added a ganged plot example

svn path=/trunk/matplotlib/; revision=257

examples/ganged_plots.py

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+"""
+Top create plots that share a common axes (visually) you need to set
+the axes locations manually by supplying the appropriate axes
+rectangles.  Normally you'll want to turn off the tick labels on all
+but one of the axes.
+
+In this example the plots share a common xaxis but you can follow the
+same logic to supply a common y axis.
+"""
+from matplotlib.matlab import *
+
+t = arange(0.0, 2.0, 0.01)
+
+s1 = sin(2*pi*t)
+s2 = exp(-t)
+s3 = s1*s2
+
+# axes rect in relative 0,1 coords left, bottom, width, height.  Turn
+# off xtick labels on all but the lower plot
+ax1 = axes([0.1, 0.1,  0.8, 0.25])  # lower 
+ax2 = axes([0.1, 0.35, 0.8, 0.25])  # middle
+ax2.set_xticklabels([])              
+ax3 = axes([0.1, 0.6,  0.8, 0.25])  # upper
+ax3.set_xticklabels([])
+
+ax1.plot(t,s1)
+ax2.plot(t,s2)
+ax3.plot(t,s3)
+
+show()

examples/image_demo_na.py

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+from matplotlib import rcParams
+rcParams['numerix'] = 'numarray'
+
+from matplotlib.matlab import *
+
+
+def bivariate_normal(X, Y, sigmax=1.0, sigmay=1.0,
+                     mux=0.0, muy=0.0, sigmaxy=0.0):
+    """
+    Bivariate gaussan distribution for equal shape X, Y
+
+    http://mathworld.wolfram.com/BivariateNormalDistribution.html
+    """
+    Xmu = X-mux
+    Ymu = Y-muy
+
+    rho = sigmaxy/(sigmax*sigmay)
+    z = Xmu**2/sigmax**2 + Ymu**2/sigmay - 2*rho*Xmu*Ymu/(sigmax*sigmay)
+    return 1.0/(2*pi*sigmax*sigmay*(1-rho**2)) * exp( -z/(2*(1-rho**2)))
+
+
+delta = 0.025
+x = arange(-3.0, 3.0, delta)
+y = arange(-3.0, 3.0, delta)
+X,Y = meshgrid(x, y)
+Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
+Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
+
+# difference of Gaussians
+im = imshow(Z2-Z1)
+
+# set the interpolation method: 'nearest', 'bilinear', 'bicubic' and much more
+im.set_interpolation('bilinear')
+
+
+axis('off')
+#savefig('test')
+show()
+