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OHLC.py
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OHLC.py
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import sys
from PyQt5.QtCore import Qt, QSize
from PyQt5.QtGui import QPalette, QColor
from PyQt5.QtWidgets import QAction, QApplication, QLabel, QMainWindow, QMenu
from PyQt5.QtWidgets import (
QHBoxLayout,
QVBoxLayout,
QStackedLayout,
QWidget,
QCheckBox,
QSlider,
QLabel,
)
import pyqtgraph as pg
import numpy as np
import pandas as pd
from abc import ABC, abstractmethod
from DataManipulation.indicators import NStepForwardPredictByD1,D1Crossing, D1, D2, MYEMA, LTSupport
class IndicatorPlot(ABC):
def __init__(self,name,data,hostplotwidget,color = None):
self.name = name
self.data = data
self.hostplotwidget = hostplotwidget
self.plot = None
if color is not None:
self.color = color
def getSerialColor(self):
colors = ('b', 'g', 'r', 'c', 'm', 'y')#, 'k', 'w')
NOPlotSharingWith = len(self.hostplotwidget.getPlotItem().dataItems)
return colors[NOPlotSharingWith%len(colors)]
def datalen(self):
return len(self.data)
@abstractmethod
def createLine(self,startidx,endidx,color = None):
pass
@abstractmethod
def updateData(self,startidx,endidx):
pass
class SeriesPlot(IndicatorPlot):
def __init__(self,name, data,hostplotwidget,color =None):
super().__init__(name,data,hostplotwidget,color)
def createLine(self,startidx,endidx,color = None):
if color is None:
if hasattr(self,'color') == False:
self.color = self.getSerialColor()
else:
self.color = color
pen = pg.mkPen(self.color) # sets the color
self.plot = self.hostplotwidget.plot(self.data[startidx:endidx],pen = pen,name=self.name)
self.hostplotwidget.plotItem.vb.disableAutoRange()
self.hostplotwidget.plotItem.setMouseEnabled(x=False, y=True)
def updateData(self,startidx,endidx):
self.plot.setData(self.data[startidx:endidx],connect="finite")
class PredictForwardPlot(IndicatorPlot):
def __init__(self,name,data,hostplotwidget,color =None):
super().__init__(name,data,hostplotwidget,color)
self.startpointratio = 4/5
self.plot = None
def createLine(self,startidx,endidx,color = None):
if color is None:
if hasattr(self,'color') == False:
self.color = self.getSerialColor()
else:
self.color = color
pen = pg.mkPen(self.color) # sets the color
self.startpoint = int(self.startpointratio*(endidx-startidx)) + startidx
self.plot = self.hostplotwidget.plot(
list(range(self.startpoint+1-startidx,self.startpoint+1-startidx+len(self.data[self.startpoint,:]))),
self.data[self.startpoint,:],
pen = pen,
name=self.name
)
def updateData(self,startidx,endidx):
self.startpoint = int(self.startpointratio*(endidx-startidx)) + startidx
self.plot.setData(
list(range(self.startpoint+1-startidx,self.startpoint+1-startidx+len(self.data[self.startpoint,:]))),
self.data[self.startpoint,:],
connect="finite"
)
class PGFigureLayoutWrap(QVBoxLayout):
def __init__(self,SeriesList,movingStats = None,datapoints = 10000, vertlabeldisplay = None):
super().__init__()
self.vertlabeldisplay = vertlabeldisplay
self.indicators = []
# self.colors = ('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w')
self.plotpanels = []
self.panelsverts = []
if isinstance(SeriesList,pd.DataFrame):
...
elif isinstance(SeriesList,list) and len(SeriesList)>0:
if isinstance(SeriesList[0],pd.Series):
...
elif isinstance(SeriesList[0],np.ndarray):
...
elif isinstance(SeriesList[0],dict):
for i in range(SeriesList[-1]['panelidx']+1):
self.plotpanels.append(pg.PlotWidget())
self.addWidget(self.plotpanels[i])
panelsvert = pg.InfiniteLine(angle = 90,movable = False)
self.panelsverts.append(panelsvert)
self.plotpanels[i].addItem(panelsvert)
for s in SeriesList:
if s['indtype'] == 'series':
self.indicators.append(
SeriesPlot(
s['name'],
s['data'],
self.plotpanels[s['panelidx']],
color = s['color'] if 'color' in s else None
)
)
elif s['indtype'] == 'predictforward':
self.indicators.append(
PredictForwardPlot(
s['name'],
s['data'],
self.plotpanels[s['panelidx']],
color = s['color'] if 'color' in s else None
)
)
else:
pass
else:
...
