First version of array casting update

src/ConfigSpace/configuration.py

@@ -163,10 +163,15 @@ def check_valid_configuration(self) -> None:
             allow_inactive_with_values=self.allow_inactive_with_values,
         )
 
-    def get_array(self) -> Array[f64]:
+    def __array__(self, dtype: type[DType]=None, copy: bool=False) -> Array[f64]:
         """The internal vector representation of this config.
 
         All continuous values are scaled between zero and one.
+        Conditional hyperparameters that are not active are represented with nan.
+
+        Args:
+            dtype: Ignored, required by numpy (dtype enforced by configuration)
+            copy: Ignored, required by numpy (is always a copy)
 
         Returns:
             The vector representation of the configuration
@@ -289,4 +294,17 @@ def get_dictionary(self) -> dict[str, Any]:
         """
         return dict(self)
 
+    @deprecated(
+        "Please use `np.array(config)` instead of `config.get_array()`.",
+    )
+    def get_array(self) -> Array[f64]:
+        """The internal vector representation of this config.
+
+        All continuous values are scaled between zero and one.
+
+        Returns:
+            The vector representation of the configuration
+        """
+        return self._vector
+
     # ---------------------------------------------------

test/test_configuration_space.py

@@ -877,6 +877,18 @@ def test_sample_configuration():
             for j in range(100):
                 assert samples[-1][j] == samples[-2][j]
 
+    # Test that sample configuration to np.array works as expected
+    cs.seed(42)
+    for _ in range(5):
+        sample = cs.sample_configuration(2)
+        for configuration in sample:
+            array = np.array(configuration)
+            expected_array = configuration._vector
+            assert len(array) == len(expected_array)
+            for value, expected in zip(array, expected_array):
+                # Values are either equal in both arrays or both are np.nan
+                assert value == expected or (np.isnan(value) and np.isnan(expected))
+
 
 def test_sample_configuration_with_or_conjunction():
     cs = ConfigurationSpace(seed=1)