Revision: 4191
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=4191&view=rev
Author:   efiring
Date:     2007-11-09 11:37:15 -0800 (Fri, 09 Nov 2007)

Log Message:
-----------
Remove numerix as nx from pylab

Modified Paths:
--------------
    trunk/matplotlib/examples/animation_blit_fltk.py
    trunk/matplotlib/examples/annotation_demo.py
    trunk/matplotlib/examples/barcode_demo.py
    trunk/matplotlib/examples/broken_barh.py
    trunk/matplotlib/examples/clippath_test.py
    trunk/matplotlib/examples/custom_figure_class.py
    trunk/matplotlib/examples/date_demo_convert.py
    trunk/matplotlib/examples/dynamic_collection.py
    trunk/matplotlib/examples/fill_demo2.py
    trunk/matplotlib/examples/gradient_bar.py
    trunk/matplotlib/examples/interp_demo.py
    trunk/matplotlib/examples/lasso_demo.py
    trunk/matplotlib/examples/pick_event_demo.py
    trunk/matplotlib/examples/scatter_custom_symbol.py
    trunk/matplotlib/examples/scatter_star_poly.py
    trunk/matplotlib/examples/spy_demos.py
    trunk/matplotlib/examples/xcorr_demo.py
    trunk/matplotlib/examples/zoom_window.py
    trunk/matplotlib/lib/matplotlib/pylab.py

Modified: trunk/matplotlib/examples/animation_blit_fltk.py
===================================================================
--- trunk/matplotlib/examples/animation_blit_fltk.py    2007-11-09 19:23:42 UTC 
(rev 4190)
+++ trunk/matplotlib/examples/animation_blit_fltk.py    2007-11-09 19:37:15 UTC 
(rev 4191)
@@ -3,7 +3,7 @@
 import matplotlib
 matplotlib.use('FltkAgg')
 import pylab as p
-import numpy as nx
+import numpy as npy
 import time
 
 
@@ -29,7 +29,7 @@
             self.background = self.canvas.copy_from_bbox(self.ax.bbox)
         self.canvas.restore_region(self.background)
         # update the data
-        line.set_ydata(nx.sin(x+self.cnt/10.0))
+        line.set_ydata(npy.sin(x+self.cnt/10.0))
         # just draw the animated artist
         self.ax.draw_artist(line)
         # just redraw the axes rectangle
@@ -45,8 +45,8 @@
 p.subplots_adjust(left=0.3, bottom=0.3) # check for flipy bugs
 p.grid() # to ensure proper background restore
 # create the initial line
-x = nx.arange(0,2*nx.pi,0.01)
-line, = p.plot(x, nx.sin(x), animated=True)
+x = npy.arange(0,2*npy.pi,0.01)
+line, = p.plot(x, npy.sin(x), animated=True)
 p.draw()
 anim=animator(ax)
 

Modified: trunk/matplotlib/examples/annotation_demo.py
===================================================================
--- trunk/matplotlib/examples/annotation_demo.py        2007-11-09 19:23:42 UTC 
(rev 4190)
+++ trunk/matplotlib/examples/annotation_demo.py        2007-11-09 19:37:15 UTC 
(rev 4191)
@@ -32,17 +32,19 @@
 """
 
 
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
 from matplotlib.patches import Ellipse
+import numpy as npy
 
+
 if 1:
     # if only one location is given, the text and xypoint being
     # annotated are assumed to be the same
     fig = figure()
     ax = fig.add_subplot(111, autoscale_on=False, xlim=(-1,5), ylim=(-3,5))
 
