Issue with Shape of X_all in getListAgeDays Function for BraTS20 Dataset

Question

I'm currently working on a project involving the BraTS20 dataset for brain tumor analysis. I'm facing an issue when trying to retrieve the shape of the calculated features in the getListAgeDays function. Here is the code : # create only age: category data

# id: age, categories
def getListAgeDays(id_list):
    x_val = []
    y_val = []
    for i in id_list:
        if (i not in age_dict):
            continue
        masks = getMaskSizesForVolume(nib.load(TRAIN_DATASET_PATH + f'BraTS20_Training_{i[-3:]}/BraTS20_Training_{i[-3:]}_seg.nii').get_fdata())
        brain_vol = getBrainSizeForVolume(nib.load(TRAIN_DATASET_PATH + f'BraTS20_Training_{i[-3:]}/BraTS20_Training_{i[-3:]}_t1.nii').get_fdata())
        masks[1] = masks[1]/brain_vol
        masks[2] = masks[2]/brain_vol
        masks[3] = masks[3]/brain_vol
        merged=[age_dict[i],masks[1],masks[2],masks[3]] ## add segments
        x_val.append(merged) 
        if (days_dict[i] < 250):
            y_val.append([1,0,0])
        elif (days_dict[i] >= 250 and days_dict[i] < 450):
            y_val.append([0,1,0])
        else:
            y_val.append([0,0,1])
            
    return np.array(x_val), np.array(y_val)

X_all, y_all = getListAgeDays(train_and_test_ids)

print(f'X_test: {X_all.shape}')
df = pd.DataFrame(np.concatenate((X_all, y_all), axis=1) , columns = ["age",f"{SEGMENT_CLASSES[1]}",f"{SEGMENT_CLASSES[2]}",f"{SEGMENT_CLASSES[3]}","short","medium","long"])
df.head()

The expected output is below:

enter image description here

But the ouput is:

 (array([], dtype=float64), array([], dtype=float64))
X_test: (0,)

Spyder variable explored image is here: enter image description here

I have verified that the inputs to the function (train_and_test_ids, age_dict, days_dict, etc.) are correctly defined and contain data. However, the shape of X_all is not as expected.

I would appreciate any insights or suggestions on why the shape of X_all is not being correctly calculated. Thank you!