Fix sparse diag by upgrading SciPy and Numpy (#650)

* updated scipy requirement

* added test

* dropped python 3.9 support

.github/workflows/test.yml

@@ -13,7 +13,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
     steps:
     - uses: actions/checkout@v4
 
@@ -112,7 +112,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu, macos, windows]
-        python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
     steps:
     - uses: actions/checkout@v4
 

pyproject.toml

@@ -7,7 +7,7 @@ name = "xgi"
 dynamic = ["version"]
 description = "XGI is a Python package for higher-order networks."
 readme = "README.md"
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 license = {file = "LICENSE.md"}
 authors = [
     {name = "XGI Developers", email = "nicholas.landry@virginia.edu"}
@@ -30,7 +30,6 @@ classifiers = [
     "License :: OSI Approved :: BSD License",
     "Operating System :: OS Independent",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
@@ -43,8 +42,8 @@ classifiers = [
     "Topic :: Scientific/Engineering :: Physics",
 ]
 dependencies = [
-    "numpy>=1.20",
-    "scipy>=1.8",
+    "numpy>=1.23.5",
+    "scipy>=1.15",
     "pandas>=1.3",
     "networkx>=2.7",
     "requests>=2.0",

requirements/default.txt

@@ -1,7 +1,7 @@
 # Generated via tools/generate_requirements.py and pre-commit hook.
 # Do not edit this file; modify pyproject.toml instead.
-numpy>=1.20
-scipy>=1.8
+numpy>=1.23.5
+scipy>=1.15
 pandas>=1.3
 networkx>=2.7
 requests>=2.0

tests/linalg/test_matrix.py

@@ -255,6 +255,23 @@ def test_adjacency_matrix(edgelist1, edgelist4):
     assert np.all(A7 == A7_sp.todense())
 
 
+def test_fix_649(): # make sure diagonal is fully zero when sparse
+
+    H = xgi.load_xgi_data(dataset="email-enron")
+    H.cleanup(isolates=True, singletons=False, connected=True, relabel=False, multiedges=False)
+
+    weighted = True
+    order = 1
+
+    adj = xgi.adjacency_matrix(H, order=order, sparse=False, weighted=weighted, index=False)
+
+    adj_sparse = xgi.adjacency_matrix(H, order=order, sparse=True, weighted=weighted, index=False)
+    adj_sparse = adj_sparse.todense()
+
+    assert np.all(np.diag(adj_sparse)==0)
+
+
+
 def test_laplacian(edgelist2, edgelist6):
     el1 = edgelist6
     H1 = xgi.Hypergraph(el1)

tools/generate_requirements.py

@@ -1,6 +1,8 @@
 #!/usr/bin/env python
 """Generate requirements/*.txt files from pyproject.toml.
 
+Run from repo root folder.
+
 Copied from NetworkX: https://github.com/networkx/networkx/blob/main/tools/generate_requirements.py
 """