freqtrade_origin/scripts/plot_dataframe.py

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#!/usr/bin/env python3
"""
Script to display when the bot will buy a specific pair
Mandatory Cli parameters:
-p / --pair: pair to examine
Option but recommended
-s / --strategy: strategy to use
Optional Cli parameters
-d / --datadir: path to pair backtest data
--timerange: specify what timerange of data to use.
-l / --live: Live, to download the latest ticker for the pair
-db / --db-url: Show trades stored in database
Indicators recommended
Row 1: sma, ema3, ema5, ema10, ema50
Row 3: macd, rsi, fisher_rsi, mfi, slowd, slowk, fastd, fastk
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Example of usage:
> python3 scripts/plot_dataframe.py --pair BTC/EUR -d user_data/data/ --indicators1 sma,ema3
--indicators2 fastk,fastd
"""
import json
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import logging
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import sys
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from argparse import Namespace
from pathlib import Path
from typing import Dict, List, Any
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import pandas as pd
import plotly.graph_objs as go
import pytz
from plotly import tools
from plotly.offline import plot
import freqtrade.optimize as optimize
from freqtrade import persistence
from freqtrade.analyze import Analyze
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from freqtrade.arguments import Arguments, TimeRange
from freqtrade.exchange import Exchange
from freqtrade.optimize.backtesting import setup_configuration
from freqtrade.persistence import Trade
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logger = logging.getLogger(__name__)
_CONF: Dict[str, Any] = {}
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timeZone = pytz.UTC
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def load_trades(args: Namespace, pair: str, timerange: TimeRange) -> pd.DataFrame:
trades: pd.DataFrame = pd.DataFrame()
if args.db_url:
persistence.init(_CONF)
columns = ["pair", "profit", "opents", "closets", "open_rate", "close_rate", "duration"]
for x in Trade.query.all():
print("date: {}".format(x.open_date))
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trades = pd.DataFrame([(t.pair, t.calc_profit(),
t.open_date.replace(tzinfo=timeZone),
t.close_date.replace(tzinfo=timeZone) if t.close_date else None,
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t.open_rate, t.close_rate,
t.close_date.timestamp() - t.open_date.timestamp() if t.close_date else None)
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for t in Trade.query.filter(Trade.pair.is_(pair)).all()],
columns=columns)
elif args.exportfilename:
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file = Path(args.exportfilename)
# must align with columns in backtest.py
columns = ["pair", "profit", "opents", "closets", "index", "duration",
"open_rate", "close_rate", "open_at_end"]
with file.open() as f:
data = json.load(f)
trades = pd.DataFrame(data, columns=columns)
trades = trades.loc[trades["pair"] == pair]
if timerange:
if timerange.starttype == 'date':
trades = trades.loc[trades["opents"] >= timerange.startts]
if timerange.stoptype == 'date':
trades = trades.loc[trades["opents"] <= timerange.stopts]
trades['opents'] = pd.to_datetime(trades['opents'],
unit='s',
utc=True,
infer_datetime_format=True)
trades['closets'] = pd.to_datetime(trades['closets'],
unit='s',
utc=True,
infer_datetime_format=True)
return trades
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def plot_analyzed_dataframe(args: Namespace) -> None:
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"""
Calls analyze() and plots the returned dataframe
:return: None
"""
global _CONF
# Load the configuration
_CONF.update(setup_configuration(args))
print(_CONF)
# Set the pair to audit
pair = args.pair
if pair is None:
logger.critical('Parameter --pair mandatory;. E.g --pair ETH/BTC')
exit()
if '/' not in pair:
logger.critical('--pair format must be XXX/YYY')
exit()
# Set timerange to use
timerange = Arguments.parse_timerange(args.timerange)
# Load the strategy
try:
analyze = Analyze(_CONF)
exchange = Exchange(_CONF)
except AttributeError:
logger.critical(
'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"',
args.strategy
)
exit()
# Set the ticker to use
tick_interval = analyze.get_ticker_interval()
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# Load pair tickers
tickers = {}
if args.live:
logger.info('Downloading pair.')
