test: fix flat uniform DDF masking and clarify harness labels

Simulation.get_ddf() is flat (9*ny*nx); view it as (Q, cells) before
applying the fluid mask, with a flat-DDF regression. Label A/E as
runner-like force-read workloads (values discarded, no aggregation or
validation; no macro/probe/CSV cost; not benchmark throughput) and split
status lines into CONSTRUCTED and WARM_READY. Test/doc only.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tests/unit/test_time_refined_dfg.py

@@ -24,7 +24,9 @@ class TimingHarnessContract(unittest.TestCase):
             self.assertFalse(t.VARIANTS[name]["force_history_valid"])
             self.assertTrue(t.VARIANTS[name]["timing_only"])
         for name in ("A", "E"):
-            self.assertTrue(t.VARIANTS[name]["force_history_valid"])
+            self.assertFalse(t.VARIANTS[name]["force_history_valid"])  # reads discarded
+            self.assertTrue(t.VARIANTS[name]["force_reads"])
+            self.assertIn("runner-like", t.VARIANTS[name]["force_note"])
         self.assertEqual({v["case"] for v in t.VARIANTS.values()}, {"refined", "uniform"})
         self.assertIn("final base interval", t.VARIANTS["C"]["force_note"])
         self.assertIn("whole-window", t.VARIANTS["E'"]["force_note"])
@@ -47,6 +49,18 @@ class TimingHarnessContract(unittest.TestCase):
         self.assertIn("infinite", t.same_state([inf], [inf.copy()]))  # matching inf still fails
         self.assertIn("infinite", t.same_state([a], [inf]))
 
+    def test_flat_uniform_ddf(self):
+        fluid = np.array([[True, False, True], [True, True, False]])
+        flat = np.ones(9 * fluid.size, np.float32)  # Simulation.get_ddf() layout
+        self.assertTrue(t.uniform_populations_finite(flat, fluid))
+        flat[1 * fluid.size + 1] = np.nan  # q=1, solid cell 1: ignored
+        self.assertTrue(t.uniform_populations_finite(flat, fluid))
+        flat[4 * fluid.size + 0] = np.nan  # q=4, fluid cell 0: detected
+        self.assertFalse(t.uniform_populations_finite(flat, fluid))
+        self.assertTrue(t.uniform_populations_finite(np.ones((9,) + fluid.shape), fluid))
+        with self.assertRaises(RuntimeError):
+            t.uniform_populations_finite(np.ones(9 * fluid.size + 1), fluid)
+
     def test_physical_health_limits(self):
         ok = (np.array([1., 1.01]), np.array([.01, .02]), np.array([0., .01]))
         health = t.physical_health([ok])