Source code for gluonts.model.trivial.identity

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import numpy as np

from gluonts.core.component import validated
from gluonts.dataset.common import DataEntry
from gluonts.dataset.field_names import FieldName
from gluonts.dataset.util import forecast_start
from gluonts.model.forecast import Forecast, SampleForecast
from gluonts.model.predictor import RepresentablePredictor


[docs]class IdentityPredictor(RepresentablePredictor): """ A `Predictor` that uses the last `prediction_length` observations to predict the future. Parameters ---------- prediction_length Prediction horizon. num_samples Number of samples to include in the forecasts. Not that the samples produced by this predictor will all be identical. """ @validated() def __init__(self, prediction_length: int, num_samples: int) -> None: super().__init__(prediction_length=prediction_length) assert num_samples > 0, "The value of `num_samples` should be > 0" self.num_samples = num_samples
[docs] def predict_item(self, item: DataEntry) -> Forecast: prediction = item["target"][-self.prediction_length :] samples = np.broadcast_to( array=np.expand_dims(prediction, 0), shape=(self.num_samples, self.prediction_length), ) return SampleForecast( samples=samples, start_date=forecast_start(item), item_id=item.get(FieldName.ITEM_ID), )