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model_monitoring_monthly
Commit a7f74ece authored by 舒皓月's avatar 舒皓月
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... 2019 07 28

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\ No newline at end of file
model_monitor_PSI_AUC.py
View file @ a7f74ece
...@@ -23,7 +23,8 @@ warnings.filterwarnings('ignore') ...@@ -23,7 +23,8 @@ warnings.filterwarnings('ignore')
class ModelMonitor: class ModelMonitor:
def __init__(self, excel_path='./model_score.xlsx', sheet_name='mongo_model', def __init__(self, excel_path='./model_score.xlsx', sheet_name='mongo_model',
passdue_day=15, save_path='./image/', passdue_day=15, save_path='./image/',
num_month=4, min_user_group=500, max_psi=0.1, min_aucr=0.85): num_month=4, min_user_group=500, max_psi=0.1, min_aucr=0.85,
if_save=True, if_load=False):
# 考虑到数据库配置基本不变, 所以不设置创建对象时对应输入变量. # 考虑到数据库配置基本不变, 所以不设置创建对象时对应输入变量.
self.mysql_engine = pymysql.connect(host='172.20.6.9', self.mysql_engine = pymysql.connect(host='172.20.6.9',
...@@ -82,6 +83,13 @@ class ModelMonitor: ...@@ -82,6 +83,13 @@ class ModelMonitor:
self.na_enough_data_psi_set = set() # 一些新的模型没有足够数据用于统计. self.na_enough_data_psi_set = set() # 一些新的模型没有足够数据用于统计.
self.na_enough_data_auc_set = set() # 一些新的模型没有足够数据用于统计. self.na_enough_data_auc_set = set() # 一些新的模型没有足够数据用于统计.
self.filed_bench_bins_ratio = None # 每个模型分在总体样本上第一个月的分箱比例.
self.filed_bench_auc = None # 每个模型分在总体样本上第一个月的AUC
# 程序数据读写模式.
self.if_save = if_save # 是否保存从数据库抽取的数据.
self.if_load = if_load # 是否从保存的数据加载数据, 而不从数据库读取.
def sql_query(self, sql): def sql_query(self, sql):
''' '''
连接MySQL数据库, 根据SQL返回数据. 连接MySQL数据库, 根据SQL返回数据.
...@@ -140,16 +148,11 @@ class ModelMonitor: ...@@ -140,16 +148,11 @@ class ModelMonitor:
def calc_psi(self, array_1, array_2): def calc_psi(self, array_1, array_2):
''' '''
计算PSI. 计算PSI.
:param array_1: pd.Series :param array_1: array
:param array_2: pd.Series :param array_2: array
:return: PSI :return: PSI
''' '''
try: try:
# print(array_2)
array_1 = array_1.values
array_2 = array_2.values
array_1 = array_1 / array_1.sum()
array_2 = array_2 / array_2.sum()
psi = ((array_1 - array_2) * np.log10(array_1 / array_2)).sum() psi = ((array_1 - array_2) * np.log10(array_1 / array_2)).sum()
return psi return psi
except: except:
...@@ -174,24 +177,33 @@ class ModelMonitor: ...@@ -174,24 +177,33 @@ class ModelMonitor:
df_g = df_g.sort_values(['month_label', 'bins']) df_g = df_g.sort_values(['month_label', 'bins'])
for i, m in enumerate(month_list): for i, m in enumerate(month_list):
amt_in_bins = df_g.loc[df_g['month_label'] == m, field].values amt_in_bins = df_g.loc[df_g['month_label'] == m, field].values
