526 lines
18 KiB
Python
526 lines
18 KiB
Python
import logging
|
|
from pathlib import Path
|
|
from typing import Any, Dict, List
|
|
|
|
import pandas as pd
|
|
|
|
from freqtrade.configuration import TimeRange
|
|
from freqtrade.data.btanalysis import (calculate_max_drawdown,
|
|
combine_dataframes_with_mean,
|
|
create_cum_profit,
|
|
extract_trades_of_period,
|
|
load_trades)
|
|
from freqtrade.data.converter import trim_dataframe
|
|
from freqtrade.data.history import load_data
|
|
from freqtrade.exceptions import OperationalException
|
|
from freqtrade.exchange import timeframe_to_prev_date
|
|
from freqtrade.misc import pair_to_filename
|
|
from freqtrade.resolvers import StrategyResolver
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
try:
|
|
from plotly.subplots import make_subplots
|
|
from plotly.offline import plot
|
|
import plotly.graph_objects as go
|
|
except ImportError:
|
|
logger.exception("Module plotly not found \n Please install using `pip3 install plotly`")
|
|
exit(1)
|
|
|
|
|
|
def init_plotscript(config):
|
|
"""
|
|
Initialize objects needed for plotting
|
|
:return: Dict with candle (OHLCV) data, trades and pairs
|
|
"""
|
|
|
|
if "pairs" in config:
|
|
pairs = config["pairs"]
|
|
else:
|
|
pairs = config["exchange"]["pair_whitelist"]
|
|
|
|
# Set timerange to use
|
|
timerange = TimeRange.parse_timerange(config.get("timerange"))
|
|
|
|
data = load_data(
|
|
datadir=config.get("datadir"),
|
|
pairs=pairs,
|
|
timeframe=config.get('timeframe', '5m'),
|
|
timerange=timerange,
|
|
data_format=config.get('dataformat_ohlcv', 'json'),
|
|
)
|
|
|
|
no_trades = False
|
|
filename = config.get('exportfilename')
|
|
if config.get('no_trades', False):
|
|
no_trades = True
|
|
elif config['trade_source'] == 'file':
|
|
if not filename.is_dir() and not filename.is_file():
|
|
logger.warning("Backtest file is missing skipping trades.")
|
|
no_trades = True
|
|
|
|
trades = load_trades(
|
|
config['trade_source'],
|
|
db_url=config.get('db_url'),
|
|
exportfilename=filename,
|
|
no_trades=no_trades,
|
|
strategy=config.get("strategy"),
|
|
)
|
|
trades = trim_dataframe(trades, timerange, 'open_date')
|
|
|
|
return {"ohlcv": data,
|
|
"trades": trades,
|
|
"pairs": pairs,
|
|
}
|
|
|
|
|
|
def add_indicators(fig, row, indicators: Dict[str, Dict], data: pd.DataFrame) -> make_subplots:
|
|
"""
|
|
Generate all the indicators selected by the user for a specific row, based on the configuration
|
|
:param fig: Plot figure to append to
|
|
:param row: row number for this plot
|
|
:param indicators: Dict of Indicators with configuration options.
|
|
Dict key must correspond to dataframe column.
|
|
:param data: candlestick DataFrame
|
|
"""
|
|
for indicator, conf in indicators.items():
|
|
logger.debug(f"indicator {indicator} with config {conf}")
|
|
if indicator in data:
|
|
kwargs = {'x': data['date'],
|
|
'y': data[indicator].values,
|
|
'mode': 'lines',
|
|
'name': indicator
|
|
}
|
|
if 'color' in conf:
|
|
kwargs.update({'line': {'color': conf['color']}})
|
|
scatter = go.Scatter(
|
|
**kwargs
|
|
)
|
|
fig.add_trace(scatter, 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) -> 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.Scatter(
|
|
x=data.index,
|
|
y=data[column],
|
|
name=name,
|
|
)
|
|
fig.add_trace(profit, row, 1)
|
|
|
|
return fig
|
|
|
|
|
|
def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
|
|
timeframe: str) -> make_subplots:
|
|
"""
|
|
Add scatter points indicating max drawdown
|
|
"""
|
|
try:
|
|
max_drawdown, highdate, lowdate = calculate_max_drawdown(trades)
|
|
|
|
drawdown = go.Scatter(
|
|
x=[highdate, lowdate],
|
|
y=[
|
|
df_comb.loc[timeframe_to_prev_date(timeframe, highdate), 'cum_profit'],
|
|
df_comb.loc[timeframe_to_prev_date(timeframe, lowdate), 'cum_profit'],
|
|
],
|
|
mode='markers',
|
|
name=f"Max drawdown {max_drawdown * 100:.2f}%",
|
|
text=f"Max drawdown {max_drawdown * 100:.2f}%",
|
|
marker=dict(
|
|
symbol='square-open',
|
|
size=9,
|
|
line=dict(width=2),
|
|
color='green'
|
|
|
|
)
|
|
)
|
|
fig.add_trace(drawdown, row, 1)
|
|
except ValueError:
|
|
logger.warning("No trades found - not plotting max drawdown.")
