Merge pull request #54 from Ian-Goodall-Halliwell/main

Added more compatibility options and w-scoring, with report changes

run_3T_test.sh

@@ -0,0 +1,54 @@
+#!/bin/bash
+
+# Enable error handling
+set -e
+
+# Set the path to the dataset, or the folder containing the 'derivatives' folder
+pth_dataset_ref="/data/mica3/BIDS_MICs"
+pth_dataset="/data/mica3/BIDS_PNI"
+# Set the directories for micapipe, hippunfold, and zbrains, which will be looked for in the 'derivates' folder
+zbrains_dir="zbrains_clinical"
+zbrains_dir_ref="zbrains_clinical"
+micapipe_dir="micapipe_v0.2.0"
+hippunfold_dir="hippunfold_v1.3.0"
+
+# Set the paths to the demographic control and patient files
+# The demo_controls are only needed for the analysis, and define the control samples to compare against.
+# The demo_patients can be provided if desired, which will run all the patients in the list when the "all" keyword is used,
+# otherwise the 'all' keyword will run every patient possible, given the micapipe and hippunfold availability, or, for the analysis
+# it will run on all patients who have had zbrains proc run before.
+# demo_controls="/host/oncilla/local_raid/oualid/zbrains_csvs/participants_mics_hc.csv"
+demo_controls="/data/mica1/03_projects/ian/participants_7T_hc.csv"
+# Set the subject IDs and session IDs to 'all', using all patients defined in the PX_participants file.
+subject_ids="sub-PNE006"
+session_ids="all"
+
+# The code below runs zbrains preserving the old behaviour, with a smooth_ctx of 10, a smooth_hip of 5, and a label_ctx of 'white'
+# The new defaults for this are a smooth_ctx of 5, a smooth_hip of 2, and a label_ctx of 'midthickness'
+# Much of the new volumetric code is dependent on cortical midthickness, so it is recommended.
+./zbrains --run "proc analysis"\
+        --sub "${subject_ids}" \
+        --ses "${session_ids}" \
+        --dataset ${pth_dataset} \
+        --zbrains ${zbrains_dir} \
+        --micapipe ${micapipe_dir} \
+        --hippunfold ${hippunfold_dir} \
+        --dataset_ref ${pth_dataset} \
+        --zbrains_ref ${zbrains_dir} \
+        --demo_ref ${demo_controls} \
+        --column_map participant_id=ID session_id=SES \
+        --smooth_ctx 10 \
+        --smooth_hip 5 \
+        --n_jobs 4 \
+        --n_jobs_wb 4 \
+        --label_ctx "white" \
+	--wb_path /usr/bin/ \
+        --verbose 2 \
+	--control_prefix "PNC" \
+        --volumetric 0 \
+        --dicoms 0 \
+        --pyinit=/data/mica1/03_projects/ian/anaconda3 
+
+
+# Pause to keep the terminal open (optional, remove if not needed)
+read -p "Press any key to continue..."

