v3.2.6

pure_ocean_breeze/__init__.py

@@ -2,8 +2,8 @@
 一个量化多因子研究的框架，包含数据、回测、因子加工等方面的功能
 """
 
-__updated__ = "2022-09-16 10:32:33"
-__version__ = "3.2.5"
+__updated__ = "2022-09-19 17:34:33"
+__version__ = "3.2.6"
 __author__ = "chenzongwei"
 __author_email__ = "[email protected]"
 __url__ = "https://github.com/chen-001/pure_ocean_breeze"
@@ -203,7 +203,6 @@ def show_use_times():
 from pure_ocean_breeze.mail import *
 from pure_ocean_breeze.initialize import *
 
-from pure_ocean_breeze.state.states import *
 from pure_ocean_breeze.state.homeplace import *
 from pure_ocean_breeze.state.decorators import *
 

pure_ocean_breeze/data/write_data.py

@@ -1,4 +1,4 @@
-__updated__ = "2022-09-15 21:53:51"
+__updated__ = "2022-09-18 01:53:55"
 
 try:
     import rqdatac
@@ -544,9 +544,8 @@ def database_update_daily_files() -> None:
     homeplace = HomePlace()
 
     def single_file(name):
-        df = pd.read_feather(homeplace.daily_data_file + name + ".feather").set_index(
-            "date"
-        )
+        df = pd.read_feather(homeplace.daily_data_file + name + ".feather")
+        df = df.set_index(list(df.columns)[0])
         startdate = df.index.max() + pd.Timedelta(days=1)
         return startdate
 

pure_ocean_breeze/labor/comment.py

@@ -1,4 +1,4 @@
-__updated__ = "2022-08-21 13:40:12"
+__updated__ = "2022-09-19 15:23:25"
 
 import numpy as np
 import pandas as pd
@@ -10,7 +10,6 @@
 plt.style.use(["science", "no-latex", "notebook"])
 plt.rcParams["axes.unicode_minus"] = False
 from pure_ocean_breeze.data.read_data import read_index_three, read_daily
-from pure_ocean_breeze.labor.process import pure_moonnight
 
 
 def comment_on_rets_and_nets(
@@ -231,30 +230,7 @@ def make_relative_comments_plot(
     return net
 
 
-def comments_ten(shen: pure_moonnight) -> pd.DataFrame:
-    """对回测的十分组结果分别给出评价
 
-    Parameters
-    ----------
-    shen : pure_moonnight
-        回测结果对象
-
-    Returns
-    -------
-    `pd.DataFrame`
-        评价指标包括年化收益率、总收益率、年化波动率、年化夏普比率、最大回撤率、胜率
-    """
-    rets_cols = list(shen.shen.group_rets.columns)
-    rets_cols = rets_cols[:-1]
-    coms = []
-    for i in rets_cols:
-        ret = shen.shen.group_rets[i]
-        net = shen.shen.group_net_values[i]
-        com = comments_on_twins(net, ret)
-        com = com.to_frame(i)
-        coms.append(com)
-    df = pd.concat(coms, axis=1)
-    return df.T
 
 
 def other_periods_comments_nets(