Raise tolerance on some tests

mdboom · mdboom · commit becc220c376c · 2015-12-09T21:18:05.000-05:00
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -1738,7 +1738,7 @@ def test_bxp_bad_positions():
     assert_raises(ValueError, ax.bxp, logstats, positions=[2, 3])
 
 
-@image_comparison(baseline_images=['boxplot', 'boxplot'])
+@image_comparison(baseline_images=['boxplot', 'boxplot'], tol=1)
 def test_boxplot():
     x = np.linspace(-7, 7, 140)
     x = np.hstack([-25, x, 25])
@@ -1797,7 +1797,7 @@ def _rc_test_bxp_helper(ax, rc_dict):
     return ax
 
 @image_comparison(baseline_images=['boxplot_rc_parameters'],
-                  savefig_kwarg={'dpi': 100}, remove_text=True)
+                  savefig_kwarg={'dpi': 100}, remove_text=True, tol=1)
 def test_boxplot_rc_parameters():
     fig, ax = plt.subplots(3)
 
@@ -2747,7 +2747,7 @@ def test_subplot_key_hash():
 
 @image_comparison(baseline_images=['specgram_freqs',
                                    'specgram_freqs_linear'],
-                  remove_text=True, extensions=['png'])
+                  remove_text=True, extensions=['png'], tol=0.01)
 def test_specgram_freqs():
     '''test axes.specgram in default (psd) mode with sinusoidal stimuli'''
     n = 10000
@@ -2800,7 +2800,7 @@ def test_specgram_freqs():
 
 @image_comparison(baseline_images=['specgram_noise',
                                    'specgram_noise_linear'],
-                  remove_text=True, extensions=['png'])
+                  remove_text=True, extensions=['png'], tol=0.01)
 def test_specgram_noise():
     '''test axes.specgram in default (psd) mode with noise stimuli'''
     np.random.seed(0)
@@ -2847,7 +2847,7 @@ def test_specgram_noise():
 
 @image_comparison(baseline_images=['specgram_magnitude_freqs',
                                    'specgram_magnitude_freqs_linear'],
-                  remove_text=True, extensions=['png'])
+                  remove_text=True, extensions=['png'], tol=0.01)
 def test_specgram_magnitude_freqs():
     '''test axes.specgram in magnitude mode with sinusoidal stimuli'''
     n = 10000
