Travis-CI:

# Histogram Demo CanvasAggΒΆ

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
import numpy as np

fig = Figure(figsize=(5, 4), dpi=100)

canvas = FigureCanvasAgg(fig)

mu, sigma = 100, 15
x = mu + sigma * np.random.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 = np.fromstring(s, np.uint8).reshape((h, w, 3))

if 0:
# pass off to PIL
from PIL import Image
im = Image.fromstring("RGB", (w, h), s)
im.show()


Total running time of the script: ( 0 minutes 0.000 seconds)

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