-    t = nx.arange(0.0, 5.0, 0.01)
-    s = nx.cos(2*nx.pi*t)
+    t = npy.arange(0.0, 5.0, 0.01)
+    s = npy.cos(2*npy.pi*t)
     line, = ax.plot(t, s, lw=3, color='purple')
 
     ax.annotate('axes center', xy=(.5, .5),  xycoords='axes fraction',
@@ -85,8 +87,8 @@
     # respected
     fig = figure()
     ax = fig.add_subplot(111, polar=True)
-    r = nx.arange(0,1,0.001)
-    theta = 2*2*nx.pi*r
+    r = npy.arange(0,1,0.001)
+    theta = 2*2*npy.pi*r
     line, = ax.plot(theta, r, color='#ee8d18', lw=3)
 
     ind = 800
@@ -115,8 +117,8 @@
     ax.add_artist(el)
     el.set_clip_box(ax.bbox)
     ax.annotate('the top',
-                xy=(nx.pi/2., 10.),      # theta, radius
-                xytext=(nx.pi/3, 20.),   # theta, radius
+                xy=(npy.pi/2., 10.),      # theta, radius
+                xytext=(npy.pi/3, 20.),   # theta, radius
                 xycoords='polar',
                 textcoords='polar',
                 arrowprops=dict(facecolor='black', shrink=0.05),

Modified: trunk/matplotlib/examples/barcode_demo.py
===================================================================
--- trunk/matplotlib/examples/barcode_demo.py   2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/barcode_demo.py   2007-11-09 19:37:15 UTC (rev 
4191)
@@ -1,14 +1,16 @@
-from pylab import figure, show, cm, nx
+from matplotlib.pyplot import figure, show, cm
+from numpy import where
+from numpy.random import rand
 
 # the bar
-x = nx.where(nx.mlab.rand(500)>0.7, 1.0, 0.0)
+x = where(rand(500)>0.7, 1.0, 0.0)
 
 axprops = dict(xticks=[], yticks=[])
 barprops = dict(aspect='auto', cmap=cm.binary, interpolation='nearest')
 
 fig = figure()
 
-# a vertical barcode
+# a vertical barcode -- this is broken at present
 x.shape = len(x), 1
 ax = fig.add_axes([0.1, 0.3, 0.1, 0.6], **axprops)
 ax.imshow(x, **barprops)

Modified: trunk/matplotlib/examples/broken_barh.py
===================================================================
--- trunk/matplotlib/examples/broken_barh.py    2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/broken_barh.py    2007-11-09 19:37:15 UTC (rev 
4191)
@@ -2,7 +2,7 @@
 """
 Make a "broken" horizontal bar plot, ie one with gaps
 """
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
 
 fig = figure()
 ax = fig.add_subplot(111)

Modified: trunk/matplotlib/examples/clippath_test.py
===================================================================
--- trunk/matplotlib/examples/clippath_test.py  2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/clippath_test.py  2007-11-09 19:37:15 UTC (rev 
4191)
@@ -1,9 +1,10 @@
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
 import matplotlib.transforms as transforms
 from matplotlib.patches import RegularPolygon
 import matplotlib.agg as agg
+from numpy import arange, sin, pi
+from numpy.random import rand
 
-
 class ClipWindow:
     def __init__(self, ax, line):
         self.ax = ax
@@ -58,9 +59,9 @@
 
 fig = figure(figsize=(8,8))
 ax = fig.add_subplot(111)
-t = nx.arange(0.0, 4.0, 0.01)
-s = 2*nx.sin(2*nx.pi*8*t)
+t = arange(0.0, 4.0, 0.01)
+s = 2*sin(2*pi*8*t)
 
-line, = ax.plot(t, 2*(nx.mlab.rand(len(t))-0.5), 'b-')
+line, = ax.plot(t, 2*(rand(len(t))-0.5), 'b-')
 clipwin = ClipWindow(ax, line)
 show()

Modified: trunk/matplotlib/examples/custom_figure_class.py
===================================================================
--- trunk/matplotlib/examples/custom_figure_class.py    2007-11-09 19:23:42 UTC 
(rev 4190)
+++ trunk/matplotlib/examples/custom_figure_class.py    2007-11-09 19:37:15 UTC 
(rev 4191)
@@ -1,7 +1,7 @@
 """
 You can pass a custom Figure constructor to figure if youy want to derive from 
the default Figure.  This simple example creates a figure with a figure title
 """
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
 from matplotlib.figure import Figure
 
 class MyFigure(Figure):

