Datasets:
Tasks:
Time Series Forecasting
Sub-tasks:
univariate-time-series-forecasting
Size:
1K<n<10K
License:
File size: 772 Bytes
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from typing import Any, Dict, List, Optional
import numpy as np
import pandas as pd
def to_dict(
target_values: np.ndarray,
start: pd.Timestamp,
cat: Optional[List[int]] = None,
item_id: Optional[Any] = None,
real: Optional[np.ndarray] = None,
) -> Dict:
def serialize(x):
if np.isnan(x):
return "NaN"
else:
# return x
return float("{0:.6f}".format(float(x)))
res = {
"start": start,
"target": [serialize(x) for x in target_values],
}
if cat is not None:
res["feat_static_cat"] = cat
if item_id is not None:
res["item_id"] = item_id
if real is not None:
res["feat_dynamic_real"] = real.astype(np.float32).tolist()
return res
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