107 lines
3.0 KiB
Python
Executable File
107 lines
3.0 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Script to display profits
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Use `python plot_profit.py --help` to display the command line arguments
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"""
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import logging
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import sys
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from typing import Any, Dict, List
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import pandas as pd
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import plotly.graph_objs as go
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from plotly import tools
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from freqtrade.arguments import ARGS_PLOT_PROFIT, Arguments
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from freqtrade.data.btanalysis import create_cum_profit
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from freqtrade.optimize import setup_configuration
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from freqtrade.plot.plotting import FTPlots, store_plot_file
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from freqtrade.state import RunMode
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logger = logging.getLogger(__name__)
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def plot_profit(config: Dict[str, Any]) -> None:
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"""
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Plots the total profit for all pairs.
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Note, the profit calculation isn't realistic.
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But should be somewhat proportional, and therefor useful
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in helping out to find a good algorithm.
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"""
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plot = FTPlots(config)
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trades = plot.trades[plot.trades['pair'].isin(plot.pairs)]
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# Create an average close price of all the pairs that were involved.
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# this could be useful to gauge the overall market trend
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# Combine close-values for all pairs, rename columns to "pair"
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df_comb = pd.concat([plot.tickers[pair].set_index('date').rename(
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{'close': pair}, axis=1)[pair] for pair in plot.tickers], axis=1)
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df_comb['mean'] = df_comb.mean(axis=1)
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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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profit = go.Scattergl(
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x=df_comb.index,
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y=df_comb['cum_profit'],
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name='Profit',
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)
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fig = tools.make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 1])
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fig.append_trace(avgclose, 1, 1)
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fig.append_trace(profit, 2, 1)
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for pair in plot.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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pair_profit = go.Scattergl(
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x=df_comb.index,
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y=df_comb[profit_col],
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name=f"Profit {pair}",
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)
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fig.append_trace(pair_profit, 3, 1)
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store_plot_file(fig, filename='freqtrade-profit-plot.html', auto_open=True)
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def plot_parse_args(args: List[str]) -> Dict[str, Any]:
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"""
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Parse args passed to the script
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:param args: Cli arguments
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:return: args: Array with all arguments
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"""
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arguments = Arguments(args, 'Graph profits')
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arguments.build_args(optionlist=ARGS_PLOT_PROFIT)
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parsed_args = arguments.parse_args()
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# Load the configuration
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config = setup_configuration(parsed_args, RunMode.OTHER)
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return config
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def main(sysargv: List[str]) -> None:
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"""
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This function will initiate the bot and start the trading loop.
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:return: None
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"""
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logger.info('Starting Plot Dataframe')
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plot_profit(
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plot_parse_args(sysargv)
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)
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if __name__ == '__main__':
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main(sys.argv[1:])
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