0.9.39 新增两个 rolling 工具函数

waditu · Dec 13, 2023 · d7e59bb · d7e59bb
1 parent ec67a2d
commit d7e59bb
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Showing 3 changed files with 52 additions and 3 deletions.
diff --git a/.github/workflows/pythonpackage.yml b/.github/workflows/pythonpackage.yml
@@ -5,7 +5,7 @@ name: Python package
 
 on:
   push:
-    branches: [ master, V0.9.38 ]
+    branches: [ master, V0.9.39 ]
   pull_request:
     branches: [ master ]
 

diff --git a/czsc/__init__.py b/czsc/__init__.py
@@ -111,12 +111,14 @@
     normalize_feature,
     normalize_ts_feature,
     feture_cross_layering,
+    rolling_rank,
+    rolling_norm,
 )
 
-__version__ = "0.9.38"
+__version__ = "0.9.39"
 __author__ = "zengbin93"
 __email__ = "[email protected]"
-__date__ = "20231126"
+__date__ = "20231212"
 
 
 def welcome():

diff --git a/czsc/utils/features.py b/czsc/utils/features.py
@@ -159,3 +159,50 @@ def _layering(x):
     df[f"{x_col}分层"] = df[f"{x_col}分层"].fillna(-1)
     df[f'{x_col}分层'] = df[f'{x_col}分层'].apply(lambda x: f'第{str(int(x+1)).zfill(2)}层')
     return df
+
+
+def rolling_rank(df: pd.DataFrame, col, n=None, new_col=None, **kwargs):
+    """计算序列的滚动排名
+
+    :param df: pd.DataFrame
+        待计算的数据
+    :param col: str
+        待计算的列
+    :param n: int
+        滚动窗口大小, 默认为None, 表示计算 expanding 排名，否则计算 rolling 排名
+    :param new_col: str
+        新列名，默认为 None, 表示使用 f'{col}_rank' 作为新列名
+    :param kwargs:
+        min_periods: int
+            最小计算周期
+    """
+    min_periods = kwargs.get('min_periods', 1)
+    new_col = new_col if new_col else f'{col}_rank'
+    if n is None:
+        df[new_col] = df[col].expanding(min_periods=min_periods).rank()
+    else:
+        df[new_col] = df[col].rolling(window=n, min_periods=min_periods).rank()
+
+
+def rolling_norm(df: pd.DataFrame, col, n=None, new_col=None, **kwargs):
+    """计算序列的滚动归一化值
+
+    :param df: pd.DataFrame
+        待计算的数据
+    :param col: str
+        待计算的列
+    :param n: int
+        滚动窗口大小, 默认为None, 表示计算 expanding ，否则计算 rolling
+    :param new_col: str
+        新列名，默认为 None, 表示使用 f'{col}_norm' 作为新列名
+    :param kwargs:
+        min_periods: int
+            最小计算周期
+    """
+    min_periods = kwargs.get('min_periods', 1)
+    new_col = new_col if new_col else f'{col}_norm'
+
+    if n is None:
+        df[new_col] = df[col].expanding(min_periods=min_periods).apply(lambda x: (x[-1] - x.mean()) / x.std(), raw=True)
+    else:
+        df[new_col] = df[col].rolling(window=n, min_periods=min_periods).apply(lambda x: (x[-1] - x.mean()) / x.std(), raw=True)