116 lines
3.9 KiB
Python
Executable File
116 lines
3.9 KiB
Python
Executable File
#!/usr/bin/env python3
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import sys
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import matplotlib # Install PYQT5 manually if you want to test this helper function
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matplotlib.use("Qt5Agg")
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import matplotlib.pyplot as plt
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import talib.abstract as ta
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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from pandas import DataFrame
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from freqtrade import exchange, analyze
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from freqtrade.misc import common_args_parser
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from freqtrade.strategy.strategy import Strategy
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def plot_parse_args(args):
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parser = common_args_parser(description='Graph utility')
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parser.add_argument(
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'-p', '--pair',
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help = 'What currency pair',
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dest = 'pair',
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default = 'BTC_ETH',
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type = str,
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)
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parser.add_argument(
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'-i', '--interval',
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help = 'what interval to use',
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dest = 'interval',
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default = 5,
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type = int,
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)
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return parser.parse_args(args)
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def plot_analyzed_dataframe(args) -> None:
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"""
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Calls analyze() and plots the returned dataframe
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:param pair: pair as str
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:return: None
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"""
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# Init strategy
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strategy = Strategy()
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strategy.init({'strategy': args.strategy})
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# Init Bittrex to use public API
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exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
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ticker = exchange.get_ticker_history(args.pair,args.interval)
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dataframe = analyze.analyze_ticker(ticker)
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dataframe = populate_indicator(dataframe)
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# Two subplots sharing x axis
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fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
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fig.suptitle(args.pair + " " + str(args.interval), fontsize=14, fontweight='bold')
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ax1.plot(dataframe.index.values, dataframe['close'], label='close')
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# ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
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ax1.plot(dataframe.index.values, dataframe['sma'], '--', label='SMA')
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ax1.plot(dataframe.index.values, dataframe['tema'], ':', label='TEMA')
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ax1.plot(dataframe.index.values, dataframe['bb_lowerband'], '-.', label='BB low')
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ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy')
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ax1.legend()
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ax2.plot(dataframe.index.values, dataframe['adx'], label='ADX')
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ax2.plot(dataframe.index.values, dataframe['mfi'], label='MFI')
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# ax2.plot(dataframe.index.values, [25] * len(dataframe.index.values))
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ax2.legend()
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ax3.plot(dataframe.index.values, dataframe['fastk'], label='k')
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ax3.plot(dataframe.index.values, dataframe['fastd'], label='d')
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ax3.plot(dataframe.index.values, [20] * len(dataframe.index.values))
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ax3.legend()
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# Fine-tune figure; make subplots close to each other and hide x ticks for
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# all but bottom plot.
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fig.subplots_adjust(hspace=0)
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plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
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plt.show()
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def populate_indicator(dataframe: DataFrame) -> DataFrame:
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dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
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dataframe.loc[dataframe['sell'] == 1, 'sell_price'] = dataframe['close']
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# ADX
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if 'adx' not in dataframe:
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dataframe['adx'] = ta.ADX(dataframe)
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# Bollinger bands
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if 'bb_lowerband' not in dataframe:
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bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
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dataframe['bb_lowerband'] = bollinger['lower']
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# Stoch fast
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if 'fastd' not in dataframe or 'fastk' not in dataframe:
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stoch_fast = ta.STOCHF(dataframe)
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dataframe['fastd'] = stoch_fast['fastd']
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dataframe['fastk'] = stoch_fast['fastk']
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# MFI
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if 'mfi' not in dataframe:
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dataframe['mfi'] = ta.MFI(dataframe)
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# SMA - Simple Moving Average
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if 'sma' not in dataframe:
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dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
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# TEMA - Triple Exponential Moving Average
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if 'tema' not in dataframe:
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dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
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return dataframe
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if __name__ == '__main__':
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args = plot_parse_args(sys.argv[1:])
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plot_analyzed_dataframe(args)
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