evaluate.BacktestResult

Per-window result of a backtest() run.

Usage

Source

evaluate.BacktestResult(
    t0,
    t1,
    t2,
    num_samples,
    walltime,
    metrics,
    train_metrics=dict(),
    prediction=None
)

Attributes

t0, t1, t2

Train-begin, train/test split, and test-end time indices.

num_samples: int

Number of forecast samples drawn.

walltime: float

Wall-clock seconds for the window’s timed forecast_fn call.

metrics: dict[str, float]

Mapping of metric name to value for the window.

train_metrics: dict[str, float]

Mapping of metric name to in-sample value for the window. Empty unless backtest was called with eval_train=True.

prediction: Array | np.ndarray | None

Out-of-sample forecast samples for the window (sample axis leading), or None unless backtest was called with keep_predictions=True.

Methods

Name	Description
to_dict()	Return a flat dictionary view (Pyro-style access).

---

to_dict()

Return a flat dictionary view (Pyro-style access).

Usage

Source

to_dict()

Returns

dict[str, Any]

All fields as a plain dictionary.