Update dependencies and cleanup code

python/featomic/examples/keys-selection.py

@@ -57,7 +57,7 @@
 
 selection = Labels(
     names=["center_type", "neighbor_1_type", "neighbor_2_type"],
-    values=np.array([[1, 1, 1], [4, 4, 4]], dtype=np.int32),
+    values=np.array([[1, 1, 1], [4, 4, 4]]),
 )
 selected_descriptor = calculator.compute(frames, selected_keys=selection)
 
@@ -104,7 +104,7 @@
 
 keys = Labels(
     names=["center_type", "neighbor_1_type", "neighbor_2_type"],
-    values=np.array([[1, 1, 1], [8, 8, 8]], dtype=np.int32),
+    values=np.array([[1, 1, 1], [8, 8, 8]]),
 )
 
 selected_properties = TensorMap(keys, blocks)
@@ -116,7 +116,7 @@
 
 selected_keys = Labels(
     names=["center_type", "neighbor_1_type", "neighbor_2_type"],
-    values=np.array([[1, 1, 1]], dtype=np.int32),
+    values=np.array([[1, 1, 1]]),
 )
 
 descriptor = calculator.compute(

python/featomic/pyproject.toml

@@ -25,8 +25,8 @@ classifiers = [
 ]
 
 dependencies = [
-    "metatensor-core >=0.1.15,<0.2.0",
-    "metatensor-operations >=0.3.0,<0.4.0",
+    "metatensor-core >=0.1.15,<0.2",
+    "metatensor-operations >=0.4.0,<0.5",
     "wigners",
 ]
 

python/featomic/tests/calculators/hypers.py

@@ -1,6 +1,6 @@
 from typing import List
 
-import metatensor
+import metatensor as mts
 import pytest
 
 import featomic
@@ -128,7 +128,7 @@ def test_hypers_classes():
     )
 
     system = SystemForTests()
-    metatensor.equal_raise(with_dict.compute(system), with_classes.compute(system))
+    mts.equal_raise(with_dict.compute(system), with_classes.compute(system))
 
 
 def test_hypers_custom_classes_errors():

python/featomic/tests/calculators/keys_selection.py

@@ -44,10 +44,7 @@ def test_selection_existing():
     assert descriptor.keys.values.tolist() == [[1], [8]]
 
     # Manually select the keys
-    selected_keys = Labels(
-        names=["center_type"],
-        values=np.array([[1]], dtype=np.int32),
-    )
+    selected_keys = Labels(names=["center_type"], values=np.array([[1]]))
     descriptor = calculator.compute(system, selected_keys=selected_keys)
 
     assert len(descriptor.keys) == 1
@@ -73,10 +70,7 @@ def test_selection_partial():
     )
 
     # Manually select the keys
-    selected_keys = Labels(
-        names=["center_type"],
-        values=np.array([[1]], dtype=np.int32),
-    )
+    selected_keys = Labels(names=["center_type"], values=np.array([[1]]))
     descriptor = calculator.compute(system, selected_keys=selected_keys)
 
     assert len(descriptor.keys) == 4
@@ -99,10 +93,7 @@ def test_select_key_not_in_systems():
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
     # Manually select the keys
-    selected_keys = Labels(
-        names=["center_type"],
-        values=np.array([[4]], dtype=np.int32),
-    )
+    selected_keys = Labels(names=["center_type"], values=np.array([[4]]))
     descriptor = calculator.compute(system, selected_keys=selected_keys)
 
     C_block = descriptor.block(center_type=4)
@@ -113,26 +104,14 @@ def test_predefined_selection():
     system = SystemForTests()
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
-    selected_keys = Labels(
-        names=["center_type"],
-        values=np.array([[1]], dtype=np.int32),
-    )
+    selected_keys = Labels(names=["center_type"], values=np.array([[1]]))
 
-    keys = Labels(
-        names=["center_type"],
-        values=np.array([[1], [8]], dtype=np.int32),
-    )
+    keys = Labels(names=["center_type"], values=np.array([[1], [8]]))
 
     # selection from TensorMap
     selected = [
-        Labels(
-            names=["index_delta", "x_y_z"],
-            values=np.array([[1, 0]], dtype=np.int32),
-        ),
-        Labels(
-            names=["index_delta", "x_y_z"],
-            values=np.array([[0, 1]], dtype=np.int32),
-        ),
+        Labels(names=["index_delta", "x_y_z"], values=np.array([[1, 0]])),
+        Labels(names=["index_delta", "x_y_z"], values=np.array([[0, 1]])),
     ]
     selected_properties = _tensor_map_selection("properties", keys, selected)
 
@@ -153,10 +132,7 @@ def test_name_errors():
     system = SystemForTests()
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
-    selected_keys = Labels(
-        names=["bad_name"],
-        values=np.array([0, 3, 1], dtype=np.int32).reshape(3, 1),
-    )
+    selected_keys = Labels(names=["bad_name"], values=np.array([[0], [3], [1]]))
 
     message = (
         "invalid parameter: 'bad_name' in keys selection is not "
@@ -182,25 +158,13 @@ def test_key_errors():
     # in the case where both selected_properties/selected_samples and
     # selected_keys are given, the selected keys must be in the keys of the
     # predefined tensor_map
-    selected_keys = Labels(
-        names=["center_type"],
-        values=np.array([[4]], dtype=np.int32),
-    )
+    selected_keys = Labels(names=["center_type"], values=np.array([[4]]))
 
