stable/scripts/plot_dataframe.py
2018-01-28 11:12:14 +02:00

148 lines
4.0 KiB
Python
Executable File

#!/usr/bin/env python3
import sys
import logging
import argparse
import os
from pandas import DataFrame
import talib.abstract as ta
import plotly
from plotly import tools
from plotly.offline import plot
import plotly.graph_objs as go
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade import exchange, analyze
from freqtrade.misc import common_args_parser
from freqtrade.strategy.strategy import Strategy
import freqtrade.misc as misc
import freqtrade.optimize as optimize
import freqtrade.analyze as analyze
logger = logging.getLogger(__name__)
def plot_parse_args(args):
parser = misc.common_args_parser('Graph dataframe')
misc.backtesting_options(parser)
misc.scripts_options(parser)
return parser.parse_args(args)
def plot_analyzed_dataframe(args) -> None:
"""
Calls analyze() and plots the returned dataframe
:param pair: pair as str
:return: None
"""
pair = args.pair.replace('-', '_')
timerange = misc.parse_timerange(args.timerange)
# Init strategy
strategy = Strategy()
strategy.init({'strategy': args.strategy})
tick_interval = strategy.ticker_interval
tickers = {}
if args.live:
logger.info('Downloading pair.')
# Init Bittrex to use public API
exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
tickers[pair] = exchange.get_ticker_history(pair, tick_interval)
else:
tickers = optimize.load_data(args.datadir, pairs=[pair],
ticker_interval=tick_interval,
refresh_pairs=False,
timerange=timerange)
dataframes = optimize.tickerdata_to_dataframe(tickers)
dataframe = dataframes[pair]
dataframe = analyze.populate_buy_trend(dataframe)
dataframe = analyze.populate_sell_trend(dataframe)
dates = misc.datesarray_to_datetimearray(dataframe['date'])
if (len(dataframe.index) > 750):
logger.warn('Ticker contained more than 750 candles, clipping.')
df = dataframe.tail(750)
candles = go.Candlestick(x=df.date,
open=df.open,
high=df.high,
low=df.low,
close=df.close,
name='Price')
df_buy = df[df['buy'] == 1]
buys = go.Scattergl(
x=df_buy.date,
y=df_buy.close,
mode='markers',
name='buy',
marker=dict(symbol='x-dot')
)
df_sell = df[df['sell'] == 1]
sells = go.Scattergl(
x=df_sell.date,
y=df_sell.close,
mode='markers',
name='sell',
marker=dict(symbol='diamond')
)
bb_lower = go.Scatter(
x=df.date,
y=df.bb_lowerband,
name='BB lower',
line={'color': "transparent"},
)
bb_upper = go.Scatter(
x=df.date,
y=df.bb_upperband,
name='BB upper',
fill="tonexty",
fillcolor="rgba(0,176,246,0.2)",
line={'color': "transparent"},
)
macd = go.Scattergl(
x=df['date'],
y=df['macd'],
name='MACD'
)
macdsignal = go.Scattergl(
x=df['date'],
y=df['macdsignal'],
name='MACD signal'
)
volume = go.Bar(
x=df['date'],
y=df['volume'],
name='Volume'
)
fig = tools.make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 4])
fig.append_trace(candles, 1, 1)
fig.append_trace(bb_lower, 1, 1)
fig.append_trace(bb_upper, 1, 1)
fig.append_trace(buys, 1, 1)
fig.append_trace(sells, 1, 1)
fig.append_trace(volume, 2, 1)
fig.append_trace(macd, 3, 1)
fig.append_trace(macdsignal, 3, 1)
fig['layout'].update(title=args.pair)
fig['layout']['yaxis1'].update(title='Price')
fig['layout']['yaxis2'].update(title='Volume')
fig['layout']['yaxis3'].update(title='MACD')
plot(fig, filename='freqtrade-plot.html')
if __name__ == '__main__':
args = plot_parse_args(sys.argv[1:])
plot_analyzed_dataframe(args)