simple version of auc roc calculate

simple_roc_curve.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

'''
simple version of auc roc calculate
'''

import numpy as np

def area(x, y):
    '''
    reference: https://en.wikipedia.org/wiki/Trapezoidal_rule
    print fpr
    print tpr
    '''
    ret = 0
    for i in xrange(1, len(x)):
        ret += (x[i] - x[i-1]) * ((y[i-1] + y[i]) / 2.0)
    return ret

def roc_auc(y_true, y_score, pos_label):
    '''
    y_true: (n, )
    y_score: (n, )
    pos_label: label of postive class
    '''
    y_true = np.array(y_true)
    y_score = np.array(y_score)
    y_true = (y_true == pos_label)

    # comput fpr and tpr
    desc_index = np.argsort(y_score)[::-1]
    y_score = y_score[desc_index]
    y_true = y_true[desc_index]
    # threshold is y_score[i]
    # score <= y_score[i] compute true pos num (tps[i])
    # and false pos num (fps[i])
    tps = np.cumsum(y_true)
    fps = 1 + np.arange(len(y_true)) - tps
    fpr = fps/float(fps[-1])
    tpr = tps/float(tps[-1])

    # reorder fpr and tpr according to fpr increase
    incr_index = np.argsort(fpr)
    fpr = fpr[incr_index]
    tpr = tpr[incr_index]
    # calculate area under roc
    return area(fpr, tpr)