56 lines
2.0 KiB
Python
Executable File
56 lines
2.0 KiB
Python
Executable File
#!/usr/bin/env python3
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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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from freqtrade import exchange, analyze
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def plot_analyzed_dataframe(pair: str) -> 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 Bittrex to use public API
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exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
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ticker = exchange.get_ticker_history(pair)
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dataframe = analyze.analyze_ticker(ticker)
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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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# Two subplots sharing x axis
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fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
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fig.suptitle(pair, 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['blower'], '-.', 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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if __name__ == '__main__':
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plot_analyzed_dataframe('BTC_ETH')
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