matplotlib · scottshambaugh · May 22, 2026 · May 22, 2026
diff --git a/lib/matplotlib/scale.py b/lib/matplotlib/scale.py
@@ -30,7 +30,6 @@
 """  # noqa: E501
 
 import inspect
-import math
 import textwrap
 from functools import wraps
 
@@ -119,17 +118,20 @@ 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.
-        """
-        try:
-            if not math.isfinite(val):
-                return False
+        Accepts a scalar or array-like ``val``. For a scalar, returns a
+        Python ``bool``. For an array, returns a bool ndarray of the same
+        shape. This is a generic implementation, and subclasses may implement
+        more efficient solutions for their domain.
+        """
+        arr = np.asarray(val)
+        with np.errstate(invalid='ignore'):
+            try:
+                vmin, vmax = self.limit_range_for_scale(arr, arr, minpos=1e-300)
+            except (TypeError, ValueError):
+                result = np.zeros(arr.shape, dtype=bool)
             else:
-                vmin, vmax = self.limit_range_for_scale(val, val, minpos=1e-300)
-                return vmin == val and vmax == val
-        except (TypeError, ValueError):
-            return False
+                result = np.isfinite(arr) & (vmin == arr) & (vmax == arr)
+        return bool(result) if arr.ndim == 0 else result
 
 
 def _make_axis_parameter_optional(init_func):
@@ -219,11 +221,13 @@ def get_transform(self):
 
     def val_in_range(self, val):
         """
-        Return whether the value is within the valid range for this scale.
+        Return whether the value(s) are within the valid range for this scale.
 
         This is True for all values, except +-inf and NaN.
         """
-        return math.isfinite(val)
+        arr = np.asarray(val)
+        result = np.isfinite(arr)
+        return bool(result) if arr.ndim == 0 else result
 
 
 class FuncTransform(Transform):
@@ -431,11 +435,14 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
 
     def val_in_range(self, val):
         """
-        Return whether the value is within the valid range for this scale.
+        Return whether the value(s) are within the valid range for this scale.
 
         This is True for value(s) > 0 except +inf and NaN.
         """
-        return math.isfinite(val) and val > 0
+        arr = np.asarray(val)
+        with np.errstate(invalid='ignore'):
+            result = np.isfinite(arr) & (arr > 0)
+        return bool(result) if arr.ndim == 0 else result
 
 
 class FuncScaleLog(LogScale):
@@ -625,11 +632,13 @@ def get_transform(self):
 
     def val_in_range(self, val):
         """
-        Return whether the value is within the valid range for this scale.
+        Return whether the value(s) are within the valid range for this scale.
 
         This is True for all values, except +-inf and NaN.
         """
-        return math.isfinite(val)
+        arr = np.asarray(val)
+        result = np.isfinite(arr)
+        return bool(result) if arr.ndim == 0 else result
 
 
 class AsinhTransform(Transform):
@@ -759,11 +768,13 @@ def set_default_locators_and_formatters(self, axis):
 
     def val_in_range(self, val):
         """
-        Return whether the value is within the valid range for this scale.
+        Return whether the value(s) are within the valid range for this scale.
 
         This is True for all values, except +-inf and NaN.
         """
-        return math.isfinite(val)
+        arr = np.asarray(val)
+        result = np.isfinite(arr)
+        return bool(result) if arr.ndim == 0 else result
 
 
 class LogitTransform(Transform):
@@ -880,11 +891,14 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
 
     def val_in_range(self, val):
         """
-        Return whether the value is within the valid range for this scale.
+        Return whether the value(s) are within the valid range for this scale.
 
