fix: symmetric gauss connectivities for pynndescent / sparse distances

[syahra712]

LLM usage

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• Closes neighbors(method="gauss") returns a non-symmetric connectivity matrix on the sparse (pynndescent / transformer) path #4416

• Tests included or not required because:

• Release notes not necessary because:

The sparse branch of _connectivity.gauss relied on _get_indices_distances_from_sparse_matrix returning neighbours sorted by distance, with the cell itself in column 0. The pynndescent distance matrix does not meet either assumption: every row stores the cell itself as an explicit 0, holds one more neighbour than sklearn, and is ordered by column index.

_has_self_column only requires one row to start with itself. As a result:

• indices[:, 1:] drops an arbitrary neighbour instead of the cell itself.
• Kernel weights were computed over every stored entry of d_sq, but only the truncated indices were mirrored.

The result was one-directional edges (max|W - W.T| = 0.655 in the issue) and self-loops with weight 1 on the diagonal.

The sparse branch now takes, for every row, the n_neighbors - 1 closest entries that are not the cell itself. It computes the kernel on exactly those edges and mirrors the missing reverse edges, which matches what the dense knn=True branch does. The new code is vectorised and replaces the per-row Python loop and the LIL conversion.

On the issue's reproducer (9000 cells):

	before	after
pynndescent max|W - W.T|	0.655	0.0
pynndescent max diag(W)	1.0	0.0
shared edges with sklearn	—	99.4 % (rest is approximate kNN)

The sklearn path gives the same output as before; the existing gauss tests pass unchanged.

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Files with missing lines	Coverage Δ
src/scanpy/neighbors/_connectivity.py	89.74% <100.00%> (ø)

[syahra712]

The "Check title, milestone, and labels" job needs a milestone, which I can't set as an outside contributor. Could a maintainer add one, or the label you use to skip it?