run_norm.sh

@@ -0,0 +1,52 @@
+#!/bin/bash
+
+# Enable error handling
+set -e
+
+# Set the path to the dataset, or the folder containing the 'derivatives' folder
+pth_dataset="/data/mica3/BIDS_MICs"
+# Set the directories for micapipe, hippunfold, and zbrains, which will be looked for in the 'derivates' folder
+zbrains_dir="wbrains"
+micapipe_dir="micapipe_v0.2.0"
+hippunfold_dir="hippunfold_v1.3.0"
+
+# Set the paths to the demographic control and patient files
+# The demo_controls are only needed for the analysis, and define the control samples to compare against.
+# The demo_patients can be provided if desired, which will run all the patients in the list when the "all" keyword is used,
+# otherwise the 'all' keyword will run every patient possible, given the micapipe and hippunfold availability, or, for the analysis
+# it will run on all patients who have had zbrains proc run before.
+demo_controls="/host/oncilla/local_raid/oualid/zbrains_csvs/participants_mics_hc.csv"
+demo="/host/verges/tank/data/ian/participants_mics_px.csv"
+# Set the subject IDs and session IDs to 'all', using all patients defined in the PX_participants file.
+subject_ids="sub-PX010"
+session_ids="all"
+
+# The code below runs zbrains preserving the old behaviour, with a smooth_ctx of 10, a smooth_hip of 5, and a label_ctx of 'white'
+# The new defaults for this are a smooth_ctx of 5, a smooth_hip of 2, and a label_ctx of 'midthickness'
+# Much of the new volumetric code is dependent on cortical midthickness, so it is recommended.
+./zbrains --run "analysis"\
+        --sub "${subject_ids}" \
+        --ses "${session_ids}" \
+        --dataset ${pth_dataset} \
+        --zbrains ${zbrains_dir} \
+        --micapipe ${micapipe_dir} \
+        --hippunfold ${hippunfold_dir} \
+        --dataset_ref ${pth_dataset} \
+        --zbrains_ref ${zbrains_dir} \
+	--demo ${demo} \
+	--demo_ref ${demo_controls} \
+        --column_map participant_id=ID session_id=SES \
+        --smooth_ctx 10 \
+        --smooth_hip 5 \
+        --n_jobs 4 \
+        --n_jobs_wb 4 \
+        --label_ctx "white" \
+	--wb_path /usr/bin/ \
+        --verbose 2 \
+        --volumetric 0 \
+        --dicoms 0 \
+        --pyinit=/data/mica1/03_projects/ian/anaconda3 \
+	--normative "age sex" 
+
+# Pause to keep the terminal open (optional, remove if not needed)
+read -p "Press any key to continue..."

src/functions/blurring.py

@@ -60,7 +60,7 @@ def compute_blurring(
         [midthicknessDataArr, midthicknessSurfaceArr],
         [wmBoundaryDataArr, wmBoundarySurfaceArr],
     ]
-    for dist in ["1", "2", "3"]:
+    for dist in ["1", "2"]:
         whiteMatterDataArr = load_gifti_data(
             f"{input_dir}/{bids_id}_hemi-{hemi}_surf-fsnative_label-swm{dist}.0mm_{feat}.func.gii"
         )

src/functions/clinical_reports.py

@@ -558,8 +558,8 @@ def _load_data_sctx(
     x = pd.read_csv(sctx_file, header=[0], index_col=0).to_numpy().ravel()
     if threshold is not None:
         x[np.abs(x) < threshold] *= threshold_alpha
-    if analysis == "asymmetry":
-        print("e")
+    # if analysis == "asymmetry":
+    #     print("e")
     # Array of data
     array_16 = np.full(16, np.nan)
     array_16[0:7] = x[0:7]
@@ -1033,7 +1033,7 @@ def generate_clinical_report(
     label_hip="midthickness",
     color_bar="bottom",
     cmap="cmo.balance",
-    color_range=(-2, 2),
+    color_range=(-3, 3),
     cmap_asymmetry="cmo.balance_r",
     tmp_dir: PathType = "/tmp",
     subject_dir=None,

src/functions/help.py

@@ -132,7 +132,7 @@
                                                         unless indicated otherwise (e.g., --column_map site=center)                 
 \t{gcolor}--n_jobs{nc} [number]         : Number of jobs to run in parallel. Default is {bcolor}1{nc}.
 \t{gcolor}--wb_path{nc} [path]          : Path to the Connectome Workbench binaries. Default is {bcolor}/data/mica1/01_programs/workbench-1.4.2/bin_linux64{nc}.
-\t{gcolor}--patient_prefix{nc} [prefix] : Prefix to use when determining patients versus controls. Default is {bcolor}PX{nc}.
+\t{gcolor}--control_prefix{nc} [prefix] : Prefix to use when determining patients versus controls. Default is {bcolor}PX{nc}.
 \t{gcolor}--delete_temps{nc} [bool]     : If set to True, will delete any ragged temp files left from crashed analyses, then exit. Default is {bcolor}False{nc}.
 \t{gcolor}--verbose{nc} [level]         : Verbosity level (default is {bcolor}-1{nc}). Levels:
                                     - 0             : Only errors

src/functions/run_analysis.py

@@ -87,9 +87,15 @@ def main(
     }
 
     # Rename covariates for normative modeling
-    cov_normative = normative
+    cov_normative = (
+        (normative.split(" ") if " " in normative else normative.split("-"))
+        if normative is not None
+        else None
+    )
     if cov_normative is not None:
-        cov_normative = [actual_to_expected.get(col, col) for col in cov_normative]
+        cov_normative = [
+            actual_to_expected.get(col, col).upper() for col in cov_normative
+        ]
 
