simcal_identifiability — SIMCAL `check` op

• データ種: calresult → calresult

• 呼び出し: import fullseye as fs; fs.ledger.simcal_identifiability(result=None, at=None, profile=True, level=0.95, threshold=None) -> 'dict' (実装を直接呼ぶなら import simcalcheck; simcalcheck.simcal_identifiability(result=None, at=None, profile=True, level=0.95, threshold=None) -> 'dict'、台帳から引くなら opssimcal.get("simcal_identifiability"))

使い方

Fisher information, Cramér-Rao bound, correlations, collinearity and profile likelihood of every fitted knob.

Computed at the fit's end point (or at at = {knob: value}, e.g. the true values of a synthetic study, without touching the estimates). Returned in identifiability:

fisher (natural units), crlb (sqrt of the diagonal of its inverse — the smallest standard deviation any unbiased estimator can have under the noise model), condition (of the Fisher matrix on the unit-scaled knobs; > 1e6 adds a warning), correlation, gamma_full and confounded_groups (sensitivity.mv_confounding), and with profile=True a profile per knob: the likelihood-ratio interval where chi^2 stays within chi^2_1(level) of its minimum (3.84 at 95 %), each other knob re-fitted at every step (Raue et al. 2009). Knobs whose profile does not rise above the threshold on both sides inside the range lose their point estimate: upper_only / lower_only (only one limit exists) or undetermined. Each profile keeps its trace (knob value, chi^2 rise) of the evaluated points. No noise model: refused.

詳しい使い方ガイド

• sim_to_real_calibration ファミリガイド

参考(サンプルデータ・文献)

• サンプルデータカタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。

• 演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。

• アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。

実行できる例(この op を実際に呼ぶ検証済みサンプル)

• poc_simcal_thin_film — py -3.11 examples/poc_simcal_thin_film.py

• simcal_checks_tour — py -3.11 examples/simcal_checks_tour.py

型が繋がる次の op(`calresult` を入力に取れる)

simcal_uncertainty · simcal_validate · simcal_discrepancy · simcal_report

同カテゴリ(`check`)

simcal_uncertainty · simcal_validate · simcal_discrepancy

*Provenance: simcalcheck.py — SIMCAL operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。*

simcal_identifiability — SIMCAL check op

使い方