Modified: trunk/matplotlib/examples/date_demo_convert.py
===================================================================
--- trunk/matplotlib/examples/date_demo_convert.py      2007-11-09 19:23:42 UTC 
(rev 4190)
+++ trunk/matplotlib/examples/date_demo_convert.py      2007-11-09 19:37:15 UTC 
(rev 4191)
@@ -1,16 +1,16 @@
 #!/usr/bin/env python
 
 import datetime
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
 from matplotlib.dates import DayLocator, HourLocator, DateFormatter, drange
+from numpy import arange
 
-
 date1 = datetime.datetime( 2000, 3, 2)
 date2 = datetime.datetime( 2000, 3, 6)
 delta = datetime.timedelta(hours=6)
 dates = drange(date1, date2, delta)
 
-y = nx.arange( len(dates)*1.0)
+y = arange( len(dates)*1.0)
 
 fig = figure()
 ax = fig.add_subplot(111)
@@ -25,7 +25,7 @@
 # tick, not the base multiple
 
 ax.xaxis.set_major_locator( DayLocator() )
-ax.xaxis.set_minor_locator( HourLocator(nx.arange(0,25,6)) )
+ax.xaxis.set_minor_locator( HourLocator(arange(0,25,6)) )
 ax.xaxis.set_major_formatter( DateFormatter('%Y-%m-%d') )
 
 ax.fmt_xdata = DateFormatter('%Y-%m-%d %H:%M:%S')

Modified: trunk/matplotlib/examples/dynamic_collection.py
===================================================================
--- trunk/matplotlib/examples/dynamic_collection.py     2007-11-09 19:23:42 UTC 
(rev 4190)
+++ trunk/matplotlib/examples/dynamic_collection.py     2007-11-09 19:37:15 UTC 
(rev 4191)
@@ -1,7 +1,8 @@
 import random
 from matplotlib.collections import RegularPolyCollection
 import matplotlib.cm as cm
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
+from numpy.random import rand
 
 fig = figure()
 ax = fig.add_subplot(111, xlim=(0,1), ylim=(0,1), autoscale_on=False)
@@ -29,8 +30,8 @@
     press 'a' to add a random point from the collection, 'd' to delete one
     """
     if event.key=='a':
-        x,y = nx.mlab.rand(2)
-        color = cm.jet(nx.mlab.rand())
+        x,y = rand(2)
+        color = cm.jet(rand())
         offsets.append((x,y))
         facecolors.append(color)
         fig.canvas.draw()

Modified: trunk/matplotlib/examples/fill_demo2.py
===================================================================
--- trunk/matplotlib/examples/fill_demo2.py     2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/fill_demo2.py     2007-11-09 19:37:15 UTC (rev 
4191)
@@ -1,8 +1,10 @@
-from pylab import figure, nx, show
+from matplotlib.pyplot import figure, show
+from numpy import arange, sin, pi
+
 fig = figure()
 ax = fig.add_subplot(111)
-t = nx.arange(0.0,3.01,0.01)
-s = nx.sin(2*nx.pi*t)
-c = nx.sin(4*nx.pi*t)
+t = arange(0.0,3.01,0.01)
+s = sin(2*pi*t)
+c = sin(4*pi*t)
 ax.fill(t, s, 'b', t, c, 'g', alpha=0.2)
 show()

Modified: trunk/matplotlib/examples/gradient_bar.py
===================================================================
--- trunk/matplotlib/examples/gradient_bar.py   2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/gradient_bar.py   2007-11-09 19:37:15 UTC (rev 
4191)
@@ -1,4 +1,6 @@
-from pylab import figure, show, nx, cm
+from matplotlib.pyplot import figure, show, cm
+from numpy import arange
+from numpy.random import rand
 
 def gbar(ax, x, y, width=0.5, bottom=0):
    X = [[.6, .6],[.7,.7]]
@@ -19,8 +21,8 @@
          extent=(xmin, xmax, ymin, ymax), alpha=1)
 
 N = 10
-x = nx.arange(N)+0.25
-y = nx.mlab.rand(N)
+x = arange(N)+0.25
+y = rand(N)
 gbar(ax, x, y, width=0.7)
 ax.set_aspect('normal')
 show()

