more pep8 failures to hide under the rug.

matplotlib · pizzathief · Oct 31, 2015 · Nov 4, 2015 · Nov 4, 2015 · Nov 4, 2015
commit 50b0e0af04721b64b27c09f2d82b42646cc604a8
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -32,6 +32,7 @@
 #       different baseline images to prevent race conditions when nose runs
 #       the tests with multiple threads.
 
+
 @image_comparison(baseline_images=['formatter_ticker_001',
                                    'formatter_ticker_002',
                                    'formatter_ticker_003',
@@ -105,7 +106,8 @@ def test_twin_axis_locaters_formatters():
     ax1.yaxis.set_major_locator(majl)
     ax1.yaxis.set_minor_locator(minl)
     ax1.yaxis.set_major_formatter(plt.FormatStrFormatter('%08.2lf'))
-    ax1.yaxis.set_minor_formatter(plt.FixedFormatter(['tricks', 'mind', 'jedi']))
+    ax1.yaxis.set_minor_formatter(plt.FixedFormatter(
+        ['tricks', 'mind', 'jedi']))
 
     ax1.xaxis.set_major_locator(plt.LinearLocator())
     ax1.xaxis.set_minor_locator(plt.FixedLocator([15, 35, 55, 75]))
@@ -139,7 +141,8 @@ def test_twinx_cla():
     assert ax.yaxis.get_visible()
 
 
-@image_comparison(baseline_images=["minorticks_on_rcParams_both"], extensions=['png'])
+@image_comparison(baseline_images=["minorticks_on_rcParams_both"],
+                  extensions=['png'])
 def test_minorticks_on_rcParams_both():
     fig = plt.figure()
     matplotlib.rcParams['xtick.minor.visible'] = True
@@ -322,26 +325,27 @@ def test_single_date():
 
 @image_comparison(baseline_images=['shaped_data'])
 def test_shaped_data():
-    xdata = np.array([[0.53295185,  0.23052951,  0.19057629,  0.66724975,  0.96577916,
-                       0.73136095,  0.60823287,  0.01792100,  0.29744742,  0.27164665],
-                      [0.27980120,  0.25814229,  0.02818193,  0.12966456,  0.57446277,
-                       0.58167607,  0.71028245,  0.69112737,  0.89923072,  0.99072476],
-                      [0.81218578,  0.80464528,  0.76071809,  0.85616314,  0.12757994,
-                       0.94324936,  0.73078663,  0.09658102,  0.60703967,  0.77664978],
-                      [0.28332265,  0.81479711,  0.86985333,  0.43797066,  0.32540082,
-                       0.43819229,  0.92230363,  0.49414252,  0.68168256,  0.05922372],
-                      [0.10721335,  0.93904142,  0.79163075,  0.73232848,  0.90283839,
-                       0.68408046,  0.25502302,  0.95976614,  0.59214115,  0.13663711],
-                      [0.28087456,  0.33127607,  0.15530412,  0.76558121,  0.83389773,
-                       0.03735974,  0.98717738,  0.71432229,  0.54881366,  0.86893953],
-                      [0.77995937,  0.99555600,  0.29688434,  0.15646162,  0.05184800,
-                       0.37161935,  0.12998491,  0.09377296,  0.36882507,  0.36583435],
-                      [0.37851836,  0.05315792,  0.63144617,  0.25003433,  0.69586032,
-                       0.11393988,  0.92362096,  0.88045438,  0.93530252,  0.68275072],
-                      [0.86486596,  0.83236675,  0.82960664,  0.57796630,  0.25724233,
-                       0.84841095,  0.90862812,  0.64414887,  0.35652720,  0.71026066],
-                      [0.01383268,  0.34060930,  0.76084285,  0.70800694,  0.87634056,
-                       0.08213693,  0.54655021,  0.98123181,  0.44080053,  0.86815815]])
+    xdata = np.array(
+        [[0.53295185,  0.23052951,  0.19057629,  0.66724975,  0.96577916,
+          0.73136095,  0.60823287,  0.01792100,  0.29744742,  0.27164665],
+         [0.27980120,  0.25814229,  0.02818193,  0.12966456,  0.57446277,
+          0.58167607,  0.71028245,  0.69112737,  0.89923072,  0.99072476],
+         [0.81218578,  0.80464528,  0.76071809,  0.85616314,  0.12757994,
+          0.94324936,  0.73078663,  0.09658102,  0.60703967,  0.77664978],
+         [0.28332265,  0.81479711,  0.86985333,  0.43797066,  0.32540082,
+          0.43819229,  0.92230363,  0.49414252,  0.68168256,  0.05922372],
+         [0.10721335,  0.93904142,  0.79163075,  0.73232848,  0.90283839,
+          0.68408046,  0.25502302,  0.95976614,  0.59214115,  0.13663711],
+         [0.28087456,  0.33127607,  0.15530412,  0.76558121,  0.83389773,
+          0.03735974,  0.98717738,  0.71432229,  0.54881366,  0.86893953],
+         [0.77995937,  0.99555600,  0.29688434,  0.15646162,  0.05184800,
+          0.37161935,  0.12998491,  0.09377296,  0.36882507,  0.36583435],
+         [0.37851836,  0.05315792,  0.63144617,  0.25003433,  0.69586032,
+          0.11393988,  0.92362096,  0.88045438,  0.93530252,  0.68275072],
+         [0.86486596,  0.83236675,  0.82960664,  0.57796630,  0.25724233,
+          0.84841095,  0.90862812,  0.64414887,  0.35652720,  0.71026066],
+         [0.01383268,  0.34060930,  0.76084285,  0.70800694,  0.87634056,
+          0.08213693,  0.54655021,  0.98123181,  0.44080053,  0.86815815]])
 
