moved things to a new place !

notebooks/autogen/Indicators.py

@@ -0,0 +1,267 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[2]:
+
+
+import pandas as pd
+import datetime
+import numpy as np
+#import plotly as pl
+
+#import plotly.graph_objs as go
+#from plotly.offline import init_notebook_mode, iplot
+#from plotly.subplots import make_subplots
+#init_notebook_mode()
+
+import CoreTraidMath 
+import CoreDraw
+
+
+# In[3]:
+
+
+class coreIndicator():
+    def __init__(self,
+                 data=pd.DataFrame(),
+                 options={},
+                 showMode='None',
+                ):
+        '''
+        showMode = None/Ind/PartOf        
+        '''
+        self.data=data
+        self.showMode=showMode
+        self.options=options
+        self.overlayInd=None #True/False
+        self.ans=None
+        self.figDict=None
+        
+    def getAns(self,data=None):
+        if type(data)!=type(None):
+            self.data=data
+        self.ans=self.getCalculate()
+        if self.showMode=='Ind' or self.showMode=='PartOf':
+            self.figDict=self.getFigDict()
+            if self.showMode=='Ind':
+                self.getFig()
+        return self.ans
+    def getFig(self,row=1):
+        CoreDraw.coreDraw(self.figDict,True)
+    def getCalculate(self):
+        return "Error"
+    def getFigDict(self):
+        return "Error"
+
+class indicatorAgrigator():
+    '''
+    Тема чисто для отладки
+    jj=indicatorAgrigator().runAll([o1,o2],df_candle[:30])
+    #jj.createIndFromList([o1,o2])
+    #jj.calculateInd(df_candle[:30])
+    
+    '''
+    def __init__(self):
+        self.indList=None
+        self.data=None
+    def createInd(self,classDict):
+        return classDict['name'](
+                options=classDict['params'],
+                showMode=classDict['showMode']
+            )
+        
+        
+    def createIndFromList(self,indList):
+        self.indList=indList
+        ans=[]
+        for i in self.indList:
+            ans.append(self.createInd(i))
+        self.indList=ans
+        return ans
+    
+    def calculateInd(self,data):
+        self.data=data
+        for i in self.indList:
+            #i.getAns(data)
+            i.data=self.data
+            i.ans=i.getCalculate()
+            i.figDict=i.getFigDict()
+            #i.getFig()
+    def agrigateFig(self):
+        req=[[]]
+        
+        for i in self.indList:
+            if i.overlayInd==True:
+                req[0].append(i)
+            else:
+                req.append([i])
+        CoreDraw.agrigateFig(req,True)
+    def runAll(self,indList,df,needDraw=False):
+        self.createIndFromList(indList)
+        self.calculateInd(df)
+        if needDraw:
+            self.agrigateFig()
+
+        
+        
+
+
+# In[4]:
+
+
+class ind_BB(coreIndicator):
+    
+    def getCalculate(self):
+        self.overlayInd=True
+        ans={}
+        opMA={'dataType':'ohcl',
+            'action':'findMean',
+            'actionOptions':{
+                'MeanType':self.options['MeanType'],
+                'valueType':self.options['valueType'],
+                'window':self.options['window']
+            }
+        }
+        ans['BB']=CoreTraidMath.CoreMath(self.data,opMA).ans
+        opSTD={'dataType':'ohcl',
+            'action':'findSTD',
+            'actionOptions':{'valueType':self.options['valueType'],'window':self.options['window']}
+        }
+        ans['STD']=CoreTraidMath.CoreMath(self.data,opSTD).ans
+        ans['pSTD']=ans['BB']+ans['STD']*self.options['kDev']
+        ans['mSTD']=ans['BB']-ans['STD']*self.options['kDev']
+        ans['x']=np.array(self.data['date'][self.options['window']-1:].to_list())
+        return ans
+    def getFigDict(self,row=1):
+        req=[]
+        
+        req.append({
+            'vtype':'Scatter',
+            'df':pd.DataFrame(
+                {'value':self.ans['BB'],'date':self.ans['x']}) ,
+            'row':row,
+            'col':1,
+            'name':'BB'
+            
+        })
+        req.append({
+            'vtype':'Scatter',
+            'df':pd.DataFrame(
+                {'value':self.ans['pSTD'],'date':self.ans['x']}) ,
+            'row':row,
+            'col':1,
+            'name':'pSTD'
+            
+        })
+        req.append({
+            'vtype':'Scatter',
+            'df':pd.DataFrame(
+                {'value':self.ans['mSTD'],'date':self.ans['x']}) ,
+            'row':row,
+            'col':1,
+            'name':'mSTD'
+            
+        })
+        
+        return req
+
+
+# In[5]:
+
+
+class ind_OCHL(coreIndicator):
+    def getCalculate(self):
+        self.overlayInd=True
+    def getFigDict(self,row=1):
+        req=[]
+        
+        req.append({
+                'vtype':'OCHL',
+                'df':self.data,
+                'row':1,
+                'col':1,
+                'name':'OHCL'
+
+        })
+        return req
+
+
+# In[7]:
+
+
+df_candle = pd.read_csv("../data/EURUSD_price_candlestick.csv")
+df_candle.rename(columns={'timestamp': 'date'}, inplace=True)
+df_candle
+
+
+# In[8]:
+
+
+o1={
+    'name':ind_OCHL,
+    'params':{},
+    'showMode':'PartOf',
+}
+o2={
+    'name':ind_BB,
+    'params':{'MeanType':'SMA','window':25,'valueType':'low','kDev':2},
+    'showMode':'PartOf',
+}
+jj=indicatorAgrigator().runAll([o1,o2],df_candle[:300],True)
+#jj.createIndFromList([o1,o2])
+#jj.calculateInd(df_candle[:30])
+
+
+# In[9]:
+
+
+op={'MeanType':'SMA','window':5,'valueType':'low','kDev':2}
+a=ind_BB(df_candle[:100],op,'PartOf')
+
+
+# In[10]:
+
+
+a.getAns()
+
+
+# In[11]:
+
+
+b=ind_OCHL(df_candle[:30],{},'Ind')
+b.getAns(df_candle[:100])
+
+
+# In[12]:
+
+
+opc={'MeanType':'SMA','window':20,'valueType':'low','kDev':2}
+c=ind_BB(df_candle[:100],opc,'PartOf')
+c.getAns()
+
+
+# In[13]:
+
+
+hhh = CoreDraw.agrigateFig([[b,a,c]],True)
+
+
+# In[14]:
+
+
+import indicators
+
+
+# In[15]:
+
+
+op_1={'MeanType':'SMA','window':5,'valueType':'low','kDev':2}
+test_1=indicators.ind_BB(df_candle[:100],op)
+test_1.getAns()
+
+
+# In[ ]:
+
+
+
+