# 某月样本量小于阈值, 放弃记录信息. ## 某月样本量小于阈值, 放弃记录信息.
if amt_in_bins.sum() < self.min_user_group: if amt_in_bins.sum() < self.min_user_group:
print('%d月样本量过小, 放弃提取信息.' % m) print('%d月样本量过小, 放弃提取信息.' % m)
continue continue
info_dict[user_group_name][str(m) + '月'] = {} info_dict[user_group_name][str(m) + '月'] = {}
info_dict[user_group_name][str(m) + '月']['该月样本量'] = amt_in_bins.sum() info_dict[user_group_name][str(m) + '月']['该月样本量'] = amt_in_bins.sum()
info_dict[user_group_name][str(m) + '月']['各分箱样本量'] = amt_in_bins info_dict[user_group_name][str(m) + '月']['各分箱样本量'] = amt_in_bins
info_dict[user_group_name][str(m) + '月']['各分箱样本占比'] = amt_in_bins / amt_in_bins.sum() info_dict[user_group_name][str(m) + '月']['各分箱样本占比'] = np.array([x[0] for x in amt_in_bins / amt_in_bins.sum()])
## 若为某模型分全样本, 则记录分箱比例.
if user_group_name == '全样本' and self.filed_bench_bins_ratio is None:
self.filed_bench_bins_ratio = info_dict[user_group_name][str(m) + '月']['各分箱样本占比']
print('%d月样本量: %d' % (m, info_dict[user_group_name][str(m) + '月']['该月样本量'])) print('%d月样本量: %d' % (m, info_dict[user_group_name][str(m) + '月']['该月样本量']))
# 计算PSI, 以样本量达标的第一个月为基准. # 计算PSI, 以样本量达标的第一个月为基准.
for i, m in enumerate(info_dict[user_group_name]): for i, m in enumerate(info_dict[user_group_name]):
if i == 0: if i == 0:
info_dict[user_group_name][m]['psi'] = 0 if user_group_name == '全样本':
bench_month = m psi = 0
else: else:
psi = self.calc_psi( psi = self.calc_psi(self.filed_bench_bins_ratio, info_dict[user_group_name][m]['各分箱样本占比'])
df_g.loc[df_g['month_label'] == int(bench_month[0]), field], if psi is not None:
df_g.loc[df_g['month_label'] == int(m[0]), field]) info_dict[user_group_name][m]['psi'] = psi
else:
info_dict[user_group_name][m]['psi'] = -999
print('计算PSI出现错误.')
bench_bins_ratio = info_dict[user_group_name][m]['各分箱样本占比']
else:
psi = self.calc_psi(bench_bins_ratio, info_dict[user_group_name][m]['各分箱样本占比'])
if psi: if psi:
info_dict[user_group_name][m]['psi'] = psi info_dict[user_group_name][m]['psi'] = psi
else: else:
...@@ -240,10 +252,12 @@ class ModelMonitor: ...@@ -240,10 +252,12 @@ class ModelMonitor:
except: except:
print('AUC计算发生错误.') print('AUC计算发生错误.')
info_dict[user_group_name][str(m) + '月']['auc'] = -999 info_dict[user_group_name][str(m) + '月']['auc'] = -999
if user_group_name == '全样本' and self.filed_bench_auc is None:
self.filed_bench_auc = info_dict[user_group_name][str(m) + '月']['auc']
for i, m in enumerate(info_dict[user_group_name]): for i, m in enumerate(info_dict[user_group_name]):
if i == 0: # 基准月. if i == 0: # 基准月.
