def f1_score()

in src/utils/str.py [0:0]

• 15 lines of code
• 2 McCabe index (conditional complexity)

def f1_score(prediction, ground_truth, term='f1score'):
    normalized_prediction = normalize_statement(prediction)
    normalized_ground_truth = normalize_statement(ground_truth)

    prediction = normalized_prediction.split()
    ground_truth = normalized_ground_truth.split()

    res_dict = {'f1score': 0, 'recall': 0, 'precision': 0, 'all': [0, 0, 0]}

    common = Counter(prediction) & Counter(ground_truth)
    num_same = sum(common.values())
    if num_same != 0:
        precision = 1.0 * num_same / len(prediction)
        recall = 1.0 * num_same / len(ground_truth)
        f1 = (2 * precision * recall) / (precision + recall)

        res_dict['precision'], res_dict['recall'], res_dict['f1score'] = precision, recall, f1
        res_dict['all'] = [precision, recall, f1]
    
    return res_dict[term]