transform op• Data kinds: image2d → table
• Call: import fullseye as fs; fs.ledger.abel_inverse_image(image, dr: 'float' = 1.0, *, center: 'float | None' = None, method: 'str' = 'onion') -> 'dict' (to call the implementation directly, import mathtransforms; mathtransforms.abel_inverse_image(image, dr: 'float' = 1.0, *, center: 'float | None' = None, method: 'str' = 'onion') -> 'dict'; from the registry, opsmath.get("abel_inverse_image"))
Turns an image of an axisymmetric object taken from the side (vertical = direction of the symmetry axis, horizontal = distance from the axis) into a cross-section image by applying the inverse Abel transform row by row.
A photo of a flame, plasma or jet only captures the projection summed along the depth direction. Each row is split left/right at the centre column, the 2 halves are averaged (evening out left-right asymmetry), then inverse Abel is applied. center is the column of the symmetry axis (default = brightness centroid, just 1 for the whole image, not per row). Returns {"slice", "center", "asymmetry"} —— slice is f(z, r) of shape (H, R), asymmetry is the magnitude of the difference between the left and right halves (the closer to 0, the better the axial-symmetry assumption holds).
Gate: from the projection of a 3-D Gaussian blob, the Gaussian cross-section is recovered (closed form).
Every mathops op validates its input before computing (nothing slips through silently):
• complex input raises ValueError — coercing to float64 silently discards the imaginary part (numpy only emits a ComplexWarning and returns a plausible-looking wrong real number). State .real/.imag/abs() explicitly, or use complexops, which handles complex data.
• masked arrays with masked elements raise ValueError — the implicit conversion that peels off the mask and uses the raw values underneath is refused. Say explicitly whether to fill or to drop.
• NaN/Inf raises ValueError on every input (refused with the count stated — it propagates through the whole result).
• Shapes are strict: 1-D and 2-D are never implicitly promoted or broadcast (a matrix in a vector slot, or a vector in a matrix slot, raises ValueError; reshape explicitly).
• Size cap: ops that take a matrix, and the stat_histogram bins, raise ValueError beyond mathops.MAX_ELEMENTS (2^26 ≈ 67 million elements).
• 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.
• transforms_tour — py -3.11 examples/transforms_tour.py
table as input)dynsys_poincare_section · dwt_inverse · chebyshev_eval_nd
transform)abel_transform · abel_inverse · abel_revolve · hankel_transform · tf_poles_zeros · tf_freq_response · tf_impulse_response · tf_step_response
*Provenance: mathtransforms.py — MATH 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.