stable/scripts/plot_dataframe.py

#!/usr/bin/env python3

import sys
import matplotlib  # Install PYQT5 manually if you want to test this helper function
matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
from pandas import DataFrame
from freqtrade import exchange, analyze
from freqtrade.misc import common_args_parser
from freqtrade.strategy.strategy import Strategy


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) -> None:
    """
    Calls analyze() and plots the returned dataframe
    :param pair: pair as str
    :return: None
    """
    # Init strategy
    strategy = Strategy()
    strategy.init({'strategy': args.strategy})

    # 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 = populate_indicator(dataframe)

    # 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['bb_lowerband'], '-.', 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()

def populate_indicator(dataframe: DataFrame) -> DataFrame:

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

    # ADX
    if 'adx' not in dataframe:
        dataframe['adx'] = ta.ADX(dataframe)

    # Bollinger bands
    if 'bb_lowerband' not in dataframe:
        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
        dataframe['bb_lowerband'] = bollinger['lower']

    # Stoch fast
    if 'fastd' not in dataframe or 'fastk' not in dataframe:
        stoch_fast = ta.STOCHF(dataframe)
        dataframe['fastd'] = stoch_fast['fastd']
        dataframe['fastk'] = stoch_fast['fastk']

    # MFI
    if 'mfi' not in dataframe:
        dataframe['mfi'] = ta.MFI(dataframe)

    # SMA - Simple Moving Average
    if 'sma' not in dataframe:
        dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)

    # TEMA - Triple Exponential Moving Average
    if 'tema' not in dataframe:
        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)

    return dataframe


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