EthoClaw ethoclaw-multiparameter-violin-stats-generate

Read HDF5 (.h5/.hdf5) data, compare groups with appropriate statistical tests (2 groups: t-test/Mann–Whitney; 3+ groups: ANOVA/Kruskal–Wallis + post-hoc pairwise), and generate violin plots + summary table/JSON. Use when the user asks for multi-parameter violin plot generation/group difference testing/batch parameter statistical plotting.

install

source · Clone the upstream repo

git clone https://github.com/penciler-star/EthoClaw

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/penciler-star/EthoClaw "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/ethoclaw-multiparameter-violin-stats-generate" ~/.claude/skills/penciler-star-ethoclaw-ethoclaw-multiparameter-violin-stats-generate && rm -rf "$T"

manifest: skills/ethoclaw-multiparameter-violin-stats-generate/SKILL.md

source content

H5 Multi-parameter Violin + Stats

Generate violin plots and run group-difference tests directly from

.h5/.hdf5

files.

Workflow

1) Inspect the H5 structure (find dataset paths)

If you don’t know the internal paths, run:

python scripts/h5_inspect.py your_data.h5

Identify:

a numeric 1D dataset path for values, e.g.
```
/metrics/score
```
a label 1D dataset path for group labels, e.g.
```
/meta/group
```

2) Run stats + generate violin plot

python scripts/h5_violin_stats.py \
  --h5 your_data.h5 \
  --dataset /metrics/score \
  --group /meta/group \
  --method auto \
  --config skills/ethoclaw-multiparameter-violin-stats-generate/config.toml \
  --out outputs/violin.png \
  --out-json outputs/result.json

--method auto

: follows

config.toml

defaults

2 groups →
```
stats.default_2_groups
```
3+ groups →
```
stats.default_3plus_groups
```

Choose nonparametric methods explicitly when needed:
- 2 groups:
```
--method mannwhitney
```
- =3 groups:
```
--method kruskal
```

3) Interpreting results

For 2 groups: the “overall” test is the direct group comparison.
For >=3 groups: script runs overall ANOVA/Kruskal first; if
```
p <= alpha
```
(default 0.05), it runs pairwise comparisons and reports Holm-adjusted p-values (
```
p_holm
```
).

Stat rules reference:

references/stats-rule.md

Notes / Assumptions

Current scripts assume
```
values
```
is a 1D numeric array and
```
group
```
is a 1D label array of the same length.
If your H5 stores multiple metrics or nested structures, extend the loader in
```
scripts/h5_violin_stats.py::_read_h5_1d
```
.
If dependencies are missing, install Python
```
pip
```
+ packages (system-dependent). In WSL/Ubuntu, you typically need
```
python3-venv
```
and
```
python3-pip
```
.