layout 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.sinogram_design(n_angles=180, n_detectors=None, size=256, detector_pitch_mm=1.0, span_deg=180.0) (to call the implementation directly, import tomography; tomography.sinogram_design(n_angles=180, n_detectors=None, size=256, detector_pitch_mm=1.0, span_deg=180.0); from the registry, opstomography.get("sinogram_design"))
What a scan geometry can and cannot resolve — before anything is built.
The axial counterpart of visiondesign.imaging_budget and of interferometry.csi_design: no data goes in, only the geometry, and what comes out are the limits that the geometry has already decided.
Returns a dict with, among others:
• resolvable_feature_mm — 2 * pitch: two detector samples per cycle is the Nyquist floor, and no reconstruction algorithm recovers a detail finer than the detector saw.
• views_for_full_sampling — ceil(pi/2 * n_detectors), the classical matching of angular to radial sampling (VIEWS_PER_DETECTOR).
• undersampling_factor — that number over n_angles. 1.0 or below is a fully sampled scan. Above it you are doing sparse-view CT on purpose and the reconstruction algorithm has to make up the difference; the measured cost is in this module's docstring and in the test suite's break table.
• streak_free_radius_px — 1 / d(theta) with d(theta) in radians: the radius, in pixels, at which the *azimuthal* sample spacing between neighbouring views (r * d(theta)) grows past one sample. Outside it, filtered back-projection lays down visible streaks. For 180 views over 180 degrees this is 57.3 px, i.e. a 256-px phantom is already streaking at its corners. It does not depend on the detector pitch: the radius is quoted in the same unit the sample spacing is, so the pitch cancels (pitch / d(theta) is the same radius in millimetres, which is what an earlier version returned under the pixel label — 28.6 "px" at 0.5 mm, 114.6 at 2 mm, for a geometry whose streak radius had not changed).
• sinogram_bytes / elements — what you are about to allocate.
• verdict — "fully sampled" / "sparse view".
:param n_angles: planned number of views. :param n_detectors: planned detector bins; None -> enough to cover the
diagonal of a *size* x *size* image.
:param size: reconstruction grid side in pixels. :param detector_pitch_mm: physical detector bin spacing. :param span_deg: angular range of the scan. :returns: dict of floats / ints / str. :raises ValueError: on non-int counts, non-positive pitch or span.
• 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.
• ct_reconstruction — py -3.11 examples/ct_reconstruction.py
• tomography_reconstruct — py -3.11 examples/tomography_reconstruct.py
table as input)—
layout)*Provenance: tomography.py — TOMOGRAPHY 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.