Source code for gluonts.model.trivial.identity
# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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# Licensed under the Apache License, Version 2.0 (the "License").
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# http://www.apache.org/licenses/LICENSE-2.0
#
# or in the "license" file accompanying this file. This file is distributed
# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
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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),
)