self.DATAPOINTS = datapoints#self.indicators[0].datalen()
self.minorDP = int(self.DATAPOINTS*2)
self.totalDP = self.indicators[0].datalen()
self.viewStartIdx = 0
self.viewEndIdx = self.DATAPOINTS
self.slidersmall = QSlider(Qt.Horizontal)
self.slidersmall.sliderMoved.connect(self.sliderSmove)
self.slidersmall.setMaximum(self.minorDP-self.DATAPOINTS)
self.sliderbig = QSlider(Qt.Horizontal)
self.sliderbig.sliderMoved.connect(self.sliderBmove)
#print(self.totalDP-self.minorDP)
self.sliderbig.setMaximum(self.totalDP-self.minorDP)
self.addWidget(self.slidersmall)
self.addWidget(self.sliderbig)
self.vertlineslide = QSlider(Qt.Horizontal)
self.vertlineslide.setMaximum(self.minorDP-self.DATAPOINTS)
self.vertlineslide.sliderMoved.connect(self.vertmove)
self.addWidget(self.vertlineslide)
#if movingStats is not None:
# self.statwidget = QWidget()
# self.statwidget.setLayout(QHBoxLayout)
# for stat in movingStats:
# self.statwidget.addWidget()
#
#
# self.addWidget(statwidget)
self.plot()
def plot(self):
self.plotlines = {}
for indicator in self.indicators:
indicator.createLine(self.viewStartIdx,self.viewEndIdx)
def updatePlotData(self):
for indicator in self.indicators:
indicator.updateData(self.viewStartIdx,self.viewEndIdx)
def sliderSmove(self,e):
self.viewStartIdx = self.sliderbig.value() + e
self.viewEndIdx = self.viewStartIdx + self.DATAPOINTS
self.updatePlotData()
def sliderBmove(self,e):
self.viewStartIdx = self.slidersmall.value() + e
self.viewEndIdx = self.viewStartIdx + self.DATAPOINTS
self.updatePlotData()
def vertmove(self,e):
for line in self.panelsverts:
line.setValue(e)
if self.vertlabeldisplay is not None:
self.vertlabeldisplay.setText(str(e))
class MainWindow(QMainWindow):
def __init__(self,period):
super(MainWindow, self).__init__()
self.setWindowTitle("My App")
self.layout = QHBoxLayout()
self.VertBarValue = QLabel("EMPTY")#QCheckBox()
self.leftbar = QVBoxLayout()
self.leftbar.addWidget(self.VertBarValue)
# right Content
if period == 'm':
self.data = self.prepareMinutes()
self.rightmain = PGFigureLayoutWrap(self.data,datapoints = 10000*10,vertlabeldisplay = self.VertBarValue)
elif period == 'h':
self.data = self.prepareHourly()
self.rightmain = PGFigureLayoutWrap(self.data,datapoints = 10000,vertlabeldisplay = self.VertBarValue)
self.layout.addLayout(self.leftbar)
self.layout.addLayout(self.rightmain)
widget = QWidget()
widget.setLayout(self.layout)
self.setCentralWidget(widget)
def prepareHourly(self,):
minutes = self.getOHLC_pickle("EURUSD_M_2010_2021.pkl")
hourly = minutes.resample('1H').agg({'Open': 'first',
'High': 'max',
'Low': 'min',
'Close': 'last'}).dropna()
emaperiods = [100,200,300,24*100,24*200]
from DataManipulation.DataHandler import DemaMinDayMultinom
dataHset = DemaMinDayMultinom(hourly,emaperiods = emaperiods)
data = [
{'name':'Close' ,'data':hourly['Close'], 'indtype':'series', 'panelidx':0,'color':'b' },
{'name':'dema9' ,'data':hourly['dema9'], 'indtype':'series', 'panelidx':0,'color': 'c' },
{'name':'ema100' ,'data':hourly['ema100'], 'indtype':'series', 'panelidx':0,'color':'r' },
{'name':'ema200' ,'data':hourly['ema200'], 'indtype':'series', 'panelidx':0,'color':'g' },
{'name':'ema300' ,'data':hourly['ema300'], 'indtype':'series', 'panelidx':0,'color':'y' },
{'name':'ema2400' ,'data':hourly['ema2400'], 'indtype':'series', 'panelidx':0,'color':'c' },
{'name':'ema4800' ,'data':hourly['ema4800'], 'indtype':'series', 'panelidx':0,'color':'m' },
