stable/scripts/plot_profit.py
2019-06-30 09:28:49 +02:00

137 lines
4.0 KiB
Python
Executable File

#!/usr/bin/env python3
"""
Script to display profits
Use `python plot_profit.py --help` to display the command line arguments
"""
import logging
import sys
from pathlib import Path
from typing import Any, Dict, List
import pandas as pd
import plotly.graph_objs as go
from plotly import tools
from freqtrade.arguments import ARGS_PLOT_PROFIT, Arguments
from freqtrade.data import history
from freqtrade.data.btanalysis import create_cum_profit, load_trades
from freqtrade.optimize import setup_configuration
from freqtrade.plot.plotting import store_plot_file
from freqtrade.resolvers import ExchangeResolver
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
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.
"""
exchange = ExchangeResolver(config.get('exchange', {}).get('name'), config).exchange
# Take pairs from the cli otherwise switch to the pair in the config file
if "pairs" in config:
pairs = config["pairs"].split(',')
else:
pairs = config["exchange"]["pair_whitelist"]
# We need to use the same pairs and the same ticker_interval
# as used in backtesting / trading
# to match the tickerdata against the results
timerange = Arguments.parse_timerange(config["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),
)
# Load the profits results
trades = load_trades(config)
trades = trades[trades['pair'].isin(pairs)]
# Create an average close price of all the pairs that were involved.
# this could be useful to gauge the overall market trend
# Combine close-values for all pairs, rename columns to "pair"
df_comb = pd.concat([tickers[pair].set_index('date').rename(
{'close': pair}, axis=1)[pair] for pair in tickers], axis=1)
df_comb['mean'] = df_comb.mean(axis=1)
# 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',
)
profit = go.Scattergl(
x=df_comb.index,
y=df_comb['cum_profit'],
name='Profit',
)
fig = tools.make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 1])
fig.append_trace(avgclose, 1, 1)
fig.append_trace(profit, 2, 1)
for pair in pairs:
profit_col = f'cum_profit_{pair}'
df_comb = create_cum_profit(df_comb, trades[trades['pair'] == pair], profit_col)
pair_profit = go.Scattergl(
x=df_comb.index,
y=df_comb[profit_col],
name=f"Profit {pair}",
)
fig.append_trace(pair_profit, 3, 1)
store_plot_file(fig,
filename='freqtrade-profit-plot.html',
auto_open=True)
def plot_parse_args(args: List[str]) -> Dict[str, Any]:
"""
Parse args passed to the script
:param args: Cli arguments
:return: args: Array with all arguments
"""
arguments = Arguments(args, 'Graph profits')
arguments.build_args(optionlist=ARGS_PLOT_PROFIT)
parsed_args = arguments.parse_args()
# Load the configuration
config = setup_configuration(parsed_args, RunMode.OTHER)
return config
def main(sysargv: List[str]) -> None:
"""
This function will initiate the bot and start the trading loop.
:return: None
"""
logger.info('Starting Plot Dataframe')
plot_profit(
plot_parse_args(sysargv)
)
if __name__ == '__main__':
main(sys.argv[1:])