moved things to a new place !
This commit is contained in:
@@ -2,12 +2,11 @@ import pandas as pd
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import datetime
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import numpy as np
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import market_trade.core.CoreTraidMath as CoreTraidMath
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import market_trade.core.CoreDraw as CoreDraw
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import CoreTraidMath
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import CoreDraw
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from tqdm import tqdm
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from market_trade.core.indicators import *
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from indicators import *
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class coreSignalTrande():
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def __init__(self,
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@@ -17,140 +16,133 @@ class coreSignalTrande():
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batchSize=None,
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indParams=None,
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signalParams=None,
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# needFig=False,
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# showOnlyIndex=False,
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# drawFig=False,
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# equalityGap=0
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):
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self.data = data.reset_index(drop=True)
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self.onlineData = data.reset_index(drop=True)
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self.dataType = dataType
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self.mode = mode
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self.ans = None
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self.softAnalizList = np.asarray([])
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self.hardAnalizList = np.asarray([])
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self.analizMetrics = {}
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self.indParams = indParams
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self.signalParams = signalParams
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self.batchSize = batchSize
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# self.needFig=needFig
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# self.showOnlyIndex=showOnlyIndex
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# self.drawFig=drawFig
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# self.equalityGap=equalityGap
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# Роутер получения ответа
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def getAns(self, data):
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# ans='Error: unknown Mode!'
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ans = None
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#needFig=False,
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#showOnlyIndex=False,
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#drawFig=False,
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#equalityGap=0
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):
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self.data=data.reset_index(drop=True)
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self.onlineData=data.reset_index(drop=True)
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self.dataType=dataType
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self.mode=mode
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self.ans=None
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self.softAnalizList=np.asarray([])
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self.hardAnalizList=np.asarray([])
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self.analizMetrics={}
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self.indParams=indParams
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self.signalParams=signalParams
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self.batchSize=batchSize
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#self.needFig=needFig
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#self.showOnlyIndex=showOnlyIndex
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#self.drawFig=drawFig
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#self.equalityGap=equalityGap
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#Роутер получения ответа
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def getAns(self,data):
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#ans='Error: unknown Mode!'
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ans=None
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print("Start processing...")
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if self.mode == 'online':
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ans = self.getOnlineAns(data.reset_index(drop=True))
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ans=self.getOnlineAns(data.reset_index(drop=True))
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elif self.mode == 'retro':
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ans = self.getRetroAns(data)
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ans=self.getRetroAns(data)
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elif self.mode == 'retroFast':
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ans = self.getRetroFastAns(data)
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ans=self.getRetroFastAns(data)
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print("Processing DONE!")
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return ans
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# Ретро режим, где расширяется окно добавлением новых элементов
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def getRetroAns(self, data):
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ans = np.asarray([])
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for i in tqdm(range(self.batchSize, len(data) - 1)):
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# self.onlineData=self.data[0:i]
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#Ретро режим, где расширяется окно добавлением новых элементов
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def getRetroAns(self,data):
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ans=np.asarray([])
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for i in tqdm(range(self.batchSize,len(data)-1)):
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#self.onlineData=self.data[0:i]
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window_data = data[0:i]
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window_data.reset_index(drop=True)
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ans = np.append(ans, (self.getOnlineAns(window_data)))
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self.ans = ans
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ans=np.append(ans,(self.getOnlineAns(window_data)))
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self.ans=ans
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self.getAnaliz()
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self.getMetrix()
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return ans
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# Ретро режим, где двигается окно
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def getRetroFastAns(self, data):
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# print('d - ',data)
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ans = np.asarray([])
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for i in tqdm(range(len(data) - 1 - self.batchSize)):
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# self.onlineData=self.data[i:i+self.batchSize]
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window_data = data[i:i + self.batchSize]
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# print('win - ',window_data)
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#Ретро режим, где двигается окно
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def getRetroFastAns(self,data):
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#print('d - ',data)
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ans=np.asarray([])
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for i in tqdm(range(len(data)-1-self.batchSize)):
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#self.onlineData=self.data[i:i+self.batchSize]
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window_data = data[i:i+self.batchSize]
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#print('win - ',window_data)
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window_data.reset_index(drop=True)
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# print('win - ',window_data)
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ans = np.append(ans, (self.getOnlineAns(window_data)))
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self.ans = ans
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#print('win - ',window_data)
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ans=np.append(ans,(self.getOnlineAns(window_data)))
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self.ans=ans
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self.getAnaliz()
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self.getMetrix()
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return ans
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# Метод, который будет переопределять каждый дочерний класс
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#Метод, который будет переопределять каждый дочерний класс
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def getOnlineAns(self):
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return 'Error'
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def getAnaliz(self):
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print("Start analiz...")
