CLN: more plotting test cleanups

pandas/tests/test_graphics.py

@@ -29,17 +29,11 @@ def _skip_if_no_scipy():
         raise nose.SkipTest
 
 
+@tm.mplskip
 class TestSeriesPlots(unittest.TestCase):
-    @classmethod
-    def setUpClass(cls):
-        try:
-            import matplotlib as mpl
-            mpl.use('Agg', warn=False)
-            cls.mpl_le_1_2_1 = str(mpl.__version__) <= LooseVersion('1.2.1')
-        except ImportError:
-            raise nose.SkipTest("matplotlib not installed")
-
     def setUp(self):
+        import matplotlib as mpl
+        self.mpl_le_1_2_1 = str(mpl.__version__) <= LooseVersion('1.2.1')
         self.ts = tm.makeTimeSeries()
         self.ts.name = 'ts'
 
@@ -50,8 +44,7 @@ def setUp(self):
         self.iseries.name = 'iseries'
 
     def tearDown(self):
-        import matplotlib.pyplot as plt
-        plt.close('all')
+        tm.close()
 
     @slow
     def test_plot(self):
@@ -352,24 +345,14 @@ def test_dup_datetime_index_plot(self):
         _check_plot_works(s.plot)
 
 
+@tm.mplskip
 class TestDataFramePlots(unittest.TestCase):
-
-    @classmethod
-    def setUpClass(cls):
-        # import sys
-        # if 'IPython' in sys.modules:
-        #    raise nose.SkipTest
-
-        try:
-            import matplotlib as mpl
-            mpl.use('Agg', warn=False)
-            cls.mpl_le_1_2_1 = str(mpl.__version__) <= LooseVersion('1.2.1')
-        except ImportError:
-            raise nose.SkipTest("matplotlib not installed")
+    def setUp(self):
+        import matplotlib as mpl
+        self.mpl_le_1_2_1 = str(mpl.__version__) <= LooseVersion('1.2.1')
 
     def tearDown(self):
-        import matplotlib.pyplot as plt
-        plt.close('all')
+        tm.close()
 
     @slow
     def test_plot(self):
@@ -949,19 +932,10 @@ def test_invalid_kind(self):
             df.plot(kind='aasdf')
 
 
+@tm.mplskip
 class TestDataFrameGroupByPlots(unittest.TestCase):
-    @classmethod
-    def setUpClass(cls):
-        try:
-            import matplotlib as mpl
-            mpl.use('Agg', warn=False)
-        except ImportError:
-            raise nose.SkipTest
-
     def tearDown(self):
-        import matplotlib.pyplot as plt
-        for fignum in plt.get_fignums():
-            plt.close(fignum)
+        tm.close()
 
     @slow
     def test_boxplot(self):
@@ -999,13 +973,16 @@ def test_time_series_plot_color_with_empty_kwargs(self):
         import matplotlib as mpl
 
         def_colors = mpl.rcParams['axes.color_cycle']
+        index = date_range('1/1/2000', periods=12)
+        s = Series(np.arange(1, 13), index=index)
+
+        ncolors = 3
 
-        for i in range(3):
-            ax = Series(np.arange(12) + 1, index=date_range('1/1/2000',
-                                                            periods=12)).plot()
+        for i in range(ncolors):
+            ax = s.plot()
 
         line_colors = [l.get_color() for l in ax.get_lines()]
-        self.assertEqual(line_colors, def_colors[:3])
+        self.assertEqual(line_colors, def_colors[:ncolors])
 
     @slow
     def test_grouped_hist(self):
@@ -1155,27 +1132,30 @@ def _check_plot_works(f, *args, **kwargs):
     import matplotlib.pyplot as plt
 
     try:
-        fig = kwargs['figure']
-    except KeyError:
-        fig = plt.gcf()
-    plt.clf()
-    ax = kwargs.get('ax', fig.add_subplot(211))
-    ret = f(*args, **kwargs)
+        try:
+            fig = kwargs['figure']
+        except KeyError:
+            fig = plt.gcf()
 
-    assert ret is not None
-    assert_is_valid_plot_return_object(ret)
+        plt.clf()
 
-    try:
-        kwargs['ax'] = fig.add_subplot(212)
+        ax = kwargs.get('ax', fig.add_subplot(211))
         ret = f(*args, **kwargs)
-    except Exception:
-        pass
-    else:
+
         assert_is_valid_plot_return_object(ret)
 
