FIX beam_width upper bound

fastcan/_fastcan.py

@@ -216,17 +216,21 @@ def fit(self, X, y):
                 "`indices_include` and `indices_exclude` should not have intersection."
             )
 
-        if (
-            n_features - self.indices_exclude_.size
-            < self.n_features_to_select + self.beam_width - 1
-        ):
+        if n_features - self.indices_exclude_.size < self.n_features_to_select:
             raise ValueError(
-                "n_features - n_exclusions should >= "
-                "n_features_to_select + beam_width - 1."
+                "n_features_to_select should <= n_features - n_exclusions."
             )
         if self.n_features_to_select < self.indices_include_.size:
             raise ValueError("n_features_to_select should >= n_inclusions.")
 
+        if (
+            self.beam_width
+            > n_features - self.indices_exclude_.size - self.indices_include_.size
+        ):
+            raise ValueError(
+                "beam_width should <= n_features - n_exclusions - n_inclusions."
+            )
+
         if self.eta:
             xy_hstack = np.hstack((X, y))
             xy_centered = xy_hstack - xy_hstack.mean(0)

tests/test_beam.py

@@ -33,6 +33,15 @@ def test_beam_error():
     X_origin = rng.normal(size=(n_samples, n_features))
     y = rng.normal(size=n_samples)
 
+    X = X_origin.copy()
+    # Should pass without error
+    FastCan(n_features_to_select=1, beam_width=n_features).fit(X, y)
+    # Should raise an error
+    with pytest.raises(ValueError, match=r"beam_width should <= .*"):
+        FastCan(n_features_to_select=1, indices_include=[0], beam_width=n_features).fit(
+            X, y
+        )
+
     X = X_origin.copy()
     X[:, [0, 1, 2]] = 0  # Zero feature
     with pytest.raises(ValueError, match=r"Beam Search: Not enough valid candidates.*"):

tests/test_fastcan.py

@@ -237,7 +237,7 @@ def test_raise_errors():
     with pytest.raises(ValueError, match=r"`indices_include` and `indices_exclu.*"):
         selector_include_exclude_intersect.fit(X, y)
 
-    with pytest.raises(ValueError, match=r"n_features - n_exclusions should.*"):
+    with pytest.raises(ValueError, match=r"n_features_to_select should <=.*"):
         selector_n_candidates.fit(X, y)
 
     with pytest.raises(ValueError, match=r"n_features_to_select should.*"):