matplotlib
diff --git a/‎lib/matplotlib/axis.py
+13-45 b/‎lib/matplotlib/axis.py
+13-45
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_angle_noise.png
23 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_angle_noise.png
23 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_freqs.png
-35 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_freqs.png
-35 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_freqs_linear.png
-35 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_freqs_linear.png
-35 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_noise.png
14 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_noise.png
14 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_noise_linear.png
14 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_magnitude_noise_linear.png
14 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_noise.png
19 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_noise.png
19 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_noise_linear.png
19 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_noise_linear.png
19 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_phase_noise.png
18 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/specgram_phase_noise.png
18 Bytes
diff --git a/‎lib/matplotlib/transforms.py
+9-3 b/‎lib/matplotlib/transforms.py
+9-3
@@ -1051,60 +1051,28 @@ def _update_ticks(self, renderer):
                     ihigh = locs[-1]
             tick_tups = [ti for ti in tick_tups if ilow <= ti[1] <= ihigh]
 
-        # so that we don't lose ticks on the end, expand out the interval ever
-        # so slightly.  The "ever so slightly" is defined to be the width of a
-        # half of a pixel.  We don't want to draw a tick that even one pixel
-        # outside of the defined axis interval.
-        if interval[0] <= interval[1]:
-            interval_expanded = interval
-        else:
-            interval_expanded = interval[1], interval[0]
-
-        if hasattr(self, '_get_pixel_distance_along_axis'):
-            # normally, one does not want to catch all exceptions that
-            # could possibly happen, but it is not clear exactly what
-            # exceptions might arise from a user's projection (their
-            # rendition of the Axis object).  So, we catch all, with
-            # the idea that one would rather potentially lose a tick
-            # from one side of the axis or another, rather than see a
-            # stack trace.
-            # We also catch users warnings here. These are the result of
-            # invalid numpy calculations that may be the result of out of
-            # bounds on axis with finite allowed intervals such as geo
-            # projections i.e. Mollweide.
-            with np.errstate(invalid='ignore'):
-                try:
-                    ds1 = self._get_pixel_distance_along_axis(
-                        interval_expanded[0], -0.5)
-                except Exception:
-                    warnings.warn("Unable to find pixel distance along axis "
-                                  "for interval padding of ticks; assuming no "
-                                  "interval padding needed.")
-                    ds1 = 0.0
-                if np.isnan(ds1):
-                    ds1 = 0.0
-                try:
-                    ds2 = self._get_pixel_distance_along_axis(
-                        interval_expanded[1], +0.5)
-                except Exception:
-                    warnings.warn("Unable to find pixel distance along axis "
-                                  "for interval padding of ticks; assuming no "
-                                  "interval padding needed.")
-                    ds2 = 0.0
-                if np.isnan(ds2):
-                    ds2 = 0.0
-            interval_expanded = (interval_expanded[0] - ds1,
-                                 interval_expanded[1] + ds2)
+        if interval[1] <= interval[0]:
+             interval = interval[1], interval[0]
+        inter = self.get_transform().transform(interval)
 
         ticks_to_draw = []
         for tick, loc, label in tick_tups:
+            # draw each tick if it is in interval.   Note the transform
+            # to pixel space to take care of log transforms etc.
+            # interval_contains has a floating point tolerance.
             if tick is None:
                 continue
             # NB: always update labels and position to avoid issues like #9397
             tick.update_position(loc)
             tick.set_label1(label)
             tick.set_label2(label)
-            if not mtransforms.interval_contains(interval_expanded, loc):
+            try:
+                loct = self.get_transform().transform(loc)
+            except AssertionError:
+                loct = None
+                continue
+            if ((loct is None) or
+                    (not mtransforms.interval_contains(inter, loct))):
                 continue
             ticks_to_draw.append(tick)
 
 
@@ -2892,7 +2892,7 @@ def nonsingular(vmin, vmax, expander=0.001, tiny=1e-15, increasing=True):
     return vmin, vmax
 
 
-def interval_contains(interval, val):
+def interval_contains(interval, val, rtol=1e-10):
     """
     Check, inclusively, whether an interval includes a given value.
 
@@ -2902,14 +2902,20 @@ def interval_contains(interval, val):
         A 2-length sequence, endpoints that define the interval.
     val : scalar
         Value to check is within interval.
+    rtol : scalar
+        Tolerance slippage allowed outside of this interval.  Default
+        1e-10 * (b - a).
 
     Returns
     -------
     bool
-        Returns true if given val is within the interval.
+        Returns true if given val is within the interval (with tolerance)
     """
     a, b = interval
-    return a <= val <= b or a >= val >= b
+    if a > b:
+        a, b = b, a
+    rtol = (b - a) * rtol
+    return a - rtol <= val <= b + rtol
 
 
 def interval_contains_open(interval, val):