-    with ensure_clean() as path:
-        plt.savefig(path)
-    plt.close(fig)
+        try:
+            kwargs['ax'] = fig.add_subplot(212)
+            ret = f(*args, **kwargs)
+        except Exception:
+            pass
+        else:
+            assert_is_valid_plot_return_object(ret)
+
+        with ensure_clean() as path:
+            plt.savefig(path)
+    finally:
+        tm.close(fig)
 
 
 def curpath():

pandas/tests/test_rplot.py

@@ -8,16 +8,11 @@
 import nose
 
 
-try:
-    import matplotlib.pyplot as plt
-except:
-    raise nose.SkipTest
-
-
 def curpath():
     pth, _ = os.path.split(os.path.abspath(__file__))
     return pth
 
+
 def between(a, b, x):
     """Check if x is in the somewhere between a and b.
 
@@ -36,6 +31,8 @@ def between(a, b, x):
     else:
         return x <= a and x >= b
 
+
+@tm.mplskip
 class TestUtilityFunctions(unittest.TestCase):
     """
     Tests for RPlot utility functions.
@@ -74,24 +71,25 @@ def test_dictionary_union(self):
         self.assertTrue(2 in keys)
         self.assertTrue(3 in keys)
         self.assertTrue(4 in keys)
-        self.assertTrue(rplot.dictionary_union(dict1, {}) == dict1)
-        self.assertTrue(rplot.dictionary_union({}, dict1) == dict1)
-        self.assertTrue(rplot.dictionary_union({}, {}) == {})
+        self.assertEqual(rplot.dictionary_union(dict1, {}), dict1)
+        self.assertEqual(rplot.dictionary_union({}, dict1), dict1)
+        self.assertEqual(rplot.dictionary_union({}, {}), {})
 
     def test_merge_aes(self):
         layer1 = rplot.Layer(size=rplot.ScaleSize('test'))
         layer2 = rplot.Layer(shape=rplot.ScaleShape('test'))
         rplot.merge_aes(layer1, layer2)
         self.assertTrue(isinstance(layer2.aes['size'], rplot.ScaleSize))
         self.assertTrue(isinstance(layer2.aes['shape'], rplot.ScaleShape))
-        self.assertTrue(layer2.aes['size'] == layer1.aes['size'])
+        self.assertEqual(layer2.aes['size'], layer1.aes['size'])
         for key in layer2.aes.keys():
             if key != 'size' and key != 'shape':
                 self.assertTrue(layer2.aes[key] is None)
 
     def test_sequence_layers(self):
         layer1 = rplot.Layer(self.data)
-        layer2 = rplot.GeomPoint(x='SepalLength', y='SepalWidth', size=rplot.ScaleSize('PetalLength'))
+        layer2 = rplot.GeomPoint(x='SepalLength', y='SepalWidth',
+                                 size=rplot.ScaleSize('PetalLength'))
         layer3 = rplot.GeomPolyFit(2)
         result = rplot.sequence_layers([layer1, layer2, layer3])
         self.assertEqual(len(result), 3)
@@ -102,6 +100,8 @@ def test_sequence_layers(self):
         self.assertTrue(self.data is last.data)
         self.assertTrue(rplot.sequence_layers([layer1])[0] is layer1)
 
+
+@tm.mplskip
 class TestTrellis(unittest.TestCase):
     def setUp(self):
         path = os.path.join(curpath(), 'data/tips.csv')
@@ -148,11 +148,15 @@ def test_trellis_cols_rows(self):
         self.assertEqual(self.trellis3.cols, 2)
         self.assertEqual(self.trellis3.rows, 1)
 
+
+@tm.mplskip
 class TestScaleGradient(unittest.TestCase):
     def setUp(self):
         path = os.path.join(curpath(), 'data/iris.csv')
         self.data = read_csv(path, sep=',')
-        self.gradient = rplot.ScaleGradient("SepalLength", colour1=(0.2, 0.3, 0.4), colour2=(0.8, 0.7, 0.6))
+        self.gradient = rplot.ScaleGradient("SepalLength", colour1=(0.2, 0.3,
+                                                                    0.4),
+                                            colour2=(0.8, 0.7, 0.6))
 
     def test_gradient(self):
         for index in range(len(self.data)):
@@ -164,6 +168,8 @@ def test_gradient(self):
             self.assertTrue(between(g1, g2, g))
             self.assertTrue(between(b1, b2, b))
 
+
+@tm.mplskip
 class TestScaleGradient2(unittest.TestCase):
     def setUp(self):
         path = os.path.join(curpath(), 'data/iris.csv')
@@ -190,6 +196,8 @@ def test_gradient2(self):
                 self.assertTrue(between(g2, g3, g))
                 self.assertTrue(between(b2, b3, b))
 
