create_subjects_mne_objects_dict breaks if just_HG_ev1_rescaled parameter is set to False

[jimzhang629]

def create_subjects_mne_objects_dict(subjects, epochs_root_file, conditions, task, just_HG_ev1_rescaled=False, LAB_root=None, acc_trials_only=True):
    """
    Adjusted to handle multiple conditions per output name, with multiple condition columns.

    Parameters:
    - subjects: List of subject IDs.
    - output_names_conditions: Dictionary where keys are output names and values are dictionaries
        of condition column names and their required values.
    - task: Task identifier.
    - combined_data: DataFrame with combined behavioral and trial information.
    - acc_array: dict of numpy arrays of 0 for incorrect and 1 for correct trials for each subject
    - LAB_root: Root directory for data (optional).
    """
    subjects_mne_objects = {}

    for sub in subjects:
        print(f"Loading data for subject: {sub}")
        sub_mne_objects = {}

        mne_objects = load_mne_objects(sub, epochs_root_file, task, just_HG_ev1_rescaled=just_HG_ev1_rescaled, LAB_root=LAB_root)
        for mne_object in mne_objects.keys():
            if acc_trials_only == True:
                mne_objects[mne_object] = mne_objects[mne_object]["Accuracy1.0"] # this needs to be done for all the epochs objects I think. So loop over them. Unless it's set to just_HG_ev1_rescaled.

            for condition_name, condition_parameters in conditions.items():
                print(f"  Loading condition: {condition_name} with parameters: {condition_parameters}")
                # Get BIDS events from the conditions, and remove it so it doesn't complicate future analyses.
                bids_events = condition_parameters.get("BIDS_events")
                if bids_events is None:
                    print(f"Warning: condition {condition_name} is missing 'BIDS_events'. Fix this!")
                # if multiple bids events are part of this condition, concatenate their epochs. Otherwise just grab epochs.
                if isinstance(bids_events, list):
                    combined_epochs = []
                    for event in bids_events:
                        partial_event_epochs = mne_objects[mne_object][event]
                        combined_epochs.append(partial_event_epochs)
                    event_epochs = mne.concatenate_epochs(combined_epochs)
                else:
                    event_epochs = mne_objects[mne_object][bids_events]

                sub_mne_objects[condition_name] = {}
                sub_mne_objects[condition_name][mne_object] = event_epochs
            subjects_mne_objects[sub] = sub_mne_objects

    return subjects_mne_objects

This is because the Evoked object is not subscriptable using the [Accuracy1.0] BIDS naming, as seen below.
mne_objects[mne_object] = mne_objects[mne_object]["Accuracy1.0"] # this needs to be done for all the epochs objects I think. So loop over them. Unless it's set to just_HG_ev1_rescaled.