matplotlib · anntzer · Oct 7, 2017
diff --git a/lib/matplotlib/artist.py b/lib/matplotlib/artist.py
@@ -4,6 +4,7 @@
 import six
 
 from collections import OrderedDict, namedtuple
+import contextlib
 from functools import wraps
 import inspect
 import re
@@ -120,6 +121,22 @@ def __init__(self):
         self._path_effects = rcParams['path.effects']
         self._sticky_edges = _XYPair([], [])
 
+        # When plotting in log-scale, force the use of clip mode instead of
+        # mask.  The typical (internal) use case is log-scaled bar plots and
+        # error bars.  Ideally we'd want BarContainers / ErrorbarContainers
+        # to have their own show() method which takes care of the patching,
+        # but right now Containers are not taken into account during
+        # the draw; instead their components (in the case of bar plots,
+        # these are Rectangle patches; in the case of ErrorbarContainers,
+        # LineCollections) are drawn individually, so tracking the force_clip
+        # state must be done by the component artists.  Note that handling of
+        # _force_clip_in_log_scale must be done by the individual artists'
+        # draw implementation; right now only Patches and Collections support
+        # it.  The `_forcing_clip_in_log_scale` decorator may be helpful to
+        # implement such support, it should typically be applied around a call
+        # to `transform_path_non_affine`.
+        self._force_clip_in_log_scale = False
+
     def __getstate__(self):
         d = self.__dict__.copy()
         # remove the unpicklable remove method, this will get re-added on load
@@ -779,6 +796,21 @@ def draw(self, renderer, *args, **kwargs):
             return
         self.stale = False
 
+    @contextlib.contextmanager
+    def _forcing_clip_in_log_scale(self):
+        # See _force_clip_in_log_scale for explanation.
+        fvs = {}
+        if self._force_clip_in_log_scale and self.axes:
+            for axis in self.axes._get_axis_list():
+                if axis.get_scale() == "log":
+                    fvs[axis] = axis._scale._transform._fill_value
+                    axis._scale._transform._fill_value = 1e-300
+        try:
+            yield
+        finally:
+            for axis, fv in fvs.items():
+                axis._scale._transform._fill_value = fv
+
     def set_alpha(self, alpha):
         """
         Set the alpha value used for blending - not supported on

diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -2158,6 +2158,7 @@ def bar(self, *args, **kwargs):
                 r.sticky_edges.y.append(b)
             elif orientation == 'horizontal':
                 r.sticky_edges.x.append(l)
+            r._force_clip_in_log_scale = True
             self.add_patch(r)
             patches.append(r)
 
@@ -3053,7 +3054,9 @@ def extract_err(err, data):
             if xlolims.any():
                 yo, _ = xywhere(y, right, xlolims & everymask)
                 lo, ro = xywhere(x, right, xlolims & everymask)
-                barcols.append(self.hlines(yo, lo, ro, **eb_lines_style))
+                ebs = self.hlines(yo, lo, ro, **eb_lines_style)
+                ebs._force_clip_in_log_scale = True
+                barcols.append(ebs)
                 rightup, yup = xywhere(right, y, xlolims & everymask)
                 if self.xaxis_inverted():
                     marker = mlines.CARETLEFTBASE
@@ -3092,7 +3095,9 @@ def extract_err(err, data):
             if noylims.any():
                 xo, _ = xywhere(x, lower, noylims & everymask)
                 lo, uo = xywhere(lower, upper, noylims & everymask)
-                barcols.append(self.vlines(xo, lo, uo, **eb_lines_style))
+                ebs = self.vlines(xo, lo, uo, **eb_lines_style)
+                ebs._force_clip_in_log_scale = True
+                barcols.append(ebs)
                 if capsize > 0:
                     caplines.append(mlines.Line2D(xo, lo, marker='_',
                                                   **eb_cap_style))
@@ -4905,6 +4910,7 @@ def get_interp_point(ind):
             polys.append(X)
 
         collection = mcoll.PolyCollection(polys, **kwargs)
+        collection._force_clip_in_log_scale = True
 
         # now update the datalim and autoscale
         XY1 = np.array([x[where], y1[where]]).T
@@ -5057,6 +5063,7 @@ def get_interp_point(ind):
             polys.append(Y)
 
         collection = mcoll.PolyCollection(polys, **kwargs)
+        collection._force_clip_in_log_scale = True
 
         # now update the datalim and autoscale
         X1Y = np.array([x1[where], y[where]]).T

diff --git a/lib/matplotlib/collections.py b/lib/matplotlib/collections.py
@@ -232,8 +232,9 @@ def _prepare_points(self):
                 offsets = np.column_stack([xs, ys])
 
         if not transform.is_affine:
-            paths = [transform.transform_path_non_affine(path)
-                     for path in paths]
+            with self._forcing_clip_in_log_scale():
+                paths = [transform.transform_path_non_affine(path)
+                         for path in paths]
             transform = transform.get_affine()
         if not transOffset.is_affine:
             offsets = transOffset.transform_non_affine(offsets)

diff --git a/lib/matplotlib/patches.py b/lib/matplotlib/patches.py
@@ -564,7 +564,10 @@ def draw(self, renderer):
 
         path = self.get_path()
         transform = self.get_transform()
-        tpath = transform.transform_path_non_affine(path)
+
+        with self._forcing_clip_in_log_scale():
+            tpath = transform.transform_path_non_affine(path)
+
         affine = transform.get_affine()
 
         if self.get_path_effects():

diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -5412,3 +5412,21 @@ def test_patch_deprecations():
         assert fig.patch == fig.figurePatch
 
     assert len(w) == 2
+
+
+@pytest.mark.parametrize("plotter",
+                         [lambda ax: ax.bar([0, 1], [1, 2]),
+                          lambda ax: ax.errorbar([0, 1], [2, 2], [1, 3]),
+                          lambda ax: ax.fill_between([0, 1], [1, 2], [1, 0])])
+def test_clipped_log_zero(plotter):
+    fig, ax = plt.subplots()
+    plotter(ax)
+    ax.set_yscale("log")
+    png1 = io.BytesIO()
+    fig.savefig(png1, format="png")
+    fig, ax = plt.subplots()
+    plotter(ax)
+    ax.set_yscale("log", nonposy="clip")
+    png2 = io.BytesIO()
+    fig.savefig(png2, format="png")
+    assert png1.getvalue() == png2.getvalue()