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bug

new_sanwei
chaopower 2024-09-18 09:47:55 +08:00
parent 6f3273af82
commit bd386023f3
1 changed files with 40 additions and 40 deletions
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80
tools/t7.py
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@ -553,48 +553,48 @@ class AutoLayout:
continue
# 不平衡文库 大于250G 的数据 先进行拆分
# 取消 20240912
if is_balance_lib == '否' and size > 250:
self.return_log.append(f'文库{library} 是不平衡文库, 数据为{size}, 大于250G, 已做拆分处理, 请注意！！！ ')
data_needed = library_df['orderdatavolume'].copy()
for num in range(int(size), 0, -200):
addnum = 200
if num <= 200:
addnum = num
library_df['orderdatavolume'] = (addnum / size) * data_needed
self.ori_lib_data.append(dict(
library=library,
sample_code=library_df['sampleCode'].values[0],
is_balance_lib=library_df['librarybalancedflag'].values[0],
size=library_df['orderdatavolume'].sum(),
split_method=library_df['cycletype'].values[0],
time=library_df['receivedtime'].values[0],
level=1950,
customer=library_df['companynamea'].values[0],
classification=library_df['classification'].values[0],
data=library_df.to_dict('records')
))
self.split_lib.add(library)
continue
# 取消 20240918
# if is_balance_lib == '否' and size > 250:
# self.return_log.append(f'文库{library} 是不平衡文库, 数据为{size}, 大于250G, 已做拆分处理, 请注意！！！ ')
# data_needed = library_df['orderdatavolume'].copy()
# for num in range(int(size), 0, -200):
# addnum = 200
# if num <= 200:
# addnum = num
# library_df['orderdatavolume'] = (addnum / size) * data_needed
#
# self.ori_lib_data.append(dict(
# library=library,
# sample_code=library_df['sampleCode'].values[0],
# is_balance_lib=library_df['librarybalancedflag'].values[0],
# size=library_df['orderdatavolume'].sum(),
# split_method=library_df['cycletype'].values[0],
# time=library_df['receivedtime'].values[0],
# level=1950,
# customer=library_df['companynamea'].values[0],
# classification=library_df['classification'].values[0],
# data=library_df.to_dict('records')
# ))
# self.split_lib.add(library)
# continue
# # 拆分处理 分为了2个大文库
# 取消 20240912
if size > self.data_limit / 2:
library_df['orderdatavolume'] = library_df['orderdatavolume'] / 2
self.return_log.append(f'文库{library} 已做拆分处理, 请注意！！！ ')
self.ori_lib_data.append(dict(
library=library,
sample_code=library_df['sampleCode'].values[0],
is_balance_lib=library_df['librarybalancedflag'].values[0],
size=library_df['orderdatavolume'].sum(),
split_method=library_df['cycletype'].values[0],
time=library_df['receivedtime'].values[0],
level=library_df['level'].values[0],
customer=library_df['companynamea'].values[0],
classification=library_df['classification'].values[0],
data=library_df.to_dict('records')
))
# 取消 20240918
# if size > self.data_limit / 2:
# library_df['orderdatavolume'] = library_df['orderdatavolume'] / 2
# self.return_log.append(f'文库{library} 已做拆分处理, 请注意！！！ ')
# self.ori_lib_data.append(dict(
# library=library,
# sample_code=library_df['sampleCode'].values[0],
# is_balance_lib=library_df['librarybalancedflag'].values[0],
# size=library_df['orderdatavolume'].sum(),
# split_method=library_df['cycletype'].values[0],
# time=library_df['receivedtime'].values[0],
# level=library_df['level'].values[0],
# customer=library_df['companynamea'].values[0],
# classification=library_df['classification'].values[0],
# data=library_df.to_dict('records')
# ))
self.ori_lib_data.append(dict(
library=library,