How can I add textures to my bars and wedges?

Question

I\'m drawing several bar and pie charts using matplotlib.pyplot.bar() and matplotlib.pyplot.pie(). In both functions, I can change the colors of the bars and wedges.

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Answer 1

import matplotlib.pyplot as plt

fig = plt.figure()

patterns = [ "/" , "\\" , "|" , "-" , "+" , "x", "o", "O", ".", "*" ]

ax1 = fig.add_subplot(111)
for i in range(len(patterns)):
    ax1.bar(i, 3, color='red', edgecolor='black', hatch=patterns[i])


plt.show()

It's in the documentation here.

Okay - so to texture a piechart, you need to do this:

if you look here:

Return value:
If autopct is None, return the tuple (patches, texts):

patches is a sequence of matplotlib.patches.Wedge instances
texts is a list of the label matplotlib.text.Text instances.

so then we look at the Wedges page, and see that it has a set_hatch() method.

so we just need to add a few lines to the piechart demo and...

Example 1:

import matplotlib.pyplot as plt

fig = plt.figure()

patterns = [ "/" , "\\" , "|" , "-" , "+" , "x", "o", "O", ".", "*" ]

ax1 = fig.add_subplot(111)
for i in range(len(patterns)):
    ax1.bar(i, 3, color='red', edgecolor='black', hatch=patterns[i])


plt.show()

Example 2:

"""
Make a pie chart - see
http://matplotlib.sf.net/matplotlib.pylab.html#-pie for the docstring.

This example shows a basic pie chart with labels optional features,
like autolabeling the percentage, offsetting a slice with "explode",
adding a shadow, and changing the starting angle.

"""

from pylab import *
import math
import numpy as np

patterns = [ "/" , "\\" , "|" , "-" , "+" , "x", "o", "O", ".", "*" ]


def little_pie(breakdown,location,size):
    breakdown = [0] + list(np.cumsum(breakdown)* 1.0 / sum(breakdown))
    for i in xrange(len(breakdown)-1):
        x = [0] + np.cos(np.linspace(2 * math.pi * breakdown[i], 2 * math.pi *    
                          breakdown[i+1], 20)).tolist()
        y = [0] + np.sin(np.linspace(2 * math.pi * breakdown[i], 2 * math.pi * 
                          breakdown[i+1], 20)).tolist()
        xy = zip(x,y)
        scatter( location[0], location[1], marker=(xy,0), s=size, facecolor=
               ['gold','yellow', 'orange', 'red','purple','indigo','violet'][i%7])

figure(1, figsize=(6,6))

little_pie([10,3,7],(1,1),600)
little_pie([10,27,4,8,4,5,6,17,33],(-1,1),800)

fracs = [10, 8, 7, 10]
explode=(0, 0, 0.1, 0)

piechart = pie(fracs, explode=explode, autopct='%1.1f%%')
for i in range(len(piechart[0])):
    piechart[0][i].set_hatch(patterns[(i)%len(patterns)])


show()

Answer 2

This may help you:

http://matplotlib.org/examples/pylab_examples/demo_ribbon_box.html

which uses matplotlib.image.BboxImage

I believe this can resize a given image according to input data.

Answer 3

With bar(), you can directly use hatches (with some backends): http://matplotlib.org/examples/pylab_examples/hatch_demo.html:

It works by adding the hatch argument to your call to bar().

---

As for pie(), it does not have a hatch keyword. You can instead get the individual pie chart patches and add hatches to them: you get the patches with:

patches = pie(…)[0]  # The first element of the returned tuple are the pie slices

then you apply the hatches to each slice (patch):

patches[0].set_hatch('/')  # Pie slice #0 hatched.

(hatches list at https://matplotlib.org/api/_as_gen/matplotlib.patches.Patch.html#matplotlib.patches.Patch.set_hatch).

And you apply the changes with:

pyplot.draw()