Remove ase dependency and update ROY dataset (#232)

examples/selection/GCH-ROY.py

@@ -27,11 +27,9 @@
 
 roy_data = load_roy_dataset()
 
-structures = roy_data["structures"]
-
-density = np.array([s.info["density"] for s in structures])
-energy = np.array([s.info["energy"] for s in structures])
-structype = np.array([s.info["type"] for s in structures])
+density = roy_data["densities"]
+energy = roy_data["energies"]
+structype = roy_data["structure_types"]
 iknown = np.where(structype == "known")[0]
 iothers = np.where(structype != "known")[0]
 
@@ -247,3 +245,5 @@
     },
 )
 """
+
+# %%

pyproject.toml

@@ -44,7 +44,6 @@ dynamic = ["version"]
 
 [project.optional-dependencies]
 examples = [
-    "ase",
     "matplotlib",
     "pandas",
     "tqdm",

src/skmatter/datasets/_base.py

@@ -119,32 +119,27 @@ def load_who_dataset():
 
 
 def load_roy_dataset():
-    """Load and returns the ROY dataset, which contains structures,
-    energies and SOAP-derived descriptors for 264 polymorphs of ROY, from [Beran et Al,
-    Chemical Science (2022)](https://doi.org/10.1039/D1SC06074K)
+    """Load and returns the ROY dataset, which contains densities,
+    energies and SOAP-derived descriptors for 264 structures of polymorphs of ROY,
+    from [Beran et Al, Chemical Science (2022)](https://doi.org/10.1039/D1SC06074K)
+    Each structure is labeled as "Known" or "Unknown".
 
     Returns
     -------
     roy_dataset : sklearn.utils.Bunch
       Dictionary-like object, with the following attributes:
-          structures : `ase.Atoms` -- the roy structures as ASE objects
-          features: `np.array` -- SOAP-derived descriptors for the structures
-          energies: `np.array` -- energies of the structures
+          densities : `np.array` -- the densities of the structures
+          structure_types : `np.array` -- the type of the structures
+          features : `np.array` -- SOAP-derived descriptors for the structures
+          energies : `np.array` -- energies of the structures
     """
     module_path = dirname(__file__)
-    target_structures = join(module_path, "data", "beran_roy_structures.xyz.bz2")
-
-    try:
-        from ase.io import read
-    except ImportError:
-        raise ImportError("load_roy_dataset requires the ASE package.")
-
-    import bz2
-
-    structures = read(bz2.open(target_structures, "rt"), ":", format="extxyz")
-    energies = np.array([f.info["energy"] for f in structures])
-
-    target_features = join(module_path, "data", "beran_roy_features.npz")
-    features = np.load(target_features)["feats"]
-
-    return Bunch(structures=structures, features=features, energies=energies)
+    target_properties = join(module_path, "data", "beran_roy_properties.npz")
+    properties = np.load(target_properties)
+
+    return Bunch(
+        densities=properties["densities"],
+        energies=properties["energies"],
+        structure_types=properties["structure_types"],
+        features=properties["feats"],
+    )

tests/test_datasets.py

@@ -107,45 +107,16 @@ class ROYTests(unittest.TestCase):
     def setUpClass(cls):
         cls.size = 264
         cls.shape = (264, 32)
-        try:
-            from ase.io import read  # NoQa: F401
-
-            cls.has_ase = True
-            cls.roy = load_roy_dataset()
-        except ImportError:
-            cls.has_ase = False
-
-    def test_load_dataset_without_ase(self):
-        """Check if the correct exception occurs when ase isn't present."""
-        with unittest.mock.patch.dict("sys.modules", {"ase.io": None}):
-            with self.assertRaises(ImportError) as cm:
-                _ = load_roy_dataset()
-            self.assertEqual(
-                str(cm.exception), "load_roy_dataset requires the ASE package."
-            )
+        cls.roy = load_roy_dataset()
 
     def test_dataset_content(self):
         """Check if the correct number of datapoints are present in the dataset.
 
         Also check if the size of the dataset is correct.
         """
-        if self.has_ase is True:
-            self.assertEqual(len(self.roy["structures"]), self.size)
-            self.assertEqual(self.roy["features"].shape, self.shape)
-            self.assertEqual(len(self.roy["energies"]), self.size)
-
-    def test_dataset_consistency(self):
-        """Check if the energies in the structures are the same as in the explicit
-        array.
-        """
-        if self.has_ase is True:
-            self.assertTrue(
-                np.allclose(
-                    self.roy["energies"],
-                    [f.info["energy"] for f in self.roy["structures"]],
-                    rtol=1e-6,
-                )
-            )
+        self.assertEqual(len(self.roy["structure_types"]), self.size)
+        self.assertEqual(self.roy["features"].shape, self.shape)
+        self.assertEqual(len(self.roy["energies"]), self.size)
 
 
 if __name__ == "__main__":