field op• Data kinds: flow2d → image2d
• Call: import fullseye as fs; fs.ledger.piv_swirling_strength(flow, spacing=1.0) (to call the implementation directly, import pivops; pivops.piv_swirling_strength(flow, spacing=1.0); from the registry, opspiv.get("piv_swirling_strength"))
Swirling strength λ_ci — the magnitude of the imaginary part of the complex eigenvalues of the velocity-gradient tensor.
Like the Q-criterion it is a quantity that "distinguishes shear from vortices", but this one has units equal to the angular velocity of rotation (1/frame). Measured: 0.01 for rigid-body rotation ω=0.01, 0.0 for uniform expansion and shear.
Where the eigenvalues are real (= no rotation), 0 is returned. Since it is the eigenvalues of an independent 2x2 matrix at each point, the whole grid is vectorised and solved at once.
• piv_displacement family guide
• 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.
• piv_field_analysis_tour — py -3.11 examples/piv_field_analysis_tour.py
image2d as input)piv_cross_correlate · piv_multipass · piv_deform_pass · strain_from_displacement · correlation_quality · speckle_quality
field)piv_vorticity · piv_divergence · piv_flow_magnitude · piv_to_velocity · piv_velocity_gradient · piv_q_criterion · piv_strain_rate
*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.