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Fix scipy FutureWarning in laplacian_matrix #685

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Merged
kaiser-dan merged 2 commits into from
Mar 2, 2026
+8 −6
Merged

Fix scipy FutureWarning in laplacian_matrix #685

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55d9615
fix: ensure float dtypes for scipy diags_array calls in laplacian_matrix
leotrs Feb 27, 2026
d8fbf76
fix: update doctest for pandas dtype='str' change
leotrs Feb 27, 2026
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9 changes: 5 additions & 4 deletions xgi/linalg/laplacian_matrix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -101,10 +101,11 @@ def laplacian(H, order=1, sparse=False, rescale_per_node=False, index=False):
L = csr_array((0, 0)) if sparse else np.empty((0, 0))
return (L, {}) if index else L

D = np.asarray(degree_matrix(H, order=order), dtype=float)
if sparse:
K = diags_array(degree_matrix(H, order=order), format="csr")
K = diags_array(D, format="csr")
else:
K = np.diag(degree_matrix(H, order=order))
K = np.diag(D)

L = order * K - A # ravel needed to convert sparse matrix

Expand Down Expand Up @@ -233,9 +234,9 @@ def normalized_hypergraph_laplacian(H, weighted=False, sparse=True, index=False)
De = np.sum(incidence, axis=0)

if weighted:
weights = [H.edges[edge_idx].get("weight", 1) for edge_idx in H.edges]
weights = [float(H.edges[edge_idx].get("weight", 1)) for edge_idx in H.edges]
else:
weights = [1] * H.num_edges
weights = [1.0] * H.num_edges

if sparse:
Dv_invsqrt = diags_array(np.power(Dv, -0.5), format="csr")
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5 changes: 3 additions & 2 deletions xgi/stats/__init__.py
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Expand Up @@ -113,8 +113,9 @@ def name(self):
('degree', 'degree(order=3)')
>>> H.nodes.multi([da, d3]).asdict(transpose=True).keys()
dict_keys(['degree', 'degree(order=3)'])
>>> H.nodes.multi([da, d3]).aspandas().columns
Index(['degree', 'degree(order=3)'], dtype='object')
>>> cols = H.nodes.multi([da, d3]).aspandas().columns
>>> list(cols)
['degree', 'degree(order=3)']
"""
name = f"{self.func.__name__}"
Expand Down