Merge branch 'main' into technosphere_mat_format

.github/workflows/python-test-pardiso.yml

@@ -36,7 +36,7 @@ jobs:
         py-version: ["3.9", "3.12"]
 
     steps:
-      - uses: actions/checkout@a5ac7e51b41094c92402da3b24376905380afc29 # v4
+      - uses: actions/checkout@692973e3d937129bcbf40652eb9f2f61becf3332 # v4
 
       # general Python setup
       - name: Set up Python ${{ matrix.py-version }}

.github/workflows/python-test-superlu.yml

@@ -36,7 +36,7 @@ jobs:
         py-version: ["3.12"]
 
     steps:
-      - uses: actions/checkout@a5ac7e51b41094c92402da3b24376905380afc29 # v4
+      - uses: actions/checkout@692973e3d937129bcbf40652eb9f2f61becf3332 # v4
 
       # general Python setup
       - name: Set up Python ${{ matrix.py-version }}

.github/workflows/python-test-umfpack-macos.yml

@@ -37,7 +37,7 @@ jobs:
         py-version: ["3.11"]
 
     steps:
-      - uses: actions/checkout@a5ac7e51b41094c92402da3b24376905380afc29 # v4
+      - uses: actions/checkout@692973e3d937129bcbf40652eb9f2f61becf3332 # v4
 
       # general Python setup
       - name: Set up Python ${{ matrix.py-version }}

bw2calc/multi_lca.py

@@ -349,15 +349,8 @@ def lci_calculation(self) -> None:
 
         """
         count = len(self.dicts.activity)
-
-        if PYPARDISO and isinstance(self.technosphere_matrix, csc_matrix):
-            self.technosphere_matrix.tocsr()
-        elif not PYPARDISO and isinstance(self.technosphere_matrix, csr_matrix):
-            self.technosphere_matrix.tocsc()
-
-        solutions = spsolve(
-            self.technosphere_matrix, np.vstack([arr for arr in self.demand_arrays.values()]).T
-        )
+        demand_matrix = np.vstack([arr for arr in self.demand_arrays.values()]).T
+        solutions = spsolve(self.technosphere_matrix, demand_matrix).reshape(count, -1)
         self.supply_arrays = {name: arr for name, arr in zip(self.demands, solutions.T)}
         # Turn 1-d array into diagonal matrix
         self.inventories = mu.SparseMatrixDict(

tests/multi_lca.py

@@ -128,6 +128,16 @@ def test_inventory_matrix_construction(dps, config, func_units):
     assert mlca.scores[(("first", "category"), "γ")] == 8 + 3
 
 
+def test_single_demand(dps, config):
+    single_func_unit = {"γ": {100: 1}}
+    mlca = MultiLCA(demands=single_func_unit, method_config=config, data_objs=dps)
+    mlca.lci()
+    mlca.lcia()
+
+    assert mlca.scores[(("first", "category"), "γ")] == 8 + 3
+    assert mlca.scores[(("second", "category"), "γ")] == 3 * 10
+
+
 def test_normalization(dps, func_units):
     config = {
         "impact_categories": [