scale: refactor val_in_range to accept scalar values and return a single bool

null-dreams · null-dreams · commit 631a52f6cb95 · 2026-03-15T14:27:20.000+05:30
diff --git a/lib/matplotlib/scale.py b/lib/matplotlib/scale.py
@@ -113,17 +113,19 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
         This is used by log scales to determine a minimum value.
         """
         return vmin, vmax
-    
+
     def val_in_range(self, val):
         """
         Return whether the value(s) are within the valid range for this scale.
+
+        This method is a generic implementation. Subclasses may implement more
+        efficient solutions for their domain.
         """
-        if np.isscalar(val):
+        try:
             vmin, vmax = self.limit_range_for_scale(val, val, minpos=1e-300)
-            return (vmax == val) and (vmin == val)
-
-        val = np.asanyarray(val)
-        return np.array([self.val_in_range(v) for v in val])
+            return vmin == val and vmax == val
+        except (TypeError, ValueError):
+            return False
 
 
 def _make_axis_parameter_optional(init_func):
@@ -206,13 +208,14 @@ def get_transform(self):
         `~matplotlib.transforms.IdentityTransform`.
         """
         return IdentityTransform()
-    
+
     def val_in_range(self, val):
         """
-        Return `True` for all values.
+        Return whether the value is within the valid range for this scale.
+
+        This is True for all values.
         """
-        val = np.asanyarray(val)
-        return np.ones(val.shape, dtype=bool)
+        return True
 
 
 class FuncTransform(Transform):
@@ -417,10 +420,17 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
 
         return (minpos if vmin <= 0 else vmin,
                 minpos if vmax <= 0 else vmax)
-    
+
     def val_in_range(self, val):
-        """Return `True` for positive values."""
-        return np.asanyarray(val) > 0
+        """
+        Return whether the value is within the valid range for this scale.
+
+        This is True for value(s) > 0
+        """
+        if np.isnan(val):
+            return False
+        else:
+            return val > 0
 
 
 class FuncScaleLog(LogScale):
@@ -841,13 +851,14 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
             minpos = 1e-7  # Should rarely (if ever) have a visible effect.
         return (minpos if vmin <= 0 else vmin,
                 1 - minpos if vmax >= 1 else vmax)
-    
+
     def val_in_range(self, val):
         """
-        Return `True` if value(s) lie between 0 and 1 (excluded)
+        Return whether the value is within the valid range for this scale.
+
+        This is True for value(s) which are between 0 and 1 (excluded).
         """
-        val = np.asanyarray(val)
-        return (val > 0) & (val < 1)
+        return (val > 0) and (val < 1)
 
 
 _scale_mapping = {
