Rasterizing multiple elements in matplotlib

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!