mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 18:23:55 +00:00
224 lines
6.6 KiB
Python
224 lines
6.6 KiB
Python
import logging
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from typing import List
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import pandas as pd
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from pathlib import Path
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logger = logging.getLogger(__name__)
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try:
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from plotly import tools
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from plotly.offline import plot
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import plotly.graph_objs 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 generate_row(fig, row, indicators: List[str], data: pd.DataFrame) -> tools.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.append_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 plot_trades(fig, trades: pd.DataFrame):
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"""
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Plot 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.append_trace(trade_buys, 1, 1)
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fig.append_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_graph(
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pair: str,
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data: pd.DataFrame,
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trades: pd.DataFrame = None,
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indicators1: List[str] = [],
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indicators2: List[str] = [],
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) -> 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 = tools.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.append_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.append_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.append_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.append_trace(bb_lower, 1, 1)
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fig.append_trace(bb_upper, 1, 1)
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# Add indicators to main plot
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fig = generate_row(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.append_trace(volume, 2, 1)
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# Add indicators to seperate row
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fig = generate_row(fig=fig, row=3, indicators=indicators2, data=data)
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return fig
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def generate_plot_file(fig, pair, ticker_interval) -> 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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logger.info('Generate plot file for %s', pair)
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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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Path("user_data/plots").mkdir(parents=True, exist_ok=True)
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plot(fig, filename=str(Path('user_data/plots').joinpath(file_name)),
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auto_open=False)
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