Hi Everyone,

I’m having problems when rasterizing many lines in a plot using the rasterized=True keyword using the pdf output.

Some version info:

matplotlib version 1.1.1rc

ubuntu 12.04

python 2.7.3

Here’s a basic example that demonstrates my problem:

# Import matplotlib to create a pdf document

import matplotlib

matplotlib.use(‘Agg’)

from matplotlib.backends.backend_pdf import PdfPages

pdf = PdfPages(‘rasterized_test.pdf’)

import matplotlib.pylab as plt

# some test data

import numpy as np

ts = np.linspace(0,2*np.pi,100) * np.ones((200,100))

ts += (np.linspace(0, np.pi, 200)[np.newaxis] * np.ones((100,200))).T

ys = np.sin(ts)

fig = plt.figure()

ax = fig.add_subplot(111)

ax.plot(ts[0], ys.T, color=‘r’, lw=0.5, alpha=0.5, rasterized=True)

pdf.savefig()

pdf.close()

Essentially, I have a lot (200 in this case) of closely overlapping lines which makes the resulting figure (not rasterized) overly difficult to load. I would like to rasterize these lines, such that the axis labels (and other elements of the plot, not shown) remain vectors while the solution trajectories are flattened to a single raster background. However, using the code above, the image still takes a long time to load since each trajectory is independently rasterized, resulting in multiple layers. (If I open the resulting pdf with a program like inkscape, I can manipulate each trajectory independently.)

Is it possible to flatten all of the rasterized elements into a single layer, so the pdf size would be greatly reduced?

Thanks,

–Peter