Modified: trunk/matplotlib/examples/interp_demo.py
===================================================================
--- trunk/matplotlib/examples/interp_demo.py    2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/interp_demo.py    2007-11-09 19:37:15 UTC (rev 
4191)
@@ -1,6 +1,9 @@
-from pylab import figure, show, nx, linspace, stineman_interp
-x = linspace(0,2*nx.pi,20);
-y = nx.sin(x); yp = None
+from matplotlib.pyplot import figure, show
+from numpy import pi, sin, linspace
+from matplotlib.mlab import stineman_interp
+
+x = linspace(0,2*pi,20);
+y = sin(x); yp = None
 xi = linspace(x[0],x[-1],100);
 yi = stineman_interp(xi,x,y,yp);
 

Modified: trunk/matplotlib/examples/lasso_demo.py
===================================================================
--- trunk/matplotlib/examples/lasso_demo.py     2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/lasso_demo.py     2007-11-09 19:37:15 UTC (rev 
4191)
@@ -13,7 +13,9 @@
 from matplotlib.colors import colorConverter
 from matplotlib.collections import RegularPolyCollection
 
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
+from numpy import nonzero
+from numpy.random import rand
 
 class Datum:
     colorin = colorConverter.to_rgba('red')
@@ -47,9 +49,7 @@
         self.cid = self.canvas.mpl_connect('button_press_event', self.onpress)
 
     def callback(self, verts):
-        #print 'all done', verts
-        #ind = matplotlib.mlab._inside_poly_deprecated(self.xys, verts)
-        ind = nx.nonzero(points_inside_poly(self.xys, verts))
+        ind = nonzero(points_inside_poly(self.xys, verts))[0]
         for i in range(self.Nxy):
             if i in ind:
                 self.facecolors[i] = Datum.colorin
@@ -66,7 +66,7 @@
         # acquire a lock on the widget drawing
         self.canvas.widgetlock(self.lasso)
 
-data = [Datum(*xy) for xy in nx.mlab.rand(100, 2)]
+data = [Datum(*xy) for xy in rand(100, 2)]
 
 fig = figure()
 ax = fig.add_subplot(111, xlim=(0,1), ylim=(0,1), autoscale_on=False)

Modified: trunk/matplotlib/examples/pick_event_demo.py
===================================================================
--- trunk/matplotlib/examples/pick_event_demo.py        2007-11-09 19:23:42 UTC 
(rev 4190)
+++ trunk/matplotlib/examples/pick_event_demo.py        2007-11-09 19:37:15 UTC 
(rev 4191)
@@ -63,23 +63,25 @@
 The examples below illustrate each of these methods.
 """
 
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
 from matplotlib.lines import Line2D
 from matplotlib.patches import Patch, Rectangle
 from matplotlib.text import Text
 from matplotlib.image import AxesImage
+import numpy as npy
+from numpy.random import rand
 
 if 1: # simple picking, lines, rectangles and text
     fig = figure()
     ax1 = fig.add_subplot(211)
     ax1.set_title('click on points, rectangles or text', picker=True)
     ax1.set_ylabel('ylabel', picker=True, bbox=dict(facecolor='red'))
-    line, = ax1.plot(nx.mlab.rand(100), 'o', picker=5)  # 5 points tolerance
+    line, = ax1.plot(rand(100), 'o', picker=5)  # 5 points tolerance
 
     # pick the rectangle
     ax2 = fig.add_subplot(212)
 
-    bars = ax2.bar(range(10), nx.mlab.rand(10), picker=True)
+    bars = ax2.bar(range(10), rand(10), picker=True)
     for label in ax2.get_xticklabels():  # make the xtick labels pickable
         label.set_picker(True)
 
@@ -90,7 +92,7 @@
             xdata = thisline.get_xdata()
             ydata = thisline.get_ydata()
             ind = event.ind
-            print 'onpick1 line:', zip(nx.take(xdata, ind), nx.take(ydata, 
ind))
+            print 'onpick1 line:', zip(npy.take(xdata, ind), npy.take(ydata, 
ind))
         elif isinstance(event.artist, Rectangle):
             patch = event.artist
             print 'onpick1 patch:', patch.get_verts()
@@ -122,12 +124,12 @@
         xdata = line.get_xdata()
         ydata = line.get_ydata()
         maxd = 0.05
-        d = nx.sqrt((xdata-mouseevent.xdata)**2. + 
(ydata-mouseevent.ydata)**2.)
+        d = npy.sqrt((xdata-mouseevent.xdata)**2. + 
(ydata-mouseevent.ydata)**2.)
 