|
|
return fig
|
|
|
|
|
|
def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
|
|
"""
|
|
Add trades to "fig"
|
|
"""
|
|
# Trades can be empty
|
|
if trades is not None and len(trades) > 0:
|
|
# Create description for sell summarizing the trade
|
|
trades['desc'] = trades.apply(lambda row: f"{round(row['profit_percent'] * 100, 1)}%, "
|
|
f"{row['sell_reason']}, "
|
|
f"{row['trade_duration']} min",
|
|
axis=1)
|
|
trade_buys = go.Scatter(
|
|
x=trades["open_date"],
|
|
y=trades["open_rate"],
|
|
mode='markers',
|
|
name='Trade buy',
|
|
text=trades["desc"],
|
|
marker=dict(
|
|
symbol='circle-open',
|
|
size=11,
|
|
line=dict(width=2),
|
|
color='cyan'
|
|
|
|
)
|
|
)
|
|
|
|
trade_sells = go.Scatter(
|
|
x=trades.loc[trades['profit_percent'] > 0, "close_date"],
|
|
y=trades.loc[trades['profit_percent'] > 0, "close_rate"],
|
|
text=trades.loc[trades['profit_percent'] > 0, "desc"],
|
|
mode='markers',
|
|
name='Sell - Profit',
|
|
marker=dict(
|
|
symbol='square-open',
|
|
size=11,
|
|
line=dict(width=2),
|
|
color='green'
|
|
)
|
|
)
|
|
trade_sells_loss = go.Scatter(
|
|
x=trades.loc[trades['profit_percent'] <= 0, "close_date"],
|
|
y=trades.loc[trades['profit_percent'] <= 0, "close_rate"],
|
|
text=trades.loc[trades['profit_percent'] <= 0, "desc"],
|
|
mode='markers',
|
|
name='Sell - Loss',
|
|
marker=dict(
|
|
symbol='square-open',
|
|
size=11,
|
|
line=dict(width=2),
|
|
color='red'
|
|
)
|
|
)
|
|
fig.add_trace(trade_buys, 1, 1)
|
|
fig.add_trace(trade_sells, 1, 1)
|
|
fig.add_trace(trade_sells_loss, 1, 1)
|
|
else:
|
|
logger.warning("No trades found.")
|
|
return fig
|
|
|
|
|
|
def create_plotconfig(indicators1: List[str], indicators2: List[str],
|
|
plot_config: Dict[str, Dict]) -> Dict[str, Dict]:
|
|
"""
|
|
Combines indicators 1 and indicators 2 into plot_config if necessary
|
|
:param indicators1: List containing Main plot indicators
|
|
:param indicators2: List containing Sub plot indicators
|
|
:param plot_config: Dict of Dicts containing advanced plot configuration
|
|
:return: plot_config - eventually with indicators 1 and 2
|
|
"""
|
|
|
|
if plot_config:
|
|
if indicators1:
|
|
plot_config['main_plot'] = {ind: {} for ind in indicators1}
|
|
if indicators2:
|
|
plot_config['subplots'] = {'Other': {ind: {} for ind in indicators2}}
|
|
|
|
if not plot_config:
|
|
# If no indicators and no plot-config given, use defaults.
|
|
if not indicators1:
|
|
indicators1 = ['sma', 'ema3', 'ema5']
|
|
if not indicators2:
|
|
indicators2 = ['macd', 'macdsignal']
