moved things to a new place !

notebooks/autogen/Signals_v2.py

@@ -0,0 +1,249 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[2]:
+
+
+import pandas as pd
+import datetime
+import numpy as np
+
+import CoreTraidMath 
+import CoreDraw
+from tqdm import tqdm
+
+from indicators_v2 import *
+
+
+# In[3]:
+
+
+df_candle = pd.read_csv(r"../data/EURUSD_price_candlestick.csv")
+df_candle.rename(columns={'timestamp': 'date'}, inplace=True)
+df_candle
+
+
+# In[4]:
+
+
+class coreSignalTrande:
+    
+    def __init__(self, name: str, req: dict, dataType: str):
+        self.name = name
+        self.agrigateInds = self.createIndicatorsInstance(req)
+        self.params = req['params']
+        self.dataType = dataType
+        
+    
+    def createIndicatorsInstance(self,req: dict) -> dict:
+        return indicatorsAgrigator(req['indicators'])
+    
+    def getIndAns(self, dataDict: dict) -> dict:
+        return self.agrigateInds.getAns(dataDict)
+    
+    def getAns(self, data: pd.DataFrame(), indDataDict: dict) -> dict:
+        return self.getSigAns(data, self.getIndAns(indDataDict)) 
+        
+    
+    
+class sig_BB(coreSignalTrande):
+    """
+    ind keys:
+        ind_BB
+    """
+    
+    def __init__(self, name: str, req:dict):
+        super().__init__(name, req, 'ochl')
+    
+    def getSigAns(self, data: pd.DataFrame(), indAnsDict: dict) -> dict:
+
+        lastValue = data[self.params['source']].to_list()[-1]
+        if lastValue>indAnsDict['ind_BB']['pSTD'][-1]:
+            ans='down'
+        elif lastValue<indAnsDict['ind_BB']['mSTD'][-1]:
+            ans='up'
+        else:
+            ans='none'
+        
+        return ans
+        
+
+
+# In[5]:
+
+
+class signalsAgrigator:
+    
+    def __init__ (self,req:dict):
+        self.signals = self.createSignalsInstance(req)
+        
+    def createSignalsInstance(self, siganlsDict: dict) -> dict:
+        ans = {}
+        for i in siganlsDict.keys():
+            ans[i]=siganlsDict[i]['className'](name = i, req = siganlsDict[i])
+        return ans
+    
+    def getAns(self, dataDict: dict) -> dict:
+        ans = {}
+        for i in dataDict.keys():
+            ans[i] = self.signals[i].getAns(data = dataDict[i]['signalData'], 
+                                   indDataDict = dataDict[i]['indicatorData'])
+        return ans
+
+
+# In[ ]:
+
+
+
+
+
+# In[6]:
+
+
+sigreq= {
+        'params':{'source':'close','target':'close'},
+        'indicators':{
+            'ind_BB':{
+                'className':ind_BB,
+                'params':{'MeanType':'SMA','window':15,'valueType':'close','kDev':2.5}
+            }            
+        }
+    }
+    
+indReqDict ={'ind_BB':df_candle[:1000]}
+
+
+# In[7]:
+
+
+sigAgrReq = {
+    'sig_BB':{
+        'className':sig_BB,
+        'params':{'source':'close','target':'close'},
+        'indicators':{
+            'ind_BB':{
+                'className':ind_BB,
+                'params':{'MeanType':'SMA','window':15,'valueType':'close','kDev':2.5}
+            }            
+        }
+    },
+    'sig_BB_2':{
+        'className':sig_BB,
+        'params':{'source':'close','target':'close'},
+        'indicators':{
+            'ind_BB':{
+                'className':ind_BB,
+                'params':{'MeanType':'SMA','window':30,'valueType':'close','kDev':2}
+            }            
+        }
+    }
+}
+
+sigAgrData = {
+    'sig_BB':{
+        'signalData': df_candle[990:1000],
+        'indicatorData' :{'ind_BB': df_candle[:1000]}
+    },
+    'sig_BB_2':{
+        'signalData': df_candle[990:1000],
+        'indicatorData' :{'ind_BB': df_candle[:1000]}
+    }    
+}
+
+
+# In[ ]:
+
+
+
+
+
+# In[8]:
+
+
+ttt=signalsAgrigator(sigAgrReq)
+
+
+# In[9]:
+
+
+ttt.__dict__
+
+
+# In[10]:
+
+
+ttt.signals['sig_BB'].__dict__
+
+
+# In[11]:
+
+
+ttt.getAns(sigAgrData)
+
+
+# In[ ]:
+
+
+
+
+
+# In[ ]:
+
+
+
+
+
+# In[12]:
+
+
+list({'ttt':2}.keys())[0]
+
+
+# In[13]:
+
+
+test = sig_BB('sig_BB', sigreq)
+
+
+# In[14]:
+
+
+test.__dict__
+
+
+# In[ ]:
+
+
+
+
+
+# In[15]:
+
+
+test.agrigateInds.__dict__
+
+
+# In[16]:
+
+
+ians = test.getIndAns(indReqDict)
+ians
+
+
+# In[17]:
+
+
+test.getAns(df_candle[:100],indReqDict)
+
+
+# In[ ]:
+
+
+
+
+
+# In[ ]:
+
+
+
+