-        ind = nx.nonzero(nx.less_equal(d, maxd))
+        ind = npy.nonzero(npy.less_equal(d, maxd))
         if len(ind):
-            pickx = nx.take(xdata, ind)
-            picky = nx.take(ydata, ind)
+            pickx = npy.take(xdata, ind)
+            picky = npy.take(ydata, ind)
             props = dict(ind=ind, pickx=pickx, picky=picky)
             return True, props
         else:
@@ -139,16 +141,16 @@
     fig = figure()
     ax1 = fig.add_subplot(111)
     ax1.set_title('custom picker for line data')
-    line, = ax1.plot(nx.mlab.rand(100), nx.mlab.rand(100), 'o', 
picker=line_picker)
+    line, = ax1.plot(rand(100), rand(100), 'o', picker=line_picker)
     fig.canvas.mpl_connect('pick_event', onpick2)
 
 
 if 1: # picking on a scatter plot 
(matplotlib.collections.RegularPolyCollection)
 
-    x, y, c, s = nx.mlab.rand(4, 100)
+    x, y, c, s = rand(4, 100)
     def onpick3(event):
         ind = event.ind
-        print 'onpick3 scatter:', ind, nx.take(x, ind), nx.take(y, ind)
+        print 'onpick3 scatter:', ind, npy.take(x, ind), npy.take(y, ind)
 
     fig = figure()
     ax1 = fig.add_subplot(111)
@@ -159,10 +161,10 @@
 if 1: # picking images (matplotlib.image.AxesImage)
     fig = figure()
     ax1 = fig.add_subplot(111)
-    im1 = ax1.imshow(nx.rand(10,5), extent=(1,2,1,2), picker=True)
-    im2 = ax1.imshow(nx.rand(5,10), extent=(3,4,1,2), picker=True)
-    im3 = ax1.imshow(nx.rand(20,25), extent=(1,2,3,4), picker=True)
-    im4 = ax1.imshow(nx.rand(30,12), extent=(3,4,3,4), picker=True)
+    im1 = ax1.imshow(rand(10,5), extent=(1,2,1,2), picker=True)
+    im2 = ax1.imshow(rand(5,10), extent=(3,4,1,2), picker=True)
+    im3 = ax1.imshow(rand(20,25), extent=(1,2,3,4), picker=True)
+    im4 = ax1.imshow(rand(30,12), extent=(3,4,3,4), picker=True)
     ax1.axis([0,5,0,5])
 
     def onpick4(event):

Modified: trunk/matplotlib/examples/scatter_custom_symbol.py
===================================================================
--- trunk/matplotlib/examples/scatter_custom_symbol.py  2007-11-09 19:23:42 UTC 
(rev 4190)
+++ trunk/matplotlib/examples/scatter_custom_symbol.py  2007-11-09 19:37:15 UTC 
(rev 4191)
@@ -1,12 +1,14 @@
-from pylab import figure, nx, show
+from matplotlib.pyplot import figure, show
+from numpy import arange, pi, cos, sin, pi
+from numpy.random import rand
 
 # unit area ellipse
 rx, ry = 3., 1.
-area = rx * ry * nx.pi
-theta = nx.arange(0, 2*nx.pi+0.01, 0.1)
-verts = zip(rx/area*nx.cos(theta), ry/area*nx.sin(theta))
+area = rx * ry * pi
+theta = arange(0, 2*pi+0.01, 0.1)
+verts = zip(rx/area*cos(theta), ry/area*sin(theta))
 
-x,y,s,c = nx.mlab.rand(4, 30)
+x,y,s,c = rand(4, 30)
 s*= 10**2.
 
 fig = figure()

