Fix/slow monotonic method

docs/release-notes.md

@@ -2,6 +2,9 @@
 
 ## 0.2.7
 
+### Bug Fixes
+- Fix a regression introduced in 0.2.6 where `is_monotonic` was significantly degrading `.sel` performance.
+
 ### Documentation
 - Achieved **100% docstring coverage** (excluding `__magic__` and private `_methods`) (@atrabattoni).
 - Improved *User Guide* index (@atrabattoni).

tests/coordinates/test_dense.py

@@ -157,3 +157,14 @@ def test_from_block(self):
         coord = DenseCoordinate.from_block(0, 5, 1, dim="x")
         expected = DenseCoordinate([0, 1, 2, 3, 4], dim="x")
         assert coord.equals(expected)
+
+    def test_is_monotonic_increasing(self):
+        assert DenseCoordinate([1, 2, 3]).is_monotonic_increasing()
+        assert not DenseCoordinate([1, 3, 2]).is_monotonic_increasing()
+        t0 = np.datetime64("2000-01-01T00:00:00")
+        times = np.array([t0, t0 + np.timedelta64(1, "s"), t0 + np.timedelta64(2, "s")])
+        assert DenseCoordinate(times).is_monotonic_increasing()
+        times_bad = np.array(
+            [t0, t0 + np.timedelta64(2, "s"), t0 + np.timedelta64(1, "s")]
+        )
+        assert not DenseCoordinate(times_bad).is_monotonic_increasing()

tests/coordinates/test_interp.py

@@ -444,3 +444,25 @@ def test_get_split_indices_overlaps_with_tolerance(self):
         result = coord.get_split_indices(kind="overlaps", tolerance=0.5)
         assert isinstance(result, np.ndarray)
         np.testing.assert_array_equal(result, [5], strict=True)
+
+    def test_is_monotonic_increasing_true(self):
+        coord = InterpCoordinate(
+            {"tie_indices": [0, 4, 5, 9], "tie_values": [0.0, 4.0, 5.0, 9.0]}
+        )
+        assert coord.is_monotonic_increasing() is True
+
+    def test_is_monotonic_increasing_false(self):
+        coord = InterpCoordinate(
+            {"tie_indices": [0, 4, 5, 9], "tie_values": [0.0, 4.0, 3.0, 7.0]}
+        )
+        assert coord.is_monotonic_increasing() is False
+
+    def test_is_monotonic_increasing_multi_segment(self):
+        # Three segments all strictly increasing — must not raise ValueError from bool()
+        coord = InterpCoordinate(
+            {
+                "tie_indices": [0, 4, 5, 9, 10, 14],
+                "tie_values": [0.0, 4.0, 5.0, 9.0, 10.0, 14.0],
+            }
+        )
+        assert coord.is_monotonic_increasing() is True

tests/coordinates/test_sampled.py

@@ -984,3 +984,26 @@ def test_get_split_indices_overlaps_with_tolerance(self):
         result = coord.get_split_indices(kind="overlaps", tolerance=1.0)
         assert isinstance(result, np.ndarray)
         np.testing.assert_array_equal(result, [5], strict=True)
+
+    def test_is_monotonic_increasing_true(self):
+        coord = SampledCoordinate(
+            {"tie_values": [0.0, 5.0], "tie_lengths": [5, 5], "sampling_interval": 1.0}
+        )
+        assert coord.is_monotonic_increasing() is True
+
+    def test_is_monotonic_increasing_false(self):
+        coord = SampledCoordinate(
+            {"tie_values": [0.0, 2.0], "tie_lengths": [5, 5], "sampling_interval": 1.0}
+        )
+        assert coord.is_monotonic_increasing() is False
+
+    def test_is_monotonic_increasing_multi_segment(self):
+        # Three segments all increasing — must not raise ValueError from bool()
+        coord = SampledCoordinate(
+            {
+                "tie_values": [0.0, 5.0, 11.0],
+                "tie_lengths": [5, 5, 5],
+                "sampling_interval": 1.0,
+            }
+        )
+        assert coord.is_monotonic_increasing() is True

xdas/coordinates/interp.py

@@ -216,6 +216,10 @@ def get_sampling_interval(self, cast=True):
             delta = delta / np.timedelta64(1, "s")
         return delta
 
+    def is_monotonic_increasing(self):
+        """Return ``True`` if no segment boundary exhibits a backward jump."""
+        return not self.get_split_indices("overlaps", tolerance=False).size
+
     def equals(self, other):
         """Return ``True`` if *other* has identical tie points, dim, and dtype."""
         return (

xdas/coordinates/sampled.py

@@ -263,6 +263,10 @@ def get_sampling_interval(self, cast=True):
             delta = delta / np.timedelta64(1, "s")
         return delta
 
+    def is_monotonic_increasing(self):
+        """Return ``True`` if no segment starts below the end of the previous one."""
+        return not self.get_split_indices("overlaps", tolerance=False).size
+
     def equals(self, other):
         """Return ``True`` if *other* has identical tie values, lengths, sampling interval, dim, and dtype."""
         return (