4aa2ae37bd
added extra key daily_profit in return of optimize_reports.generate_daily_stats
this allows us to analyze and plot a daily profit chart / equity line using snippet below inside jupyter notebook
```
# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)
from freqtrade.configuration import Configuration
from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats
import plotly.express as px
import pandas as pd
# strategy = 'Strat'
# config = Configuration.from_files(["user_data/config.json"])
# backtest_dir = config["user_data_dir"] / "backtest_results"
stats = load_backtest_stats(backtest_dir)
strategy_stats = stats['strategy'][strategy]
equity = 0
equity_daily = []
for dp in strategy_stats['daily_profit']:
equity_daily.append(equity)
equity += float(dp)
dates = pd.date_range(strategy_stats['backtest_start'], strategy_stats['backtest_end'])
df = pd.DataFrame({'dates':dates,'equity_daily':equity_daily})
fig = px.line(df, x="dates", y="equity_daily")
fig.show()
```
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|---|---|---|
| .. | ||
| space | ||
| __init__.py | ||
| backtesting.py | ||
| default_hyperopt_loss.py | ||
| edge_cli.py | ||
| hyperopt_auto.py | ||
| hyperopt_interface.py | ||
| hyperopt_loss_interface.py | ||
| hyperopt_loss_onlyprofit.py | ||
| hyperopt_loss_sharpe_daily.py | ||
| hyperopt_loss_sharpe.py | ||
| hyperopt_loss_sortino_daily.py | ||
| hyperopt_loss_sortino.py | ||
| hyperopt_tools.py | ||
| hyperopt.py | ||
| optimize_reports.py | ||