         This is True for value(s) which are between 0 and 1 (excluded).
         """
-        return 0 < val < 1
+        arr = np.asarray(val)
+        with np.errstate(invalid='ignore'):
+            result = (0 < arr) & (arr < 1)
+        return bool(result) if arr.ndim == 0 else result
 
 
 _scale_mapping = {

diff --git a/lib/matplotlib/tests/test_scale.py b/lib/matplotlib/tests/test_scale.py
@@ -477,3 +477,27 @@ def test_val_in_range_base_fallback():
     assert s.val_in_range(np.nan) is False
     assert s.val_in_range(np.inf) is False
     assert s.val_in_range(-np.inf) is False
+
+
+def test_val_in_range_array():
+    # Vectorized: scalar in -> scalar bool, array in -> bool array.
+    arr = np.array([1.0, -1.0, 0.0, np.nan, np.inf, 5.0])
+    cases = {
+        'linear': [True, True, True, False, False, True],
+        'log':    [True, False, False, False, False, True],
+        'symlog': [True, True, True, False, False, True],
+        'asinh':  [True, True, True, False, False, True],
+    }
+    for name, expected in cases.items():
+        s = mscale._scale_mapping[name](axis=None)
+        np.testing.assert_array_equal(s.val_in_range(arr), expected)
+
+    s = mscale._scale_mapping['logit'](axis=None)
+    np.testing.assert_array_equal(
+        s.val_in_range(np.array([0.1, 0.5, 0.0, 1.0, -0.1, 1.1])),
+        [True, True, False, False, False, False])
+
+    # 2D shape is preserved.
+    out = mscale._scale_mapping['log'](axis=None).val_in_range(
+        np.array([[1.0, -1.0], [0.5, np.nan]]))
+    np.testing.assert_array_equal(out, [[True, False], [True, False]])
diff --git a/lib/mpl_toolkits/mplot3d/art3d.py b/lib/mpl_toolkits/mplot3d/art3d.py
@@ -97,6 +97,30 @@ def _viewlim_mask(xs, ys, zs, axes):
     return mask
 
 
+def _scale_invalid_mask(xs, ys, zs, axes):
+    """
+    Return the mask of points whose coordinates are invalid for the axis
+    scale they live on (e.g. <=0 on a log axis).
+
+    Parameters
+    ----------
+    xs, ys, zs : array-like
+        The points to check, in data coordinates.
+    axes : Axes3D
+        The axes whose scales are queried.
+
+    Returns
+    -------
+    mask : np.ndarray
+        Boolean array, ``True`` where any of x/y/z is out of its scale's
+        valid domain.
+    """
+    return np.logical_or.reduce((
+        np.logical_not(axes.xaxis._scale.val_in_range(xs)),
+        np.logical_not(axes.yaxis._scale.val_in_range(ys)),
+        np.logical_not(axes.zaxis._scale.val_in_range(zs))))
+
+
 class Text3D(mtext.Text):
     """
     Text object with 3D position and direction.
@@ -191,8 +215,10 @@ def set_3d_properties(self, z=0, zdir='z', axlim_clip=False):
 
     @artist.allow_rasterization
     def draw(self, renderer):
+        mask = _scale_invalid_mask(self._x, self._y, self._z, self.axes)
         if self._axlim_clip:
-            mask = _viewlim_mask(self._x, self._y, self._z, self.axes)
+            mask = mask | _viewlim_mask(self._x, self._y, self._z, self.axes)
+        if np.any(mask):
             pos3d = np.ma.array([self._x, self._y, self._z],
                                 mask=mask, dtype=float).filled(np.nan)
         else:
@@ -328,9 +354,12 @@ def get_data_3d(self):
 
