visualise op• Data kinds: flow2d → rgb
• Call: import fullseye as fs; fs.ledger.piv_flow_to_rgbimage(flow, scale=None) (to call the implementation directly, import pivops; pivops.piv_flow_to_rgbimage(flow, scale=None); from the registry, opspiv.get("piv_flow_to_rgbimage"))
Standard flow visualisation with hue = direction and brightness = speed. Returns (h, w, 3).
2-D version of reprconv.flow_to_rgbimage (that one is dedicated to 3-D scene flow of (3, D, H, W), and planar flow is rejected by shape).
Always burn the hue-wheel legend into the figure along with it —— a flow figure that does not say what the colours mean is merely pretty and cannot be read. Omitting scale normalises by the maximum speed, so the meaning of the colours changes from figure to figure. When placing several figures side by side, fix it explicitly.
Args:
flow: (2, h, w).
scale: speed [px] corresponding to brightness 1.0. None uses the maximum.
Returns:
(h, w, 3) float64, range [0, 1].
• 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
rgb as input)—
visualise)piv_line_integral_convolution · piv_streamlines · piv_quiver · piv_streamline_image
*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.