info_dict[user_group_name][m]['aucR'] = 1 info_dict[user_group_name][m]['aucR'] = info_dict[user_group_name][m]['auc'] / self.filed_bench_auc
bench_month = m bench_month = m
else: else:
info_dict[user_group_name][m]['aucR'] = info_dict[user_group_name][m]['auc'] / \ info_dict[user_group_name][m]['aucR'] = info_dict[user_group_name][m]['auc'] / \
...@@ -265,7 +279,7 @@ class ModelMonitor: ...@@ -265,7 +279,7 @@ class ModelMonitor:
for m in range(self.first_month, self.current_month + 1): for m in range(self.first_month, self.current_month + 1):
bins = self.make_bin(df_copy.loc[df_copy['month_label'] == m, field]) bins = self.make_bin(df_copy.loc[df_copy['month_label'] == m, field])
if bins: if bins:
print('以%d月为基准月.' % m) print('%s以%d月为基准月.' % (self.model_feild_name_dict[field], m))
break break
if not bins: if not bins:
self.na_enough_data_psi_set.add(self.model_feild_name_dict[field]) self.na_enough_data_psi_set.add(self.model_feild_name_dict[field])
...@@ -326,6 +340,7 @@ class ModelMonitor: ...@@ -326,6 +340,7 @@ class ModelMonitor:
remove_list.append(user_group_name) remove_list.append(user_group_name)
for user_group_name in remove_list: for user_group_name in remove_list:
del info_dict[user_group_name] del info_dict[user_group_name]
self.filed_bench_bins_ratio = None
# 画图. # 画图.
print('开始画图.') print('开始画图.')
...@@ -334,8 +349,11 @@ class ModelMonitor: ...@@ -334,8 +349,11 @@ class ModelMonitor:
print(self.model_feild_name_dict[field] + '-' + user_group_name) print(self.model_feild_name_dict[field] + '-' + user_group_name)
plt.figure(figsize=(16, 8)) plt.figure(figsize=(16, 8))
for m in info_dict[user_group_name]: for m in info_dict[user_group_name]:
# print(m)
# print(info_dict[user_group_name][m]['psi'])
# print(info_dict[user_group_name][m]['该月样本量'])
plt.plot(range(len(info_dict[user_group_name][m]['各分箱样本占比'])), plt.plot(range(len(info_dict[user_group_name][m]['各分箱样本占比'])),
[round(x[0], 3) for x in info_dict[user_group_name][m]['各分箱样本占比']], [round(x, 3) for x in info_dict[user_group_name][m]['各分箱样本占比']],
label='%s PSI: %.3f \n 样本量: %d' % ( label='%s PSI: %.3f \n 样本量: %d' % (
m, info_dict[user_group_name][m]['psi'], info_dict[user_group_name][m]['该月样本量'])) m, info_dict[user_group_name][m]['psi'], info_dict[user_group_name][m]['该月样本量']))
plt.legend(loc='upper right') plt.legend(loc='upper right')
...@@ -376,7 +394,7 @@ class ModelMonitor: ...@@ -376,7 +394,7 @@ class ModelMonitor:
for m in range(self.first_month, self.response_month + 1): for m in range(self.first_month, self.response_month + 1):
bins = self.make_bin(df_copy.loc[df_copy['month_label'] == m, field]) bins = self.make_bin(df_copy.loc[df_copy['month_label'] == m, field])
if bins: if bins:
print('以%d月为基准月.' % m) print('%s以%d月为基准月.' % (self.model_feild_name_dict[field], m))
break break
if not bins: if not bins:
self.na_enough_data_auc_set.add(self.model_feild_name_dict[field]) self.na_enough_data_auc_set.add(self.model_feild_name_dict[field])
...@@ -441,6 +459,7 @@ class ModelMonitor: ...@@ -441,6 +459,7 @@ class ModelMonitor:
remove_list.append(user_group_name) remove_list.append(user_group_name)
for user_group_name in remove_list: for user_group_name in remove_list:
del info_dict[user_group_name] del info_dict[user_group_name]
self.filed_bench_auc = None
# 画图. # 画图.
print('开始画图.') print('开始画图.')
