TEXTOIR-main/open_intent_detection/utils/metrics.py

import numpy as np 

def F_measure(cm):
    idx = 0
    rs, ps, fs = [], [], []
    n_class = cm.shape[0]
    
    for idx in range(n_class):
        TP = cm[idx][idx]
        r = TP / cm[idx].sum() if cm[idx].sum() != 0 else 0
        p = TP / cm[:, idx].sum() if cm[:, idx].sum() != 0 else 0
        f = 2 * r * p / (r + p) if (r + p) != 0 else 0
        rs.append(r * 100)
        ps.append(p * 100)
        fs.append(f * 100)
        
    f = np.mean(fs).round(4)
    f_seen = np.mean(fs[:-1]).round(4)
    f_unseen = round(fs[-1], 4)
    
    results = {}
    results['F1-known'] = f_seen
    results['F1-open'] = f_unseen
    results['F1'] = f
    
    return results