-    keys = Labels(
-        names=["center_type"],
-        values=np.array([[1], [8]], dtype=np.int32),
-    )
+    keys = Labels(names=["center_type"], values=np.array([[1], [8]]))
 
     selected = [
-        Labels(
-            names=["index_delta", "x_y_z"],
-            values=np.array([[1, 0]], dtype=np.int32),
-        ),
-        Labels(
-            names=["index_delta", "x_y_z"],
-            values=np.array([[0, 1]], dtype=np.int32),
-        ),
+        Labels(names=["index_delta", "x_y_z"], values=np.array([[1, 0]])),
+        Labels(names=["index_delta", "x_y_z"], values=np.array([[0, 1]])),
     ]
     selected_properties = _tensor_map_selection("properties", keys, selected)
 

python/featomic/tests/calculators/properties_selection.py

@@ -41,7 +41,7 @@ def test_selection():
     # Manually constructing the selected properties
     selected_properties = Labels(
         names=["index_delta", "x_y_z"],
-        values=np.array([[1, 0]], dtype=np.int32),
+        values=np.array([[1, 0]]),
     )
     descriptor = calculator.compute(
         system, use_native_system=False, selected_properties=selected_properties
@@ -65,7 +65,7 @@ def test_subset_variables():
     # Only a subset of the variables defined
     selected_properties = Labels(
         names=["index_delta"],
-        values=np.array([[1]], dtype=np.int32),
+        values=np.array([[1]]),
     )
     descriptor = calculator.compute(
         system, use_native_system=False, selected_properties=selected_properties
@@ -88,8 +88,7 @@ def test_empty_selection():
 
     # empty selected features
     selected_properties = Labels(
-        names=["index_delta", "x_y_z"],
-        values=np.array([], dtype=np.int32).reshape(0, 2),
+        names=["index_delta", "x_y_z"], values=np.empty((0, 2), dtype=np.int32)
     )
     descriptor = calculator.compute(
         system, use_native_system=False, selected_properties=selected_properties
@@ -106,21 +105,12 @@ def test_predefined_selection():
     system = SystemForTests()
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
-    keys = Labels(
-        names=["center_type"],
-        values=np.array([[1], [8]], dtype=np.int32),
-    )
+    keys = Labels(names=["center_type"], values=np.array([[1], [8]]))
 
     # selection from TensorMap
     selected = [
-        Labels(
-            names=["index_delta", "x_y_z"],
-            values=np.array([[1, 0]], dtype=np.int32),
-        ),
-        Labels(
-            names=["index_delta", "x_y_z"],
-            values=np.array([[0, 1]], dtype=np.int32),
-        ),
+        Labels(names=["index_delta", "x_y_z"], values=np.array([[1, 0]])),
+        Labels(names=["index_delta", "x_y_z"], values=np.array([[0, 1]])),
     ]
     selected_properties = _tensor_map_selection("properties", keys, selected)
 
@@ -143,10 +133,7 @@ def test_errors():
     system = SystemForTests()
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
-    selected_properties = Labels(
-        names=["bad_name"],
-        values=np.array([0, 3, 1], dtype=np.int32).reshape(3, 1),
-    )
+    selected_properties = Labels(names=["bad_name"], values=np.array([[0], [3], [1]]))
 
     message = (
         "invalid parameter: 'bad_name' in properties selection is not "

python/featomic/tests/calculators/sample_selection.py

@@ -40,8 +40,7 @@ def test_selection():
 
     # Manually constructing the selected samples
     selected_samples = Labels(
-        names=["system", "atom"],
-        values=np.array([(0, 0), (0, 3), (0, 1)], dtype=np.int32),
+        names=["system", "atom"], values=np.array([[0, 0], [0, 3], [0, 1]])
     )
     descriptor = calculator.compute(
         system, use_native_system=False, selected_samples=selected_samples
@@ -62,10 +61,7 @@ def test_subset_variables():
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
     # Only a subset of the variables defined
-    selected_samples = Labels(
-        names=["atom"],
-        values=np.array([0, 3, 1], dtype=np.int32).reshape(3, 1),
-    )
+    selected_samples = Labels(names=["atom"], values=np.array([0, 3, 1]).reshape(3, 1))
     descriptor = calculator.compute(
         system, use_native_system=False, selected_samples=selected_samples
     )
@@ -85,10 +81,7 @@ def test_empty_selection():
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
     # empty selected samples
-    selected_samples = Labels(
-        names=["atom"],
-        values=np.empty((0, 1), dtype=np.int32),
-    )
+    selected_samples = Labels(names=["atom"], values=np.empty((0, 1), dtype=np.int32))
     descriptor = calculator.compute(
         system, use_native_system=False, selected_samples=selected_samples
     )
@@ -104,21 +97,12 @@ def test_predefined_selection():
     system = SystemForTests()
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
-    keys = Labels(
-        names=["center_type"],
-        values=np.array([[1], [8]], dtype=np.int32),
-    )
+    keys = Labels(names=["center_type"], values=np.array([[1], [8]]))
 
     # selection from TensorMap
     selected = [
-        Labels(
-            names=["system", "atom"],
-            values=np.array([[0, 1]], dtype=np.int32),
-        ),
-        Labels(
-            names=["system", "atom"],
-            values=np.array([[0, 3]], dtype=np.int32),
-        ),
+        Labels(names=["system", "atom"], values=np.array([[0, 1]])),
+        Labels(names=["system", "atom"], values=np.array([[0, 3]])),
     ]
     selected_samples = _tensor_map_selection("samples", keys, selected)
 
@@ -139,10 +123,7 @@ def test_errors():
     system = SystemForTests()
     calculator = DummyCalculator(cutoff=3.2, delta=2, name="")
 
-    samples = Labels(
-        names=["bad_name"],
-        values=np.array([0, 3, 1], dtype=np.int32).reshape(3, 1),
-    )
+    samples = Labels(names=["bad_name"], values=np.array([0, 3, 1]).reshape(3, 1))
 
     message = (
         "invalid parameter: 'bad_name' in samples selection is not part "