#!/usr/bin/env python3 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 def plot_analyzed_dataframe(pair: str) -> None: """ 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(pair) 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(pair, 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__': plot_analyzed_dataframe('BTC_ETH')