#{'name':'5StepEMA2400','data':NStepForwardPredictByD1(24*5).look(hourly['ema2400'].to_numpy()), 'indtype':'predictforward','panelidx':0,'color':'b' },
#{'name':'5StepEMA4800','data':NStepForwardPredictByD1(24*5).look(hourly['ema4800'].to_numpy()), 'indtype':'predictforward','panelidx':0,'color':'r' },
#{'name':'24_48crossing','data':D1Crossing(hourly['ema2400'].to_numpy(), hourly['ema4800'].to_numpy(),n=24*5).astype('int8'), 'indtype':'series','panelidx':1 },
{'name':'4800Var4800','data':hourly['ema4800'].rolling(4800).std(),'indtype':'series','panelidx':1,'color':'m'},
{'name':'2400Var2400','data':hourly['ema2400'].rolling(2400).std(),'indtype':'series','panelidx':1,'color':'c'},
{'name':'300Var300','data':hourly['ema300'].rolling(300).std() ,'indtype':'series','panelidx':1,'color':'y'},
{'name':'100Var100','data':hourly['ema100'].rolling(100).std() ,'indtype':'series','panelidx':1,'color':'r'},
{'name':'100Var100D1','data':D1(hourly['ema100'].rolling(100).std()) ,'indtype':'series','panelidx':2,'color':'r'},
{'name':'300Var300D1','data':D1(hourly['ema300'].rolling(300).std()) ,'indtype':'series','panelidx':2,'color':'y'},
{'name':'2400Var2400D1','data':D1(hourly['ema2400'].rolling(2400).std()) ,'indtype':'series','panelidx':2,'color':'c'},
{'name':'2400Var2400D1','data':D1(hourly['ema2400'].rolling(4800).std()) ,'indtype':'series','panelidx':2,'color':'m'},
{'name':'_DIVIDER','data':np.zeros(len(hourly['ema300'])) ,'indtype':'series','panelidx':2,'color':'b'},
{'name':'100-300','data':MYEMA(hourly['ema100']-hourly['ema300'],period=100) ,'indtype':'series','panelidx':3,'color':'r'},
{'name':'100-300','data':MYEMA(hourly['ema100']-hourly['ema300'],period=300) ,'indtype':'series','panelidx':3,'color':'y'},
{'name':'100-300','data':hourly['ema100']-hourly['ema300'] ,'indtype':'series','panelidx':3,'color':'c'},
#{'name':'100-300','data':(hourly['ema100']-hourly['ema300']).rolling(300).std() ,'indtype':'series','panelidx':3,'color':'c'},
{'name':'_DIVIDER','data':np.zeros(len(hourly['ema300'])) ,'indtype':'series','panelidx':3,'color':'b'},
#{'name':'300Var300D2','data':D2(hourly['ema300'].rolling(300).std()) ,'indtype':'series','panelidx':3,'color':'y'},
#{'name':'2400Var2400D2','data':D2(hourly['ema2400'].rolling(2400).std()) ,'indtype':'series','panelidx':3,'color':'c'},
#{'name':'4800Var4800D2','data':D2(hourly['ema4800'].rolling(4800).std()) ,'indtype':'series','panelidx':3,'color':'m'},
#{'name':'ema2400D1' ,'data':D1(hourly['ema2400']), 'indtype':'series', 'panelidx':4,'color':'c' },
#{'name':'ema2400support' ,'data':LTSupport(hourly['ema2400'].to_numpy(),emaperiod=2400), 'indtype':'series', 'panelidx':4,'color':'c' },
{'name':'2400-4800','data':MYEMA(hourly['ema2400']-hourly['ema4800'],period=2400) ,'indtype':'series','panelidx':4,'color':'r'},
{'name':'2400-4800','data':MYEMA(hourly['ema2400']-hourly['ema4800'],period=4800) ,'indtype':'series','panelidx':4,'color':'y'},
{'name':'2400-4800','data':hourly['ema2400']-hourly['ema4800'] ,'indtype':'series','panelidx':4,'color':'c'},
#{'name':'100-300','data':(hourly['ema100']-hourly['ema300']).rolling(300).std() ,'indtype':'series','panelidx':3,'color':'c'},
{'name':'_DIVIDER','data':np.zeros(len(hourly['ema300'])) ,'indtype':'series','panelidx':4,'color':'b'},
#{'name':'300D1DEV','data':hourly['ema300']-hourly['ema300'].rolling(300).mean(),'indtype':'series','panelidx':3}, Unstable
]
#print(MYEMA(hourly['ema100']-hourly['ema300'],period = 100,debug = True) )
