strategies_horizon.py

def get_metrics_by_horizon(ts: TSDataset, horizon: int, total_points: int):
    if total_points % horizon != 0:
        raise ValueError("Horizon should divide total number of points!")

    n_folds = total_points // horizon

    transforms = [
        LagTransform(
            in_column="target",
            lags=list(range(horizon, MAX_LAG)),
            out_column="lag_target",
        ),
        SegmentEncoderTransform(),
    ]
    model = CatBoostMultiSegmentModel()
    pipeline = Pipeline(model=model, transforms=transforms, horizon=horizon)

    start_time = time.perf_counter()
    metrics_df, forecast_df, fold_info_df = pipeline.backtest(
        ts=ts, metrics=[SMAPE()], n_folds=n_folds
    )
    elapsed_time = time.perf_counter() - start_time
    smape_value = metrics_df.mean().to_dict()["SMAPE"]
    return {"SMAPE": smape_value, "time": elapsed_time}


horizon_values = [24, 12, 6, 4, 3, 2, 1]
horizon_results = []

for horizon in horizon_values:
    cur_res = get_metrics_by_horizon(
        ts=ts, horizon=horizon, total_points=HORIZON * N_FOLDS
    )
    horizon_results.append({"horizon": horizon, **cur_res})