matplotlib
diff --git a/‎lib/matplotlib/mlab.py
Lines changed: 10 additions & 14 deletions b/‎lib/matplotlib/mlab.py
Lines changed: 10 additions & 14 deletions
diff --git a/‎lib/matplotlib/widgets.py
Lines changed: 4 additions & 4 deletions b/‎lib/matplotlib/widgets.py
Lines changed: 4 additions & 4 deletions
diff --git a/‎unit/legend_unit.py
Lines changed: 6 additions & 6 deletions b/‎unit/legend_unit.py
Lines changed: 6 additions & 6 deletions
@@ -2999,17 +2999,15 @@ def poly_below(xmin, xs, ys):
       ax.fill(xv, yv)
     """
     if ma.isMaskedArray(xs) or ma.isMaskedArray(ys):
-        nx = ma
-    else:
-        nx = np
+        np = ma
 
-    xs = nx.asarray(xs)
-    ys = nx.asarray(ys)
+    xs = np.asarray(xs)
+    ys = np.asarray(ys)
     Nx = len(xs)
     Ny = len(ys)
     assert(Nx==Ny)
-    x = xmin*nx.ones(2*Nx)
-    y = nx.ones(2*Nx)
+    x = xmin*np.ones(2*Nx)
+    y = np.ones(2*Nx)
     x[:Nx] = xs
     y[:Nx] = ys
     y[Nx:] = ys[::-1]
@@ -3028,19 +3026,17 @@ def poly_between(x, ylower, yupper):
     :meth:`matplotlib.axes.Axes.fill`.
     """
     if ma.isMaskedArray(ylower) or ma.isMaskedArray(yupper) or ma.isMaskedArray(x):
-        nx = ma
-    else:
-        nx = np
+        np = ma
 
     Nx = len(x)
     if not cbook.iterable(ylower):
-        ylower = ylower*nx.ones(Nx)
+        ylower = ylower*np.ones(Nx)
 
     if not cbook.iterable(yupper):
-        yupper = yupper*nx.ones(Nx)
+        yupper = yupper*np.ones(Nx)
 
-    x = nx.concatenate( (x, x[::-1]) )
-    y = nx.concatenate( (yupper, ylower[::-1]) )
+    x = np.concatenate( (x, x[::-1]) )
+    y = np.concatenate( (yupper, ylower[::-1]) )
     return x,y
 
 
 
@@ -827,11 +827,11 @@ class MultiCursor:
     Example usage::
 
         from matplotlib.widgets import MultiCursor
-        from pylab import figure, show, nx
+        from pylab import figure, show, np
 
-        t = nx.arange(0.0, 2.0, 0.01)
-        s1 = nx.sin(2*nx.pi*t)
-        s2 = nx.sin(4*nx.pi*t)
+        t = np.arange(0.0, 2.0, 0.01)
+        s1 = np.sin(2*np.pi*t)
         s2 = np.sin(4*np.pi*t)
         fig = figure()
         ax1 = fig.add_subplot(211)
         ax1.plot(t, s1)
 
@@ -1,22 +1,22 @@
 from __future__ import print_function
-from pylab import figure, show, nx
+from pylab import figure, show, np
 
 Ntests = 3
-t = nx.arange(0.0, 1.0, 0.05)
-s = nx.sin(2*nx.pi*t)
+t = np.arange(0.0, 1.0, 0.05)
+s = np.sin(2*np.pi*t)
 
 # scatter creates a RegPolyCollection
 fig = figure()
 ax = fig.add_subplot(Ntests, 1, 1)
 N = 100
-x, y = 0.9*nx.mlab.rand(2,N)
-area = nx.pi*(10 * nx.mlab.rand(N))**2 # 0 to 10 point radiuses
+x, y = 0.9*np.random.rand(2,N)
+area = np.pi*(10 * np.random.rand(N))**2 # 0 to 10 point radiuses
 ax.scatter(x,y,s=area, marker='^', c='r', label='scatter')
 ax.legend()
 
 # vlines creates a LineCollection
 ax = fig.add_subplot(Ntests, 1, 2)
-ax.vlines(t, [0], nx.sin(2*nx.pi*t), label='vlines')
+ax.vlines(t, [0], np.sin(2*np.pi*t), label='vlines')
 ax.legend()
 
 # vlines creates a LineCollection