piv_quiver — PIV `visualise` op

• Data kinds: flow2d → rgb

• Call: import fullseye as fs; fs.ledger.piv_quiver(flow, spacing=None, scale=None, upsample=8, background=None, color=(0.08, 0.08, 0.12), width=1.5) (to call the implementation directly, import pivops; pivops.piv_quiver(flow, spacing=None, scale=None, upsample=8, background=None, color=(0.08, 0.08, 0.12), width=1.5); from the registry, opspiv.get("piv_quiver"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

矢印図(MATLAB の `quiver)。返りは (h*upsample, w*upsample, 3)`。

`spacing 格子ごとに 1 本、起点を格子点に置き、先端を 起点 + scale * v`

に引く。`scale` を省くと 最も長い矢印が間隔の 0.9 倍 になる(MATLAB の

自動倍率と同じ考え方で、隣の矢印に重ならない)。倍率は図ごとに変わる

ので、並べて比べる図では `scale` を固定する。長さが 1 画素に満たない

矢印は描かない(向きの無い点は印と読まれる)。

Args:

flow: `(2, h, w)(dy, dx`)。

spacing: 矢印の間隔 [格子]。`None` で長い辺に約 20 本。

scale: 矢印の長さ = `scale * 速さ` [格子]。

upsample: 出力の倍率(矢じりを描ける大きさにする)。

background: `(h*upsample, w*upsample) か (…, 3)。None` で白。

色相図(`piv_flow_to_rgbimage` を拡大したもの)や LIC を敷ける。

color / width: 矢印の色(palette の役割名か RGB)と軸の太さ [px]。

既定は黒に近い墨色(色相図を敷いても読める)。

Returns:

`(h*upsample, w*upsample, 3)` float64、値域 [0, 1]。

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_field_analysis_tour — py -3.11 examples/piv_field_analysis_tour.py

Ops the type connects to (they accept `rgb` as input)

—

Same category (`visualise`)

piv_flow_to_rgbimage · piv_line_integral_convolution · piv_streamlines · piv_streamline_image

*Provenance: pivops.py — PIV operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

piv_quiver — PIV visualise op