piv_replace_outliers — PIV validate op

• Data kinds: flow2d × mask → flow2d

• Call: import fullseye as fs; fs.ledger.piv_replace_outliers(flow, mask, method='median') (to call the implementation directly, import pivops; pivops.piv_replace_outliers(flow, mask, method='median'); from the registry, opspiv.get("piv_replace_outliers"))

Usage

Fills outliers from their neighbourhood. With method="nan" they are not filled but marked as missing.

The price of filling is that filled places can no longer be told apart from measured ones, so it is assumed that the caller keeps where filling happened as mask (this op does not return mask —— it is something received as input).

Detailed usage guide

• piv_displacement family guide

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• piv_flow_from_particles — py -3.11 examples/piv_flow_from_particles.py

• poc_river_surface_velocity — py -3.11 examples/poc_river_surface_velocity.py

Ops the type connects to (they accept flow2d as input)

piv_deform_pass · piv_outlier_mask · piv_vorticity · piv_divergence · piv_flow_magnitude · piv_to_velocity · piv_velocity_gradient · piv_q_criterion

Same category (validate)

piv_outlier_mask


*Provenance: pivops.py — PIV 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.