#print(MYEMA(hourly['Close'],period = 100,debug = True) )
return data
def prepareMinutes(self,):
minutes = self.getOHLC_pickle("EURUSD_M_2010_2021.pkl")
emaperiods = [100,200,300,24*100,24*200]
from DataManipulation.DataHandler import DemaMinDayMultinom
dataMset = DemaMinDayMultinom(minutes,emaperiods = emaperiods)
ema100h = MYEMA(minutes['Close'],100*60)
ema300h = MYEMA(minutes['Close'],300*60)
ema2400h = MYEMA(minutes['Close'],2400*60)
ema4800h = MYEMA(minutes['Close'],4800*60)
data = [
{'name':'Close' ,'data':minutes['Close'], 'indtype':'series', 'panelidx':0,'color':'b' },
{'name':'ema100' ,'data':minutes['ema100'], 'indtype':'series', 'panelidx':0,'color':'r' },
{'name':'ema200' ,'data':minutes['ema200'], 'indtype':'series', 'panelidx':0,'color':'g' },
{'name':'ema300' ,'data':minutes['ema300'], 'indtype':'series', 'panelidx':0,'color':'y' },
{'name':'ema2400' ,'data':minutes['ema2400'], 'indtype':'series', 'panelidx':0,'color':'c' },
{'name':'ema4800' ,'data':minutes['ema4800'], 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'ema100h' ,'data':ema100h, 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'ema300h' ,'data':ema300h, 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'ema2400h' ,'data':ema2400h, 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'ema4800h' ,'data':ema4800h, 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'4800hVar4800','data':pd.Series(ema4800h).rolling(4800*60).std(),'indtype':'series','panelidx':1,'color':'m'},
{'name':'2400hVar2400','data':pd.Series(ema2400h).rolling(2400*60).std(),'indtype':'series','panelidx':1,'color':'c'},
{'name':'300hVar300','data':pd.Series(ema300h).rolling(300*60).std() ,'indtype':'series','panelidx':1,'color':'y'},
{'name':'100hVar100','data':pd.Series(ema100h).rolling(100*60).std() ,'indtype':'series','panelidx':1,'color':'r'},
{'name':'300hVar300D1','data':D1(pd.Series(ema300h).rolling(300*60).std()) ,'indtype':'series','panelidx':2,'color':'y'},
#{'name':'_DIVIDER','data':np.zeros(len(minutes['ema300'])) ,'indtype':'series','panelidx':2,'color':'b'},
{'name':'2400-4800','data':MYEMA(minutes['ema2400']-minutes['ema4800'],period=2400) ,'indtype':'series','panelidx':3,'color':'r'},
{'name':'2400-4800','data':MYEMA(minutes['ema2400']-minutes['ema4800'],period=4800) ,'indtype':'series','panelidx':3,'color':'y'},
{'name':'2400-4800','data':minutes['ema2400']-minutes['ema4800'] ,'indtype':'series','panelidx':3,'color':'c'},
{'name':'_DIVIDER','data':np.zeros(len(minutes['ema300'])) ,'indtype':'series','panelidx':3,'color':'b'},
]
return data
def prepareMinutes_Old(self,):
minutes = self.getOHLC_pickle("EURUSD_M_2010_2021.pkl")
emaperiods = [100,200,300,24*100,24*200]
from DataManipulation.DataHandler import DemaMinDayMultinom
dataMset = DemaMinDayMultinom(minutes,emaperiods = emaperiods)
ema100h = MYEMA(minutes['Close'],100*60)
ema300h = MYEMA(minutes['Close'],300*60)
ema2400h = MYEMA(minutes['Close'],2400*60)
ema4800h = MYEMA(minutes['Close'],4800*60)
data = [
{'name':'Close' ,'data':minutes['Close'], 'indtype':'series', 'panelidx':0,'color':'b' },
{'name':'ema100' ,'data':minutes['ema100'], 'indtype':'series', 'panelidx':0,'color':'r' },
{'name':'ema200' ,'data':minutes['ema200'], 'indtype':'series', 'panelidx':0,'color':'g' },
{'name':'ema300' ,'data':minutes['ema300'], 'indtype':'series', 'panelidx':0,'color':'y' },
{'name':'ema2400' ,'data':minutes['ema2400'], 'indtype':'series', 'panelidx':0,'color':'c' },