Modified: trunk/matplotlib/examples/scatter_star_poly.py
===================================================================
--- trunk/matplotlib/examples/scatter_star_poly.py      2007-11-09 19:23:42 UTC 
(rev 4190)
+++ trunk/matplotlib/examples/scatter_star_poly.py      2007-11-09 19:37:15 UTC 
(rev 4191)
@@ -1,7 +1,7 @@
 import pylab
 
-x = pylab.nx.mlab.rand(10)
-y = pylab.nx.mlab.rand(10)
+x = pylab.rand(10)
+y = pylab.rand(10)
 
 pylab.subplot(321)
 pylab.scatter(x,y,s=80,marker=">")

Modified: trunk/matplotlib/examples/spy_demos.py
===================================================================
--- trunk/matplotlib/examples/spy_demos.py      2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/spy_demos.py      2007-11-09 19:37:15 UTC (rev 
4191)
@@ -2,7 +2,8 @@
 Plot the sparsity pattern of arrays
 """
 
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
+import numpy
 
 fig = figure()
 ax1 = fig.add_subplot(221)
@@ -10,7 +11,7 @@
 ax3 = fig.add_subplot(223)
 ax4 = fig.add_subplot(224)
 
-x = nx.mlab.randn(20,20)
+x = numpy.random.randn(20,20)
 x[5] = 0.
 x[:,12] = 0.
 

Modified: trunk/matplotlib/examples/xcorr_demo.py
===================================================================
--- trunk/matplotlib/examples/xcorr_demo.py     2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/xcorr_demo.py     2007-11-09 19:37:15 UTC (rev 
4191)
@@ -1,6 +1,7 @@
-from pylab import figure, show, nx
+from matplotlib.pylab import figure, show
+import numpy
 
-x,y = nx.mlab.randn(2,100)
+x,y = numpy.random.randn(2,100)
 fig = figure()
 ax1 = fig.add_subplot(211)
 ax1.xcorr(x, y, usevlines=True, maxlags=50, normed=True)
@@ -13,3 +14,4 @@
 ax2.axhline(0, color='black', lw=2)
 
 show()
+

Modified: trunk/matplotlib/examples/zoom_window.py
===================================================================
--- trunk/matplotlib/examples/zoom_window.py    2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/examples/zoom_window.py    2007-11-09 19:37:15 UTC (rev 
4191)
@@ -9,15 +9,17 @@
 Note the diameter of the circles in the scatter are defined in
 points**2, so their size is independent of the zoom
 """
-from pylab import figure, show, nx
+from matplotlib.pyplot import figure, show
+import numpy
 figsrc = figure()
 figzoom = figure()
 
 axsrc = figsrc.add_subplot(111, xlim=(0,1), ylim=(0,1), autoscale_on=False)
-axzoom = figzoom.add_subplot(111, xlim=(0.45,0.55), ylim=(0.4,.6), 
autoscale_on=False)
+axzoom = figzoom.add_subplot(111, xlim=(0.45,0.55), ylim=(0.4,.6),
+                                                    autoscale_on=False)
 axsrc.set_title('Click to zoom')
 axzoom.set_title('zoom window')
-x,y,s,c = nx.mlab.rand(4,200)
+x,y,s,c = numpy.random.rand(4,200)
 s *= 200
 
 

Modified: trunk/matplotlib/lib/matplotlib/pylab.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/pylab.py    2007-11-09 19:23:42 UTC (rev 
4190)
+++ trunk/matplotlib/lib/matplotlib/pylab.py    2007-11-09 19:37:15 UTC (rev 
4191)
@@ -202,8 +202,13 @@
 from cbook import flatten, is_string_like, exception_to_str, popd, \
      silent_list, iterable, enumerate, dedent
 
-import matplotlib.numerix as nx
 import numpy as npy
+# The masked array namespace is brought in as ma; getting
+# this from numerix allows one to select either numpy.ma or
+# Pierre G-M's maskedarray implementation, which may
+# replace the present numpy.ma implementation in a future
+# numpy release.
+from matplotlib.numerix import npyma as ma
 
 from matplotlib import mpl  # pulls in most modules
 


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