+
+@tm.mplskip
 class TestScaleRandomColour(unittest.TestCase):
     def setUp(self):
         path = os.path.join(curpath(), 'data/iris.csv')
@@ -208,13 +216,16 @@ def test_random_colour(self):
             self.assertTrue(g <= 1.0)
             self.assertTrue(b <= 1.0)
 
+
+@tm.mplskip
 class TestScaleConstant(unittest.TestCase):
     def test_scale_constant(self):
         scale = rplot.ScaleConstant(1.0)
         self.assertEqual(scale(None, None), 1.0)
         scale = rplot.ScaleConstant("test")
         self.assertEqual(scale(None, None), "test")
 
+
 class TestScaleSize(unittest.TestCase):
     def setUp(self):
         path = os.path.join(curpath(), 'data/iris.csv')
@@ -235,8 +246,10 @@ def f():
         self.assertRaises(ValueError, f)
 
 
+@tm.mplskip
 class TestRPlot(unittest.TestCase):
     def test_rplot1(self):
+        import matplotlib.pyplot as plt
         path = os.path.join(curpath(), 'data/tips.csv')
         plt.figure()
         self.data = read_csv(path, sep=',')
@@ -247,6 +260,7 @@ def test_rplot1(self):
         self.plot.render(self.fig)
 
     def test_rplot2(self):
+        import matplotlib.pyplot as plt
         path = os.path.join(curpath(), 'data/tips.csv')
         plt.figure()
         self.data = read_csv(path, sep=',')
@@ -257,6 +271,7 @@ def test_rplot2(self):
         self.plot.render(self.fig)
 
     def test_rplot3(self):
+        import matplotlib.pyplot as plt
         path = os.path.join(curpath(), 'data/tips.csv')
         plt.figure()
         self.data = read_csv(path, sep=',')
@@ -267,6 +282,7 @@ def test_rplot3(self):
         self.plot.render(self.fig)
 
     def test_rplot_iris(self):
+        import matplotlib.pyplot as plt
         path = os.path.join(curpath(), 'data/iris.csv')
         plt.figure()
         self.data = read_csv(path, sep=',')
@@ -277,5 +293,6 @@ def test_rplot_iris(self):
         self.fig = plt.gcf()
         plot.render(self.fig)
 
+
 if __name__ == '__main__':
     unittest.main()

pandas/tseries/tests/test_plotting.py

@@ -26,16 +26,8 @@ def _skip_if_no_scipy():
         raise nose.SkipTest
 
 
+@tm.mplskip
 class TestTSPlot(unittest.TestCase):
-
-    @classmethod
-    def setUpClass(cls):
-        try:
-            import matplotlib as mpl
-            mpl.use('Agg', warn=False)
-        except ImportError:
-            raise nose.SkipTest
-
     def setUp(self):
         freq = ['S', 'T', 'H', 'D', 'W', 'M', 'Q', 'Y']
         idx = [period_range('12/31/1999', freq=x, periods=100) for x in freq]
@@ -52,9 +44,7 @@ def setUp(self):
                             for x in idx]
 
     def tearDown(self):
-        import matplotlib.pyplot as plt
-        for fignum in plt.get_fignums():
-            plt.close(fignum)
+        tm.close()
 
     @slow
     def test_ts_plot_with_tz(self):

pandas/util/testing.py

@@ -18,6 +18,8 @@
 from numpy.random import randn, rand
 import numpy as np
 
+import nose
+
 from pandas.core.common import isnull, _is_sequence
 import pandas.core.index as index
 import pandas.core.series as series
@@ -70,6 +72,31 @@ def choice(x, size=10):
     except AttributeError:
         return np.random.randint(len(x), size=size).choose(x)
 
+
+def close(fignum=None):
+    from matplotlib.pyplot import get_fignums, close as _close
+
+    if fignum is None:
+        for fignum in get_fignums():
+            _close(fignum)
+    else:
+        _close(fignum)
+
+
+def mplskip(cls):
+    """Skip a TestCase instance if matplotlib isn't installed"""
+    @classmethod
+    def setUpClass(cls):
+        try:
+            import matplotlib as mpl
+            mpl.use("Agg", warn=False)
+        except ImportError:
+            raise nose.SkipTest("matplotlib not installed")
+
+    cls.setUpClass = setUpClass
+    return cls
+
+
 #------------------------------------------------------------------------------
 # Console debugging tools