fit op• Data kinds: simmodel → calresult
• Call: import fullseye as fs; fs.ledger.simcal_fit(model=None, method='lm', n_starts=16, fix=None, threshold=10.0, allow_undetermined=False, seed=0) -> 'dict' (implementation को सीधे call करना हो तो import simcal; simcal.simcal_fit(model=None, method='lm', n_starts=16, fix=None, threshold=10.0, allow_undetermined=False, seed=0) -> 'dict', registry से लेना हो तो opssimcal.get("simcal_fit"))
observed simmodel के free knobs को उसकी images पर fit करता है (weighted least squares) -> calresult।
> नीचे का विस्तृत विवरण मूल text में है — सारांश और headings का अनुवाद हो चुका है।
Minimises chi^2 = sum over valid pixels of (observed − simulated)^2 / variance, the variance coming from the noise model at the current prediction (re-weighted each
iteration: the quasi-likelihood estimating equation, unbiased for a signal-dependent variance). Knobs live in u in [0, 1] (log knobs on a log axis).
Starting point: the initial knobs and n_starts Latin-hypercube points over the ranges are scored by chi^2 and the best is used (the design's "start from the best point of the plan"). method: "lm" (Levenberg-Marquardt, Marquardt-scaled damping; a raw step that leaves the range is not taken — its projection onto the range is tried, a knob on a range end whose descent points outward is held there, and a point the forward model refuses rejects the step and raises the damping, as in lensopt), "nm" (Nelder-Mead; a point outside the range scores the metric's worst value via metriccontract.value_or_worst), "multistart" (LM from the best n_starts // 4 plan points, at least 2, ranked with metriccontract.best_of — for multi-modal problems such as thin-film fringe orders). fix = {knob: value} pins knobs for this fit.
Refusal (metriccontract.MetricContractError, a ValueError) when, at the end point, a knob has no influence (a full-range move changes chi^2 by less than 3.84), is confounded with others (collinearity index gamma_K > threshold, sensitivity.mv_confounding), or sits within 1 % of a range end — the message names the knobs, the reason and the combinations the data do fix. With allow_undetermined=True those knobs get no value (undetermined holds the reason, status = partial) and determined_combos carries the combinations with their values (a product of powers for log knobs). No noise model / no observed images:
refused.
• sim_to_real_calibration family guide
• Sample data catalog (DL URL / license) — 2-D के लिए skimage.data (BSD/public) + synthetic, 3-D के लिए real data sources (Stanford/PDS आदि) के DL URL।
• Operators का स्रोत और संदर्भ — इस op family के मूल research/methods के स्रोत।
• Algorithm का मानक स्रोत (लेखक, वर्ष) और उपयोग ऊपर की family usage guide में दिए गए हैं।
• poc_pocket_interreflection — py -3.11 examples/poc_pocket_interreflection.py
• poc_simcal_thin_film — py -3.11 examples/poc_simcal_thin_film.py
• simcal_checks_tour — py -3.11 examples/simcal_checks_tour.py
• simcal_tour — py -3.11 examples/simcal_tour.py
calresult को input के रूप में लेते हैं)simcal_identifiability · simcal_uncertainty · simcal_validate · simcal_discrepancy · simcal_report
fit)*Provenance: simcal.py — SIMCAL operator registry. यह per-op note tools/opdocs.py md से अपने-आप generate होता है (हाथ से edit न करें)।*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.