tickers[pair] = exchange.get_ticker_history(pair, tick_interval)
else:
tickers = optimize.load_data(
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datadir=_CONF.get("datadir"),
pairs=[pair],
ticker_interval=tick_interval,
refresh_pairs=_CONF.get('refresh_pairs', False),
timerange=timerange,
exchange=Exchange(_CONF)
)
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# No ticker found, or impossible to download
if tickers == {}:
exit()
# Get trades already made from the DB
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trades = load_trades(args, pair, timerange)
dataframes = analyze.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) > args.plot_limit:
logger.warning('Ticker contained more than %s candles as defined '
'with --plot-limit, clipping.', args.plot_limit)
dataframe = dataframe.tail(args.plot_limit)
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trades = trades.loc[trades['opents'] >= dataframe.iloc[0]['date']]
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fig = generate_graph(
pair=pair,
trades=trades,
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data=dataframe,
args=args
)
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plot(fig, filename=str(Path('user_data').joinpath('freqtrade-plot.html')))
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def generate_graph(pair, trades: pd.DataFrame, data: pd.DataFrame, args) -> tools.make_subplots:
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"""
Generate the graph from the data generated by Backtesting or from DB
:param pair: Pair to Display on the graph
:param trades: All trades created
:param data: Dataframe
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:param args: sys.argv that contrains the two params indicators1, and indicators2
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:return: None
"""
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# Define the graph
fig = tools.make_subplots(
rows=3,
cols=1,
shared_xaxes=True,
row_width=[1, 1, 4],
vertical_spacing=0.0001,
)
fig['layout'].update(title=pair)
fig['layout']['yaxis1'].update(title='Price')
fig['layout']['yaxis2'].update(title='Volume')
fig['layout']['yaxis3'].update(title='Other')
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# Common information
candles = go.Candlestick(
x=data.date,
open=data.open,
high=data.high,
low=data.low,
close=data.close,
name='Price'
)
df_buy = data[data['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 = data[data['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',
)
)
trade_buys = go.Scattergl(
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x=trades["opents"],
y=trades["open_rate"],
mode='markers',
name='trade_buy',
marker=dict(
symbol='square-open',
size=11,
line=dict(width=2),
color='green'
)
)
trade_sells = go.Scattergl(
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x=trades["closets"],
y=trades["close_rate"],
mode='markers',
name='trade_sell',
marker=dict(
symbol='square-open',
size=11,
line=dict(width=2),
color='red'
)
)
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# Row 1
fig.append_trace(candles, 1, 1)
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if 'bb_lowerband' in data and 'bb_upperband' in data:
bb_lower = go.Scatter(
x=data.date,
y=data.bb_lowerband,
name='BB lower',
line={'color': 'rgba(255,255,255,0)'},
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)
bb_upper = go.Scatter(
x=data.date,
y=data.bb_upperband,
name='BB upper',
fill="tonexty",
fillcolor="rgba(0,176,246,0.2)",
line={'color': 'rgba(255,255,255,0)'},
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)
fig.append_trace(bb_lower, 1, 1)
fig.append_trace(bb_upper, 1, 1)
fig = generate_row(fig=fig, row=1, raw_indicators=args.indicators1, data=data)
fig.append_trace(buys, 1, 1)
fig.append_trace(sells, 1, 1)
fig.append_trace(trade_buys, 1, 1)
fig.append_trace(trade_sells, 1, 1)
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# Row 2
volume = go.Bar(
x=data['date'],
y=data['volume'],
name='Volume'
)
fig.append_trace(volume, 2, 1)
# Row 3
fig = generate_row(fig=fig, row=3, raw_indicators=args.indicators2, data=data)
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return fig
def generate_row(fig, row, raw_indicators, data) -> tools.make_subplots:
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"""
Generator all the indicator selected by the user for a specific row
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"""
for indicator in raw_indicators.split(','):
if indicator in data:
scattergl = go.Scattergl(
x=data['date'],
y=data[indicator],
name=indicator
)
fig.append_trace(scattergl, row, 1)
else:
logger.info(
'Indicator "%s" ignored. Reason: This indicator is not found '
'in your strategy.',
indicator
)
return fig
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def plot_parse_args(args: List[str]) -> Namespace:
"""
Parse args passed to the script
:param args: Cli arguments
:return: args: Array with all arguments
"""
arguments = Arguments(args, 'Graph dataframe')
arguments.scripts_options()
arguments.parser.add_argument(
'--indicators1',
help='Set indicators from your strategy you want in the first row of the graph. Separate '
'them with a coma. E.g: ema3,ema5 (default: %(default)s)',
type=str,
default='sma,ema3,ema5',
dest='indicators1',
)
arguments.parser.add_argument(
'--indicators2',
help='Set indicators from your strategy you want in the third row of the graph. Separate '
'them with a coma. E.g: fastd,fastk (default: %(default)s)',
type=str,
default='macd',
dest='indicators2',
)
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arguments.parser.add_argument(
'--plot-limit',
help='Specify tick limit for plotting - too high values cause huge files - '
'Default: %(default)s',
dest='plot_limit',
default=750,
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type=int,
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)
arguments.common_args_parser()
arguments.optimizer_shared_options(arguments.parser)
arguments.backtesting_options(arguments.parser)
return arguments.parse_args()
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def main(sysargv: List[str]) -> None:
"""
This function will initiate the bot and start the trading loop.
:return: None
"""
logger.info('Starting Plot Dataframe')
plot_analyzed_dataframe(
plot_parse_args(sysargv)
)
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if __name__ == '__main__':
main(sys.argv[1:])