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