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"""
This is an example that shows you how to work directly with the agg
figure canvas to create a figure using the pythonic API.
In this example, the contents of the agg canvas are extracted to a
string, which can in turn be passed off to PIL or put in a numeric
array
"""
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.figure import Figure
from matplotlib.mlab import normpdf
from numpy.random import randn
import numpy
fig = Figure(figsize=(5, 4), dpi=100)
ax = fig.add_subplot(111)
canvas = FigureCanvasAgg(fig)
mu, sigma = 100, 15
x = mu + sigma*randn(10000)
# the histogram of the data
n, bins, patches = ax.hist(x, 50, normed=1)
# add a 'best fit' line
y = normpdf(bins, mu, sigma)
line, = ax.plot(bins, y, 'r--')
line.set_linewidth(1)
ax.set_xlabel('Smarts')
ax.set_ylabel('Probability')
ax.set_title(r'$\mathrm{Histogram of IQ: }\mu=100, \sigma=15$')
ax.set_xlim((40, 160))
ax.set_ylim((0, 0.03))
canvas.draw()
s = canvas.tostring_rgb() # save this and convert to bitmap as needed
# get the figure dimensions for creating bitmaps or numpy arrays,
# etc.
l, b, w, h = fig.bbox.bounds
w, h = int(w), int(h)
if 0:
# convert to a numpy array
X = numpy.fromstring(s, numpy.uint8)
X.shape = h, w, 3
if 0:
# pass off to PIL
from PIL import Image
im = Image.fromstring("RGB", (w, h), s)
im.show()
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