stable/scripts/plot_dataframe.py

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#!/usr/bin/env python3
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import sys
import logging
from plotly import tools
from plotly.offline import plot
import plotly.graph_objs as go
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from freqtrade import exchange, analyze
from freqtrade.strategy.strategy import Strategy
import freqtrade.misc as misc
import freqtrade.optimize as optimize
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logger = logging.getLogger(__name__)
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def plot_parse_args(args):
parser = misc.common_args_parser('Graph dataframe')
misc.backtesting_options(parser)
misc.scripts_options(parser)
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return parser.parse_args(args)
def plot_analyzed_dataframe(args) -> None:
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"""
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)
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if (len(dataframe.index) > 750):
logger.warn('Ticker contained more than 750 candles, clipping.')
df = dataframe.tail(750)
candles = go.Candlestick(x=df.date,
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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='triangle-up-dot',
size=9,
line=dict(
width=1,
),
color='green',
)
)
df_sell = df[df['sell'] == 1]
sells = go.Scattergl(
x=df_sell.date,
y=df_sell.close,
mode='markers',
name='sell',
marker=dict(
symbol='triangle-down-dot',
size=9,
line=dict(
width=1,
),
color='red',
)
)
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",
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fillcolor="rgba(0,176,246,0.2)",
line={'color': "transparent"},
)
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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],
vertical_spacing=0.0001,
)
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')
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if __name__ == '__main__':
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args = plot_parse_args(sys.argv[1:])
plot_analyzed_dataframe(args)