     y1 = np.arange(10)
     y1.shape = 1, 10
@@ -428,7 +432,7 @@ def test_polar_units():
     y1 = [y*km for y in y1]
     plt.polar(x2, y1, color="blue", thetaunits="rad", runits="km")
     assert isinstance(plt.gca().get_xaxis().get_major_formatter(),
-                      units.UnitDblFormatter)  == True
+                      units.UnitDblFormatter) == True
 
 
 @image_comparison(baseline_images=['polar_rmin'])
@@ -524,7 +528,7 @@ def test_hexbin_extent():
 
 
 @image_comparison(baseline_images=['hexbin_empty'], remove_text=True,
-	extensions=['png'])
+    extensions=['png'])
 def test_hexbin_empty():
     # From #3886: creating hexbin from empty dataset raises ValueError
     ax = plt.gca()
@@ -592,7 +596,10 @@ def test_inverted_limits():
 @image_comparison(baseline_images=['nonfinite_limits'])
 def test_nonfinite_limits():
     x = np.arange(0., np.e, 0.01)
-    olderr = np.seterr(divide='ignore')  # silence divide by zero warning from log(0)
+
+    # silence divide by zero warning from log(0)
+    olderr = np.seterr(divide='ignore')
+
     try:
         y = np.log(x)
     finally:
@@ -620,7 +627,7 @@ def test_imshow():
     ax.imshow(r)
 
     # Reuse testcase from above for a labeled data test
-    data={"r": r}
+    data = {"r": r}
     fig = plt.figure()
     ax = fig.add_subplot(111)
     ax.imshow("r", data=data)
@@ -679,17 +686,21 @@ def test_fill_between_interpolate():
     fig = plt.figure()
     ax = fig.add_subplot(211)
     ax.plot(x, y1, x, y2, color='black')
-    ax.fill_between(x, y1, y2, where=y2 >= y1, facecolor='white', hatch='/', interpolate=True)
-    ax.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red', interpolate=True)
+    ax.fill_between(x, y1, y2, where=y2 >= y1, facecolor='white',
+                    hatch='/', interpolate=True)
+    ax.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red',
+                    interpolate=True)
 
     # Test support for masked arrays.
     y2 = np.ma.masked_greater(y2, 1.0)
     # Test that plotting works for masked arrays with the first element masked
     y2[0] = np.ma.masked
     ax1 = fig.add_subplot(212, sharex=ax)
     ax1.plot(x, y1, x, y2, color='black')
-    ax1.fill_between(x, y1, y2, where=y2 >= y1, facecolor='green', interpolate=True)
-    ax1.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red', interpolate=True)
+    ax1.fill_between(x, y1, y2, where=y2 >= y1, facecolor='green',
+                     interpolate=True)
+    ax1.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red',
+                     interpolate=True)
 
 
 @image_comparison(baseline_images=['symlog'])
@@ -884,7 +895,8 @@ def test_arc_ellipse():
 
     fig = plt.figure()
     ax = fig.add_subplot(211, aspect='auto')
-    ax.fill(x, y, alpha=0.2, facecolor='yellow', edgecolor='yellow', linewidth=1, zorder=1)
+    ax.fill(x, y, alpha=0.2, facecolor='yellow', edgecolor='yellow',
+            linewidth=1, zorder=1)
 
     e1 = patches.Arc((xcenter, ycenter), width, height,
                      angle=angle, linewidth=2, fill=False, zorder=2)
@@ -1111,20 +1123,23 @@ def test_hist_log():
 
