---
license: apache-2.0
authors:
- Joe Clinton
task_categories:
- robotics
tags:
- tsfile
- timeseries
- tabular
modality:
- timeseries
- tabular
pretty_name: Wedgit Stack Single Dual Cam TsFile
configs:
- config_name: default
  data_files:
  - split: train
    path: data/jclinton1_wedgit_stack_single_dual_cam.tsfile
size_categories:
- 10K<n<100K
---

# Wedgit Stack Single Dual Cam TsFile

This Apache TsFile dataset is derived from
[`jclinton1/wedgit_stack_single_dual_cam`](https://huggingface.co/datasets/jclinton1/wedgit_stack_single_dual_cam), a LeRobot v2.1
`so100_with_koch` dataset for stacking a yellow Wedgit block on a blue block.

## Source dataset

- Repository owner and uploader: [Joe Clinton (`jclinton1`)](https://huggingface.co/jclinton1)
- License: Apache-2.0
- Paper and formal citation: not provided by the source repository
- Split: `train`; sampling frequency: 30 fps
- Task 0: `Stack the yellow wedgit block on the blue one`
- Scale: 101 episodes, 31,354 frame rows, one task, 101 Parquet shards
- Source data path: `data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`

## TsFile contents

- File: `data/jclinton1_wedgit_stack_single_dual_cam.tsfile`
- Table: `jclinton1_wedgit_stack_single_dual_cam`
- Rows: 31,354; episode devices: 101
- Time precision: milliseconds
- Source Parquet size: 1,829,132 bytes
- TsFile size: 605,066 bytes
- TsFile/source size ratio: 0.330794

The source `meta/` files are retained. `meta/info.json` points `data_path` to
the TsFile and records the source video location and frame-alignment policy.

## Schema

| Column or group | TsFile role | Type | Description |
|---|---|---|---|
| `Time` | TIME | INT64 | `round(timestamp * 1000)` ms; restarts at zero per episode |
| `episode_index` | TAG | STRING | Original episode index stored through the device/TAG mechanism |
| `task_index` | TAG | STRING | Original task index stored through the device/TAG mechanism |
| `frame_index` | FIELD | INT64 | Original per-episode frame index |
| `sample_index` | FIELD | INT64 | Renamed from source `index` |
| `action_0` ... `action_5` | FIELD | FLOAT | Flattened source `action[6]` |
| `observation_state_0` ... `observation_state_5` | FIELD | FLOAT | Flattened source `observation.state[6]` |

Vector prefixes preserve the source column names, with `.` replaced by `_`.
The source `timestamp` is removed after Time synthesis because it equals
`Time / 1000` seconds. No frame rows, action/state elements, frame indexes,
episode indexes, or task indexes are removed. Camera pixels are external video
assets and were never fields in the source Parquet tables.

## Storage profile

- Time: `TS_2DIFF + LZ4`
- FLOAT/DOUBLE: `GORILLA + LZ4`
- INT32/INT64: `TS_2DIFF + LZ4`
- BOOLEAN: `RLE + LZ4` when present; this source has no BOOLEAN field
- TAG values: TsFile table-model device/tag storage

All episodes are merged into one table and sorted by `episode_index`,
`task_index`, and `Time`.

## Source videos

Videos are not included. The original repository stores 202 frame-aligned AV1
MP4 files under [`videos/`](https://huggingface.co/datasets/jclinton1/wedgit_stack_single_dual_cam/tree/main/videos): 101 files for
`observation.images.webcam` and 101 files for `observation.images.wrist`.
The path template is
`videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4`.
The video files total 684,781,139 bytes, are 640x480 at 30 fps, and have no
audio. Use `episode_index` and `frame_index` to align a row with both views.

## Data checks

The generated TsFile was read in full with the Apache TsFile Java reader.
Source, staged, and TsFile row counts all equal 31,354.
Physical column codecs, TAG roles, vector widths, per-episode Time ordering,
duplicate TAG+Time keys, and file-size reduction were also checked locally.

## Minimal read example

```python
from tsfile import TsFileReader

reader = TsFileReader("data/jclinton1_wedgit_stack_single_dual_cam.tsfile")
columns = [
    "episode_index",
    "task_index",
    "frame_index",
    "sample_index",
    "action_0",
    "observation_state_0",
]
with reader.query_table("jclinton1_wedgit_stack_single_dual_cam", columns, batch_size=65536) as result:
    batch = result.read_arrow_batch()
    print(batch.to_pandas().head())
reader.close()
```

When using this dataset, cite the original Hugging Face repository and Joe
Clinton (`jclinton1`).