Tabulating_eegip_events_washington.py

Tabulating_eegip_events_washington.py

import numpy as np
import mne
import pandas as pd
from pathlib import Path
root = Path("/home/oreillyc/projects/def-emayada/eegip/washington/derivatives/lossless/")
results = {"subjects": [],
           "ages": []}
for age in ["06", "12", "18"]:
    for path in root.glob(f"sub-s*/ses-m{age}/eeg/sub-s*_ses-m{age}_*_eeg_qcr.set"):
        print(path)
        results["subjects"].append(str(path)[-35:-32])
        results["ages"].append(age)
        raw = mne.io.read_raw_eeglab(path)
        event_names, counts = np.unique([annot["description"] for annot in raw.annotations], return_counts=True)
        event_counts = dict(list(zip(event_names, counts)))
        for event_name in event_names:
            if event_name not in results:
                if len(results["ages"]) == 1:
                    results[event_name] = []
                else:
                    results[event_name] = [0]*(len(results["ages"])-1)  
        for event_name in results:
            if event_name in ["ages", "subjects"]:
                continue
            if event_name in event_counts:
                results[event_name].append(event_counts[event_name])
            else:
                results[event_name].append(0)

pd.DataFrame(results).sort_values(["ages", "subjects"]).to_csv("event_counts_washington.csv")