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Merge pull request #954 from freqtrade/feat/allow_backtest_plot
allow backtest ploting
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commit
6dd5f85fb6
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@ -70,6 +70,34 @@ Where `-s TestStrategy` refers to the class name within the strategy file `test_
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python3 ./freqtrade/main.py backtesting --export trades
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```
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The exported trades can be read using the following code for manual analysis, or can be used by the plotting script `plot_dataframe.py` in the scripts folder.
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``` python
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import json
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from pathlib import Path
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import pandas as pd
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filename=Path('user_data/backtest_data/backtest-result.json')
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with filename.open() as file:
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data = json.load(file)
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columns = ["pair", "profit", "opents", "closets", "index", "duration",
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"open_rate", "close_rate", "open_at_end"]
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df = pd.DataFrame(data, columns=columns)
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df['opents'] = pd.to_datetime(df['opents'],
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unit='s',
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utc=True,
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infer_datetime_format=True
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)
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df['closets'] = pd.to_datetime(df['closets'],
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unit='s',
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utc=True,
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infer_datetime_format=True
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)
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```
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#### Exporting trades to file specifying a custom filename
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```bash
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@ -38,6 +38,8 @@ class BacktestResult(NamedTuple):
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close_index: int
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trade_duration: float
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open_at_end: bool
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open_rate: float
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close_rate: float
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class Backtesting(object):
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@ -116,11 +118,10 @@ class Backtesting(object):
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def _store_backtest_result(self, recordfilename: Optional[str], results: DataFrame) -> None:
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records = [(trade_entry.pair, trade_entry.profit_percent,
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trade_entry.open_time.timestamp(),
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trade_entry.close_time.timestamp(),
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trade_entry.open_index - 1, trade_entry.trade_duration)
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for index, trade_entry in results.iterrows()]
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records = [(t.pair, t.profit_percent, t.open_time.timestamp(),
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t.close_time.timestamp(), t.open_index - 1, t.trade_duration,
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t.open_rate, t.close_rate, t.open_at_end)
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for index, t in results.iterrows()]
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if records:
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logger.info('Dumping backtest results to %s', recordfilename)
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@ -159,7 +160,9 @@ class Backtesting(object):
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trade_duration=(sell_row.date - buy_row.date).seconds // 60,
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open_index=buy_row.Index,
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close_index=sell_row.Index,
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open_at_end=False
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open_at_end=False,
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open_rate=buy_row.close,
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close_rate=sell_row.close
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)
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if partial_ticker:
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# no sell condition found - trade stil open at end of backtest period
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@ -172,7 +175,9 @@ class Backtesting(object):
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trade_duration=(sell_row.date - buy_row.date).seconds // 60,
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open_index=buy_row.Index,
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close_index=sell_row.Index,
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open_at_end=True
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open_at_end=True,
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open_rate=buy_row.close,
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close_rate=sell_row.close
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)
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logger.debug('Force_selling still open trade %s with %s perc - %s', btr.pair,
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btr.profit_percent, btr.profit_abs)
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@ -627,9 +627,13 @@ def test_backtest_record(default_conf, fee, mocker):
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Arrow(2017, 11, 14, 22, 10, 00).datetime,
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Arrow(2017, 11, 14, 22, 43, 00).datetime,
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Arrow(2017, 11, 14, 22, 58, 00).datetime],
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"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
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"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
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"open_index": [1, 119, 153, 185],
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"close_index": [118, 151, 184, 199],
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"trade_duration": [123, 34, 31, 14]})
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"trade_duration": [123, 34, 31, 14],
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"open_at_end": [False, False, False, True]
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})
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backtesting._store_backtest_result("backtest-result.json", results)
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assert len(results) == 4
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# Assert file_dump_json was only called once
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@ -640,12 +644,16 @@ def test_backtest_record(default_conf, fee, mocker):
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# ('UNITTEST/BTC', 0.00331158, '1510684320', '1510691700', 0, 117)
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# Below follows just a typecheck of the schema/type of trade-records
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oix = None
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for (pair, profit, date_buy, date_sell, buy_index, dur) in records:
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for (pair, profit, date_buy, date_sell, buy_index, dur,
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openr, closer, open_at_end) in records:
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assert pair == 'UNITTEST/BTC'
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isinstance(profit, float)
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assert isinstance(profit, float)
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# FIX: buy/sell should be converted to ints
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isinstance(date_buy, str)
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isinstance(date_sell, str)
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assert isinstance(date_buy, float)
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assert isinstance(date_sell, float)
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assert isinstance(openr, float)
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assert isinstance(closer, float)
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assert isinstance(open_at_end, bool)
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isinstance(buy_index, pd._libs.tslib.Timestamp)
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if oix:
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assert buy_index > oix
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@ -25,11 +25,13 @@ Example of usage:
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--indicators2 fastk,fastd
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"""
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import logging
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import os
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import sys
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import json
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from pathlib import Path
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from argparse import Namespace
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from typing import Dict, List, Any
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import pandas as pd
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import plotly.graph_objs as go
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from plotly import tools
