test: add grid utility tests

Author: Hem-W

tests/test_grid_utils.py

@@ -0,0 +1,75 @@
+import numpy as np
+import pytest
+
+from dominosee.grid import (
+    deg_to_equatorial_distance,
+    equatorial_distance_to_deg,
+    neighbour_distance,
+    geo_distance,
+)
+
+
+def test_deg_equatorial_roundtrip_values():
+    for deg in [0.5, 1.0, 5.0, 10.0, 30.0]:
+        d = deg_to_equatorial_distance(deg)
+        back = equatorial_distance_to_deg(d)
+        assert pytest.approx(back, rel=1e-6, abs=1e-8) == deg
+
+
+def test_known_value_5deg_equator():
+    # 5 degrees at equator is circumference * 5/360
+    d = deg_to_equatorial_distance(5.0)
+    # Use expected from formula to avoid hardcoding magic numbers
+    R = 6371.0
+    expected = 2 * np.pi * R * (5.0 / 360.0)
+    assert pytest.approx(d, rel=1e-6, abs=1e-6) == expected
+    # And inverse
+    back = equatorial_distance_to_deg(d)
+    assert pytest.approx(back, rel=1e-9, abs=1e-9) == 5.0
+
+
+def test_invalid_inputs_raise():
+    with pytest.raises(ValueError):
+        deg_to_equatorial_distance(0)
+    with pytest.raises(ValueError):
+        deg_to_equatorial_distance(-1)
+    with pytest.raises(ValueError):
+        equatorial_distance_to_deg(0)
+    with pytest.raises(ValueError):
+        equatorial_distance_to_deg(-10)
+
+
+def test_neighbour_distance_on_equator_line():
+    # Three points on equator along longitude: (0,0), (1,0), (2,0)
+    grid = {
+        'lon': np.array([0.0, 1.0, 2.0]),
+        'lat': np.array([0.0, 0.0, 0.0]),
+    }
+    nd = neighbour_distance(grid)
+    assert nd.shape == (3,)
+    expected = deg_to_equatorial_distance(1.0)
+    assert pytest.approx(nd[0], rel=1e-6) == expected
+    assert pytest.approx(nd[1], rel=1e-6) == expected
+    assert pytest.approx(nd[2], rel=1e-6) == expected
+
+
+def test_neighbour_distance_on_unit_rectangle():
+    # Four points forming a 1x1 degree rectangle near equator
+    # (0,0), (0,1), (1,0), (1,1)
+    grid = {
+        'lon': np.array([0.0, 0.0, 1.0, 1.0]),
+        'lat': np.array([0.0, 1.0, 0.0, 1.0]),
+    }
+    nd = neighbour_distance(grid)
+    assert nd.shape == (4,)
+    # Expected nearest distances per point
+    # (0,0): min to (0,1) or (1,0) at equator
+    e00 = min(geo_distance(0.0, 0.0, 0.0, 1.0), geo_distance(0.0, 0.0, 1.0, 0.0))
+    # (0,1): min to (0,0) (lat diff) or (1,1) (lon diff at 1° lat)
+    e01 = min(geo_distance(0.0, 1.0, 0.0, 0.0), geo_distance(0.0, 1.0, 1.0, 1.0))
+    # (1,0): min to (0,0) or (1,1)
+    e10 = min(geo_distance(1.0, 0.0, 0.0, 0.0), geo_distance(1.0, 0.0, 1.0, 1.0))
+    # (1,1): min to (1,0) (lat diff) or (0,1) (lon diff at 1° lat)
+    e11 = min(geo_distance(1.0, 1.0, 1.0, 0.0), geo_distance(1.0, 1.0, 0.0, 1.0))
+    expected = np.array([e00, e01, e10, e11])
+    assert np.allclose(nd, expected, rtol=1e-6)