 
 @image_comparison(baseline_images=['hist_bar_empty'], remove_text=True,
-	extensions=['png'])
+    extensions=['png'])
 def test_hist_bar_empty():
     # From #3886: creating hist from empty dataset raises ValueError
     ax = plt.gca()
     ax.hist([], histtype='bar')
 
+
 @image_comparison(baseline_images=['hist_step_empty'], remove_text=True,
-	extensions=['png'])
+    extensions=['png'])
 def test_hist_step_empty():
     # From #3886: creating hist from empty dataset raises ValueError
     ax = plt.gca()
     ax.hist([], histtype='step')
 
-@image_comparison(baseline_images=['hist_steplog'], remove_text=True, tol=0.05)
+
+@image_comparison(baseline_images=['hist_steplog'], remove_text=True,
+                  tol=0.05)
 def test_hist_steplog():
     np.random.seed(0)
     data = np.random.standard_normal(2000)
@@ -1143,7 +1158,8 @@ def test_hist_steplog():
     plt.hist(data, 100, weights=weights, histtype='stepfilled', log=True)
 
     ax = plt.subplot(4, 1, 4)
-    plt.hist(data_big, 100, histtype='stepfilled', log=True, orientation='horizontal')
+    plt.hist(data_big, 100, histtype='stepfilled', log=True,
+             orientation='horizontal')
 
 
 @image_comparison(baseline_images=['hist_step_log_bottom'],
@@ -1316,7 +1332,8 @@ def _as_mpl_axes(self):
     ax_via_gca = plt.gca(projection=prj2)
     assert ax_via_gca is not ax
     assert ax.get_theta_offset() == 0, ax.get_theta_offset()
-    assert ax_via_gca.get_theta_offset() == np.pi, ax_via_gca.get_theta_offset()
+    assert ax_via_gca.get_theta_offset() == \
+           np.pi, ax_via_gca.get_theta_offset()
     # try getting the axes given an == (not is) polar projection
     ax_via_gca = plt.gca(projection=prj3)
     assert ax_via_gca is ax
@@ -1353,7 +1370,7 @@ def test_stackplot():
     ax.set_ylim((0, 70))
 
     # Reuse testcase from above for a labeled data test
-    data={"x": x, "y1": y1, "y2": y2, "y3": y3}
+    data = {"x": x, "y1": y1, "y2": y2, "y3": y3}
     fig = plt.figure()
     ax = fig.add_subplot(1, 1, 1)
     ax.stackplot("x", "y1", "y2", "y3", data=data)
@@ -1754,7 +1771,7 @@ def test_boxplot():
     ax.set_ylim((-30, 30))
 
     # Reuse testcase from above for a labeled data test
-    data={"x": [x, x]}
+    data = {"x": [x, x]}
     fig, ax = plt.subplots()
     ax.boxplot("x", bootstrap=10000, notch=1, data=data)
     ax.set_ylim((-30, 30))
@@ -1795,13 +1812,15 @@ def test_boxplot_autorange_whiskers():
     ax.boxplot([x, x], bootstrap=10000, notch=1)
     ax.set_ylim((-5, 5))
 
+
 def _rc_test_bxp_helper(ax, rc_dict):
     x = np.linspace(-7, 7, 140)
     x = np.hstack([-25, x, 25])
     with matplotlib.rc_context(rc_dict):
         ax.boxplot([x, x])
     return ax
 
+
 @image_comparison(baseline_images=['boxplot_rc_parameters'],
                   savefig_kwarg={'dpi': 100}, remove_text=True, tol=1)
 def test_boxplot_rc_parameters():
@@ -2181,7 +2200,6 @@ def test_errorbar():
 
     fig.suptitle('Variable errorbars')
 
-
     # Reuse te first testcase from above for a labeled data test
     data = {"x": x, "y": y}
     fig = plt.figure()
@@ -2285,7 +2303,8 @@ def test_hist_offset():
     ax.hist(d2, bottom=15)
 
 
-@image_comparison(baseline_images=['hist_step'], extensions=['png'], remove_text=True)
+@image_comparison(baseline_images=['hist_step'], extensions=['png'],
+                  remove_text=True)
 def test_hist_step():
     # make some data
     d1 = np.linspace(1, 3, 20)
@@ -2376,7 +2395,8 @@ def test_hist_stacked_normed():
     ax.hist((d1, d2), stacked=True, normed=True)
 
 
-@image_comparison(baseline_images=['hist_step_bottom'], extensions=['png'], remove_text=True)
+@image_comparison(baseline_images=['hist_step_bottom'],
+                  extensions=['png'], remove_text=True)
 def test_hist_step_bottom():
     # make some data
     d1 = np.linspace(1, 3, 20)
@@ -2399,7 +2419,8 @@ def test_hist_stacked_bar():
     labels = ['green', 'orange', ' yellow', 'magenta', 'black']
     fig = plt.figure()
     ax = fig.add_subplot(111)
-    ax.hist(d, bins=10, histtype='barstacked', align='mid', color=colors, label=labels)
+    ax.hist(d, bins=10, histtype='barstacked', align='mid',
+            color=colors, label=labels)
     ax.legend(loc='upper right', bbox_to_anchor=(1.0, 1.0), ncol=1)
 