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from plotly.offline import plot
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@ -37,7 +39,7 @@ from plotly.offline import plot
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import freqtrade.optimize as optimize
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from freqtrade import persistence
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from freqtrade.analyze import Analyze
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from freqtrade.arguments import Arguments
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from freqtrade.arguments import Arguments, TimeRange
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from freqtrade.exchange import Exchange
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from freqtrade.optimize.backtesting import setup_configuration
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from freqtrade.persistence import Trade
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@ -46,6 +48,45 @@ logger = logging.getLogger(__name__)
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_CONF: Dict[str, Any] = {}
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def load_trades(args: Namespace, pair: str, timerange: TimeRange) -> pd.DataFrame:
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trades: pd.DataFrame = pd.DataFrame()
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if args.db_url:
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persistence.init(_CONF)
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columns = ["pair", "profit", "opents", "closets", "open_rate", "close_rate", "duration"]
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trades = pd.DataFrame([(t.pair, t.calc_profit(),
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t.open_date, t.close_date,
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t.open_rate, t.close_rate,
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t.close_date.timestamp() - t.open_date.timestamp())
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for t in Trade.query.filter(Trade.pair.is_(pair)).all()],
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columns=columns)
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if args.exportfilename:
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file = Path(args.exportfilename)
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# must align with columns in backtest.py
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columns = ["pair", "profit", "opents", "closets", "index", "duration",
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"open_rate", "close_rate", "open_at_end"]
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with file.open() as f:
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data = json.load(f)
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trades = pd.DataFrame(data, columns=columns)
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trades = trades.loc[trades["pair"] == pair]
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if timerange:
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if timerange.starttype == 'date':
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trades = trades.loc[trades["opents"] >= timerange.startts]
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if timerange.stoptype == 'date':
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trades = trades.loc[trades["opents"] <= timerange.stopts]
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trades['opents'] = pd.to_datetime(trades['opents'],
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unit='s',
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utc=True,
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infer_datetime_format=True)
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trades['closets'] = pd.to_datetime(trades['closets'],
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unit='s',
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utc=True,
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infer_datetime_format=True)
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return trades
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def plot_analyzed_dataframe(args: Namespace) -> None:
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"""
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Calls analyze() and plots the returned dataframe
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@ -102,31 +143,32 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
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if tickers == {}:
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exit()
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if args.db_url and args.exportfilename:
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logger.critical("Can only specify --db-url or --export-filename")
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# Get trades already made from the DB
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trades: List[Trade] = []
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if args.db_url:
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persistence.init(_CONF)
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trades = Trade.query.filter(Trade.pair.is_(pair)).all()
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trades = load_trades(args, pair, timerange)
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dataframes = analyze.tickerdata_to_dataframe(tickers)
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dataframe = dataframes[pair]
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dataframe = analyze.populate_buy_trend(dataframe)
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dataframe = analyze.populate_sell_trend(dataframe)
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if len(dataframe.index) > 750:
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logger.warning('Ticker contained more than 750 candles, clipping.')
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if len(dataframe.index) > args.plot_limit:
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logger.warning('Ticker contained more than %s candles as defined '
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'with --plot-limit, clipping.', args.plot_limit)
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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(
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pair=pair,
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trades=trades,
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data=dataframe.tail(750),
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data=dataframe,
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args=args
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)
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plot(fig, filename=os.path.join('user_data', 'freqtrade-plot.html'))
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plot(fig, filename=str(Path('user_data').joinpath('freqtrade-plot.html')))
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def generate_graph(pair, trades, data, args) -> tools.make_subplots:
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def generate_graph(pair, trades: pd.DataFrame, data: pd.DataFrame, args) -> tools.make_subplots:
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"""
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Generate the graph from the data generated by Backtesting or from DB
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:param pair: Pair to Display on the graph
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@ -187,8 +229,8 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
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)
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trade_buys = go.Scattergl(
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x=[t.open_date.isoformat() for t in trades],
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y=[t.open_rate for t in trades],
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x=trades["opents"],
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y=trades["open_rate"],
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mode='markers',
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name='trade_buy',
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marker=dict(
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@ -199,8 +241,8 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
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)
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)
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trade_sells = go.Scattergl(
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x=[t.close_date.isoformat() for t in trades],
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y=[t.close_rate for t in trades],
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x=trades["closets"],
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y=trades["close_rate"],
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mode='markers',
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name='trade_sell',
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marker=dict(
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@ -299,11 +341,17 @@ def plot_parse_args(args: List[str]) -> Namespace:
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default='macd',
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dest='indicators2',
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)
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arguments.parser.add_argument(
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'--plot-limit',
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help='Specify tick limit for plotting - too high values cause huge files - '
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'Default: %(default)s',
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dest='plot_limit',
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default=750,
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type=int,
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)
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arguments.common_args_parser()
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arguments.optimizer_shared_options(arguments.parser)
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arguments.backtesting_options(arguments.parser)
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return arguments.parse_args()
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