evaluate.BacktestResult

Per-window result of a backtest() run.

Usage

evaluate.BacktestResult(
    t0,
    t1,
    t2,
    num_samples,
    train_walltime,
    test_walltime,
    metrics,
    params=dict(),
    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.
train_walltime, test_walltime: Wall-clock seconds for fitting and forecasting.
metrics: dict[str, float]: Mapping of metric name to value for the window.
params: dict[str, float]: Mapping of scalar parameter name to value (when available).
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 | 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.