Fix KDTree scalar return when max_num_neighbours=1

[Aadrit555]

Changes made -

I fixed a crash in connect_nodes_across_graphs when called with method="nearest_neighbours" and max_num_neighbours=1.

Root cause: scipy.spatial.KDTree.query() returns different types depending on the value of k:

• k = 1 → scalar (numpy.int64)
• k > 1 → numpy.ndarray

The function _find_neighbour_node_idxs_in_source_mesh returned the raw query result, which the caller then iterated over. When k=1, iterating over a scalar raises:

TypeError: 'numpy.int64' object is not iterable

Fix: Wrap the return value with np.atleast_1d() so the result is always iterable, regardless of k.

# BEFORE
def _find_neighbour_node_idxs_in_source_mesh(xy_target):
    neigh_idxs = kdt_s.query(xy_target, max_num_neighbours)[1]
    return neigh_idxs

# AFTER
def _find_neighbour_node_idxs_in_source_mesh(xy_target):
    neigh_idxs = kdt_s.query(xy_target, max_num_neighbours)[1]
    # KDTree.query returns a scalar when k=1 and a 1-D array when k>1.
    # np.atleast_1d normalises both cases so the caller can always iterate.
    return np.atleast_1d(neigh_idxs)

No dependencies are required for this change.

Issue Link

Closes #83

Type of change

• 🐛 Bug fix (non-breaking change that fixes an issue)
• ✨ New feature (non-breaking change that adds functionality)
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  • fixes: connect_nodes_across_graphs crash when max_num_neighbours=1 due to KDTree.query returning a scalar for k=1

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[leifdenby]

Looking good. Please add a changelog entry :)

[Aadrit555]

@leifdenby did it can you check please, thanks.

[leifdenby]

Can you fix the linting errors please? Just run pre-commit locally before re-committing

[Aadrit555]

@leifdenby Sorry for the messy commits — being fairly new to open source I got a bit confused while trying to fix the linting errors. I've got all pre-commit checks passing locally now. I tried to squash the commits via rebase but would need your help to do that since I don't have the required permissions. Happy to clean it up however works best for you!