From 3ea84f8adaeeb851e590fa74ceed009a0a19b08c Mon Sep 17 00:00:00 2001
From: Administrator <admin@example.com>
Date: 星期二, 28 十一月 2023 17:46:38 +0800
Subject: [PATCH] 近6个交易日涨幅过高实现

---
 code_attribute/code_nature_analyse.py |   29 +++++++++++++++++++++++++++--
 1 files changed, 27 insertions(+), 2 deletions(-)

diff --git a/code_attribute/code_nature_analyse.py b/code_attribute/code_nature_analyse.py
index 5600454..d4f9886 100644
--- a/code_attribute/code_nature_analyse.py
+++ b/code_attribute/code_nature_analyse.py
@@ -224,7 +224,7 @@
 
 # 鏄惁鍏锋湁K绾垮舰鎬�
 def is_has_k_format(limit_up_price, record_datas):
-    is_too_high, is_new_top, is_lowest, is_near_new_top, is_n, is_v, has_format, volume_info, is_special = get_k_format(
+    is_too_high, is_new_top, is_lowest, is_near_new_top, is_n, is_v, has_format, volume_info, is_special, has_max_volume = get_k_format(
         float(limit_up_price), record_datas)
     if not has_format:
         return False, "涓嶆弧瓒矺绾垮舰鎬�"
@@ -255,7 +255,7 @@
 
 
 # 鏄惁娑ㄥ緱澶珮
-def is_up_too_high_in_10d(record_datas):
+def is_up_too_high_in_10d_with_limit_up(record_datas):
     datas = copy.deepcopy(record_datas)
     datas.sort(key=lambda x: x["bob"])
     datas = datas[-10:]
@@ -348,6 +348,31 @@
     return False
 
 
+# 鍦ㄦ渶杩戝嚑澶╁唴鑲′环鏄惁闀垮緱澶珮
+def is_price_too_high_in_days(record_datas, limit_up_price, day_count=6):
+    datas = copy.deepcopy(record_datas)
+    datas.sort(key=lambda x: x["bob"])
+    datas = datas[0 - day_count:]
+    min_price = None
+    max_price = None
+    for d in datas:
+        if min_price is None:
+            min_price = d["low"]
+        if max_price is None:
+            max_price = d["high"]
+        if min_price > d["low"]:
+            min_price = d["low"]
+        if max_price < d["high"]:
+            max_price = d["high"]
+    if max_price > float(limit_up_price):
+        return False
+    rate = (float(limit_up_price) - min_price) / min_price
+    # print(rate)
+    if rate >= 0.25:
+        return True
+    return False
+
+
 # 鏄惁鏈夋定鍋�
 def get_first_limit_up_count(datas):
     datas = copy.deepcopy(datas)

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