@@ -1,21 +1,19 @@
-from pylab import *
 import numpy as np
+import matplotlib.pyplot as plt
 from matplotlib.transforms import Bbox
 from matplotlib.path import Path
-from matplotlib.patches import Rectangle
 
-rect = Rectangle((-1, -1), 2, 2, facecolor="#aaaaaa")
-gca().add_patch(rect)
+rect = plt.Rectangle((-1, -1), 2, 2, facecolor="#aaaaaa")
+plt.gca().add_patch(rect)
 bbox = Bbox.from_bounds(-1, -1, 2, 2)
 
 for i in range(12):
-    vertices = (np.random.random((4, 2)) - 0.5) * 6.0
-    vertices = np.ma.masked_array(vertices, [[False, False], [True, True], [False, False], [False, False]])
+    vertices = (np.random.random((2, 2)) - 0.5) * 6.0
     path = Path(vertices)
     if path.intersects_bbox(bbox):
         color = 'r'
     else:
         color = 'b'
-    plot(vertices[:,0], vertices[:,1], color=color)
+    plt.plot(vertices[:,0], vertices[:,1], color=color)
 
-show()
+plt.show()
@@ -3,7 +3,6 @@
 """
 import numpy as np
 import matplotlib.pyplot as plt
-import matplotlib.path as path
 import matplotlib.patches as patches
 
 
 
@@ -17,31 +17,31 @@
 
 '''
 
-import matplotlib.pyplot as P
-from matplotlib import collections, axes, transforms
+import matplotlib.pyplot as plt
+from matplotlib import collections, transforms
 from matplotlib.colors import colorConverter
-import numpy as N
+import numpy as np
 
 nverts = 50
 npts = 100
 
 # Make some spirals
-r = N.array(range(nverts))
-theta = N.array(range(nverts)) * (2*N.pi)/(nverts-1)
-xx = r * N.sin(theta)
-yy = r * N.cos(theta)
+r = np.array(range(nverts))
+theta = np.array(range(nverts)) * (2*np.pi)/(nverts-1)
+xx = r * np.sin(theta)
+yy = r * np.cos(theta)
 spiral = list(zip(xx,yy))
 
 # Make some offsets
-rs = N.random.RandomState([12345678])
+rs = np.random.RandomState([12345678])
 xo = rs.randn(npts)
 yo = rs.randn(npts)
 xyo = list(zip(xo, yo))
 
 # Make a list of colors cycling through the rgbcmyk series.
 colors = [colorConverter.to_rgba(c) for c in ('r','g','b','c','y','m','k')]
 
-fig = P.figure()
+fig = plt.figure()
 
 a = fig.add_subplot(2,2,1)
 col = collections.LineCollection([spiral], offsets=xyo,
@@ -88,7 +88,7 @@
 a = fig.add_subplot(2,2,3)
 
 col = collections.RegularPolyCollection(7,
-                                        sizes = N.fabs(xx)*10.0, offsets=xyo,
+                                        sizes = np.fabs(xx)*10.0, offsets=xyo,
                                         transOffset=a.transData)
 trans = transforms.Affine2D().scale(fig.dpi/72.0)
 col.set_transform(trans)  # the points to pixels transform
@@ -108,9 +108,9 @@
 ncurves = 20
 offs = (0.1, 0.0)
 
-yy = N.linspace(0, 2*N.pi, nverts)
-ym = N.amax(yy)
-xx = (0.2 + (ym-yy)/ym)**2 * N.cos(yy-0.4) * 0.5
+yy = np.linspace(0, 2*np.pi, nverts)
+ym = np.amax(yy)
+xx = (0.2 + (ym-yy)/ym)**2 * np.cos(yy-0.4) * 0.5
 segs = []
 for i in range(ncurves):
     xxx = xx + 0.02*rs.randn(nverts)
@@ -128,6 +128,6 @@
 a.set_ylim(a.get_ylim()[::-1])
 
 
-P.show()
+plt.show()
 
 
@@ -1,11 +1,10 @@
 from __future__ import unicode_literals
+
 from matplotlib.axes import Axes
-from matplotlib import cbook
 from matplotlib.patches import Circle
 from matplotlib.path import Path
-from matplotlib.ticker import Formatter, Locator, NullLocator, FixedLocator, NullFormatter
-from matplotlib.transforms import Affine2D, Affine2DBase, Bbox, \
-    BboxTransformTo, IdentityTransform, Transform, TransformWrapper
+from matplotlib.ticker import NullLocator, Formatter, FixedLocator
+from matplotlib.transforms import Affine2D, BboxTransformTo, Transform
 from matplotlib.projections import register_projection
 import matplotlib.spines as mspines
 import matplotlib.axis as maxis
@@ -309,7 +308,7 @@ class -- it provides a more convenient interface to set the
         # by degrees.
         number = (360.0 / degrees) + 1
         self.xaxis.set_major_locator(
-            FixedLocator(
+            plt.FixedLocator(
                 np.linspace(-np.pi, np.pi, number, True)[1:-1]))
         # Set the formatter to display the tick labels in degrees,
         # rather than radians.
@@ -447,11 +446,12 @@ def inverted(self):
 # it.
 register_projection(HammerAxes)
 
