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EthoClaw ethoclaw-multiparameter-radar-generate

Generate GraphPad Prism-like multi-parameter radar charts from a folder of HDF5 .h5/.hdf5 files (KinematicParameter/ParameterName + ParameterData). Summarize frames per sample (mean/median/max), normalize (min-max or z-score), and plot per-sample radars and/or group-mean comparison radars (group inferred from filenames). Outputs publication-style PNG/PDF and CSV. Use when user asks for multi-parameter radar chart generation/radar chart comparison.

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 "$T/skills/ethoclaw-multiparameter-radar-generate" ~/.claude/skills/penciler-star-ethoclaw-ethoclaw-multiparameter-radar-generate && rm -rf "$T"
manifest: skills/ethoclaw-multiparameter-radar-generate/SKILL.md
source content

H5 Multi-parameter Radar

One skill, focused on the two outputs you want:

  • per_sample: single-sample radar for each sample (all parameters).
  • group_means (recommended for group comparison): one polygon per group, using each group mean.
  • both: generate both per_sample + group_means in one run.

(Still supports all_samples as a legacy overlay mode, if you ever need it.)

Assumed HDF5 layout

Preferred:

  • /KinematicParameter/ParameterName
  • /KinematicParameter/ParameterData
    (frames × params)

Grouping

Default group inference regex (1 capture group):

  • rec-\d+-([^-_]+)[-_]

Override with 

--group_regex
if your filenames differ.

Run (Windows / Anaconda example)

Generate both outputs (recommended)

D:\Anaconda3\python.exe plot_h5_radar.py --project_dir "C:\Users\ASUS\Desktop\2Dxy_test_project\random_project" --mode both --stat mean --normalize minmax --style nature

Group means only (one polygon per group)

D:\Anaconda3\python.exe plot_h5_radar.py --project_dir "C:\Users\ASUS\Desktop\2Dxy_test_project\random_project" --mode group_means --stat mean --normalize minmax --style nature

Per-sample only (one radar per sample)

D:\Anaconda3\python.exe plot_h5_radar.py --project_dir "C:\Users\ASUS\Desktop\2Dxy_test_project\random_project" --mode per_sample --stat mean --normalize minmax --style nature

Legacy: all samples overlay

D:\Anaconda3\python.exe plot_h5_radar.py --project_dir "C:\Users\ASUS\Desktop\2Dxy_test_project\random_project" --mode all_samples --stat mean --normalize minmax --max_samples_combined 50 --style nature

Key flags

  • --mode
    : 
    both|per_sample|group_means|all_samples
  • --stat
    : 
    mean|median|max
  • --normalize
    : 
    none|minmax|zscore
  • --n_params
    : limit to N parameters for readability
  • --max_samples_combined
    : limit sample count in all-samples combined overlay

Outputs

Default output root (relative to 

project_dir
):

  • results/h5_radar/<mode>/
    (for 
    both
    , it writes into 
    results/h5_radar/per_sample/
    and 
    results/h5_radar/group_means/
    )

Includes CSV matrices and PNG/PDF radars. If some files lack required datasets, see 

skipped_files.txt
.