{'name':'ema4800' ,'data':minutes['ema4800'], 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'ema100h' ,'data':ema100h, 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'ema300h' ,'data':ema300h, 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'ema2400h' ,'data':ema2400h, 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'ema4800h' ,'data':ema4800h, 'indtype':'series', 'panelidx':0,'color':'m' },
{'name':'4800hVar4800','data':pd.Series(ema4800h).rolling(4800*60).std(),'indtype':'series','panelidx':1,'color':'m'},
{'name':'2400hVar2400','data':pd.Series(ema2400h).rolling(2400*60).std(),'indtype':'series','panelidx':1,'color':'c'},
{'name':'300hVar300','data':pd.Series(ema300h).rolling(300*60).std() ,'indtype':'series','panelidx':1,'color':'y'},
{'name':'100hVar100','data':pd.Series(ema100h).rolling(100*60).std() ,'indtype':'series','panelidx':1,'color':'r'},
{'name':'300hVar300D1','data':D1(pd.Series(ema300h).rolling(300*60).std()) ,'indtype':'series','panelidx':2,'color':'y'},
#{'name':'_DIVIDER','data':np.zeros(len(minutes['ema300'])) ,'indtype':'series','panelidx':2,'color':'b'},
{'name':'300Var300D2','data':D2(pd.Series(ema300h).rolling(300*60).std()) ,'indtype':'series','panelidx':3,'color':'y'},
#{'name':'4800Var4800','data':minutes['ema4800'].rolling(4800).std(),'indtype':'series','panelidx':1,'color':'m'},
#{'name':'2400Var2400','data':minutes['ema2400'].rolling(2400).std(),'indtype':'series','panelidx':1,'color':'c'},
#{'name':'300Var300','data':minutes['ema300'].rolling(300).std() ,'indtype':'series','panelidx':1,'color':'y'},
#{'name':'100Var100','data':minutes['ema100'].rolling(100).std() ,'indtype':'series','panelidx':1,'color':'r'},
#{'name':'300Var300D1','data':D1(minutes['ema300'].rolling(300).std()) ,'indtype':'series','panelidx':2,'color':'y'},
#{'name':'_DIVIDER','data':np.zeros(len(minutes['ema300'])) ,'indtype':'series','panelidx':3,'color':'b'},
#{'name':'300Var300D2','data':D2(minutes['ema300'].rolling(300).std()) ,'indtype':'series','panelidx':3,'color':'y'},
#{'name':'300D1DEV','data':minutes['ema300']-minutes['ema300'].rolling(300).mean(),'indtype':'series','panelidx':3}, Unstable
]
return data
def getOHLC_pickle(self,pklpath):
import pickle
with open(pklpath,'rb') as f:
data = pickle.load(f)
return data
def getOHLC_raw(self,to_pickle=False):
from DataManipulation.DataHandler import mergeMonths, DemaMinDayMultinom
import pandas as pd
from torch.utils.data import ConcatDataset
#data = mergePeriod(1,4,beg="DAT_ASCII_EURUSD_M1_2021",dir="./eurusd2021/",dump=False)
data2021 = mergeMonths(start=1, end=9,beg="DAT_ASCII_EURUSD_M1_2021",dir = './Data/eurusd2021/', dump=False)
dir = "./Data/"
beg = "DAT_ASCII_EURUSD_M1_"
years = range(2010,2021)
dataY = []
for y in years:
dataY.append(pd.read_csv(dir+beg+str(y)+'.csv',sep=';',names = ['Open','High','Low','Close','Volume']))
dataY.append(data2021)
data = pd.concat(dataY)
data.index.name = "Date"
data.index = pd.to_datetime(data.index)
if to_pickle:
import pickle
with open('OHLC.pkl','wb') as f:
pickle.dump(data,f,protocol=pickle.HIGHEST_PROTOCOL)
return data
if __name__ == '__main__':
print("MAIN")
import argparse
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('-p','--period',action='store',required=True,help = "h for hour, m for minutes")
args = parser.parse_args()
if args.period == 'h' or args.period == 'm':
app = QApplication(sys.argv)
window = MainWindow(args.period)
window.show()
app.exec()
else:
print("not supported")