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/' def django_pass(func_stock, func_param): # my_args = sys.argv[1:] my_args = func_stock tick = my_args # filter=int(my_args[1]) filter = func_param visual=50 # print(tick) # path='./Samples/'+tick+'/2020-12-07/' path='/home/kraken/Stock/v04/Samples/'+tick+'/' all_dirs = glob.glob(path+"*") # print(path) # print(all_dirs) latest_dir = max(all_dirs, key=os.path.getmtime) # 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=[] avg_total=[] 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) 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='r',label='Actual',linewidth=2) # 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() # plt.xlim([len(date)+len(extend)-30, len(date)+len(extend)]) ret_data = [] ret_date = [] ret_date.append(hasil[2]+extend) ret_data.append(avg_total) # ret_data.append(hasil[1]) ret_data.append(hasil[1]) return ret_data, ret_date