verification op• Data kinds: none → table (an op determined by its arguments alone — it takes no image or data input)
• Call: import fullseye as fs; fs.ledger.conv_gci(phi=None, h=None, r=None, n_cells=None, dim=None, safety_factor=1.25) -> 'dict' (to call the implementation directly, import converge; converge.conv_gci(phi=None, h=None, r=None, n_cells=None, dim=None, safety_factor=1.25) -> 'dict'; from the registry, opsconverge.get("conv_gci"))
Grid convergence index of the finest solution: Celik et al. 2008 procedure, eqs. (1)-(7).
Takes the same inputs as conv_observed_order (three solutions, finest first, and the refinement) and returns, with p from eq. (3):
phi_ext21 = (r21^p phi1 - phi2) / (r21^p - 1) (4) (and phi_ext32)
e_a21 = |(phi1 - phi2) / phi1| (5)
e_ext21 = |(phi_ext12 - phi1) / phi_ext12| (6)
GCI_fine21 = 1.25 e_a21 / (r21^p - 1) (7)
(safety_factor = 1.25 as in eq. (7)). Fractions and percentages are both returned, and report reads "phi1 +- GCI". Note what the GCI is not: it bounds the discretization error of the fine solution only — "this does not account for modeling errors" (Celik).
Refusal as in conv_observed_order, plus phi1 = 0 or phi_ext = 0 (relative errors undefined). Defaults: Celik Table 1, first column (GCI 2.2 %).
• convergent_computation family guide
• 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.
• converge_tour — py -3.11 examples/converge_tour.py
table as input)—
verification)*Provenance: converge.py — CONVERGE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.