188 lines
6.4 KiB
Python
188 lines
6.4 KiB
Python
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import matplotlib.pyplot as plt
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import json
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import os
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from datetime import datetime, date, timedelta
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from matplotlib.dates import date2num
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import yfinance as yf
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import sys
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import glob
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import numpy as np
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from collections import Counter
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# path='../Febrian/Bang Nino/Samples/NEE/2020-05-08/'
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def django_pass(func_stock, func_param):
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# my_args = sys.argv[1:]
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my_args = func_stock
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tick = my_args
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# filter=int(my_args[1])
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filter = func_param
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visual=50
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# print(tick)
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# path='./Samples/'+tick+'/2020-12-07/'
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path='/home/kraken/Stock/v04/Samples/'+tick+'/'
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all_dirs = glob.glob(path+"*")
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# print(path)
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# print(all_dirs)
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latest_dir = max(all_dirs, key=os.path.getmtime)
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# print("Latest Data = ", latest_dir)
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latest_dir = latest_dir + "/"
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listsymbol = os.listdir(latest_dir+'/')
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# print(listsymbol)
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with open(latest_dir+listsymbol[0],'r') as f:
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# print(latest_dir+listsymbol[0])
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hasil=json.load(f)
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# print(hasil)
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# print(len(hasil[0]))
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# print(len(hasil[1]))
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# print(len(hasil[2]))
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akhir=datetime.strptime(str(hasil[2][-1]),'%Y-%m-%d').date()
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# print("Current Log : ",akhir)
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extend1=[akhir+timedelta(days=x) for x in range(1,50,1)]
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extend=[]
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for x in extend1:
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if x.weekday() not in [5,6]:
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extend.append(x)
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extend=extend[:14]
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extend=[str(x) for x in extend]
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# print("ASasdasdsa",extend)
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# date=date2num(date)
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date=hasil[2]
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# plt.plot(hasil[1],color='grey',linewidth=3, linestyle='--', marker='x', alpha=0.8, label="Confirmation")
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# plt.plot(hasil[2],hasil[1][0:-7],color='b',linewidth=2)
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# plt.show()
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symbol=yf.Ticker(tick)
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symbol=symbol.history(start=akhir,end=akhir+timedelta(days=30),interval='1d')
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# print(symbol)
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symbol=symbol.drop(symbol.index[0])
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symbol=symbol.drop(symbol.index[0])
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symbol=symbol['Close'][0:14].tolist()
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# plt.plot(extend,symbol,color='g',linewidth=10)
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avg=[]
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gap_avg = []
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for ex,x in enumerate(listsymbol):
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gap_val = []
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with open(latest_dir+x) as f:
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# print("#################################################")
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# print(x)
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hasil=json.load(f)
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# a=hasil[0][-14:][:14]
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a = hasil[0][-14:][:7]
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b=hasil[1][-7:]
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# print("A & B Temp :")
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# print(a)
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# print(b)
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count=0
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# print("Predict - Real ")
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for x in range(len(b)):
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# print("%.2f" % (a[x]-b[x]))
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if (b[x]-(filter/10) <= a[x] <= b[x]+(filter/10)):
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count=count+1
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if count>4:
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# print("ACCEPTED . . .")
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for i in range(len(b)):
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gap_val.append(abs(a[i]-b[i]))
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# print(len(gap_val))
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predict_val = hasil[0][-14:]
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avg.append(predict_val)
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# avg.append(hasil[0][-10][:14])
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# plt.plot(date+extend,hasil[0], label='Sample %s'%ex, alpha=0.3)
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gap_avg.append(gap_val)
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# print()
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# else:
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# print("NOT ACCEPTED . . .")
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# print()
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# print(avg)
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# print("#################################################")
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# print(avg)
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# print(len(avg))
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# print(gap_avg)
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# print(len(gap_avg))
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# print("#################################################")
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# avg_total=[]
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good_index=[]
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avg_total=[]
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for x in range(len(extend)):
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# print("NOW ", x)
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temp=[]
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gap_temp = []
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pred_temp = []
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if x < 7:
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for a in range(len(gap_avg)):
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# print(gap_temp.size())
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gap_temp.append(gap_avg[a][x])
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# print("Gap Temp")
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# print(gap_temp)
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# for b in range(len(gap_avg)):
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good_index.append(gap_temp.index(min(gap_temp)))
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else:
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# print("LOL")
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c = Counter(good_index)
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c = c.most_common(1)
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good_index.append(c[0][0])
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# print("Good Index")
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# print(len(good_index))
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# print(good_index)
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# print()
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for c in range(len(extend)):
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# print(c)
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temp.append(avg[int(good_index[c])][c])
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# print(temp)
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# avg_total.append(sum(temp)/len(temp))
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# mean_pred = np.mean(temp)
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# print(mean_pred)
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avg_total = temp
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# print(avg_total)
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atas=[x+(1/visual*x) for x in avg_total]
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bawah=[x-(1/visual*x) for x in avg_total]
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# print([hasil[1][0:-5][-1]]+bawah)
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# print([hasil[1][0:-5][-1]]+atas)
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# print([date[-1]]+extend)
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# plt.fill_between([date[-1]]+extend,[hasil[1][0:-5][-1]]+bawah,[hasil[1][0:-5][-1]]+atas,alpha=0.2,label='Prediction Band')
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# plt.plot([date[-1]]+extend,[hasil[1][-5]]+avg_total,color='y',linewidth=3,label='Prediction', marker='x')
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# plt.grid()
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# plt.show()
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# print("Date Extended ",(date+extend))
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symbol = yf.Ticker(tick)
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symbol = symbol.history(start=akhir,end=akhir+timedelta(days=20),interval='1d')
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#print(symbol)
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symbol = symbol.drop(symbol.index[0])
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symbol = symbol.drop(symbol.index[0])
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symbol = symbol['Close'][0:14].tolist()
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# symbol = symbol['Close'].tolist()
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## print(symbol)
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# plt.plot(extend[0:len(symbol)],symbol,color='r',label='Actual',linewidth=2)
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# plt.plot(hasil[1],color='r', linestyle='--', label='Confirmation',linewidth=2)
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# plt.plot(hasil[2]+extend[0:14],hasil[0],color='b',label='Train',linewidth=2, alpha=0.4)
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# plt.plot(symbol, label="Symbol Real")
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# plt.plot(hasil[0], label="Real Predictioh")
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# print(symbol)
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# print(symbol)
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# detail = str(akhir)+"\n"+"Prediction :"+str(avg_total[-1:])+"\n"+"Real : "
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# plt.text(0.05, 120, detail, color='black', bbox=dict(facecolor='none', edgecolor='black', boxstyle='round,pad=1'))
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# plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.01),
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# fancybox=True, shadow=True, ncol=7)
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# plt.title(tick+" Date: "+str(hasil[2][-1])+" to "+str(extend[-1]))
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# plt.get_xaxis().set_ticks([])
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# plt.xticks([])
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# plt.show()
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# plt.xlim([len(date)+len(extend)-30, len(date)+len(extend)])
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ret_data = []
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ret_date = []
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ret_date.append(hasil[2]+extend)
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ret_data.append(avg_total)
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# ret_data.append(hasil[1])
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ret_data.append(hasil[1])
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return ret_data, ret_date
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