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for i in (range(len(self.ans))):
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sourceValue = self.data[self.signalParams['source']][i + self.batchSize]
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targetValue = self.data[self.signalParams['target']][i + self.batchSize + 1]
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if (targetValue) > sourceValue:
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if self.ans[i] == 1:
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self.softAnalizList = np.append(self.softAnalizList, 1)
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self.hardAnalizList = np.append(self.hardAnalizList, 1)
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elif self.ans[i] == -1:
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self.softAnalizList = np.append(self.softAnalizList, -1)
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self.hardAnalizList = np.append(self.hardAnalizList, -1)
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sourceValue=self.data[self.signalParams['source']][i+self.batchSize]
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targetValue=self.data[self.signalParams['target']][i+self.batchSize + 1]
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if (targetValue)>sourceValue:
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if self.ans[i]==1:
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self.softAnalizList=np.append(self.softAnalizList,1)
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self.hardAnalizList=np.append(self.hardAnalizList,1)
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elif self.ans[i]==-1:
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self.softAnalizList=np.append(self.softAnalizList,-1)
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self.hardAnalizList=np.append(self.hardAnalizList,-1)
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else:
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self.softAnalizList = np.append(self.softAnalizList, 0)
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self.hardAnalizList = np.append(self.hardAnalizList, -1)
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elif (targetValue) < sourceValue:
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if self.ans[i] == 1:
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self.softAnalizList = np.append(self.softAnalizList, -1)
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self.hardAnalizList = np.append(self.hardAnalizList, -1)
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elif self.ans[i] == -1:
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self.softAnalizList = np.append(self.softAnalizList, 1)
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self.hardAnalizList = np.append(self.hardAnalizList, 1)
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self.softAnalizList=np.append(self.softAnalizList,0)
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self.hardAnalizList=np.append(self.hardAnalizList,-1)
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elif (targetValue)<sourceValue:
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if self.ans[i]==1:
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self.softAnalizList=np.append(self.softAnalizList,-1)
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self.hardAnalizList=np.append(self.hardAnalizList,-1)
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elif self.ans[i]==-1:
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self.softAnalizList=np.append(self.softAnalizList,1)
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self.hardAnalizList=np.append(self.hardAnalizList,1)
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else:
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self.softAnalizList = np.append(self.softAnalizList, 0)
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self.hardAnalizList = np.append(self.hardAnalizList, -1)
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self.softAnalizList=np.append(self.softAnalizList,0)
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self.hardAnalizList=np.append(self.hardAnalizList,-1)
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else:
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if self.ans[i] == 1:
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self.softAnalizList = np.append(self.softAnalizList, -1)
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self.hardAnalizList = np.append(self.hardAnalizList, -1)
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elif self.ans[i] == -1:
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self.softAnalizList = np.append(self.softAnalizList, -1)
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self.hardAnalizList = np.append(self.hardAnalizList, -1)
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if self.ans[i]==1:
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self.softAnalizList=np.append(self.softAnalizList,-1)
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self.hardAnalizList=np.append(self.hardAnalizList,-1)
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elif self.ans[i]==-1:
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self.softAnalizList=np.append(self.softAnalizList,-1)
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self.hardAnalizList=np.append(self.hardAnalizList,-1)
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else:
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self.softAnalizList = np.append(self.softAnalizList, 0)
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self.hardAnalizList = np.append(self.hardAnalizList, 1)
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self.softAnalizList=np.append(self.softAnalizList,0)
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self.hardAnalizList=np.append(self.hardAnalizList,1)
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print("Analiz DONE!")