     @artist.allow_rasterization
     def draw(self, renderer):
+        scale_mask = _scale_invalid_mask(*self._verts3d, self.axes)
         if self._axlim_clip:
+            scale_mask = scale_mask | _viewlim_mask(*self._verts3d, self.axes)
+        if np.any(scale_mask):
             mask = np.broadcast_to(
-                _viewlim_mask(*self._verts3d, self.axes),
+                scale_mask,
                 (len(self._verts3d), *self._verts3d[0].shape)
             )
             xs3d, ys3d, zs3d = np.ma.array(self._verts3d,
@@ -424,10 +453,13 @@ class Collection3D(Collection):
     def do_3d_projection(self):
         """Project the points according to renderer matrix."""
         vs_list = [vs for vs, _ in self._3dverts_codes]
+        masks = [_scale_invalid_mask(*vs.T, self.axes) for vs in vs_list]
         if self._axlim_clip:
-            vs_list = [np.ma.array(vs, mask=np.broadcast_to(
-                       _viewlim_mask(*vs.T, self.axes), vs.shape))
-                       for vs in vs_list]
+            masks = [m | _viewlim_mask(*vs.T, self.axes)
+                     for m, vs in zip(masks, vs_list)]
+        vs_list = [np.ma.array(vs, mask=np.broadcast_to(m, vs.shape))
+                   if np.any(m) else vs
+                   for vs, m in zip(vs_list, masks)]
         xyzs_list = [proj3d._scale_proj_transform(
             vs[:, 0], vs[:, 1], vs[:, 2], self.axes) for vs in vs_list]
         self._paths = [mpath.Path(np.ma.column_stack([xs, ys]), cs)
@@ -508,6 +540,14 @@ def do_3d_projection(self):
         if np.ma.isMA(segments):
             mask = segments.mask
 
+        scale_mask = _scale_invalid_mask(segments[..., 0],
+                                         segments[..., 1],
+                                         segments[..., 2],
+                                         self.axes)
+        if np.any(scale_mask):
+            mask = mask | np.broadcast_to(scale_mask[..., np.newaxis],
+                                          (*scale_mask.shape, 3))
+
         if self._axlim_clip:
             viewlim_mask = _viewlim_mask(segments[..., 0],
                                          segments[..., 1],
@@ -597,12 +637,15 @@ def get_path(self):
 
     def do_3d_projection(self):
         s = self._segment3d
+        xs0, ys0, zs0 = zip(*s)
+        mask = _scale_invalid_mask(xs0, ys0, zs0, self.axes)
         if self._axlim_clip:
-            mask = _viewlim_mask(*zip(*s), self.axes)
+            mask = mask | _viewlim_mask(xs0, ys0, zs0, self.axes)
+        if np.any(mask):
             xs, ys, zs = np.ma.array(zip(*s),
                                      dtype=float, mask=mask).filled(np.nan)
         else:
-            xs, ys, zs = zip(*s)
+            xs, ys, zs = xs0, ys0, zs0
         vxs, vys, vzs, vis = proj3d._scale_proj_transform_clip(xs, ys, zs, self.axes)
         self._path2d = mpath.Path(np.ma.column_stack([vxs, vys]))
         return min(vzs)
@@ -657,12 +700,15 @@ def set_3d_properties(self, path, zs=0, zdir='z', axlim_clip=False):
 
     def do_3d_projection(self):
         s = self._segment3d
+        xs0, ys0, zs0 = zip(*s)
+        mask = _scale_invalid_mask(xs0, ys0, zs0, self.axes)
         if self._axlim_clip:
-            mask = _viewlim_mask(*zip(*s), self.axes)
+            mask = mask | _viewlim_mask(xs0, ys0, zs0, self.axes)
+        if np.any(mask):
             xs, ys, zs = np.ma.array(zip(*s),
                                      dtype=float, mask=mask).filled(np.nan)
         else:
-            xs, ys, zs = zip(*s)
+            xs, ys, zs = xs0, ys0, zs0
         vxs, vys, vzs, vis = proj3d._scale_proj_transform_clip(xs, ys, zs, self.axes)
         self._path2d = mpath.Path(np.ma.column_stack([vxs, vys]), self._code3d)
         return min(vzs)
@@ -801,8 +847,10 @@ def set_3d_properties(self, zs, zdir, axlim_clip=False):
         self.stale = True
 