 
@@ -2436,6 +2457,7 @@ def test_rgba_markers():
     for ax in axs:
         ax.axis([-1, 4, 0, 5])
 
+
 @image_comparison(baseline_images=['mollweide_grid'], remove_text=True)
 def test_mollweide_grid():
     # test that both horizontal and vertical gridlines appear on the Mollweide
@@ -2568,7 +2590,8 @@ def test_eventplot():
     np.testing.assert_equal(num_collections, num_datasets)
 
 
-@image_comparison(baseline_images=['test_eventplot_defaults'], extensions=['png'], remove_text=True)
+@image_comparison(baseline_images=['test_eventplot_defaults'],
+                  extensions=['png'], remove_text=True)
 def test_eventplot_defaults():
     '''
     test that eventplot produces the correct output given the default params
@@ -2585,7 +2608,8 @@ def test_eventplot_defaults():
     colls = axobj.eventplot(data)
 
 
-@image_comparison(baseline_images=['test_eventplot_problem_kwargs'], extensions=['png'], remove_text=True)
+@image_comparison(baseline_images=['test_eventplot_problem_kwargs'],
+                  extensions=['png'], remove_text=True)
 def test_eventplot_problem_kwargs():
     '''
     test that 'singular' versions of LineCollection props raise an
@@ -2623,14 +2647,16 @@ def test_empty_eventplot():
     plt.draw()
 
 
-@image_comparison(baseline_images=['marker_styles'], extensions=['png'], remove_text=True)
+@image_comparison(baseline_images=['marker_styles'], extensions=['png'],
+                  remove_text=True)
 def test_marker_styles():
     fig = plt.figure()
     ax = fig.add_subplot(111)
-    for y, marker in enumerate(sorted(matplotlib.markers.MarkerStyle.markers.keys(),
-                                      key=lambda x: str(type(x))+str(x))):
-        ax.plot((y % 2)*5 + np.arange(10)*10, np.ones(10)*10*y, linestyle='', marker=marker,
-                markersize=10+y/5, label=marker)
+    for y, marker in enumerate(
+            sorted(matplotlib.markers.MarkerStyle.markers.keys(),
+                   key=lambda x: str(type(x))+str(x))):
+        ax.plot((y % 2)*5 + np.arange(10)*10, np.ones(10)*10*y, linestyle='',
+                marker=marker, markersize=10+y/5, label=marker)
 
 
 @image_comparison(baseline_images=['rc_markerfill'], extensions=['png'])
@@ -3632,8 +3658,8 @@ def make_patch_spines_invisible(ax):
     # placed on the right by twinx above.
     par2.spines["right"].set_position(("axes", 1.2))
     # Having been created by twinx, par2 has its frame off, so the line of its
-    # detached spine is invisible.  First, activate the frame but make the patch
-    # and spines invisible.
+    # detached spine is invisible.  First, activate the frame but make the
+    # patch and spines invisible.
     make_patch_spines_invisible(par2)
     # Second, show the right spine.
     par2.spines["right"].set_visible(True)
@@ -3813,7 +3839,7 @@ def test_pie_center_radius():
     labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
     sizes = [15, 30, 45, 10]
     colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
-    explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'Hogs')
+    explode = (0, 0.1, 0, 0)  # only "explode" the 2nd slice (i.e. 'Hogs')
 
     plt.pie(sizes, explode=explode, labels=labels, colors=colors,
             autopct='%1.1f%%', shadow=True, startangle=90,
@@ -3899,10 +3925,11 @@ def test_set_get_ticklabels():
     ax[0].set_xticklabels(('a', 'b', 'c', 'd'))
     ax[0].set_yticklabels(('11', '12', '13', '14'))
 
-    # set ticklabel to the other plot, expect the 2 plots have same label setting
+    # set ticklabel to the other plot, expect the 2 plots have
+    # same label setting
     # pass get_ticklabels return value as ticklabels argument
-    ax[1].set_xticklabels(ax[0].get_xticklabels() )
-    ax[1].set_yticklabels(ax[0].get_yticklabels() )
+    ax[1].set_xticklabels(ax[0].get_xticklabels())
+    ax[1].set_yticklabels(ax[0].get_yticklabels())
 
 
 @image_comparison(baseline_images=['o_marker_path_snap'], extensions=['png'],