BUG: IntervalIndex.unique() only contains the first interval if all interval borders are negative

pandas/core/arrays/interval.py

@@ -1990,12 +1990,20 @@ def _from_combined(self, combined: np.ndarray) -> IntervalArray:
         return self._shallow_copy(left=new_left, right=new_right)
 
     def unique(self) -> IntervalArray:
-        # No overload variant of "__getitem__" of "ExtensionArray" matches argument
-        # type "Tuple[slice, int]"
-        nc = unique(
-            self._combined.view("complex128")[:, 0]  # type: ignore[call-overload]
-        )
-        nc = nc[:, None]
+        # Using .view("complex128") with negatives causes issues. # GH#61917
+        combined = self._combined
+        combined = np.ascontiguousarray(combined)
+        if combined.dtype == np.object_:
+            nc = unique(
+                self._combined.view("complex128")[:, 0]  # type: ignore[call-overload]
+            )
+            nc = nc[:, None]
+        else:
+            structured = combined.view(
+                [("left", combined.dtype), ("right", combined.dtype)]
+            )[:, 0]
+            unique_structured = unique(structured)
+            nc = unique_structured.view(combined.dtype)
         return self._from_combined(nc)
 
 

pandas/tests/arrays/interval/test_interval.py

@@ -111,6 +111,26 @@ def test_shift_datetime(self):
         with pytest.raises(TypeError, match=msg):
             a.shift(1, fill_value=np.timedelta64("NaT", "ns"))
 
+    def test_unique_with_negatives(self):
+        # GH#61917
+        idx_pos = IntervalIndex.from_tuples(
+            [(3, 4), (3, 4), (2, 3), (2, 3), (1, 2), (1, 2)]
+        )
+        result = idx_pos.unique()
+        assert result.shape == (3,), f"Expected shape (3,), got {result.shape}"
+
+        idx_neg = IntervalIndex.from_tuples(
+            [(-4, -3), (-4, -3), (-3, -2), (-3, -2), (-2, -1), (-2, -1)]
+        )
+        result = idx_neg.unique()
+        assert result.shape == (3,), f"Expected shape (3,), got {result.shape}"
+
+        idx_mix = IntervalIndex.from_tuples(
+            [(1, 2), (0, 1), (-1, 0), (-2, -1), (-3, -2), (-3, -2)]
+        )
+        result = idx_mix.unique()
+        assert result.shape == (5,), f"Expected shape (5,), got {result.shape}"
+
 
 class TestSetitem:
     def test_set_na(self, left_right_dtypes):