Add support of custom strategy into plot_dataframe.py

scripts/plot_dataframe.py

@@ -1,12 +1,15 @@
 #!/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):
@@ -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:])