python

view plaincopyprint?

1. import pandas as pd  
2. import numpy as np  
3. import datetime  
4. import time  
5. #获取数据  
6. df=pd.read_csv('C:/Users/HXWD/Desktop/000001.csv',encoding='gbk')  
7. df.columns=['date','code','name','close','high','low','open','preclose',  
8. 'change','change_per','volume','amt']  
9. df=df[['date','open','high','low','close','volume','amt']]  
10. df.head()  
11. def get_SAR(df,N=10,step=2,maxp=20):  
12.     sr_value=[]  
13.     sr_up=[]  
14.     ep_up=[]  
15.     af_up=[]  
16.     sr_down=[]  
17.     ep_down=[]  
18.     af_down=[]  
19.     for i in range(len(df)):  
20.               
21.         if i >=N:  
22.             if len(sr_up)==0 and len(sr_down)==0:  
23.                 if df.ix[i,'close']>df.ix[0,'close']:  
24.                      #标记为上涨趋势  
25.                     sr0=df['low'][0:i].min()  
26.                     af0=0.02  
27.                     ep0=df.ix[i,'high']  
28.                     sr_up.append(sr0)  
29.                     ep_up.append(ep0)  
30.                     af_up.append(af0)  
31.                     sr_value.append(sr0)  
32.                 if df.ix[i,'close']<=df.ix[0,'close']:  
33.                     #标记为上涨趋势  
34.                     sr0=df['high'][0:i].max()  
35.                     af0=0.02  
36.                     ep0=df.ix[i,'high']  
37.                     sr_down.append(sr0)  
38.                     ep_down.append(ep0)  
39.                     af_down.append(af0)  
40.                     sr_value.append(sr0)  
41.             if len(sr_up)>0:  
42.                 if df.ix[i-1,'low']>sr_up[-1]:  
43.                    sr0=sr_up[-1]  
44.                    ep0=df['high'][-len(sr_up):].max()  
45.                    if df.ix[i,'high']>df['high'][-(len(sr_up)-1):].max() :  
46.                       af0=af_up[-1] 0.02  
47.                    if df.ix[i,'high']<=df['high'][-(len(sr_up)-1):].max() :  
48.                       af0=af_up[-1]  
49.                      
50.                    sr=sr0 af0*(ep0-sr0)  
51.                    sr_up.append(sr)  
52.                    ep_up.append(ep0)  
53.                    af_up.append(af0)  
54.                    sr_value.append(sr)  
55.                    print('上涨sr0={},ep0={},af0={},sr={}'.format(sr0,ep0,af0,sr))  
56.                 if df.ix[i-1,'low']<=sr_up[-1]:  
57.                    ep0=df['high'][-len(sr_up):].max()  
58.                    sr0=ep0  
59.                    af0=0.02  
60.                    sr_down.append(sr0)  
61.                    ep_down.append(ep0)  
62.                    af_down.append(af0)  
63.                    sr_value.append(sr0)  
64.                    sr_up=[]  
65.                    ep_up=[]  
66.                    af_up=[]  
67.             if len(sr_down)>0:  
68.                 if df.ix[i-1,'high']<sr_down[-1]:  
69.                     sr0=sr_down[-1]  
70.                     ep0=df['low'][-len(sr_down):].max()  
71.                     if df.ix[i,'low']<df['low'][-(len(sr_down)-1):].max() :  
72.                       af0=af_down[-1] 0.02  
73.                     if df.ix[i,'low']>=df['low'][-(len(sr_down)-1):].max() :  
74.                       af0=af_down[-1]  
75.                      
76.                     sr=sr0 af0*(ep0-sr0)  
77.                     sr_down.append(sr)  
78.                     ep_down.append(ep0)  
79.                     af_down.append(af0)  
80.                     sr_value.append(sr)  
81.                     print('下跌sr0={},ep0={},af0={},sr={}'.format(sr0,ep0,af0,sr))  
82.                 if df.ix[i-1,'high']>=sr_down[-1]:  
83.                    ep0=df['low'][-len(sr_up):].max()  
84.                    sr0=ep0  
85.                    af0=0.02  
86.                    sr_up.append(sr0)  
87.                    ep_up.append(ep0)  
88.                    af_up.append(af0)  
89.                    sr_value.append(sr0)  
90.                    sr_down=[]  
91.                    ep_down=[]  
92.                    af_down=[]  
93.     return sr_value  
94. sar=get_SAR(df)  

