64 lines
2.1 KiB
Python
64 lines
2.1 KiB
Python
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import numpy as np
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from mvector.utils.logger import setup_logger
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logger = setup_logger(__name__)
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class TprAtFpr(object):
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def __init__(self, max_fpr=0.01):
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self.pos_score_list = []
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self.neg_score_list = []
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self.max_fpr = max_fpr
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def add(self, y_labels, y_scores):
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for y_label, y_score in zip(y_labels, y_scores):
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if y_label == 0:
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self.neg_score_list.append(y_score)
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else:
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self.pos_score_list.append(y_score)
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def reset(self):
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self.pos_score_list = []
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self.neg_score_list = []
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def calculate_eer(self, tprs, fprs):
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# 记录所有的eer值
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eer_list = []
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n = len(tprs)
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eer = 1.0
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index = 0
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for i in range(n):
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eer_list.append(fprs[i] + (1 - tprs[i]))
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if fprs[i] + (1 - tprs[i]) < eer:
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eer = fprs[i] + (1 - tprs[i])
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index = i
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return eer, index,eer_list
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def calculate(self):
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tprs, fprs, thresholds = [], [], []
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pos_score_list = np.array(self.pos_score_list)
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neg_score_list = np.array(self.neg_score_list)
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if len(pos_score_list) == 0:
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msg = f"The number of positive samples is 0, please add positive samples."
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logger.warning(msg)
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return tprs, fprs, thresholds, None, None
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if len(neg_score_list) == 0:
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msg = f"The number of negative samples is 0, please add negative samples."
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logger.warning(msg)
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return tprs, fprs, thresholds, None, None
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for i in range(0, 100):
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threshold = i / 100.
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tpr = np.sum(pos_score_list > threshold) / len(pos_score_list)
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fpr = np.sum(neg_score_list > threshold) / len(neg_score_list)
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tprs.append(tpr)
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fprs.append(fpr)
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thresholds.append(threshold)
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eer, index,eer_list = self.calculate_eer(fprs=fprs, tprs=tprs)
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# 根据对应的eer_list输出所有对应的阈值
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for i in range(len(eer_list)):
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print(f"threshold: {thresholds[i]}, eer: {eer_list[i]}")
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return tprs, fprs, thresholds, eer, index
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