@@ -126,6 +126,7 @@
                                 cycler)
 
 import numpy
+import numpy.ma
 from matplotlib.externals.six.moves.urllib.request import urlopen
 from matplotlib.externals.six.moves import reload_module as reload
 
 
@@ -5387,7 +5387,7 @@ def pcolor(self, *args, **kwargs):
 
         if t and any(t.contains_branch_seperately(self.transData)):
             trans_to_data = t - self.transData
-            pts = np.vstack([x, y]).T.astype(np.float)
+            pts = np.vstack([x, y]).T.astype(float)
             transformed_pts = trans_to_data.transform(pts)
             x = transformed_pts[..., 0]
             y = transformed_pts[..., 1]
@@ -5537,7 +5537,7 @@ def pcolormesh(self, *args, **kwargs):
 
         if t and any(t.contains_branch_seperately(self.transData)):
             trans_to_data = t - self.transData
-            pts = np.vstack([X, Y]).T.astype(np.float)
+            pts = np.vstack([X, Y]).T.astype(float)
             transformed_pts = trans_to_data.transform(pts)
             X = transformed_pts[..., 0]
             Y = transformed_pts[..., 1]
 
@@ -12,7 +12,6 @@
 from operator import itemgetter
 
 import numpy as np
-from numpy import ma
 
 import matplotlib
 
@@ -1917,7 +1916,7 @@ def update_datalim(self, xys, updatex=True, updatey=True):
 
         if iterable(xys) and not len(xys):
             return
-        if not ma.isMaskedArray(xys):
+        if not isinstance(xys, np.ma.MaskedArray):
             xys = np.asarray(xys)
         self.dataLim.update_from_data_xy(xys, self.ignore_existing_data_limits,
                                          updatex=updatex, updatey=updatey)
 
@@ -12,10 +12,7 @@
 def _fn_name(): return sys._getframe(1).f_code.co_name
 import io
 
-try:
-    from hashlib import md5
-except ImportError:
-    from md5 import md5 #Deprecated in 2.5
+from hashlib import md5
 
 from tempfile import mkstemp
 from matplotlib import verbose, __version__, rcParams, checkdep_ghostscript
@@ -44,10 +41,6 @@ def _fn_name(): return sys._getframe(1).f_code.co_name
 import numpy as np
 import binascii
 import re
-try:
-    set
-except NameError:
-    from sets import Set as set
 
 if sys.platform.startswith('win'): cmd_split = '&'
 else: cmd_split = ';'
 
@@ -31,7 +31,6 @@
 from weakref import ref, WeakKeyDictionary
 
 import numpy as np
-import numpy.ma as ma
 
 
 class MatplotlibDeprecationWarning(UserWarning):
@@ -677,7 +676,7 @@ def is_string_like(obj):
     if isinstance(obj, six.string_types):
         return True
     # numpy strings are subclass of str, ma strings are not
-    if ma.isMaskedArray(obj):
+    if isinstance(obj, np.ma.MaskedArray):
         if obj.ndim == 0 and obj.dtype.kind in 'SU':
             return True
         else:
@@ -1728,7 +1727,7 @@ def delete_masked_points(*args):
     for i, x in enumerate(args):
         if (not is_string_like(x)) and iterable(x) and len(x) == nrecs:
             seqlist[i] = True
-            if ma.isMA(x):
+            if isinstance(x, np.ma.MaskedArray):
                 if x.ndim > 1:
                     raise ValueError("Masked arrays must be 1-D")
             else:
@@ -1739,8 +1738,8 @@ def delete_masked_points(*args):
         if seqlist[i]:
             if x.ndim > 1:
                 continue  # Don't try to get nan locations unless 1-D.
-            if ma.isMA(x):
-                masks.append(~ma.getmaskarray(x))  # invert the mask
+            if isinstance(x, np.ma.MaskedArray):
+                masks.append(~np.ma.getmaskarray(x))  # invert the mask
                 xd = x.data
             else:
                 xd = x
@@ -1758,7 +1757,7 @@ def delete_masked_points(*args):
                 if seqlist[i]:
                     margs[i] = x.take(igood, axis=0)
     for i, x in enumerate(margs):
-        if seqlist[i] and ma.isMA(x):
+        if seqlist[i] and isinstance(x, np.ma.MaskedArray):
             margs[i] = x.filled()
     return margs
 
@@ -2344,7 +2343,7 @@ def pts_to_poststep(x, *args):
     # do normalization
     vertices = _step_validation(x, *args)
     # create the output array
-    steps = ma.zeros((vertices.shape[0], 2 * len(x) - 1), np.float)
+    steps = np.zeros((vertices.shape[0], 2 * len(x) - 1), np.float)
     # do the to step conversion logic
     steps[0, ::2], steps[0, 1:-1:2] = vertices[0, :], vertices[0, 1:]
     steps[1:, 0::2], steps[1:, 1::2] = vertices[1:, :], vertices[1:, :-1]
@@ -2385,7 +2384,7 @@ def pts_to_midstep(x, *args):
     # do normalization
     vertices = _step_validation(x, *args)
     # create the output array
-    steps = ma.zeros((vertices.shape[0], 2 * len(x)), np.float)
+    steps = np.zeros((vertices.shape[0], 2 * len(x)), np.float)
     steps[0, 1:-1:2] = 0.5 * (vertices[0, :-1] + vertices[0, 1:])
     steps[0, 2::2] = 0.5 * (vertices[0, :-1] + vertices[0, 1:])
     steps[0, 0] = vertices[0, 0]
 
