Adjust documentation and test formatting

chelseatroy · chelseatroy · commit bdcaab552a9a · 2017-01-17T17:40:48.000-06:00
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -5923,7 +5923,7 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
 
             Default is ``None``
 
-        normed or density : boolean, optional
+        normed, density : boolean, optional
             Either the 'normed' or the 'density' arg can be set to
             accomplish this behavior:
 
@@ -5945,19 +5945,21 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
         weights : (n, ) array_like or None, optional
             An array of weights, of the same shape as `x`.  Each value in `x`
             only contributes its associated weight towards the bin count
-            (instead of 1).  If `normed` and/or 'density' is True, the weights are normalized,
-            so that the integral of the density over the range remains 1.
+            (instead of 1).  If `normed` and/or 'density' is True,
+            the weights are normalized, so that the integral of the density
+            over the range remains 1.
 
             Default is ``None``
 
         cumulative : boolean, optional
             If `True`, then a histogram is computed where each bin gives the
             counts in that bin plus all bins for smaller values. The last bin
-            gives the total number of datapoints.  If `normed` and/or 'density' is also `True`
-            then the histogram is normalized such that the last bin equals 1.
-            If `cumulative` evaluates to less than 0 (e.g., -1), the direction
-            of accumulation is reversed.  In this case, if `normed` and/or 'density' is also
-            `True`, then the histogram is normalized such that the first bin
+            gives the total number of datapoints. If `normed` and/or 'density'
+            is also `True` then the histogram is normalized such that the last
+            bin equals 1. If `cumulative` evaluates to less than 0 (e.g., -1),
+            the direction of accumulation is reversed.  In this case, if
+            `normed` and/or 'density' is also `True`, then the histogram is
+            normalized such that the first bin
             equals 1.
 
             Default is ``False``
@@ -6077,12 +6079,14 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
 
         """
 
-        # This sets the density variable, if necessary, to its predecessor, 'normed.'
-        if density != None and normed != None and density != normed:
-            raise ValueError('The density and normed arguments represent the same concept. Please set only one of them, or set them to the same value.')
-        elif normed != None and density == None:
+        # Sets the density variable, if necessary, to its predecessor, 'normed.'
+        if density is not None and normed is not None and density is not normed:
+            raise ValueError('The density and normed arguments represent the '
+                             'same concept. Please set only one of them, or '
+                             'set them to the same value.')
+        elif normed is not None and density is None:
             density = normed
-        elif normed == None and density == None:
+        elif normed is None and density is None:
             density = False
 
         def _normalize_input(inp, ename='input'):
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -2541,13 +2541,13 @@ def test_hist_stacked_normed():
     ax = fig.add_subplot(111)
     ax.hist((d1, d2), stacked=True, normed=True)
 
+
 @image_comparison(baseline_images=['hist_stacked_normed'])
 def test_hist_stacked_density():
     # make some data
     d1 = np.linspace(1, 3, 20)
     d2 = np.linspace(0, 10, 50)
-    fig = plt.figure()
-    ax = fig.add_subplot(111)
+    fig, ax = plt.subplots()
     ax.hist((d1, d2), stacked=True, density=True)
 
     with pytest.raises(ValueError):
@@ -3274,6 +3274,10 @@ def test_specgram_angle_freqs():
                       noverlap=noverlap, pad_to=pad_to, sides='onesided',
                       mode='phase', scale='dB')
 
+    with pytest.raises(ValueError):
+        ax13.specgram(y, NFFT=NFFT, Fs=Fs,
+                      noverlap=noverlap, pad_to=pad_to, sides='twosided',
+                      mode='phase', scale='dB')
 
 
 @image_comparison(baseline_images=['specgram_angle_noise'],