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return 0
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def getMeteixDict(self, d):
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def getMeteixDict(self,d):
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'''
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1 - (сбывшиеся + несбывшиеся) \ (сбывшиеся + несбывшиеся +0)
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2 - (сбывшиеся - несбывшиеся) \ (сбывшиеся + несбывшиеся +0)
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'''
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return {
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'1': (d['1'] + d['-1']) / (d['1'] + d['-1'] + d['0']),
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'2': (d['1'] - d['-1']) / (d['1'] + d['-1'] + d['0']),
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'1':(d['1'] + d['-1']) / (d['1'] + d['-1'] + d['0']),
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'2':(d['1'] - d['-1']) / (d['1'] + d['-1'] + d['0']),
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}
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def getMetrix(self):
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softAnalizCount = {'-1': 0, '0': 0, '1': 0}
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hardAnalizCount = {'-1': 0, '0': 0, '1': 0}
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softAnalizCount = {'-1':0,'0':0,'1':0}
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hardAnalizCount = {'-1':0,'0':0,'1':0}
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for i in range(len(self.softAnalizList)):
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softAnalizCount[str(int(self.softAnalizList[i]))] += 1
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hardAnalizCount[str(int(self.hardAnalizList[i]))] += 1
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self.analizMetrics = {'softAnaliz': self.getMeteixDict(softAnalizCount),
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'hardAnaliz': self.getMeteixDict(hardAnalizCount)
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}
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softAnalizCount[str(int(self.softAnalizList[i]))]+=1
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hardAnalizCount[str(int(self.hardAnalizList[i]))]+=1
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self.analizMetrics = {'softAnaliz':self.getMeteixDict(softAnalizCount),
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'hardAnaliz':self.getMeteixDict(hardAnalizCount)
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}
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class signal_BB(coreSignalTrande):
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def __init__(self,
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data=pd.DataFrame(),
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dataType='candel',
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@@ -158,37 +150,101 @@ class signal_BB(coreSignalTrande):
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batchSize=None,
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indParams=None,
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signalParams=None,
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):
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):
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super().__init__(
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data=data,
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dataType=dataType,
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mode=mode,
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batchSize=batchSize,
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indParams=indParams,
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signalParams=signalParams,
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)
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data=data,
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dataType=dataType,
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mode=mode,
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batchSize=batchSize,
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indParams=indParams,
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signalParams=signalParams,
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)
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if self.indParams == None:
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indParams = {'MeanType': 'SMA', 'window': 15, 'valueType': 'low', 'kDev': 2}
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indParams={'MeanType':'SMA','window':15,'valueType':'low','kDev':2}
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else:
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indParams = self.indParams
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self.BB = ind_BB(
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indParams=self.indParams
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self.BB=ind_BB(
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data=data,
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options=indParams,
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)
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def getOnlineAns(self, data):
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ans = 0
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# print(data)
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def getOnlineAns(self,data):
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ans=0
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#print(data)
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self.BB.getAns(data)
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# print(BB)
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lastValue = data[self.signalParams['source']].to_list()[-1]
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if lastValue > self.BB.ans['pSTD'][-1]:
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ans = -1
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elif lastValue < self.BB.ans['mSTD'][-1]:
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ans = +1
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#print(BB)
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lastValue=data[self.signalParams['source']].to_list()[-1]
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if lastValue>self.BB.ans['pSTD'][-1]:
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ans=-1
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elif lastValue<self.BB.ans['mSTD'][-1]:
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ans=+1
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else:
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ans = 0
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ans=0
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return ans
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class signalAgrigator:
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"""
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dictAgrigSignal
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key - name str
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value - dict
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className - class
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indParams - dict
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signalParams - dict
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batchSize - int
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"""
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def __init__(self,
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data=pd.DataFrame(),
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dictAgrigSignal={},
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mode='online',
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dataType='candel',
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batchSize=None
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):
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self.createSingnalInstances(
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data,
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dictAgrigSignal,
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dataType,
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batchSize
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)
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self.mode=mode
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def createSingnalInstances(
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self,
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data,
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dictAgrigSignal,
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dataType,
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batchSize
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):
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ans={}
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for i in dictAgrigSignal:
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ans[i]=dictAgrigSignal[i]['className'](
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data=data,
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dataType=dataType,
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batchSize=batchSize,
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indParams=dictAgrigSignal[i]['indParams'],
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signalParams=dictAgrigSignal[i]['signalParams'],
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mode=self.mode
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)
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self.signalsInstances = ans
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return ans
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def getAns(self, data):
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ans={}
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if self.mode == 'online':
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for i in self.signalsInstances:
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ans[i]=(self.signalsInstances[i].getAns(data))
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elif self.mode == 'retroFast' or self.mode == 'retro':
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for i in self.signalsInstances:
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self.signalsInstances[i].getAns(data)
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ans[i]=self.signalsInstances[i].analizMetrics
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return ans
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