test_mpts_metrics and dummy_mpts_metrics

tests/test_matbench_genmetrics.py

@@ -4,6 +4,7 @@
 import numpy as np
 import numpy.typing as npt
 import pytest
+from mp_time_split.utils.gen import DummyGenerator
 from numpy.testing import assert_array_equal
 from pymatgen.core.lattice import Lattice
 from pymatgen.core.structure import Structure
@@ -12,7 +13,6 @@
 
 # from pytest_cases import fixture, parametrize, parametrize_with_cases
 
-
 coords = [[0, 0, 0], [0.75, 0.5, 0.75]]
 lattice = Lattice.from_parameters(a=3.84, b=3.84, c=3.84, alpha=120, beta=90, gamma=60)
 dummy_structures = [
@@ -38,7 +38,13 @@ def dummy_gen_metrics():
 # @fixture
 def dummy_mpts_metrics():
     """Get MPTSMetrics() with dummy MPTS as train/test, dummy_structures as pred/gen."""
-    return MPTSMetrics(dummy_structures, dummy_structures, dummy=True)
+    mptm = MPTSMetrics(dummy=True)
+
+    fold = 0
+    mptm.get_train_and_val_data(fold)
+    mptm.record(fold, dummy_structures)
+
+    return mptm
 
 
 dummy_matcher_expected = {
@@ -102,6 +108,21 @@ def test_numerical_attributes(fixture: object, checkitem: Tuple[str, npt.ArrayLi
     )
 
 
+def test_mpts_metrics():
+    mptm = MPTSMetrics(dummy=True)
+    for fold in mptm.folds:
+        train_val_inputs = mptm.get_train_and_val_data(fold)
+
+        np.random.seed(10)
+        dg = DummyGenerator()
+        dg.fit(train_val_inputs)
+        gen_structures = dg.gen(n=100)
+
+        mptm.record(fold, gen_structures)
+
+    print(mptm.recorded_metrics)
+
+
 # %% Code Graveyard
 # def flatten_params(
 #     fixtures: List[Callable], expecteds: List[dict]