freqtrade_origin/scripts/plot_dataframe.py

#!/usr/bin/env python3

import sys
import argparse
import matplotlib  # Install PYQT5 manually if you want to test this helper function
matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt
from freqtrade import exchange, analyze
from freqtrade.misc import common_args_parser


def plot_parse_args(args ):
    parser = common_args_parser(description='Graph utility')
    parser.add_argument(
        '-p', '--pair',
        help = 'What currency pair',
        dest = 'pair',
        default = 'BTC_ETH',
        type = str,
    )
    parser.add_argument(
        '-i', '--interval',
        help = 'what interval to use',
        dest = 'interval',
        default = '5',
        type = int,
    )
    return parser.parse_args(args)


def plot_analyzed_dataframe(args):
    """
    Calls analyze() and plots the returned dataframe
    :param pair: pair as str
    :return: None
    """

    # Init Bittrex to use public API
    exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
    ticker = exchange.get_ticker_history(args.pair,args.interval)
    dataframe = analyze.analyze_ticker(ticker)

    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(args.pair + " " + str(args.interval), fontsize=14, fontweight='bold')
    ax1.plot(dataframe.index.values, dataframe['close'], label='close')
    # ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
    ax1.plot(dataframe.index.values, dataframe['sma'], '--', label='SMA')
    ax1.plot(dataframe.index.values, dataframe['tema'], ':', label='TEMA')
    ax1.plot(dataframe.index.values, dataframe['blower'], '-.', label='BB low')
    ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy')
    ax1.legend()

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

    ax3.plot(dataframe.index.values, dataframe['fastk'], label='k')
    ax3.plot(dataframe.index.values, dataframe['fastd'], label='d')
    ax3.plot(dataframe.index.values, [20] * len(dataframe.index.values))
    ax3.legend()

    # Fine-tune figure; make subplots close to each other and hide x ticks for
    # all but bottom plot.
    fig.subplots_adjust(hspace=0)
    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)