#!/usr/bin/python3.6

import pandas as pd
import pandas_datareader.data
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.ticker as ticker
from mpl_finance import candlestick_ohlc
from mpl_finance import candlestick2_ohlc
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
import datetime
import cgi
import os, random, re

form = cgi.FieldStorage() 
select_day = ""

if form.getvalue("select-day"):
   select_day = form.getvalue("select-day")
   m_select_day = re.match("([0-9]{4})-([0-9]{2})-([0-9]{2})", select_day)
   if m_select_day:
      year = m_select_day.groups()[0]
      month = m_select_day.groups()[1]
      day = m_select_day.groups()[2]

chart_type = form.getvalue("chart_type")

if chart_type == "line":

   today_s = datetime.date.today().strftime('%Y%m%d')

   #df = pd.read_csv('futures.' + today_s + '.txt', names=['Time', 'HSIF', 'Volume'], delim_whitespace=True)
   df = pd.read_csv('/root/futures/' + year + '-' + month + '/futures.' + year + month + day + '.txt', names=['Time', 'HSIF', 'Volume'], delim_whitespace=True)
   #df = pd.read_csv('/root/futures/2019-05/futures-sample.txt', names=['Time', 'HSIF', 'Volume'], delim_whitespace=True)
   df['Time'] = pd.to_datetime(df['Time'])

   # RSI
   window_length = 14
   df['Delta'] = df['HSIF'].diff().shift(0)
   df['DeltaUp'] = df['Delta'].apply(lambda x: x if x > 0 else 0)
   df['DeltaDown'] = df['Delta'].apply(lambda x: -x if x < 0 else 0)
   df['RollUp'] = df['DeltaUp'].rolling(window_length).mean()
   df['RollDown'] = df['DeltaDown'].rolling(window_length).mean()
   df['RS'] = df['RollUp'] / df['RollDown']
   df['RSI'] = 100.0 - (100.0 / (1.0 + df['RS']))
   pd.set_option('display.max_rows', 10000)

   #df = df.set_index('Time')
   #print(df)
   df = df[df['Volume']>0]
   df = df.reset_index(drop=True)
   N = len(df)

   def format_date(x, pos=None):
      thisind = np.clip(int(x+0.5), 0, N-1)
      return df.Time[thisind].strftime('%H:%M')


   fig , ax1 = plt.subplots()
   ax1.set_title(year + month + day + ' HSIF Chart   -   by Patrick Chan')
   ax1.set_xlim([0,N+3])
   ax1.set_xlabel('Time')
   ax1.set_ylabel('HSIF', color='blue')
   ax1.plot(np.arange(len(df)),df['HSIF'], color='blue')
   ax1.tick_params(axis='y', labelcolor='blue')
   ax1.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
   ax1.xaxis.set_major_locator(ticker.FixedLocator([15,45,75,105,135,166,197,227,257,287,317,347,377]))
   ax1.grid(True)
   #ax2= ax1.twinx()
   #ax2.set_ylabel('RSI', color='orchid')
   #ax2.plot(np.arange(len(df)),df['RSI'], color='orchid')
   #ax2.tick_params(axis='y', labelcolor='orchid')


   fig = ax1.get_figure()
   fig.set_size_inches(8, 5)
   fig.savefig('/var/www/html/chart.png', dpi=100)

elif chart_type == "candlestick":

   pd.set_option('display.max_rows', 10000)

   df = pd.read_csv('/root/futures/' + year + '-' + month + '/futures.' + year + month + day + '.txt', names=['Time', 'HSIF', 'Volume'], delim_whitespace=True)
   df['Time'] = pd.to_datetime(df['Time'], format='%Y/%m/%d-%H:%M')
   df = df[df['Volume']>0]
   df_ohlc = df.set_index('Time')['HSIF'].resample('5T').ohlc()
   df_ohlc = df_ohlc[pd.notnull(df_ohlc['open'])]
   df_ohlc.reset_index(inplace=True)
   #print(df_ohlc)

   xtime = [ i.strftime('%H:%M') for i in df_ohlc['Time'] ]
   #print(xtime)

   df_ohlc['Time'] = df_ohlc['Time'].apply(mdates.date2num)
   #print(df_ohlc)

   def mydate(x, pos):
      return xtime[pos*6]

   N = len(df_ohlc)
   fig, ax = plt.subplots()
   #candlestick_ohlc(ax, df_ohlc.values, width=5/(24*60), colorup='g', colordown='r')
   candlestick2_ohlc(ax, df_ohlc['open'], df_ohlc['high'], df_ohlc['low'], df_ohlc['close'], width=.6, colorup='g', colordown='r')
   ax.set_title(year + month + day + ' HSIF Chart   -   by Patrick Chan')
   ax.set_xlim([0,N+3])
   ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
   ax.xaxis.set_major_locator(ticker.FixedLocator(np.arange(0,len(df_ohlc),6)))
   #ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
   #ax.xaxis_date()
   ax.grid(True)
   fig.set_size_inches(8,5)
   fig.savefig('/var/www/html/chart.png', dpi=100)

# OS Walk
path = '/root/futures'
available_days = []
for root,dirs,files in os.walk(path):
   for name in files:
      m = re.match(r"futures\.([0-9]{8})\.txt", name)
      if m:
         available_day = m.groups()[0]
         available_day_formatted = available_day[0:4] + '-' + available_day[4:6] + '-' + available_day[6:8]
         available_days.append(available_day_formatted) 
available_days = sorted(available_days, reverse=True)


# Print HTML
print("Content-type:text/html\r\n\r\n")
print('''
<html>
<head>
</head>
<body>
<center>
''')

print('<img name="chart" src="/chart.png?rand=' + str(random.randint(1,999)) + '">')

print('''
<form action="/cgi-bin/plot.py" method="post">
<select name="select-day" autofocus>
''')

for i in available_days:
   if i == select_day:
      print('<option value="' + i + '" selected>' + i + '</option>')
   else:
      print('<option value="' + i + '">' + i + '</option>')

print('''
</select>&nbsp;&nbsp
<input type="radio" name="chart_type" value="candlestick" checked>CandleStick
<input type="radio" name="chart_type" value="line">Line
<p>
<input type="submit" value="Submit">
</form>
</center>
</body>
</html>
''')