import pandas as pd import numpy as np import datetime import time #获取数据 df=pd.read_csv('C:/Users/HXWD/Desktop/000001.csv',encoding='gbk') df.columns=['date','code','name','close','high','low','open','preclose', 'change','change_per','volume','amt'] df=df[['date','open','high','low','close','volume','amt']] df.head() def get_SAR(df,N=10,step=2,maxp=20): sr_value=[] sr_up=[] ep_up=[] af_up=[] sr_down=[] ep_down=[] af_down=[] for i in range(len(df)): if i >=N: if len(sr_up)==0 and len(sr_down)==0: if df.ix[i,'close']>df.ix[0,'close']: #标记为上涨趋势 sr0=df['low'][0:i].min() af0=0.02 ep0=df.ix[i,'high'] sr_up.append(sr0) ep_up.append(ep0) af_up.append(af0) sr_value.append(sr0) if df.ix[i,'close']<=df.ix[0,'close']: #标记为上涨趋势 sr0=df['high'][0:i].max() af0=0.02 ep0=df.ix[i,'high'] sr_down.append(sr0) ep_down.append(ep0) af_down.append(af0) sr_value.append(sr0) if len(sr_up)>0: if df.ix[i-1,'low']>sr_up[-1]: sr0=sr_up[-1] ep0=df['high'][-len(sr_up):].max() if df.ix[i,'high']>df['high'][-(len(sr_up)-1):].max() : af0=af_up[-1] 0.02 if df.ix[i,'high']<=df['high'][-(len(sr_up)-1):].max() : af0=af_up[-1] sr=sr0 af0*(ep0-sr0) sr_up.append(sr) ep_up.append(ep0) af_up.append(af0) sr_value.append(sr) print('上涨sr0={},ep0={},af0={},sr={}'.format(sr0,ep0,af0,sr)) if df.ix[i-1,'low']<=sr_up[-1]: ep0=df['high'][-len(sr_up):].max() sr0=ep0 af0=0.02 sr_down.append(sr0) ep_down.append(ep0) af_down.append(af0) sr_value.append(sr0) sr_up=[] ep_up=[] af_up=[] if len(sr_down)>0: if df.ix[i-1,'high']<sr_down[-1]: sr0=sr_down[-1] ep0=df['low'][-len(sr_down):].max() if df.ix[i,'low']<df['low'][-(len(sr_down)-1):].max() : af0=af_down[-1] 0.02 if df.ix[i,'low']>=df['low'][-(len(sr_down)-1):].max() : af0=af_down[-1] sr=sr0 af0*(ep0-sr0) sr_down.append(sr) ep_down.append(ep0) af_down.append(af0) sr_value.append(sr) print('下跌sr0={},ep0={},af0={},sr={}'.format(sr0,ep0,af0,sr)) if df.ix[i-1,'high']>=sr_down[-1]: ep0=df['low'][-len(sr_up):].max() sr0=ep0 af0=0.02 sr_up.append(sr0) ep_up.append(ep0) af_up.append(af0) sr_value.append(sr0) sr_down=[] ep_down=[] af_down=[] return sr_value sar=get_SAR(df)

[python] view plaincopyprint?

1. #测试下来看，似乎中间逻辑有问题，有时间进一步修改  

#测试下来看，似乎中间逻辑有问题，有时间进一步修改

[python] view plaincopyprint?

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注：需要单独编写文华财经，金字塔，大智慧，通达信，TB，Python平台的指标、策略等，请联系扣扣1733505732，兼职时间：工作日下午18:00-22:00，节假日。