diff --git a/scripts/plot_dataframe.py b/scripts/plot_dataframe.py index d2c32d754..415ca1882 100755 --- a/scripts/plot_dataframe.py +++ b/scripts/plot_dataframe.py @@ -1,15 +1,18 @@ #!/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 +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 ): +def plot_parse_args(args): parser = common_args_parser(description='Graph utility') parser.add_argument( '-p', '--pair', @@ -22,26 +25,28 @@ def plot_parse_args(args ): '-i', '--interval', help = 'what interval to use', dest = 'interval', - default = '5', + default = 5, type = int, ) return parser.parse_args(args) -def plot_analyzed_dataframe(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.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close'] - dataframe.loc[dataframe['sell'] == 1, 'sell_price'] = dataframe['close'] + dataframe = populate_indicator(dataframe) # Two subplots sharing x axis fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True) @@ -50,7 +55,7 @@ def plot_analyzed_dataframe(args): # 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['bb_lowerband'], '-.', label='BB low') ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy') ax1.legend() @@ -70,6 +75,40 @@ def plot_analyzed_dataframe(args): 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:])