["task"]
+
+        # acquisition
+        if entities["acquisition"] == "":
+            acq = None
+        else:
+            acq = entities["acquisition"]
+
+        # run
+        if entities["run"] == "":
+            run = None
+        else:
+            run = entities["run"]
+
+        # processing
+        if entities["processing"] == "":
+            proc = None
+        else:
+            proc = entities["processing"]
+
+        # split
+        if entities["split"] == "":
+            split = None
+        else:
+            split = entities["split"]
+
+        # Create an MNE BIDSpath
+        bids_path = BIDSPath(
+            subject=sub,
+            session=ses,
+            task=task,
+            acquisition=acq,
+            run=run,
+            processing=proc,
+            split=split,
+            datatype=datatype,
+            root=bids_root_dir
+        )
+
+        print("Converting MEG data to BIDS")
+        empty_room = None
+        if "emptyroom" in subjects and sub != "emptyroom":
+            er_idx = subjects.index("emptyroom")
+            raw_er_data = finalized_json_data["objects"][er_idx]["SeriesDescription"]
+            raw_er = read_raw(raw_er_data, verbose=0)
+            empty_room = raw_er
+
+        write_raw_bids(raw, bids_path=bids_path, verbose=0, empty_room=empty_room, overwrite=True)
+
+print("Finished MEG BIDS conversion (with MNE-BIDS)")
+print("")

handler/ezBIDS_core/createThumbnailsMovies.py

@@ -17,14 +17,53 @@
 import nibabel as nib
 from PIL import Image
 from math import floor
+from natsort import natsorted
 matplotlib.use('Agg')
 plt.style.use('dark_background')
 
 os.environ['MPLCONFIGDIR'] = os.getcwd() + "/configs/"
 
+DATA_DIR = sys.argv[1]
+
 
 # Functions
 
+def create_MEG_thumbnail():
+    """
+    Generate a simple visualization of the MEG data.
+    """
+    import mne.viz
+
+    uploaded_json_list = natsorted(pd.read_csv("list", header=None, lineterminator='\n').to_numpy().flatten().tolist())
+
+    MEG_extensions = [".ds", ".fif", ".sqd", ".con", ".raw", ".ave", ".mrk", ".kdf", ".mhd", ".trg", ".chn", ".dat"]
+
+    """
+    Get the MEG data organized
+    """
+    data_files = [x.split("./")[-1] for x in uploaded_json_list]
+    MEG_data_files = []
+    for data in data_files:
+        if any(x in data for x in MEG_extensions):
+            MEG_data_files.append(data)
+
+    if len(MEG_data_files):
+        for meg in MEG_data_files:
+            fname = f"{DATA_DIR}/{meg}"
+            raw = mne.io.read_raw(fname, verbose=0)
+            mne.viz.set_browser_backend('matplotlib', verbose=None)
+
+            png_types = ["channels", "psd"]
+            for png_type in png_types:
+                output_file = fname.split(".")[0] + f"_{png_type}.png"
+
+                if png_type == "channels":
+                    fig = raw.plot()
+                elif png_type == "psd":
+                    fig = raw.compute_psd().plot()
+
+                fig.savefig(output_file, bbox_inches='tight')
+
 
 def create_thumbnail(nifti_file, image):
     """
@@ -118,7 +157,7 @@ def create_DWIshell_thumbnails(nifti_file, image, bval_file):
 
         w, h, d = buf.shape
         png = Image.frombytes("RGBA", (w, h), buf.tobytes())
-        png.save("{}_shell-{}.png".format(output_file, bval))
+        png.save(f"{output_file}_shell-{bval}.png")
 
 
 # Begin:
@@ -133,14 +172,16 @@ def create_DWIshell_thumbnails(nifti_file, image, bval_file):
 print(nifti_file)
 print("")
 
-if not os.path.isfile("{}/{}".format(data_dir, nifti_file)):  # no corresponding nifti, so don't process
-    print("{} does not have a corresponding NIfTI file, cannot process".format(json_file))
+create_MEG_thumbnail()
+
+if not os.path.isfile(f"{data_dir}/{nifti_file}"):  # no corresponding nifti, so don't process
+    print(f"{json_file} does not have a corresponding NIfTI file, cannot process")
 else:
     output_dir = nifti_file.split(".nii.gz")[0]
     image = nib.load(nifti_file)
 
     if len([x for x in image.shape if x < 0]):  # image has negative dimension(s), cannot process
-        print("{} has negative dimension(s), cannot process".format(nifti_file))
+        print(f"{nifti_file} has negative dimension(s), cannot process")
     else:
         # if image.get_data_dtype() == [('R', 'u1'), ('G', 'u1'), ('B', 'u1')]:
         if image.get_data_dtype() not in ["<i2", "<u2", "<f4", "int16", "uint16"]:
@@ -155,7 +196,7 @@ def create_DWIshell_thumbnails(nifti_file, image, bval_file):
             # object_img_array = image.dataobj[:]
 
             bval_file = json_file.split(".json")[0].split("./")[-1] + ".bval"
-            if not os.path.isfile("{}/{}".format(data_dir, bval_file)):
+            if not os.path.isfile(f"{data_dir}/{bval_file}"):
                 bval_file = "n/a"
             else:
                 bvals = [x.split(" ") for x in pd.read_csv(bval_file).columns.tolist()][0]
@@ -167,14 +208,14 @@ def create_DWIshell_thumbnails(nifti_file, image, bval_file):
             # Create thumbnail
             if nifti_file != "n/a":
                 print("")
-                print("Creating thumbnail for {}".format(nifti_file))
+                print(f"Creating thumbnail for {nifti_file}")
                 print("")
                 create_thumbnail(nifti_file, image)
 
             # Create thumbnail of each DWI's unique shell
             if bval_file != "n/a":
                 print("")
-                print("Creating thumbnail(s) for each DWI shell in {}".format(nifti_file))
+                print(f"Creating thumbnail(s) for each DWI shell in {nifti_file}")
                 print("")
                 create_DWIshell_thumbnails(nifti_file, image, bval_file)