     def do_3d_projection(self):
+        mask = _scale_invalid_mask(*self._offsets3d, self.axes)
         if self._axlim_clip:
-            mask = _viewlim_mask(*self._offsets3d, self.axes)
+            mask = mask | _viewlim_mask(*self._offsets3d, self.axes)
+        if np.any(mask):
             xs, ys, zs = np.ma.array(self._offsets3d, mask=mask)
         else:
             xs, ys, zs = self._offsets3d
@@ -1023,8 +1071,10 @@ def do_3d_projection(self):
         for xyz in self._offsets3d:
             if np.ma.isMA(xyz):
                 mask = mask | xyz.mask
+        mask = mask | _scale_invalid_mask(*self._offsets3d, self.axes)
         if self._axlim_clip:
             mask = mask | _viewlim_mask(*self._offsets3d, self.axes)
+        if np.any(mask):
             mask = np.broadcast_to(mask,
                                    (len(self._offsets3d), *self._offsets3d[0].shape))
             xyzs = np.ma.array(self._offsets3d, mask=mask)
@@ -1362,9 +1412,11 @@ def do_3d_projection(self):
             if self._edge_is_mapped:
                 self._edgecolor3d = self._edgecolors
 
-        needs_masking = np.any(self._invalid_vertices)
         num_faces = len(self._faces)
-        mask = self._invalid_vertices
+        mask = self._invalid_vertices | _scale_invalid_mask(
+            self._faces[..., 0], self._faces[..., 1],
+            self._faces[..., 2], self.axes)
+        needs_masking = np.any(mask)
 
         # Some faces might contain masked vertices, so we want to ignore any
         # errors that those might cause

diff --git a/lib/mpl_toolkits/mplot3d/axes3d.py b/lib/mpl_toolkits/mplot3d/axes3d.py
@@ -58,6 +58,20 @@
 from . import axis3d
 
 
+def _mask_scale_invalid(data, axis):
+    """
+    Return ``data`` with values invalid for ``axis``'s scale (e.g. ``<=0`` on a
+    log axis) replaced by NaN, so they don't pollute data limits.
+    """
+    if data is None:
+        return data
+    data = np.asanyarray(data, dtype=float)
+    valid = axis._scale.val_in_range(data)
+    if np.all(valid):
+        return data
+    return np.where(valid, data, np.nan)
+
+
 @_docstring.interpd
 @_api.define_aliases({
     "xlim": ["xlim3d"], "ylim": ["ylim3d"], "zlim": ["zlim3d"]})
@@ -640,13 +654,16 @@ def autoscale(self, enable=True, axis='both', tight=None):
     def auto_scale_xyz(self, X, Y, Z=None, had_data=None):
         # This updates the bounding boxes as to keep a record as to what the
         # minimum sized rectangular volume holds the data.
+        X = _mask_scale_invalid(X, self.xaxis)
+        Y = _mask_scale_invalid(Y, self.yaxis)
         if np.shape(X) == np.shape(Y):
             self.xy_dataLim.update_from_data_xy(
                 np.column_stack([np.ravel(X), np.ravel(Y)]), not had_data)
         else:
             self.xy_dataLim.update_from_data_x(X, not had_data)
             self.xy_dataLim.update_from_data_y(Y, not had_data)
         if Z is not None:
+            Z = _mask_scale_invalid(Z, self.zaxis)
             self.zz_dataLim.update_from_data_x(Z, not had_data)
         # Let autoscale_view figure out how to use this data.
         self.autoscale_view()

diff --git a/lib/mpl_toolkits/mplot3d/tests/test_axes3d.py b/lib/mpl_toolkits/mplot3d/tests/test_axes3d.py
@@ -3189,3 +3189,17 @@ def test_scale3d_calc_coord():
     # Pane coordinate should match axis limit (y-pane at max)
     assert pane_idx == 1
     assert point[pane_idx] == pytest.approx(ax.get_ylim()[1])
+
+
+def test_plot_surface_log_scale_invalid_values():
+    """Ensure non-positive Z values on a log z-axis does not corrupt zlim."""
+    fig = plt.figure()
+    ax = fig.add_subplot(projection='3d')
+    ax.set_zscale('log')
+    X, Y = np.meshgrid(np.linspace(1, 3, 4), np.linspace(1, 3, 4))
+    Z = X * Y - 4  # half the entries are <= 0, invalid for a log scale
+    ax.plot_surface(X, Y, Z)
+    fig.canvas.draw()
+
+    zmin, zmax = ax.get_zlim()
+    assert 1e-3 < zmin < zmax < 1e3, f"zlim corrupted: {(zmin, zmax)}"