mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 18:23:55 +00:00
325 lines
9.9 KiB
Python
325 lines
9.9 KiB
Python
import logging
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from pathlib import Path
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from typing import Dict, List, Optional
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import pandas as pd
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from freqtrade.configuration import Arguments
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from freqtrade.data import history
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from freqtrade.data.btanalysis import (combine_tickers_with_mean,
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create_cum_profit, load_trades)
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from freqtrade.exchange import Exchange
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from freqtrade.resolvers import ExchangeResolver, StrategyResolver
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logger = logging.getLogger(__name__)
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try:
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from plotly.subplots import make_subplots
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from plotly.offline import plot
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import plotly.graph_objects as go
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except ImportError:
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logger.exception("Module plotly not found \n Please install using `pip install plotly`")
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exit(1)
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def init_plotscript(config):
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"""
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Initialize objects needed for plotting
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:return: Dict with tickers, trades, pairs and strategy
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"""
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exchange: Optional[Exchange] = None
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# Exchange is only needed when downloading data!
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if config.get("live", False) or config.get("refresh_pairs", False):
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exchange = ExchangeResolver(config.get('exchange', {}).get('name'),
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config).exchange
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strategy = StrategyResolver(config).strategy
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if "pairs" in config:
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pairs = config["pairs"].split(',')
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else:
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pairs = config["exchange"]["pair_whitelist"]
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# Set timerange to use
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timerange = Arguments.parse_timerange(config.get("timerange"))
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tickers = history.load_data(
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datadir=Path(str(config.get("datadir"))),
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pairs=pairs,
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ticker_interval=config['ticker_interval'],
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refresh_pairs=config.get('refresh_pairs', False),
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timerange=timerange,
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exchange=exchange,
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live=config.get("live", False),
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)
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trades = load_trades(config)
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return {"tickers": tickers,
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"trades": trades,
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"pairs": pairs,
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"strategy": strategy,
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}
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def add_indicators(fig, row, indicators: List[str], data: pd.DataFrame) -> make_subplots:
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"""
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Generator all the indicator selected by the user for a specific row
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:param fig: Plot figure to append to
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:param row: row number for this plot
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:param indicators: List of indicators present in the dataframe
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:param data: candlestick DataFrame
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"""
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for indicator in indicators:
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if indicator in data:
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# TODO: Figure out why scattergl causes problems
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scattergl = go.Scatter(
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x=data['date'],
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y=data[indicator].values,
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mode='lines',
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name=indicator
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)
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fig.add_trace(scattergl, row, 1)
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else:
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logger.info(
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'Indicator "%s" ignored. Reason: This indicator is not found '
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'in your strategy.',
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indicator
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)
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return fig
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def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> make_subplots:
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"""
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Add profit-plot
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:param fig: Plot figure to append to
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:param row: row number for this plot
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:param data: candlestick DataFrame
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:param column: Column to use for plot
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:param name: Name to use
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:return: fig with added profit plot
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"""
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profit = go.Scattergl(
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x=data.index,
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y=data[column],
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name=name,
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)
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fig.add_trace(profit, row, 1)
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return fig
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def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
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"""
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Add trades to "fig"
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"""
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# Trades can be empty
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if trades is not None and len(trades) > 0:
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trade_buys = go.Scatter(
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x=trades["open_time"],
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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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symbol='square-open',
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size=11,
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line=dict(width=2),
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color='green'
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)
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)
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# Create description for sell summarizing the trade
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desc = trades.apply(lambda row: f"{round(row['profitperc'], 3)}%, {row['sell_reason']}, "
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f"{row['duration']}min",
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axis=1)
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trade_sells = go.Scatter(
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x=trades["close_time"],
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y=trades["close_rate"],
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text=desc,
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mode='markers',
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name='trade_sell',
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marker=dict(
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symbol='square-open',
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size=11,
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line=dict(width=2),
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color='red'
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)
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)
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fig.add_trace(trade_buys, 1, 1)
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fig.add_trace(trade_sells, 1, 1)
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else:
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logger.warning("No trades found.")
