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!