...@@ -476,8 +495,16 @@ class ModelMonitor: ...@@ -476,8 +495,16 @@ class ModelMonitor:
def abnormal_psi(self): def abnormal_psi(self):
def is_abnormal_psi(data): def is_abnormal_psi(data):
for i in data.index: first = True
if 'PSI' in i and data[i] > self.max_psi: for idx in data.index:
if 'PSI' in idx and pd.notna(data[idx]):
if first:
if data[idx] > self.max_psi * 5:
return True
else:
first = False
else:
if data[idx] > self.max_psi:
return True return True
return False return False
...@@ -494,6 +521,7 @@ class ModelMonitor: ...@@ -494,6 +521,7 @@ class ModelMonitor:
def run(self): def run(self):
# 获取MySQL数据, 取近期num_month个月数据(如今天7.27, 则这27天算进7月). # 获取MySQL数据, 取近期num_month个月数据(如今天7.27, 则这27天算进7月).
if not self.if_load:
self.mysql_df = self.sql_query('''SELECT order_no, applied_at, self.mysql_df = self.sql_query('''SELECT order_no, applied_at,
applied_type, applied_from, applied_channel, transacted, passdue_day applied_type, applied_from, applied_channel, transacted, passdue_day
FROM risk_analysis FROM risk_analysis
...@@ -501,10 +529,13 @@ class ModelMonitor: ...@@ -501,10 +529,13 @@ class ModelMonitor:
AND applied_at <= "%s 00:00:00"''' AND applied_at <= "%s 00:00:00"'''
% (self.first_date, self.current_date)) % (self.first_date, self.current_date))
print('MySQL数据获取成功.') print('MySQL数据获取成功.')
# self.mysql_df.to_csv('./mysql_data.csv', index=False) if self.if_save:
# self.mysql_df = pd.read_csv('./mysql_data.csv') self.mysql_df.to_csv('./mysql_data.csv', index=False)
else:
self.mysql_df = pd.read_csv('./mysql_data.csv')
# 获取MongoDB数据, 取近期num_month个月数据(如今天7.27, 则这27天算进7月). # 获取MongoDB数据, 取近期num_month个月数据(如今天7.27, 则这27天算进7月).
if not self.if_load:
condition = {'wf_created_at': {'$gte': '%s 00:00:00' % self.first_date, condition = {'wf_created_at': {'$gte': '%s 00:00:00' % self.first_date,
'$lte': '%s 00:00:00' % self.current_date}} '$lte': '%s 00:00:00' % self.current_date}}
fields = {'wf_biz_no': 1, 'wf_created_at': 1} fields = {'wf_biz_no': 1, 'wf_created_at': 1}
...@@ -512,9 +543,10 @@ class ModelMonitor: ...@@ -512,9 +543,10 @@ class ModelMonitor:
fields[f] = 1 fields[f] = 1
self.mongo_df = self.mongo_query(condition, fields) self.mongo_df = self.mongo_query(condition, fields)
print('MongoDB数据获取成功.') print('MongoDB数据获取成功.')
if self.if_save:
# self.mongo_df.to_csv('./mongo_data.csv', index=False) self.mongo_df.to_csv('./mongo_data.csv', index=False)
# self.mongo_df = pd.read_csv('./mongo_data.csv') else:
self.mongo_df = pd.read_csv('./mongo_data.csv')
# MySQL数据去重. # MySQL数据去重.
self.mysql_df = self.mysql_df.sort_values('passdue_day') self.mysql_df = self.mysql_df.sort_values('passdue_day')
...@@ -567,15 +599,14 @@ class ModelMonitor: ...@@ -567,15 +599,14 @@ class ModelMonitor:
# 画图. # 画图.
## AUC.
print('开始画图-AUC.')
for field in self.model_feild_list:
self.plot_auc(field)
## PSI. ## PSI.
print('开始画图-PSI.') print('开始画图-PSI.')
for field in self.model_feild_list: for field in self.model_feild_list:
self.plot_psi(field) self.plot_psi(field)
## AUC.
print('开始画图-AUC.')
for field in self.model_feild_list:
self.plot_auc(field)
# 输出数据不足的模型. # 输出数据不足的模型.
print('PSI 数据不足以统计的模型:') print('PSI 数据不足以统计的模型:')
......
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