THULab/SMAP
SMAP (TsFile) Apache TsFile version of the SMAP anomaly-detection subset of thuml/Time-Series-Library. Overview Soil Moisture Active Passive satellite telemetry (25 channels) for anomaly detection. Train: 135,183 rows (all normal). Test: 427,617 rows (with per-timestep 0/1 anomaly labels). Channels: 25. The train and test segments are stored as two separate TsFiles (SMAP_train.tsfile / SMAP_test.tsfile), preserving the original split. Schema (TsFile… See the full description on the dataset page: https://huggingface.co/datasets/THULab/SMAP.
SMAP (TsFile)
Apache TsFile version of the SMAP anomaly-detection subset of `thuml/Time-Series-Library`.
Overview
Soil Moisture Active Passive satellite telemetry (25 channels) for anomaly detection.
- Train: 135,183 rows (all normal).
- Test: 427,617 rows (with per-timestep 0/1 anomaly labels).
- Channels: 25.
The train and test segments are stored as two separate TsFiles (SMAP_train.tsfile / SMAP_test.tsfile), preserving the original split.
Schema (TsFile structure)
- Time (INT64, milliseconds) — row index * 1000 ms (the
.npysource has no timestamp; a monotone 1 Hz proxy axis). - FIELD (25 channels, FLOAT) — the sensor/metric channels.
- label (INT32) — per-timestep anomaly flag (0/1). The train file is all 0 (no ground-truth labels); the test file carries the anomaly labels.
No channels or rows are dropped.
Usage
Read the .tsfile files with the Apache TsFile Java or Python SDK.
Source & license
- Original dataset: https://huggingface.co/datasets/thuml/Time-Series-Library (subset
SMAP) - Author / publisher: thuml (Tsinghua University)
- Paper: https://arxiv.org/abs/2407.13278
- License: CC BY 4.0