matplotlib
diff --git a/‎doc/_static/logo2.svg
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+48-16Lines changed: 48 additions & 16 deletions b/‎doc/_static/logo2.svg
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+48-16Lines changed: 48 additions & 16 deletions
diff --git a/‎lib/matplotlib/tests/test_axes.py
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+8-2Lines changed: 8 additions & 2 deletions b/‎lib/matplotlib/tests/test_axes.py
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+8-2Lines changed: 8 additions & 2 deletions
diff --git a/‎lib/matplotlib/ticker.py
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+8-8Lines changed: 8 additions & 8 deletions b/‎lib/matplotlib/ticker.py
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+8-8Lines changed: 8 additions & 8 deletions
@@ -2748,7 +2748,7 @@ def test_subplot_key_hash():
 
 @image_comparison(baseline_images=['specgram_freqs',
                                    'specgram_freqs_linear'],
-                  remove_text=True, extensions=['png'], tol=0.01)
+                  remove_text=True, extensions=['png'], tol=0.03)
 def test_specgram_freqs():
     '''test axes.specgram in default (psd) mode with sinusoidal stimuli'''
     n = 10000
@@ -2848,7 +2848,7 @@ def test_specgram_noise():
 
 @image_comparison(baseline_images=['specgram_magnitude_freqs',
                                    'specgram_magnitude_freqs_linear'],
-                  remove_text=True, extensions=['png'], tol=0.01)
+                  remove_text=True, extensions=['png'], tol=0.03)
 def test_specgram_magnitude_freqs():
     '''test axes.specgram in magnitude mode with sinusoidal stimuli'''
     n = 10000
@@ -4286,6 +4286,12 @@ def test_broken_barh_empty():
     ax.broken_barh([], (.1, .5))
 
 
+@cleanup
+def test_broken_barh_empty():
+    fig, ax = plt.subplots()
+    ax.broken_barh([], (.1, .5))
+
+
 if __name__ == '__main__':
     import nose
     import sys
 
@@ -1642,17 +1642,17 @@ def view_limits(self, vmin, vmax):
             vmin = b ** (vmax - self.numdecs)
             return vmin, vmax
 
-        if rcParams['axes.autolimit_mode'] == 'round_numbers':
-            minpos = self.axis.get_minpos()
+        minpos = self.axis.get_minpos()
 
-            if minpos <= 0 or not np.isfinite(minpos):
-                raise ValueError(
-                    "Data has no positive values, and therefore can not be "
-                    "log-scaled.")
+        if minpos <= 0 or not np.isfinite(minpos):
+            raise ValueError(
+                "Data has no positive values, and therefore can not be "
+                "log-scaled.")
 
-            if vmin <= minpos:
-                vmin = minpos
+        if vmin <= minpos:
+            vmin = minpos
 
+        if rcParams['axes.autolimit_mode'] == 'round_numbers':
             if not is_decade(vmin, self._base):
                 vmin = decade_down(vmin, self._base)
             if not is_decade(vmax, self._base):