0.1.0

First public release of croma, a lean library of robustness metrics for pathology foundation models.

It measures how much a model's representation is driven by biology rather than by non-biological technical variation — staining, scanning, tissue preparation — across centers.

Metric	Name	What it does
RI	Robustness Index	Counts favourable vs. unfavourable neighbours
MaRI	Margin-aware Robustness Index	Weights that same evidence by feature distance
CRoMa	Cross-confounder Robustness Margin	A signed margin, with tail-aware reporting

RI was introduced in the PathoROB study; croma provides a clean re-implementation of it, adds MaRI as its margin-aware extension, and introduces CRoMa. Also ships croma.downstream — the confounder-biased probe protocol and its two reductions, APD and nAPD.

pip install croma

The core package depends only on numpy, pandas, scikit-learn and tqdm, and never loads a model or reads an image — you bring the embeddings.

📖 Documentation · full detail in CHANGELOG.md

The paper describing MaRI and CRoMa is in preparation; until it is out, please cite this repository together with the PathoROB study.