fix(m1): _random_window fallback could return end < start

Root cause (found during 50k sample generation at seed 6975, surfacing as
'ValueError: Number of samples, -187, must be non-negative' from linspace in
_inject_drift): _random_window's best-effort fallback after 50 failed
non-overlap attempts drew start and end from TWO INDEPENDENT random integers,
so end could be < start. The primary loop was consistent (start, start+length).

Fix: reuse the same start in the fallback so end >= start always holds
(overlap is still allowed in best-effort, just no inversion).

- tests/test_synthesis.py: regression sweeping 300 seeds × 4 type combos,
  asserting every segment's end >= start. 146 tests passing.

src/tsmm/data/synthesis.py

@@ -103,8 +103,10 @@ def _random_window(rng: np.random.Generator, T: int, length: int, occupied=None)
         cand = (start, start + length)
         if all(cand[1] <= s or cand[0] >= e for (s, e) in occupied):
             return cand
-    # could not find a non-overlapping window; return best effort
+    # could not find a non-overlapping window; return best effort (overlap
-    return int(rng.integers(0, T - length + 1)), int(rng.integers(0, T - length + 1)) + length
+    # allowed) but keep start/end consistent so end >= start always holds.
+    start = int(rng.integers(0, T - length + 1))
+    return start, start + length
 
 
 def _inject_spike(rng, series, T, C, occupied):

tests/test_synthesis.py

@@ -127,3 +127,22 @@ def test_add_missing_reproducible():
     a = add_missing(s, rate=0.1, seed=3)
     b = add_missing(s, rate=0.1, seed=3)
     assert np.array_equal(a, b, equal_nan=True)
+
+
+# ─── regression: _random_window end >= start (found during 50k generation) ─
+def test_inject_anomaly_end_ge_start_across_many_seeds():
+    """Regression: _random_window fallback used to draw end independently,
+    producing end < start (ValueError in linspace). Sweep many seeds + types."""
+    import numpy as np
+    s0 = generate_series(T=512, C=5, seed=0)
+    for seed in range(300):
+        for types in (
+            ["drift"], ["level_shift"], ["variance_change"],
+            ["drift", "level_shift", "variance_change", "spike"],
+        ):
+            s = s0.copy()
+            out, labels, segments = inject_anomaly(s, types=types, seed=seed)
+            for seg in segments:
+                assert seg["end"] >= seg["start"], (seed, types, seg)
+            assert out.shape == s.shape
+            assert labels.shape == (512,)