     # Rename covariates for deconfounding
     cov_deconfound = deconfound
@@ -113,10 +119,10 @@ def main(
     px_demo = None
     if demo is not None:
         px_demo = load_demo(demo, rename=actual_to_expected, dtypes=col_dtypes, tmp=tmp)
-        px_demo = px_demo.loc[(px_demo["participant_id"] == px_id)]
-        # px_demo = px_demo.loc[
-        #     (px_demo["participant_id"] == px_id) & (px_demo["session_id"] == px_ses)
-        # ]
+        # px_demo = px_demo.loc[(px_demo["participant_id"] == px_id)]
+        px_demo = px_demo.loc[
+            (px_demo["participant_id"] == px_id) & (px_demo["session_id"] == px_ses)
+        ]
 
         # If no such row exists, create an empty DataFrame with the same columns
         if px_demo.empty:
@@ -168,7 +174,7 @@ def main(
             struct,
             smooth_ctx,
             smooth_hip,
-            zbrains_ref,
+            zbrains,
             px_id,
             px_ses,
             px_demo,
@@ -197,9 +203,10 @@ def main(
     print(lab_ctx, lab_hip)
     age = None
     sex = None
+    print(px_demo)
     if px_demo is not None:
-        age = px_demo.iloc[0].get("age", None)
-        sex = px_demo.iloc[0].get("sex", None)
+        age = px_demo["AGE"]
+        sex = px_demo["SEX"]
 
     feat_ctx = available_features["cortex"][res_ctx][lab_ctx]
     feat_sctx = available_features["subcortex"]
@@ -242,7 +249,7 @@ def main(
         label_ctx=lab_ctx,
         label_hip=lab_hip,
         tmp_dir=tmp,
-        feature_means=feature_means
+        feature_means=feature_means,
     )
 
 
@@ -393,9 +400,10 @@ def handle_unhandled_exception(exc_type, exc_value, exc_traceback):
     args.labels_ctx = eval(args.labels_ctx)
     args.struct = args.struct.split("-")
     args.feat = args.feat.split("-")
-    args.demo_ref = args.demo_ref.split("-")
+    args.demo_ref = args.demo_ref.split("¥")
     args.zbrains_ref = args.zbrains_ref.split("-")
     args.resolution = args.resolution.split("-")
+
     print(args.labels_ctx)
     run(
         subject_id=args.subject_id,

src/functions/surface_to_volume.py

@@ -380,13 +380,13 @@ def process_cortex(
     ]
 
     # Run the commands
-    subprocess.run(command_struct)
+    subprocess.run(command_struct, shell=True)
     # subprocess.run(command_struct_native)
 
-    subprocess.run(command1)
-    subprocess.run(command_struct_2)
-    subprocess.run(command2)
-    subprocess.run(command3)
+    subprocess.run(command1, shell=True)
+    subprocess.run(command_struct_2, shell=True)
+    subprocess.run(command2, shell=True)
+    subprocess.run(command3, shell=True)
     os.replace(
         f"{tmp}/{feature}_{analysis}_{struct}_{smooth}_{hemi}_temp.nii.gz",
         f"{outdir}/{subj}_{ses}_hemi-{hemi}_surf-fsLR-32k_label-midthickness_feature-{feature}_smooth-{smooth}_analysis-{analysis}.nii.gz",
@@ -1015,7 +1015,7 @@ def surface_to_volume(
         None
     """
     rootfolder = os.path.join(rootfolder, "derivatives")
-    zbrainsdir = zbrainsdir[0]
+    # zbrainsdir = zbrainsdir
     smooth_ctx = f"{str(smooth_ctx)}mm"
     smooth_hipp = f"{str(smooth_hipp)}mm"