-# Now make a simple example using the custom projection.
-from pylab import *
+if __name__ == '__main__':
+    import matplotlib.pyplot as plt
+    # Now make a simple example using the custom projection.
+    plt.subplot(111, projection="custom_hammer")
+    p = plt.plot([-1, 1, 1], [-1, -1, 1], "o-")
+    plt.grid(True)
 
-subplot(111, projection="custom_hammer")
-p = plot([-1, 1, 1], [-1, -1, 1], "o-")
-grid(True)
+    plt.show()
 
-show()
@@ -1,6 +1,11 @@
 from __future__ import unicode_literals
+
+import numpy as np
+from numpy import ma
 from matplotlib import scale as mscale
 from matplotlib import transforms as mtransforms
+from matplotlib.ticker import Formatter, FixedLocator
+
 
 class MercatorLatitudeScale(mscale.ScaleBase):
     """
@@ -149,18 +154,20 @@ def inverted(self):
 # that ``matplotlib`` can find it.
 mscale.register_scale(MercatorLatitudeScale)
 
-from pylab import *
-import numpy as np
 
-t = arange(-180.0, 180.0, 0.1)
-s = t / 360.0 * np.pi
+if __name__ == '__main__':
+    import matplotlib.pyplot as plt
+
+    t = np.arange(-180.0, 180.0, 0.1)
+    s = t / 360.0 * np.pi
+
+    plt.plot(t, s, '-', lw=2)
+    plt.gca().set_yscale('mercator')
 
-plot(t, s, '-', lw=2)
-gca().set_yscale('mercator')
+    plt.xlabel('Longitude')
+    plt.ylabel('Latitude')
+    plt.title('Mercator: Projection of the Oppressor')
+    plt.grid(True)
 
-xlabel('Longitude')
-ylabel('Latitude')
-title('Mercator: Projection of the Oppressor')
-grid(True)
+    plt.show()
 
-show()
 
@@ -13,10 +13,8 @@
 """
 import datetime
 import numpy as np
-import matplotlib
 import matplotlib.pyplot as plt
 import matplotlib.dates as mdates
-import matplotlib.mlab as mlab
 import matplotlib.cbook as cbook
 
 years    = mdates.YearLocator()   # every year
 
@@ -6,8 +6,6 @@
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 import matplotlib.cm as cm
-import matplotlib.mlab as mlab
-from pylab import rand
 
 mpl.rcParams['xtick.labelsize'] = 10
 mpl.rcParams['ytick.labelsize'] = 12
 
@@ -1,26 +1,28 @@
+import numpy as np
 import matplotlib
 from matplotlib.patches import Circle, Wedge, Polygon
 from matplotlib.collections import PatchCollection
-import pylab
+import matplotlib.pyplot as plt
 
-fig=pylab.figure()
+
+fig=plt.figure()
 ax=fig.add_subplot(111)
 
 resolution = 50 # the number of vertices
 N = 3
-x       = pylab.rand(N)
-y       = pylab.rand(N)
-radii   = 0.1*pylab.rand(N)
+x       = np.random.rand(N)
+y       = np.random.rand(N)
+radii   = 0.1*np.random.rand(N)
 patches = []
 for x1,y1,r in zip(x, y, radii):
     circle = Circle((x1,y1), r)
     patches.append(circle)
 
-x       = pylab.rand(N)
-y       = pylab.rand(N)
-radii   = 0.1*pylab.rand(N)
-theta1  = 360.0*pylab.rand(N)
-theta2  = 360.0*pylab.rand(N)
+x       = np.random.rand(N)
+y       = np.random.rand(N)
+radii   = 0.1*np.random.rand(N)
+theta1  = 360.0*np.random.rand(N)
+theta2  = 360.0*np.random.rand(N)
 for x1,y1,r,t1,t2 in zip(x, y, radii, theta1, theta2):
     wedge = Wedge((x1,y1), r, t1, t2)
     patches.append(wedge)
@@ -34,13 +36,13 @@
 ]
 
 for i in range(N):
-    polygon = Polygon(pylab.rand(N,2), True)
+    polygon = Polygon(np.random.rand(N,2), True)
     patches.append(polygon)
 
-colors = 100*pylab.rand(len(patches))
+colors = 100*np.random.rand(len(patches))
 p = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
-p.set_array(pylab.array(colors))
+p.set_array(np.array(colors))
 ax.add_collection(p)
-pylab.colorbar(p)
+plt.colorbar(p)
 
