#!/usr/bin/env python3

import sys
import logging
import argparse
import matplotlib
import matplotlib.dates as mdates
import matplotlib.pyplot as plt
from freqtrade import exchange, analyze
import freqtrade.misc as misc
import freqtrade.optimize as optimize
import freqtrade.analyze as analyze

logger = logging.getLogger(__name__)


def plot_parse_args(args):
    parser = misc.common_args_parser('Graph dataframe')
    misc.backtesting_options(parser)
    misc.scripts_options(parser)
    return parser.parse_args(args)


def plot_analyzed_dataframe(args):
    """
    Calls analyze() and plots the returned dataframe
    :param pair: pair as str
    :return: None
    """
    pair = args.pair
    pairs = [pair]
    timerange = misc.parse_timerange(args.timerange)

    tickers = {}
    if args.live:
        logger.info('Downloading pair.')
        exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
        tickers[pair] = exchange.get_ticker_history(pair, args.ticker_interval)
    else:
        tickers = optimize.load_data(args.datadir, pairs=pairs,
                                     ticker_interval=args.ticker_interval,
                                     refresh_pairs=False,
                                     timerange=timerange)
    dataframes = optimize.tickerdata_to_dataframe(tickers)
    dataframe = dataframes[pair]
    dataframe = analyze.populate_buy_trend(dataframe)
    dataframe = analyze.populate_sell_trend(dataframe)

    dates = misc.datesarray_to_datetimearray(dataframe['date'])

    dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
    dataframe.loc[dataframe['sell'] == 1, 'sell_price'] = dataframe['close']

    # Two subplots sharing x axis
    fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
    fig.suptitle(pair + " " + str(args.ticker_interval), fontsize=14, fontweight='bold')
    ax1.plot(dates, dataframe['close'], label='close')
    # ax1.plot(dates, dataframe['sell'], 'ro', label='sell')
    ax1.plot(dates, dataframe['sma'], '--', label='SMA')
    ax1.plot(dates, dataframe['tema'], ':', label='TEMA')
    ax1.plot(dates, dataframe['blower'], '-.', label='BB low')
    ax1.plot(dates, dataframe['buy_price'], 'bo', label='buy')
    ax1.legend()

    ax2.plot(dates, dataframe['adx'], label='ADX')
    ax2.plot(dates, dataframe['mfi'], label='MFI')
    # ax2.plot(dates, [25] * len(dataframe.index.values))
    ax2.legend()

    ax3.plot(dates, dataframe['fastk'], label='k')
    ax3.plot(dates, dataframe['fastd'], label='d')
    ax3.plot(dates, [20] * len(dataframe.index.values))
    ax3.legend()
    xfmt = mdates.DateFormatter('%d-%m-%y %H:%M')  # Dont let matplotlib autoformat date
    ax3.xaxis.set_major_formatter(xfmt)

    # Fine-tune figure; make subplots close to each other and hide x ticks for
    # all but bottom plot.
    fig.subplots_adjust(hspace=0)
    fig.autofmt_xdate()  # Rotate the dates
    plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
    plt.show()


if __name__ == '__main__':
    args = plot_parse_args(sys.argv[1:])
    plot_analyzed_dataframe(args)