tests: add test cases for val_in_range for different scales

null-dreams · null-dreams · commit 59bd52b5bd1a · 2026-03-18T16:40:46.000+05:30
diff --git a/lib/matplotlib/tests/test_scale.py b/lib/matplotlib/tests/test_scale.py
@@ -371,3 +371,63 @@ def set_default_locators_and_formatters(self, axis):
         # cleanup - there's no public unregister_scale()
         del mscale._scale_mapping["custom"]
         del mscale._scale_has_axis_parameter["custom"]
+
+
+def test_val_in_range():
+
+    test_cases = [
+        # LinearScale: Always True (even for Inf/NaN)
+        ('linear', 10.0, True),
+        ('linear', -10.0, True),
+        ('linear', 0.0, True),
+        ('linear', np.inf, True),
+        ('linear', np.nan, True),
+
+        # LogScale: Only positive values (> 0)
+        ('log', 1.0, True),
+        ('log', 1e-300, True),
+        ('log', 0.0, False),
+        ('log', -1.0, False),
+        ('log', np.inf, True),
+        ('log', np.nan, False),
+
+        # LogitScale: Strictly between 0 and 1
+        ('logit', 0.5, True),
+        ('logit', 0.0, False),
+        ('logit', 1.0, False),
+        ('logit', -0.1, False),
+        ('logit', 1.1, False),
+        ('logit', np.inf, False),
+        ('logit', np.nan, False),
+
+        # SymmetricalLogScale: Valid for all real numbers
+        # Uses ScaleBase fallback. NaN returns False since NaN != NaN
+        ('symlog', 10.0, True),
+        ('symlog', -10.0, True),
+        ('symlog', 0.0, True),
+        ('symlog', np.inf, True),
+        ('symlog', np.nan, False),
+    ]
+
+    for name, val, expected in test_cases:
+        scale_cls = mscale._scale_mapping[name]
+        s = scale_cls(axis=None)
+
+        result = s.val_in_range(val)
+        assert result is expected, (
+            f"Failed {name}.val_in_range({val})."
+            f"Expected {expected}, got {result}"
+        )
+
+
+def test_val_in_range_base_fallback():
+    # Directly test the ScaleBase fallback for custom scales.
+    # ScaleBase.limit_range_for_scale returns values unchanged by default
+    s = mscale.ScaleBase(axis=None)
+
+    # Normal values should be True
+    assert s.val_in_range(1.0) is True
+    assert s.val_in_range(-5.5) is True
+
+    # NaN check: fallback uses 'vmin == vmax'
+    assert s.val_in_range(np.nan) is False
