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