piv_error_stats — PIV `assess` op

• Data kinds: flow2d × flow2d → table

• Call: import pivops; pivops.piv_error_stats(flow, truth, trim=1) (or opspiv.get("piv_error_stats"))

Usage

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

真値との差の内訳。偏りと散らばりを分けて返す。

どちらか一方だけを出すと、系統的にずれている実装が「誤差 0.3 px」として

通ってしまう。偏り(平均誤差)と散らばり(標準偏差)は別の原因を指す。

Args:

flow: 推定 `(2, h, w)`。

truth: 同じ格子の真値 `(2, h, w)(:func:piv_sample_at_windows` の返り)。

trim: 外周から除く格子数。窓が画像の縁にかかると相関が落ちるので、

既定で 1 列ぶん落とす。0 で全格子。

Returns:

dict: `bias_dy / bias_dx / std_dy / std_dx / rms`

(2 成分合わせた二乗平均平方根) / `median_abs / p95_abs` /

`n_valid / n_total`。

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_strain_history — py -3.11 examples/poc_strain_history.py

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

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Same category (`assess`)

piv_sample_at_windows · piv_peak_locking · piv_time_statistics

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

piv_error_stats — PIV assess op