test: integrate explicitly repinned uniform LES shear diagnostic

tests/unit/test_les_flow_oracle.py

@@ -0,0 +1,70 @@
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "validation"))
+import json
+import unittest
+import numpy as np
+from les_flow_oracle import H, U, NU, TIMES, solve, relative, amplitude
+
+
+class OracleTests(unittest.TestCase):
+    def test_linear_exact(self):
+        y, states = solve(0, n=256)
+        for t, u in states.items():
+            exact = U * np.sin(np.pi * y / H) * np.exp(-NU * (np.pi / H) ** 2 * t)
+            self.assertLess(relative(u, exact), 1e-5)
+
+    def test_nonlinear_refinement_symmetry_and_dissipation(self):
+        y, states = solve(1, n=256)
+        yc, coarse = solve(1, n=128)
+        energy = U**2 / 2
+        for t, u in states.items():
+            self.assertTrue(np.all(np.isfinite(u)))
+            self.assertGreaterEqual(float(u.min()), 0)
+            self.assertLessEqual(float(u.max()), U)
+            np.testing.assert_allclose(u, u[::-1], atol=1e-14)
+            self.assertLess(float(np.mean(u * u)), energy)
+            energy = float(np.mean(u * u))
+            self.assertLess(relative(np.interp(yc, y, u), coarse[t]), 8e-5)
+
+    def test_filter_is_independent_of_oracle_grid(self):
+        y, a = solve(1, n=128, times=(TIMES[-1],))
+        _, b = solve(0.5, n=128, times=(TIMES[-1],), delta=2)
+        np.testing.assert_array_equal(a[TIMES[-1]], b[TIMES[-1]])
+
+    def test_fixed_grid_timestep_halving(self):
+        errors = []
+        for cs in (0.0, 0.16, 1.0):
+            _, full = solve(cs, n=256, cfl=0.4)
+            _, half = solve(cs, n=256, cfl=0.2)
+            errors.extend(relative(full[t], half[t]) for t in TIMES)
+        self.assertLess(max(errors), 1e-8)
+        print(
+            json.dumps({"fixed_grid_timestep_half_max_relative": max(errors)}),
+            flush=True,
+        )
+
+    def test_signal_and_wrong_convention_separate(self):
+        y, std = solve(1, n=256, times=(TIMES[-1],))
+        _, wrong = solve(2 ** (-0.25), n=256, times=(TIMES[-1],))
+        t = TIMES[-1]
+        base = U * np.exp(-NU * (np.pi / H) ** 2 * t)
+        signal = (base - amplitude(y, std[t])) / base
+        separation = relative(wrong[t], std[t])
+        print(
+            json.dumps(
+                {
+                    "final_time": t,
+                    "standard_sgs_amplitude_signal": signal,
+                    "wrong_convention_profile_separation": separation,
+                }
+            ),
+            flush=True,
+        )
+        self.assertGreater(signal, 0.04)
+        self.assertGreater(separation, 0.01)
+
+
+if __name__ == "__main__":
+    unittest.main()