MultiLCA progress, now with tests

bw2calc/lca.py

@@ -86,7 +86,7 @@ def __init__(
             List of `bw_processing.Datapackage` objects. Can be loaded via
             `bw2data.prepare_lca_inputs` or constructed manually. Should include data for all needed
             matrices.
-        remapping_dicts : dict[str : dict]
+        remapping_dicts : dict[str, dict]
             Dict of remapping dictionaries that link Brightway `Node` ids to `(database, code)`
             tuples. `remapping_dicts` can provide such remapping for any of `activity`, `product`,
             `biosphere`.
@@ -98,7 +98,7 @@ def __init__(
             Use arrays instead of vectors from the given `data_objs`
         use_distributions : bool
             Use probability distributions from the given `data_objs`
-        selective_use : dict[str : dict]
+        selective_use : dict[str, dict]
             Dictionary that gives more control on whether `use_arrays` or `use_distributions` should
             be used. Has the form `{matrix_label: {"use_arrays"|"use_distributions": bool}`.
             Standard matrix labels are `technosphere_matrix`, `biosphere_matrix`, and

bw2calc/lca_base.py

@@ -193,7 +193,7 @@ def lcia(self, demand: Optional[dict] = None) -> None:
         Doesn't return anything, but creates ``self.characterized_inventory``.
 
         """
-        assert hasattr(self, "inventory"), "Must do lci first"
+        assert hasattr(self, "inventory") or (self, "inventories"), "Must do lci first"
         if not self.dicts.biosphere:
             raise EmptyBiosphere
 

tests/multi_lca.py

@@ -0,0 +1,99 @@
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+from bw2calc import MultiLCA
+from bw2calc.utils import get_datapackage
+
+# Technosphere
+#           α: 1    β: 2    γ: 3    δ: 4    ε: 5    ζ: 6
+#   L: 100  -0.2    -0.5    1       -0.1            -0.1
+#   M: 101  1                       -0.2    -0.1
+#   N: 102  -0.5    1                               -0.2
+#   O: 103                          -0.4    1
+#   P: 104                          1
+#   Q: 105                                          1
+
+# Biosphere
+#           α: 1    β: 2    γ: 3    δ: 4    ε: 5    ζ: 6
+#   200     2       4       8       1       2       1
+#   201     1       2       3
+#   202                                     1       2
+#   203                                             3
+
+fixture_dir = Path(__file__).resolve().parent / "fixtures"
+
+
+@pytest.fixture
+def dps():
+    return [
+        get_datapackage(fixture_dir / "multi_lca_simple_1.zip"),
+        get_datapackage(fixture_dir / "multi_lca_simple_2.zip"),
+        get_datapackage(fixture_dir / "multi_lca_simple_3.zip"),
+        get_datapackage(fixture_dir / "multi_lca_simple_4.zip"),
+        get_datapackage(fixture_dir / "multi_lca_simple_5.zip"),
+    ]
+
+
+@pytest.fixture
+def config():
+    return {
+        "impact_categories": [
+            ("first", "category"),
+            ("second", "category"),
+        ]
+    }
+
+
+@pytest.fixture
+def func_units():
+    return {
+        "γ": {100: 1},
+        "ε": {103: 2},
+        "ζ": {105: 3},
+    }
+
+
+def test_inventory_matrix_construction(dps, config, func_units):
+    mlca = MultiLCA(demands=func_units, method_config=config, data_objs=dps)
+    mlca.lci()
+    mlca.lcia()
+
+    print(mlca.scores)
+    print(mlca.technosphere_matrix.todense())
+    print(mlca.biosphere_matrix.todense())
+
+    for name, mat in mlca.characterization_matrices.items():
+        print(name)
+        print(mat.todense())
+
+    tm = [
+        (100, 1, -0.2),
+        (100, 2, -0.5),
+        (100, 3, 1),
+        (100, 4, -0.1),
+        (100, 6, -0.1),
+    ]
+    for a, b, c in tm:
+        assert mlca.technosphere_matrix[mlca.dicts.product[a], mlca.dicts.activity[b]] == c
+
+    assert (
+        mlca.technosphere_matrix.sum()
+        == np.array([-0.2, -0.5, 1, -0.1, -0.1, 1, -0.2, -0.1, -0.2, -0.5, 1, -0.4, 1, 1, 1]).sum()
+    )
+
+    bm = [
+        (200, 1, 2),
+        (200, 2, 4),
+        (200, 3, 8),
+        (200, 4, 1),
+        (200, 5, 2),
+        (200, 6, 1),
+    ]
+    for a, b, c in bm:
+        assert mlca.biosphere_matrix[mlca.dicts.biosphere[a], mlca.dicts.activity[b]] == c
+
+    assert mlca.biosphere_matrix.sum() == np.array([2, 4, 8, 1, 2, 1, 1, 2, 3, 1, 2, 3]).sum()
+
+    assert 0