Add support of custom strategy into plot_dataframe.py

This commit is contained in:
Gerald Lonlas 2018-01-22 21:09:40 -08:00
parent 41aa8f18fb
commit 00f1c57279

View File

@ -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:])