|
|
|
|
# Create subplot configuration if plot_config is not available.
|
|
plot_config = {
|
|
'main_plot': {ind: {} for ind in indicators1},
|
|
'subplots': {'Other': {ind: {} for ind in indicators2}},
|
|
}
|
|
if 'main_plot' not in plot_config:
|
|
plot_config['main_plot'] = {}
|
|
|
|
if 'subplots' not in plot_config:
|
|
plot_config['subplots'] = {}
|
|
return plot_config
|
|
|
|
|
|
def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None, *,
|
|
indicators1: List[str] = [],
|
|
indicators2: List[str] = [],
|
|
plot_config: Dict[str, Dict] = {},
|
|
) -> 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
|
|
:param plot_config: Dict of Dicts containing advanced plot configuration
|
|
:return: Plotly figure
|
|
"""
|
|
plot_config = create_plotconfig(indicators1, indicators2, plot_config)
|
|
|
|
rows = 2 + len(plot_config['subplots'])
|
|
row_widths = [1 for _ in plot_config['subplots']]
|
|
# Define the graph
|
|
fig = make_subplots(
|
|
rows=rows,
|
|
cols=1,
|
|
shared_xaxes=True,
|
|
row_width=row_widths + [1, 4],
|
|
vertical_spacing=0.0001,
|
|
)
|
|
fig['layout'].update(title=pair)
|
|
fig['layout']['yaxis1'].update(title='Price')
|
|
fig['layout']['yaxis2'].update(title='Volume')
|
|
for i, name in enumerate(plot_config['subplots']):
|
|
fig['layout'][f'yaxis{3 + i}'].update(title=name)
|
|
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.add_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.add_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.add_trace(sells, 1, 1)
|
|
else:
|
|
logger.warning("No sell-signals found.")
|
|
|
|
# TODO: Figure out why scattergl causes problems plotly/plotly.js#2284
|
|
if 'bb_lowerband' in data and 'bb_upperband' in data:
|
|
bb_lower = go.Scatter(
|
|
x=data.date,
|
|
y=data.bb_lowerband,
|
|
showlegend=False,
|
|
line={'color': 'rgba(255,255,255,0)'},
|
|
)
|
|
bb_upper = go.Scatter(
|
|
x=data.date,
|
|
y=data.bb_upperband,
|
|
name='Bollinger Band',
|
|
fill="tonexty",
|
|
fillcolor="rgba(0,176,246,0.2)",
|
|
line={'color': 'rgba(255,255,255,0)'},
|
|
)
|
|
fig.add_trace(bb_lower, 1, 1)
|
|
fig.add_trace(bb_upper, 1, 1)
|
|
if ('bb_upperband' in plot_config['main_plot']
|
|
and 'bb_lowerband' in plot_config['main_plot']):
|
|
del plot_config['main_plot']['bb_upperband']
|
|
del plot_config['main_plot']['bb_lowerband']
|
|
|
|
# Add indicators to main plot
|
|
fig = add_indicators(fig=fig, row=1, indicators=plot_config['main_plot'], data=data)
|
|
|
|
fig = plot_trades(fig, trades)
|
|
|
|
# Volume goes to row 2
|
|
volume = go.Bar(
|
|
x=data['date'],
|
|
y=data['volume'],
|
|
name='Volume',
|
|
marker_color='DarkSlateGrey',
|
|
marker_line_color='DarkSlateGrey'
|
|
)
|
|
fig.add_trace(volume, 2, 1)
|
|
|
|
# Add indicators to separate row
|
|
for i, name in enumerate(plot_config['subplots']):
|
|
fig = add_indicators(fig=fig, row=3 + i,
|
|
indicators=plot_config['subplots'][name],
|
|
data=data)
|
|
|
|
return fig
|
|
|
|
|
|
def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
|
|
trades: pd.DataFrame, timeframe: str) -> go.Figure:
|
|
# Combine close-values for all pairs, rename columns to "pair"
|
|
df_comb = combine_dataframes_with_mean(data, "close")
|
|
|
|
# Trim trades to available OHLCV data
|
|
trades = extract_trades_of_period(df_comb, trades, date_index=True)
|
|
|
|
# Add combined cumulative profit
|
|
df_comb = create_cum_profit(df_comb, trades, 'cum_profit', timeframe)
|
|
|
|
# Plot the pairs average close prices, and total profit growth
|
|
avgclose = go.Scatter(
|
|
x=df_comb.index,
|
|
y=df_comb['mean'],
|
|
name='Avg close price',
|
|
)
|
|
|
|
fig = make_subplots(rows=3, cols=1, shared_xaxes=True,
|
|
row_width=[1, 1, 1],
|
|
vertical_spacing=0.05,
|
|
subplot_titles=["AVG Close Price", "Combined Profit", "Profit per pair"])
|
|
fig['layout'].update(title="Freqtrade Profit plot")
|
|
fig['layout']['yaxis1'].update(title='Price')
|
|
fig['layout']['yaxis2'].update(title='Profit')
|
|
fig['layout']['yaxis3'].update(title='Profit')
|
|
fig['layout']['xaxis']['rangeslider'].update(visible=False)
