anomaly_eval op• Data kinds: signal × signal → table
• Call: import fullseye as fs; fs.ledger.anomaly_image_f1_max(scores, labels) (to call the implementation directly, import anomeval; anomeval.anomaly_image_f1_max(scores, labels); from the registry, opsspc.get("anomaly_image_f1_max"))
Best image-level F1 over all thresholds from one anomaly score per image and a good/defective label (table).
scores is a 1-D array (higher = more anomalous), labels the same length with 1 / True = defective; an image is predicted defective when its score is >= the threshold. Exact at every distinct score; the highest threshold wins a tie. Returns f1, threshold, precision, recall, n_pos and n_neg (images).
Raises ValueError on empty / mismatched / non-finite input, non-binary labels, or when all images carry the same label.
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• (none yet)
table as input)msa_anova_table · msa_gauge_rr · msa_bias_linearity · msa_attribute_agreement · gum_standard_uncertainty · gum_propagate · gum_expanded · gum_monte_carlo
anomaly_eval)anomaly_image_auroc · anomaly_pixel_auroc · anomaly_pro · anomaly_region_overlap · anomaly_pixel_f1_max · anomaly_operating_point
*Provenance: anomeval.py — SPC operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.