validation.py

import numpy as np


#Method to compute the accruarcy. Call predict_labels to get the labels for the dataset
def compute_f1(predictions, correct, idx2Label): 
    label_pred = []    
    for sentence in predictions:
        label_pred.append([idx2Label[element] for element in sentence])
        
    label_correct = []    
    for sentence in correct:
        label_correct.append([idx2Label[element] for element in sentence])
            
    
    #print label_pred
    #print label_correct
    
    prec = compute_precision(label_pred, label_correct)
    rec = compute_precision(label_correct, label_pred)
    
    f1 = 0
    if (rec+prec) > 0:
        f1 = 2.0 * prec * rec / (prec + rec);
        
    return prec, rec, f1

def compute_precision(guessed_sentences, correct_sentences):
    assert(len(guessed_sentences) == len(correct_sentences))
    correctCount = 0
    count = 0
    
    
    for sentenceIdx in range(len(guessed_sentences)):
        guessed = guessed_sentences[sentenceIdx]
        correct = correct_sentences[sentenceIdx]
        assert(len(guessed) == len(correct))
        idx = 0
        while idx < len(guessed):
            if guessed[idx][0] == 'B': #A new chunk starts
                count += 1
                
                if guessed[idx] == correct[idx]:
                    idx += 1
                    correctlyFound = True
                    
                    while idx < len(guessed) and guessed[idx][0] == 'I': #Scan until it no longer starts with I
                        if guessed[idx] != correct[idx]:
                            correctlyFound = False
                        
                        idx += 1
                    
                    if idx < len(guessed):
                        if correct[idx][0] == 'I': #The chunk in correct was longer
                            correctlyFound = False
                        
                    
                    if correctlyFound:
                        correctCount += 1
                else:
                    idx += 1
            else:  
                idx += 1
    
    precision = 0
    if count > 0:    
        precision = float(correctCount) / count
        
    return precision