| --- |
| license: cc0-1.0 |
| language: |
| - en |
| tags: |
| - biology |
| - animal-behavior |
| - collective-behavior |
| - animal-tracking |
| - mosaic |
| pretty_name: "Golden shiners: collective motion across group size" |
| size_categories: |
| - 10M<n<100M |
| --- |
| |
| # Golden shiners, collective motion across group size |
|
|
| Pose tracks for ten trials of free-swimming golden shiners (*Notemigonus |
| crysoleucas*) at four group sizes, converted to |
| [mosaic](https://github.com/EcodylicScience/mosaic) parquet tables and ready to |
| analyse without a conversion step. |
|
|
| Worked example: |
| [`notebooks/collective-motion-shiners.ipynb`](https://github.com/EcodylicScience/mosaic/blob/main/notebooks/collective-motion-shiners.ipynb). |
| Set `SOURCE = "download"` (the default) and it fetches both files below. |
|
|
| ## Read this before comparing against another tracker |
|
|
| **`X` / `Y` is the fish's HEAD, not its body centre.** SchoolTracker measures no |
| centroid. It locates the head, within 2 px of the midpoint between the two eyes, |
| and that is what these tables carry. Every other tracker mosaic converts (TRex, |
| SLEAP, Ultralytics, DeepLabCut) puts a body centroid in `X` / `Y`, so a feature |
| reading `X` across this dataset and one of those is comparing two landmarks about |
| half a body length apart, with nothing in the numbers to say so. |
|
|
| The same warning travels with the data: it is written into the `schooltracker_v1` |
| schema description recorded in `tracks/index.csv`. |
|
|
| There are **no `poseX*` / `poseY*` columns**. The head is the one point measured |
| and it is already in `X` / `Y`; a keypoint pair would be a verbatim copy under a |
| name promising a second, separately detected landmark. |
|
|
| ## Files |
|
|
| | File | Size | What it is | |
| | --- | --- | --- | |
| | `shiners-tracks.tar.gz` | 350 MB | A complete mosaic dataset: `dataset.yaml` + `tracks/`. Ten trials, 10,827,539 rows. | |
| | `shiners-raw-sample.tar.gz` | 8.9 MB | One trial (`10-fish/0066`, 7 segments) of raw SchoolTracker `_fov.h5`, reduced to the fields the converter reads. | |
|
|
| `SHA256SUMS` carries the checksums. |
|
|
| The raw sample exists so the example notebook can *run* its converter rather than |
| only display it. Converting the sample reproduces the shipped table for that |
| trial exactly, and the notebook asserts this before going on. |
|
|
| ## Contents |
|
|
| | group | trials | frames each | individuals | |
| | --- | --- | --- | --- | |
| | `10-fish` | 0066, 0105, 0126 | ~24,600 | 10 | |
| | `30-fish` | 0084, 0115, 0120 | ~24,580 | 30 | |
| | `70-fish` | 0103, 0107, 0124 | ~24,570 | 70 | |
| | `150-fish` | one trial | 17,999 | **151** | |
|
|
| The last row is not a typo: the source directory is named `150-fish` and the file |
| reports 151 tracks. Both are preserved rather than one being corrected to match |
| the other. |
|
|
| Columns: `frame, time, id, group, sequence, X, Y, ANGLE, body_length`. Positions |
| are **video pixels**. `ANGLE` is the tracker's own measured body-axis heading, not |
| an inference from displacement — which is why the schema is `schooltracker_v1` |
| (`mosaic_v1` plus `ANGLE`) rather than plain `mosaic_v1`. |
|
|
| ## Use |
|
|
| ```python |
| import tarfile |
| from huggingface_hub import hf_hub_download |
| from mosaic.core.dataset import Dataset |
| |
| path = hf_hub_download("EcodylicScience/mosaic-example-shiners", |
| "shiners-tracks.tar.gz", repo_type="dataset") |
| with tarfile.open(path) as tar: |
| tar.extractall("data") |
| |
| ds = Dataset("data/shiners-tracks/dataset.yaml").load() |
| tracks = ds.load_tracks("10-fish", "0066") |
| ``` |
|
|
| `huggingface_hub >= 1.2.0` is worth pinning: older clients retry a rate-limit |
| response with a 25-second backoff against a 5-minute window, so they fail where a |
| current client waits. |
|
|
| ## Provenance and changes |
|
|
| Derived from the Dryad record accompanying Davidson et al. (2021). **CC0 1.0**, |
| so this derivative carries the same terms. |
|
|
| Source: [doi:10.5061/dryad.sbcc2fr2h](https://doi.org/10.5061/dryad.sbcc2fr2h) |
| (32 GB across 11 zips; about 45 GB of `_fov.h5` unpacked). |
|
|
| What was changed: |
|
|
| - The `_fov.h5` pose arrays were converted to mosaic `schooltracker_v1` parquet |
| tables. Column names and layout differ from the original release. **Positions |
| and headings are unaltered** — `x`, `y` and the heading vector are carried |
| through verbatim, with `ANGLE = arctan2(heading_y, heading_x)`. |
| - Each trial's segment files were joined into one table: frame numbers offset by |
| the preceding segments' lengths, and track identities re-linked across joins by |
| linear-sum assignment on the last and first frames. The converter's docstring |
| gives the margins. |
| - Fields not converted: the 256-ray visual field (`fov_*`, the bulk of the |
| 45 GB), the body-local midline and shape descriptors, the eye positions, and |
| the all-zero stimulus-object fields. |
| - The raw sample additionally has every unread field removed, which is why one |
| trial is 8.9 MB rather than 932 MB. Kept arrays are byte-identical to the |
| originals. |
|
|
| Not included: video, and the visual-field arrays. Both are in the Dryad record. |
|
|
| ## Citation |
|
|
| Davidson JD, Sosna MMG, Twomey CR, Sridhar VH, Leblanc SP, Couzin ID (2021) |
| Collective detection based on visual information in animal groups. *Journal of |
| the Royal Society Interface* 18: 20210142. |
| [doi:10.1098/rsif.2021.0142](https://doi.org/10.1098/rsif.2021.0142) |
|
|
