Plots¶

Visualization functions for backtest results. Requires matplotlib:

pip install replaybt[plots]

All functions return a matplotlib.figure.Figure. Call fig.savefig("plot.png") to save.

from replaybt.analysis.plots import plot_equity

plot_equity¶

Equity curve with optional drawdown shading.

fig = plot_equity(results, show_drawdown=True, figsize=(12, 6))
fig.savefig("equity.png")

Parameter	Type	Default	Description
`results`	`BacktestResults`	required	Results with equity curve
`show_drawdown`	`bool`	`True`	Shade drawdown regions
`figsize`	`Tuple[int, int]`	`(12, 6)`	Figure size

Drawdown as negative percentage filled area.

fig = plot_drawdown(results, figsize=(12, 4))

Parameter	Type	Default	Description
`results`	`BacktestResults`	required	Results with equity curve
`figsize`	`Tuple[int, int]`	`(12, 4)`	Figure size

Entry/exit markers, optionally on a price chart.

fig = plot_trades(results, prices=price_list, figsize=(14, 6))

Parameter	Type	Default	Description
`results`	`BacktestResults`	required	Results with trades
`prices`	`Optional[List[Tuple]]`	`None`	`(timestamp, price)` tuples for price line
`figsize`	`Tuple[int, int]`	`(14, 6)`	Figure size

Markers: ^ = long entry, v = short entry, x = exit. Green = profit, red = loss.

Monthly PnL as a Year x Month heatmap.

fig = plot_monthly_heatmap(results, figsize=(10, 5))

Parameter	Type	Default	Description
`results`	`BacktestResults`	required	Results with monthly data
`figsize`	`Tuple[int, int]`	`(10, 5)`	Figure size

Green cells = profit, red cells = loss. Values annotated inside cells.

Exit reason breakdown as bar or pie chart.

fig = plot_exit_breakdown(results, kind="bar", figsize=(8, 5))

Parameter	Type	Default	Description
`results`	`BacktestResults`	required	Results with exit breakdown
`kind`	`str`	`"bar"`	`"bar"` or `"pie"`
`figsize`	`Tuple[int, int]`	`(8, 5)`	Figure size

Per-symbol equity curves with optional combined portfolio overlay.

fig = plot_multi_equity(multi_results, show_combined=True, figsize=(14, 7))

Parameter	Type	Default	Description
`results`	`MultiAssetResults`	required	Multi-asset results
`show_combined`	`bool`	`True`	Show combined equity line
`figsize`	`Tuple[int, int]`	`(14, 7)`	Figure size

2D parameter sweep as a heatmap.

fig = plot_sweep_heatmap(
    sweep_results,
    x_param="take_profit_pct",
    y_param="stop_loss_pct",
    metric="net_pnl",
    figsize=(10, 7),
)

Parameter	Type	Default	Description
`results`	`SweepResults`	required	Sweep results
`x_param`	`str`	required	Parameter for x-axis
`y_param`	`str`	required	Parameter for y-axis
`metric`	`str`	`"net_pnl"`	Metric to display
`figsize`	`Tuple[int, int]`	`(10, 7)`	Figure size