-pylab.show()
+plt.show()
@@ -5,7 +5,7 @@
 __author__ = "Yannick Copin <ycopin@ipnl.in2p3.fr>"
 __version__ = "Time-stamp: <10/02/2010 16:49 ycopin@lyopc548.in2p3.fr>"
 
-import numpy as N
+import numpy as np
 
 def sankey(ax,
            outputs=[100.], outlabels=None,
@@ -30,19 +30,19 @@ def sankey(ax,
     import matplotlib.patches as mpatches
     from matplotlib.path import Path
 
-    outs = N.absolute(outputs)
-    outsigns = N.sign(outputs)
+    outs = np.absolute(outputs)
+    outsigns = np.sign(outputs)
     outsigns[-1] = 0 # Last output
 
-    ins = N.absolute(inputs)
-    insigns = N.sign(inputs)
+    ins = np.absolute(inputs)
+    insigns = np.sign(inputs)
     insigns[0] = 0 # First input
 
     assert sum(outs)==100, "Outputs don't sum up to 100%"
     assert sum(ins)==100, "Inputs don't sum up to 100%"
 
     def add_output(path, loss, sign=1):
-        h = (loss/2+w)*N.tan(outangle/180.*N.pi) # Arrow tip height
+        h = (loss/2+w)*np.tan(outangle/180.*np.pi) # Arrow tip height
         move,(x,y) = path[-1] # Use last point as reference
         if sign==0: # Final loss (horizontal)
             path.extend([(Path.LINETO,[x+dx,y]),
@@ -64,7 +64,7 @@ def add_output(path, loss, sign=1):
             outtips.append((sign,path[-5][1]))
 
     def add_input(path, gain, sign=1):
-        h = (gain/2)*N.tan(inangle/180.*N.pi) # Dip depth
+        h = (gain/2)*np.tan(inangle/180.*np.pi) # Dip depth
         move,(x,y) = path[-1] # Use last point as reference
         if sign==0: # First gain (horizontal)
             path.extend([(Path.LINETO,[x-dx,y]),
@@ -109,7 +109,7 @@ def revert(path):
     path = urpath + revert(lrpath) + llpath + revert(ulpath)
 
     codes,verts = zip(*path)
-    verts = N.array(verts)
+    verts = np.array(verts)
 
     # Path patch
     path = Path(verts,codes)
@@ -168,15 +168,15 @@ def put_labels(labels,positions,output=True):
 
 if __name__=='__main__':
 
-    import matplotlib.pyplot as P
+    import matplotlib.pyplot as plt
 
     outputs = [10.,-20.,5.,15.,-10.,40.]
     outlabels = ['First','Second','Third','Fourth','Fifth','Hurray!']
     outlabels = [ s+'\n%d%%' % abs(l) for l,s in zip(outputs,outlabels) ]
 
     inputs = [60.,-25.,15.]
 
-    fig = P.figure()
+    fig = plt.figure()
     ax = fig.add_subplot(1,1,1, xticks=[],yticks=[],
                          title="Sankey diagram"
                          )
@@ -187,5 +187,5 @@ def put_labels(labels,positions,output=True):
     outtexts[1].set_color('r')
     outtexts[-1].set_fontweight('bold')
 
-    P.show()
+    plt.show()
 
@@ -1,17 +1,6 @@
 import numpy as np
-from pylab import figure, show
 
 
-X = np.random.rand(100, 200)
-xs = np.mean(X, axis=1)
-ys = np.std(X, axis=1)
-
-fig = figure()
-ax = fig.add_subplot(211)
-ax.set_title('click on point to plot time series')
-line, = ax.plot(xs, ys, 'o', picker=5)  # 5 points tolerance
-ax2 = fig.add_subplot(212)
-
 class PointBrowser:
     """
     Click on a point to select and highlight it -- the data that
@@ -74,9 +63,23 @@ def update(self):
         fig.canvas.draw()
 
 
-browser = PointBrowser()
+if __name__ == '__main__':
+    import matplotlib.pyplot as plt
+
+    X = np.random.rand(100, 200)
+    xs = np.mean(X, axis=1)
+    ys = np.std(X, axis=1)
+
+    fig = plt.figure()
+    ax = fig.add_subplot(211)
+    ax.set_title('click on point to plot time series')
+    line, = ax.plot(xs, ys, 'o', picker=5)  # 5 points tolerance
+    ax2 = fig.add_subplot(212)
+
+    browser = PointBrowser()
+
+    fig.canvas.mpl_connect('pick_event', browser.onpick)
+    fig.canvas.mpl_connect('key_press_event', browser.onpress)
 
-fig.canvas.mpl_connect('pick_event', browser.onpick)
-fig.canvas.mpl_connect('key_press_event', browser.onpress)
+    plt.show()
 
-show()