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return fig
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def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None,
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indicators1: List[str] = [],
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indicators2: List[str] = [],) -> go.Figure:
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"""
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Generate the graph from the data generated by Backtesting or from DB
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Volume will always be ploted in row2, so Row 1 and 3 are to our disposal for custom indicators
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:param pair: Pair to Display on the graph
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:param data: OHLCV DataFrame containing indicators and buy/sell signals
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:param trades: All trades created
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:param indicators1: List containing Main plot indicators
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:param indicators2: List containing Sub plot indicators
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:return: None
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"""
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# Define the graph
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fig = make_subplots(
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rows=3,
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cols=1,
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shared_xaxes=True,
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row_width=[1, 1, 4],
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vertical_spacing=0.0001,
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)
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fig['layout'].update(title=pair)
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fig['layout']['yaxis1'].update(title='Price')
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fig['layout']['yaxis2'].update(title='Volume')
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fig['layout']['yaxis3'].update(title='Other')
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fig['layout']['xaxis']['rangeslider'].update(visible=False)
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# Common information
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candles = go.Candlestick(
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x=data.date,
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open=data.open,
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high=data.high,
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low=data.low,
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close=data.close,
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name='Price'
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)
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fig.add_trace(candles, 1, 1)
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if 'buy' in data.columns:
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df_buy = data[data['buy'] == 1]
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if len(df_buy) > 0:
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buys = go.Scatter(
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x=df_buy.date,
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y=df_buy.close,
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mode='markers',
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name='buy',
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marker=dict(
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symbol='triangle-up-dot',
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size=9,
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line=dict(width=1),
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color='green',
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)
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)
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fig.add_trace(buys, 1, 1)
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else:
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logger.warning("No buy-signals found.")
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if 'sell' in data.columns:
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df_sell = data[data['sell'] == 1]
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if len(df_sell) > 0:
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sells = go.Scatter(
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x=df_sell.date,
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y=df_sell.close,
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mode='markers',
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name='sell',
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marker=dict(
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symbol='triangle-down-dot',
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size=9,
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line=dict(width=1),
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color='red',
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)
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)
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fig.add_trace(sells, 1, 1)
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else:
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logger.warning("No sell-signals found.")
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if 'bb_lowerband' in data and 'bb_upperband' in data:
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bb_lower = go.Scattergl(
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x=data.date,
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y=data.bb_lowerband,
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name='BB lower',
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line={'color': 'rgba(255,255,255,0)'},
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)
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bb_upper = go.Scattergl(
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x=data.date,
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y=data.bb_upperband,
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name='BB upper',
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fill="tonexty",
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fillcolor="rgba(0,176,246,0.2)",
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line={'color': 'rgba(255,255,255,0)'},
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)
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fig.add_trace(bb_lower, 1, 1)
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fig.add_trace(bb_upper, 1, 1)
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# Add indicators to main plot
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fig = add_indicators(fig=fig, row=1, indicators=indicators1, data=data)
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fig = plot_trades(fig, trades)
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# Volume goes to row 2
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volume = go.Bar(
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x=data['date'],
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y=data['volume'],
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name='Volume'
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)
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fig.add_trace(volume, 2, 1)
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# Add indicators to seperate row
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fig = add_indicators(fig=fig, row=3, indicators=indicators2, data=data)
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return fig
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def generate_profit_graph(pairs: str, tickers: Dict[str, pd.DataFrame],
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trades: pd.DataFrame) -> go.Figure:
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# Combine close-values for all pairs, rename columns to "pair"
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df_comb = combine_tickers_with_mean(tickers, "close")
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# Add combined cumulative profit
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df_comb = create_cum_profit(df_comb, trades, 'cum_profit')
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# Plot the pairs average close prices, and total profit growth
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avgclose = go.Scattergl(
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x=df_comb.index,
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y=df_comb['mean'],
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name='Avg close price',
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)
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fig = make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 1])
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fig['layout'].update(title="Profit plot")
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fig.add_trace(avgclose, 1, 1)
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fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
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for pair in pairs:
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profit_col = f'cum_profit_{pair}'
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df_comb = create_cum_profit(df_comb, trades[trades['pair'] == pair], profit_col)
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fig = add_profit(fig, 3, df_comb, profit_col, f"Profit {pair}")
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return fig
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def generate_plot_filename(pair, ticker_interval) -> str:
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"""
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Generate filenames per pair/ticker_interval to be used for storing plots
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"""
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pair_name = pair.replace("/", "_")
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file_name = 'freqtrade-plot-' + pair_name + '-' + ticker_interval + '.html'
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logger.info('Generate plot file for %s', pair)
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return file_name
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def store_plot_file(fig, filename: str, auto_open: bool = False) -> None:
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"""
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Generate a plot html file from pre populated fig plotly object
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:param fig: Plotly Figure to plot
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:param pair: Pair to plot (used as filename and Plot title)
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:param ticker_interval: Used as part of the filename
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:return: None
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"""
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Path("user_data/plots").mkdir(parents=True, exist_ok=True)
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_filename = Path('user_data/plots').joinpath(filename)
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plot(fig, filename=str(_filename),
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auto_open=auto_open)
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logger.info(f"Stored plot as {_filename}")
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