seg_wiring_variation — EMPROOF wiring op

• 資料種類:labels2d × labels2d × table → table

• 呼叫: import fullseye as fs; fs.ledger.seg_wiring_variation(a, b, synapses, spacing=None, background=0)(要直接呼叫實作,import segcompare; segcompare.seg_wiring_variation(a, b, synapses, spacing=None, background=0);從台帳取用則 opsemproof.get("seg_wiring_variation"))

用法

> 該運算子的說明尚無譯文,以下照原文給出。

How a candidate segmentation `b corrupts the wiring diagram of truth a`, in bits.

Two levels, both VOI split / merge (`synapses as in :func:seg_synapse_partners`):

• synapse ends (`split / merge, voi`): the segmentation VOI measured only

at the `2n synapse ends instead of every pixel. split` = two ends on one true

neuron now on different objects (the neuron was cut between its synapses); `merge`

= ends on different true neurons now on one object (they were glued). Cutting a

neuron whose `s ends divide s1 / s2 raises split` by exactly

`(s / 2n)·H2(s1 / s)`. Pixels far from any synapse cost nothing here.

• connections (`connection_split / connection_merge`): synapses grouped by

their (pre object, post object) pair — one true connection scattered over several,

or different true connections fused into one (synapses attributed to the wrong

partner). A connection with a single synapse cannot scatter, so this level is blind

to cuts that only rename a one-synapse connection; the ends level is not.

Provenance: the ends level is the "synapse VI" of Plaza, Scheffer & Chklovskii 2014

(*Focused proofreading*, arXiv:1409.1199; VI over the voxels carrying synaptic

annotations, implemented in NeuroProof, C++). The connection level, the lost-synapse

convention and the per-edit closed forms (`(s/2n)·H2(s1/s)` for a cut) are this module's. Synapses with an end on

`background` in the truth are dropped; in the candidate, each such synapse is lost

and counted in `n_lost` as its own singleton at both levels (not one shared

"background" object, which would fake a huge merge). Also returns `split_connections` (true connections

spread over 2+ candidate ones), `merged_connections` (candidate connections holding

synapses of 2+ true ones), `edges_a / edges_b and n` (synapses scored).

Raises `ValueError: as :func:seg_synapse_partners; shapes of a and b`

differ; no synapse left after dropping background in the truth.

詳細使用指南

• emproof 族使用指南

參考(範例資料・文獻)

• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。

• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。

• 演算法的正典(作者・年份)與用途見上面的族使用指南。

可執行的範例(實際呼叫該運算子並已驗證的樣例)

• poc_em_wiring_errors — py -3.11 examples/poc_em_wiring_errors.py

型別可銜接的下一個運算子(可接受 table 作為輸入)

seg_synapse_partners · seg_synapse_nri · seg_wiring_exposure

同類別(wiring)

seg_synapse_partners · seg_synapse_nri · seg_wiring_exposure


*Provenance: segcompare.py — EMPROOF 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.