148 lines
3.6 KiB
Python
148 lines
3.6 KiB
Python
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import pandas as pd
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import datetime
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import numpy as np
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import plotly as pl
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import plotly.graph_objs as go
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import matplotlib.pyplot as plt
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import math
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import scipy
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import random
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import statistics
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import datetime
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import matplotlib.dates as mdates
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import matplotlib.pyplot as plt
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import mplfinance as mpf
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import plotly
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#import plotly.plotly as py
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import plotly.graph_objs as go
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# these two lines allow your code to show up in a notebook
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from plotly.offline import init_notebook_mode, iplot
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from plotly.subplots import make_subplots
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init_notebook_mode()
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import CoreTraidMath
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import CoreDraw
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class Stochastic:
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def __init__(self, base_df, options={
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'dataType':'ohcl',
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'window':14,
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'windowSMA':5
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}, needFig=False,showOnlyIndex=True,drawFig=False
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):
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self.base_df=base_df.reset_index(drop=True)
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self.options=options
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self.ans=self.getAns()
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if needFig:
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self.fig=self.pltShow(showOnlyIndex,drawFig)
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def getKn(self):
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ans={}
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y=np.asarray([])
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x=np.asarray([])
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for i in range(self.options['window'],self.base_df.shape[0]):
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minValue=min(self.base_df['low'][i-self.options['window']:i])
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maxValue=max(self.base_df['high'][i-self.options['window']:i])
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y=np.append(y,(self.base_df['close'][i-1]-minValue)/(maxValue-minValue))
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x=np.append(x,self.base_df['date'][i-1])
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#print(i,minValue,maxValue,self.base_df[self.options['colName']['close']][i],y[-1])
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ans['y'],ans['x']=y,x
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return ans
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def getSMA(self,col):
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ans=None
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ser = pd.Series(col, copy=False)
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op={'dataType':'series',
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'action':'findMean',
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'actionOptions':{'MeanType':'SMA','window':self.options['windowSMA']}
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}
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ans=np.asarray(CoreTraidMath.CoreMath(ser,op).ans)
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return ans
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#return np.convolve(col, np.ones(self.options['windowSMA']), 'valid') /self.options['windowSMA']
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def getDn(self,col):
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ans={}
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y=np.asarray([])
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x=np.asarray([])
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for i in range(self.options['windowSMA'],len(col['y'])):
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y=np.append(y, self.getSMA(col['y'][i-self.options['windowSMA']:i]))
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x=np.append(x,col['x'][i])
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ans['y'],ans['x']=y,x
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return ans
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def getAns(self):
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ans={}
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ans['Kn']=self.getKn()
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ans['Dn']=self.getDn(ans['Kn'])
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#print(ans)
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return(ans)
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def pltShow(self,showOnlyIndex,drawFig):
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ans=None
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req=[]
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row=1
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if not showOnlyIndex:
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row=2
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req.append({
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'vtype':'OCHL',
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'df':self.base_df,
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'row':1,
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'col':1,
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'name':'OHCL'
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})
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req.append({
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'vtype':'Scatter',
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'df':pd.DataFrame(
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{'value':self.ans['Kn']['y'],'date':self.ans['Kn']['x']}) ,
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'row':row,
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'col':1,
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'name':'Kn'
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})
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req.append({
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'vtype':'Scatter',
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'df':pd.DataFrame(
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{'value':self.ans['Dn']['y'],'date':self.ans['Dn']['x']}) ,
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'row':row,
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'col':1,
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'name':'Dn'
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})
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self.figDict=req
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ans = CoreDraw.coreDraw(req,drawFig)
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return ans
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