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import numpy as np

P_D = np.array([0.6, 0.4])
P_I = np.array([0.7, 0.3])

P_G_ID = np.array([
    [[0.3, 0.05],
     [0.9, 0.5]],

    [[0.4, 0.25],

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_para1 = {'red': ((0.0, 0.019390722, 0.019390722), (0.125, 0.355334722,
                  0.355334722), (0.25, 0.565570631, 0.565570631), (0.375,
                  0.76583663, 0.76583663), (0.5, 0.966006412, 0.966006412),
                  (0.625, 0.953403586, 0.953403586), (0.75, 0.906621393,
                  0.906621393), (0.875, 0.831556904, 0.831556904), (1.0,
                  0.732691891, 0.732691891)),

          'green': ((0.0, 0.390501895, 0.390501895), (0.125, 0.524474908,
                    0.524474908), (0.25, 0.665714642, 0.665714642), (0.375,
                    0.813150205, 0.813150205), (0.5, 0.96603773, 0.96603773),

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from skimage import io, filter, morphology, segmentation, measure, img_as_float

import os

# Download the image

if not os.path.exists('cell.png'):
    print "Downloading snowflakes image..."
    import urllib2
    u = urllib2.urlopen('http://people.sc.fsu.edu/~jburkardt/data/tif/cell.png')

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*Vertddices     198
*Arcs
*Edges
       1       8        1
       1      24        1
       1      35        1
       1      42        1
       1      46        1
       1      60        1
       1      74        1

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$ git diff -w notebook.css
diff --git a/IPython/frontend/html/notebook/static/css/notebook.css b/IPython/frontend
index 9396bf7..55e3a64 100644
--- a/IPython/frontend/html/notebook/static/css/notebook.css
+++ b/IPython/frontend/html/notebook/static/css/notebook.css
@@ -311,6 +311,7 @@ div.text_cell_render {
 
 .CodeMirror {
     line-height: 1.231;  /* Changed from 1em to our global default */
+    font-family: Consolas;

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def my_boxplot(ax, positions, values, width=None, color=None, label=None):
    """Custom box plot to work around some of matplotlib's quirks.

    Parameters
    ----------
    ax : matplotlib axis
        Target axis.
    positions : (M,) ndarray of float
        Where to positions boxes on the x-axis.
    values : (M, N) ndarray of float

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