piv_streamline_image — PIV `visualise` op

• Data kinds: flow2d → rgb

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

Usage

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

流線図(MATLAB の `streamslice)。返りは (h*upsample, w*upsample, 3)`。

:func:piv_streamlines の等間隔配置で線を引き、各線の弧長の中ほどに

向きの矢じりを 1 つ置く(LIC と違って前後が読める)。線の間隔が揃うので、

線の密度では速さを表さない —— 速さを見たいときは `background` に

`piv_flow_magnitude` か色相図を敷く。

Args:

flow: `(2, h, w)`。

upsample / background / color / width: :func:piv_quiver と同じ。

arrows: 矢じりを置くか。

**stream_kw: :func:piv_streamlines へ素通し(`separation` など)。

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)

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Same category (`visualise`)

piv_flow_to_rgbimage · piv_line_integral_convolution · piv_streamlines · piv_quiver

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

piv_streamline_image — PIV visualise op