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pytorch-ts/pts/dataset/repository/_artificial.py
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# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
#
# 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
# express or implied. See the License for the specific language governing
# permissions and limitations under the License.
# Standard library imports
import json
from pathlib import Path
# First-party imports
from pts.dataset import ArtificialDataset, generate_sf2, serialize_data_entry
def generate_artificial_dataset(dataset_path: Path, dataset: ArtificialDataset) -> None:
dataset_path_train = dataset_path / "train"
dataset_path_test = dataset_path / "test"
dataset_path.mkdir(exist_ok=True)
dataset_path_train.mkdir(exist_ok=False)
dataset_path_test.mkdir(exist_ok=False)
ds = dataset.generate()
assert ds.test is not None
with (dataset_path / "metadata.json").open("w") as fp:
json.dump(ds.metadata.dict(), fp, indent=2, sort_keys=True)
generate_sf2(
filename=str(dataset_path_train / "train.json"),
time_series=list(map(serialize_data_entry, ds.train)),
is_missing=False,
num_missing=0,
)
generate_sf2(
filename=str(dataset_path_test / "test.json"),
time_series=list(map(serialize_data_entry, ds.test)),
is_missing=False,
num_missing=0,
)