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#!/usr/bin/env python3

# -*- coding: utf-8 -*-

# Author: xurongzhong#126.com wechat:pythontesting qq:37391319

# CreateDate: 2018-1-8

# data_common.py

import multiprocessing

import os

import sys

import multiprocessing

import bisect

import numpy as np

from sklearn.metrics import roc_curve

from data_common import output_file

def compute_roc_part(worker_id, scores, meta1, meta2, delta, thres, tp, fp, total_pos_neg):

labels = (meta1.reshape(-1,1) == meta2.reshape(1,-1)).astype(np.int)

if delta != -1:

indices = np.triu_indices(delta, k=1)

scores = scores[indices]

labels = labels[indices]

else:

scores = scores.reshape(-1)

labels = labels.reshape(-1)

sorted_idx = np.argsort(scores)

sorted_scores = scores[sorted_idx]

sorted_labels = labels[sorted_idx]

cum_pos = np.cumsum(sorted_labels, dtype=float)

total_pos = cum_pos[-1]

n = labels.size

fn = cum_pos - sorted_labels

tp_tmp = total_pos - fn

fp_tmp = np.arange(n, 0, -1) - tp_tmp

c_tp = [0]*len(thres)

c_fp = [0]*len(thres)

start = 0

for i, th in enumerate(thres):

#'Find rightmost value less than or equal to x'

pos = bisect.bisect_right(sorted_scores, th, start)

if pos != len(sorted_scores):

c_tp[i] = tp_tmp[pos]

c_fp[i] = fp_tmp[pos]

start = pos

else:

c_tp[i] = total_pos

c_fp[i] = 0

total_pos_neg[worker_id] = np.array([total_pos, n - total_pos])

tp[worker_id] = c_tp

fp[worker_id] = c_fp

def roc(score,label, fprs=[0.40+0.01*p for p in np.arange(1,10)],

output='output/roc.txt'):

scores = np.loadtxt(score, dtype=np.float32, delimiter='\n')

labels = np.loadtxt(label, dtype=np.int32, delimiter='\n')

assert(len(scores) == len(labels))

score = scores

scores = scores[score >= 0]

labels = labels[score >= 0]

roc_fpr, roc_tpr, roc_thresholds = roc_curve(labels, scores, pos_label=1, drop_intermediate=False)

tpr_k_score = []

th_k_score = []

for fpr_ratio in fprs:

idx = np.argmin(np.abs(roc_fpr - fpr_ratio))

tpr = roc_tpr[idx]

th = roc_thresholds[idx]

tpr_k_score.append(tpr)

th_k_score.append(th)

if output == sys.stdout:

f = output

else:

f = open(output, 'w')

print("fpr | "+" | ".join('{:.2f}'.format(i) for i in fprs),file=f)

print("|".join(" :-: " for i in range(len(fprs)+1)),file=f)

print("tpr(%) | "+" | ".join('{:.2f}'.format(i*100) for i in tpr_k_score),file=f)

print("thres | "+" | ".join('{:.3f}'.format(i) for i in th_k_score),file=f)

if output != sys.stdout:

f.close()

return output

def verify_roc(score,label,output='output/roc.txt',one_vs_one=False):

print(score)

print(label)

fprs = [10**(-p) for p in np.arange(1, 7, 1.)]

thres = np.arange(0, 1, 1e-3)

th_idx = range(650, 850, 10)

fprs = [10**(-p) for p in np.arange(1, 7, 1.)]

score = np.fromfile(score, dtype=np.float32)

max_step = 2000

pool = multiprocessing.Pool(multiprocessing.cpu_count())

mgr = multiprocessing.Manager()

if one_vs_one:

label = np.loadtxt(label, dtype=np.int, delimiter=',').reshape(-1)[1:]

n = label.shape[0]

assert(len(score) == n*n)

score = score.reshape(n, n)

i_range = (n-1)//max_step+1

total_num = i_range * (i_range + 1) / 2

tp = mgr.list(range(total_num))

fp = mgr.list(range(total_num))

total_pos_neg = mgr.list(range(total_num))

worker_id = 0

for i in range(i_range):

beg_i = i*max_step

end_i = min(beg_i + max_step, n)

for j in range(i, (n-1)//max_step+1):

delta = -1

beg_j = j*max_step

end_j = min(beg_j + max_step, n)

if i == j:

assert end_i-beg_i == end_j-beg_j

delta = end_i-beg_i

score_part = score[beg_i:end_i,beg_j:end_j]

meta1 = label[beg_i:end_i]

meta2 = label[beg_j:end_j]

pool.apply_async(compute_roc_part, args=(worker_id, score_part, meta1, meta2, delta, thres, tp, fp, total_pos_neg))

worker_id += 1

else:

with open(label, 'r') as f:

lines = f.readlines()

assert(len(lines) == 2)

label_enroll = np.fromstring(lines[0].strip(), sep=' ', dtype=int)

label_real = np.fromstring(lines[1].strip(), sep=' ', dtype=int)

assert(len(score) == len(label_enroll) * len(label_real))

score = score.reshape(len(label_enroll), len(label_real))

total_num = (label_real.shape[0]-1)//max_step+1

tp = mgr.list(range(total_num))

fp = mgr.list(range(total_num))

total_pos_neg = mgr.list(range(total_num))

worker_id = 0

for beg_j in range(0, label_real.shape[0], max_step):

end_j = min(beg_j + max_step, label_real.shape[0])

label_real_part = label_real[beg_j:end_j]

score_part = score[:, beg_j:end_j]

pool.apply_async(compute_roc_part, args=(worker_id, score_part, label_enroll, label_real_part, -1, thres, tp, fp, total_pos_neg))

worker_id += 1

pool.close()

pool.join()

tp = np.sum(tp, axis=0)

fp = np.sum(fp, axis=0)

total_pos_neg = np.sum(total_pos_neg, axis=0)

tpr = tp/total_pos_neg[0]

fpr = fp/total_pos_neg[1]

csvnp = np.array([thres, 1-tpr, fpr]).T

np.savetxt('roc.csv', csvnp, fmt='%.4f,%1.4e,%1.4e')

tpr_k_score = []

th_k_score = []

for fp in fprs:

idx = np.argmin(np.abs(fpr-fp))

tpr_k_score.append(tpr[idx])

th_k_score.append(thres[idx])

with open(output, 'w') as f:

print("fpr | "+" | ".join(format(i, '>5.0e') for i in fprs), file=f)

print("|".join(" :-: " for i in range(len(fprs)+1)), file=f)

print("tpr(%) | "+" | ".join('{:>5.2f}'.format(i*100) for i in tpr_k_score), file=f)

print("thres | "+" | ".join('{:>5.3f}'.format(i) for i in th_k_score), file=f)

print("======================================================")

print("thres | "+" | ".join('{:>5.3f}'.format(i) for i in thres[th_idx]), file=f)

print("|".join(" :-: " for i in range(len(th_idx)+1)), file=f)

print("fpr(‰) | "+" | ".join('{:>5.2f}'.format(i*1000) for i in fpr[th_idx]), file=f)

print("tpr(%) | "+" | ".join('{:>5.2f}'.format(i*100) for i in tpr[th_idx]), file=f)