@@ -15,7 +15,6 @@
 from matplotlib.externals.six.moves import zip
 import warnings
 import numpy as np
-import numpy.ma as ma
 import matplotlib as mpl
 import matplotlib.cbook as cbook
 import matplotlib.colors as mcolors
@@ -199,7 +198,7 @@ def get_datalim(self, transData):
             transOffset = transOffset.get_affine()
 
         offsets = np.asanyarray(offsets, np.float_)
-        if np.ma.isMaskedArray(offsets):
+        if isinstance(offsets, np.ma.MaskedArray):
             offsets = offsets.filled(np.nan)
             # get_path_collection_extents handles nan but not masked arrays
         offsets.shape = (-1, 2)                     # Make it Nx2
@@ -252,7 +251,7 @@ def _prepare_points(self):
             # This might have changed an ndarray into a masked array.
             transOffset = transOffset.get_affine()
 
-        if np.ma.isMaskedArray(offsets):
+        if isinstance(offsets, np.ma.MaskedArray):
             offsets = offsets.filled(np.nan)
             # Changing from a masked array to nan-filled ndarray
             # is probably most efficient at this point.
@@ -875,14 +874,14 @@ def __init__(self, verts, sizes=None, closed=True, **kwargs):
 
     def set_verts(self, verts, closed=True):
         '''This allows one to delay initialization of the vertices.'''
-        if np.ma.isMaskedArray(verts):
-            verts = verts.astype(np.float_).filled(np.nan)
+        if isinstance(verts, np.ma.MaskedArray):
+            verts = verts.astype(float).filled(np.nan)
             # This is much faster than having Path do it one at a time.
         if closed:
             self._paths = []
             for xy in verts:
                 if len(xy):
-                    if np.ma.isMaskedArray(xy):
+                    if isinstance(xy, np.ma.MaskedArray):
                         xy = np.ma.concatenate([xy, xy[0:1]])
                     else:
                         xy = np.asarray(xy)
@@ -1162,7 +1161,7 @@ def set_segments(self, segments):
         _segments = []
 
         for seg in segments:
-            if not np.ma.isMaskedArray(seg):
+            if not isinstance(seg, np.ma.MaskedArray):
                 seg = np.asarray(seg, np.float_)
             _segments.append(seg)
 
@@ -1779,7 +1778,7 @@ def convert_mesh_to_paths(meshWidth, meshHeight, coordinates):
         """
         Path = mpath.Path
 
-        if ma.isMaskedArray(coordinates):
+        if isinstance(coordinates, np.ma.MaskedArray):
             c = coordinates.data
         else:
             c = coordinates
@@ -1800,7 +1799,7 @@ def convert_mesh_to_triangles(self, meshWidth, meshHeight, coordinates):
         with its own color.  This is useful for experiments using
         `draw_qouraud_triangle`.
         """
-        if ma.isMaskedArray(coordinates):
+        if isinstance(coordinates, np.ma.MaskedArray):
             p = coordinates.data
         else:
             p = coordinates
 
@@ -891,12 +891,12 @@ def process_value(value):
                 # (list, tuple, deque, ndarray, Series, ...)
                 result = result.copy()
             elif result.dtype.itemsize > 2:
-                result = result.astype(np.float)
+                result = result.astype(float)
             else:
                 result = result.astype(np.float32)
         else:
             is_scalar = True
-            result = ma.array([value]).astype(np.float)
+            result = ma.array([value]).astype(float)
         return result, is_scalar
 
     def __call__(self, value, clip=None):
@@ -1121,7 +1121,7 @@ def _transform_vmin_vmax(self):
         Calculates vmin and vmax in the transformed system.
         """
         vmin, vmax = self.vmin, self.vmax
-        arr = np.array([vmax, vmin]).astype(np.float)
+        arr = np.array([vmax, vmin]).astype(float)
         self._upper, self._lower = self._transform(arr)
 
     def inverse(self, value):
 
@@ -48,10 +48,6 @@
 
 import json
 import os, sys, warnings
-try:
-    set
-except NameError:
-    from sets import Set as set
 from collections import Iterable
 import matplotlib
 from matplotlib import afm
 
@@ -12,7 +12,6 @@
 import warnings
 
 import numpy as np
-from numpy import ma
 from matplotlib import verbose
 from . import artist, colors as mcolors
 from .artist import Artist
@@ -628,17 +627,17 @@ def recache_always(self):
     def recache(self, always=False):
         if always or self._invalidx:
             xconv = self.convert_xunits(self._xorig)
-            if ma.isMaskedArray(self._xorig):
-                x = ma.asarray(xconv, np.float_).filled(np.nan)
+            if isinstance(self._xorig, np.ma.MaskedArray):
+                x = np.ma.asarray(xconv, np.float_).filled(np.nan)
             else:
                 x = np.asarray(xconv, np.float_)
             x = x.ravel()
         else:
             x = self._x
         if always or self._invalidy:
             yconv = self.convert_yunits(self._yorig)
-            if ma.isMaskedArray(self._yorig):
-                y = ma.asarray(yconv, np.float_).filled(np.nan)
+            if isinstance(self._yorig, np.ma.MaskedArray):
+                y = np.ma.asarray(yconv, np.float_).filled(np.nan)
             else:
                 y = np.asarray(yconv, np.float_)
             y = y.ravel()
 
@@ -22,10 +22,6 @@
 import os, sys
 from matplotlib.externals.six import unichr
 from math import ceil
-try:
-    set
-except NameError:
-    from sets import Set as set
 import unicodedata
 from warnings import warn