CRYPTO FORECASTING TOOL 2.6

#☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀ CRYPTO FORECASTING TOOL ☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀

'''
Contact: https://steemit.com/@profitgenerator

Copyright 2017 Profitgenerator

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
'''

#☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀ ▶ dependencies ◀ ☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀

import os.path
import math

#☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀ ▶ parameters ◀ ☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀

version  = "2.6"
ARRAY    = []
FORECAST = []
file_name= "btc_usd.csv"
period   = 840
forward_steps =1
best_period   = 0
min_error     = 999999999999.0

#☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀ ▶ functions ◀ ☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀

def process_file():
    with open("data/"+file_name,'r') as f:
        lines=f.readlines()
    ARRAY.append(['dummytime', 'dummyprice'])
    FORECAST.append('dummyforecast')
    for i in range(0,len(lines)):
        ARRAY.append(lines[i].strip().split(','))
        FORECAST.append("dummy")
    return (len(ARRAY) -1)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

def linear_forecast_diff(limit,f_period):
      f_diff=0.0
      for i in range(limit-f_period+1,limit+1): # make it [,]
           f_diff=f_diff +   (float(ARRAY[i][1])-float(ARRAY[i-1][1]))
      f_diff/=f_period
      return (f_diff)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

def verification(limit,f_period_corrector,f_error_ignore,f_period):
   f_diff=linear_forecast_diff(limit,f_period)
   last_real    =float(ARRAY[limit+1][1])
   last_forecast=float(ARRAY[limit  ][1])+(f_diff*forward_steps)
   # manual correction for negative log values or zero division
   if(last_forecast<=0):
        f_period_corrector+=1
        f_error_ignore=True
        FORECAST[limit+1]="error"
       # print("here "+str(f_period)+" "+str(f_diff)+" "+str(limit))
        return (0,f_period_corrector,f_error_ignore)
   else:
        FORECAST[limit+1]=last_forecast
        error=abs(math.log(float(last_real/last_forecast)))
        return (error,f_period_corrector,f_error_ignore)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

# formula: https://docs.oracle.com/cd/E17236_01/epm.1112/cb_statistical/frameset.htm?ch07s02s03s04.html
def theil_u():
   upper=0.0
   lower=0.0
   for x in range(1+period,arraysize-forward_steps): # N-1 for Theil's U
       if(ARRAY[x+1][1]!="error" and ARRAY[x+2][1]!="error" and FORECAST[x+1]!="error" and FORECAST[x+2]!="error"):
          cur_real       =float(ARRAY   [x+1][1])
          cur_forecast   =float(FORECAST[x+1])
          future_real    =float(ARRAY   [x+2][1])
          future_forecast=float(FORECAST[x+2])
          upper+= ((future_forecast-future_real)/cur_real)**2
          lower+= ((future_real-cur_real)       /cur_real)**2
   if(upper!=0.0 and lower!=0.0):
       theil=math.sqrt(upper/lower)
       return (theil)

   else:
       return (1)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

def user_interaction():
   print ("\n")
   print ("Choose Option!")
   print ("Backtest: 0")
   print ("Forecast: 1")
   print ("Brute Force: 2")
   return(input())

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

def main_function(f_period,f_best_period,f_min_error):
   if(userinput=="0" or userinput=="2" ):
        error=0.0
        period_corrector=0
        error_ignore=False
        theilu=0.0
        for k in range(1+f_period,arraysize-forward_steps+1): # +1 to fill the [] zone , -1 to go until the prev value
            output=verification(k,period_corrector,error_ignore,f_period)
            if(output[2]==False):
              error+=output[0]
            error_ignore=False
        error/= (arraysize-f_period-forward_steps-output[1])

        if(userinput=="2" ):
          if (error<f_min_error):
            f_min_error=error
            f_best_period=f_period

        if(userinput=="0"):
            theilu=theil_u()
            print ("    "+'\033[103m'+'\033[1m'  +"Profitgenerator's CRYPTO FORECASTING TOOL v"+version+ '\033[0m')
            print ("\n")
            print ("    Mode:              "+"Backtest")
            print ("    File Name:         "+file_name)
            print ("    From:              "+str(ARRAY[1][0])+" to "+str(ARRAY[arraysize][0]))
            print ("    Array Size:        "+str(arraysize))
            print ("    Period:            "+str(f_period))
            print ("    Forward Steps:     "+str(forward_steps))
            print ("    Iterations:        "+str((arraysize-f_period-forward_steps)))
            print ("    "+'\033[106m' +'\033[1m'  +"LN Error:          "+str(error)+ '\033[0m'    )
            print ("    Theil's U:         "+str(theilu))
            if(theilu<1):
                print ("    "+'\033[102m'+'\033[1m'  +"Predictive Edge:   "+str((1-theilu)) + '\033[0m')
            else:
                print ("    "+'\033[101m'+'\033[1m'  +"Predictive Edge:   "+str((1-theilu)) + '\033[0m')

   if(userinput=="1"):
        difference=linear_forecast_diff(arraysize,f_period)
        lastprice=float(ARRAY[arraysize][1])
        forecast=lastprice+(difference*forward_steps)
        print ("    "+'\033[103m'+'\033[1m'  +"Profitgenerator's CRYPTO FORECASTING TOOL v"+version+ '\033[0m')
        print ("\n")
        print("    Mode:                  "+"Forecast")
        print("    File Name:             "+file_name)
        print("    Array Size:            "+str(arraysize))
        print("    Period:                "+str(f_period))
        print("    Forward Steps:         "+str(forward_steps))
        print("    Last Price:            "+str(lastprice))
        print("    "+'\033[106m' +'\033[1m'  +"Forecasted Next Price: "+str(forecast)+ '\033[0m')
  # print(f_best_period,f_min_error)
   return (f_best_period,f_min_error)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -


#☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀ ▶ main ◀ ☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀☀


arraysize=process_file()


if((period+forward_steps)>arraysize-2):
   period=1
   forward_steps=1
userinput     = user_interaction()


print ("\n\n")
if(userinput=="0" or userinput=="1" ):
   main_function(period,best_period,min_error)
if(userinput=="2" ):
   for period in range (1,arraysize-forward_steps):
     main_output=main_function(period,best_period,min_error) # +1 to fill the [] zone
     best_period=main_output[0]
     min_error  =main_output[1]
   print ("    Mode:                  "+"Brute Force")
   print ("    Forward Steps:         "+str(forward_steps))
   print ("    Best Period:           "+str(best_period))
   print ("    Error:                 "+str(min_error))
print ("\n\n")



'''
for x in range (0,200):
     print('\033['+str(x)+'m' +"    testcolors12345678: "+ '\033[0m'+str(x))
'''