selfmotion opmatrix × table → tableimport fullseye as fs; fs.ledger.fly_egomotion_from_flow(flow, lattice, axes=None, weights=None) (実装を直接呼ぶなら import flyvision; flyvision.fly_egomotion_from_flow(flow, lattice, axes=None, weights=None)、台帳から引くなら opsflyvision.get("fly_egomotion_from_flow"))Least-squares rotation of the eye from its flow field — and how badly the eye’s own shape conditions the answer.
Given the flow f_i at known viewing directions d_i, a pure rotation
w predicts f_i = -(w x d_i), which is linear in w: projecting on
the tangent basis gives f_az = -w . (d x e_az) and
f_el = -w . (d x e_el), so the estimate is one 2n x 3 least-squares
solve with no iteration and no starting guess (Franz et al.’s linear
egomotion estimate, Biol. Cybern. 2004).
The catch is not the algebra, it is the eye. A single patch of ommatidia sees a small piece of the sphere, and over a small piece the flow of a yaw and the flow of a sideways translation — or of a pitch — look nearly the same. This op therefore returns the condition number of that solve next to the answer, so that “the fit converged” and “the fit was identifiable” stay separate claims.
flow: (n, 2) azimuth/elevation components per ommatidium
(:func:fly_flow_from_directions or :func:fly_matched_filter).
lattice: the eye they were measured on.
axes: None to solve for the full 3-D rotation, or a (k, 3) array of
axes to restrict the fit to ([[0, 0, 1]] = yaw only, the well-conditioned
question a forward-looking eye can actually answer).
weights: None or (n,) non-negative per-ommatidium weights — a
confidence, e.g. the local contrast, or zeros to drop the rim.
Returns a dict::
{"omega_rad_s": (3,), "yaw_rad_s": float, "pitch_rad_s": float,
"roll_rad_s": float, "residual_rms": float, "flow_rms": float,
"explained": float, "condition": float, "n_ommatidia": int}
with yaw about +z (left positive), pitch about +y, roll about +x, and
explained = 1 - residual_rms/flow_rms (1.0 = the flow is exactly a
rotation, 0.0 = the fit explains none of it).
Ground truth: handed a :func:fly_matched_filter template scaled by a known
rate, it returns that rate to machine precision and explained = 1; handed
a pure translation field it returns a small rate with a low explained; and
the condition number of a narrow forward eye is large (the tests measure it)
while the yaw-only fit is near 1.
Raises ValueError: a flow that is not (n, 2) for this lattice,
non-finite entries, a malformed axes / weights, all-zero weights, and a
lattice with fewer ommatidia than the fit has unknowns.
py -3.11 examples/poc_fly_optomotor_steering.pytable を入力に取れる)fly_t4t5_field · fly_flow_from_directions · fly_matched_filter · fly_eye_merge · fly_hex_resample · fly_hs_readout
selfmotion)fly_matched_filter · fly_eye_merge
Provenance: flyvision.py — FLYVISION 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)。
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.