|
|
|
|
fig.add_trace(avgclose, 1, 1)
|
|
fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
|
|
fig = add_max_drawdown(fig, 2, trades, df_comb, timeframe)
|
|
|
|
for pair in pairs:
|
|
profit_col = f'cum_profit_{pair}'
|
|
try:
|
|
df_comb = create_cum_profit(df_comb, trades[trades['pair'] == pair], profit_col,
|
|
timeframe)
|
|
fig = add_profit(fig, 3, df_comb, profit_col, f"Profit {pair}")
|
|
except ValueError:
|
|
pass
|
|
|
|
return fig
|
|
|
|
|
|
def generate_plot_filename(pair: str, timeframe: str) -> str:
|
|
"""
|
|
Generate filenames per pair/timeframe to be used for storing plots
|
|
"""
|
|
pair_s = pair_to_filename(pair)
|
|
file_name = 'freqtrade-plot-' + pair_s + '-' + timeframe + '.html'
|
|
|
|
logger.info('Generate plot file for %s', pair)
|
|
|
|
return file_name
|
|
|
|
|
|
def store_plot_file(fig, filename: str, directory: Path, auto_open: bool = False) -> None:
|
|
"""
|
|
Generate a plot html file from pre populated fig plotly object
|
|
:param fig: Plotly Figure to plot
|
|
:param filename: Name to store the file as
|
|
:param directory: Directory to store the file in
|
|
:param auto_open: Automatically open files saved
|
|
:return: None
|
|
"""
|
|
directory.mkdir(parents=True, exist_ok=True)
|
|
|
|
_filename = directory.joinpath(filename)
|
|
plot(fig, filename=str(_filename),
|
|
auto_open=auto_open)
|
|
logger.info(f"Stored plot as {_filename}")
|
|
|
|
|
|
def load_and_plot_trades(config: Dict[str, Any]):
|
|
"""
|
|
From configuration provided
|
|
- Initializes plot-script
|
|
- Get candle (OHLCV) data
|
|
- Generate Dafaframes populated with indicators and signals based on configured strategy
|
|
- Load trades excecuted during the selected period
|
|
- Generate Plotly plot objects
|
|
- Generate plot files
|
|
:return: None
|
|
"""
|
|
strategy = StrategyResolver.load_strategy(config)
|
|
|
|
plot_elements = init_plotscript(config)
|
|
trades = plot_elements['trades']
|
|
pair_counter = 0
|
|
for pair, data in plot_elements["ohlcv"].items():
|
|
pair_counter += 1
|
|
logger.info("analyse pair %s", pair)
|
|
|
|
df_analyzed = strategy.analyze_ticker(data, {'pair': pair})
|
|
trades_pair = trades.loc[trades['pair'] == pair]
|
|
trades_pair = extract_trades_of_period(df_analyzed, trades_pair)
|
|
|
|
fig = generate_candlestick_graph(
|
|
pair=pair,
|
|
data=df_analyzed,
|
|
trades=trades_pair,
|
|
indicators1=config.get("indicators1", []),
|
|
indicators2=config.get("indicators2", []),
|
|
plot_config=strategy.plot_config if hasattr(strategy, 'plot_config') else {}
|
|
)
|
|
|
|
store_plot_file(fig, filename=generate_plot_filename(pair, config['timeframe']),
|
|
directory=config['user_data_dir'] / "plot")
|
|
|
|
logger.info('End of plotting process. %s plots generated', pair_counter)
|
|
|
|
|
|
def plot_profit(config: Dict[str, Any]) -> None:
|
|
"""
|
|
Plots the total profit for all pairs.
|
|
Note, the profit calculation isn't realistic.
|
|
But should be somewhat proportional, and therefor useful
|
|
in helping out to find a good algorithm.
|
|
"""
|
|
plot_elements = init_plotscript(config)
|
|
trades = plot_elements['trades']
|
|
# Filter trades to relevant pairs
|
|
# Remove open pairs - we don't know the profit yet so can't calculate profit for these.
|
|
# Also, If only one open pair is left, then the profit-generation would fail.
|
|
trades = trades[(trades['pair'].isin(plot_elements["pairs"]))
|
|
& (~trades['close_date'].isnull())
|
|
]
|
|
if len(trades) == 0:
|
|
raise OperationalException("No trades found, cannot generate Profit-plot without "
|
|
"trades from either Backtest result or database.")
|
|
|
|
# Create an average close price of all the pairs that were involved.
|
|
# this could be useful to gauge the overall market trend
|
|
fig = generate_profit_graph(plot_elements["pairs"], plot_elements["ohlcv"],
|
|
trades, config.get('timeframe', '5m'))
|
|
store_plot_file(fig, filename='freqtrade-profit-plot.html',
|
|
directory=config['user_data_dir'] / "plot", auto_open=True)
|