Upgrade of trim-low-abund for better, more profitable streaming.

Support for k-mer spectral error analysis, sublinear error profile calculations from shotgun data sets (sandbox/calc-error-profile.py), adaptive variant collection based on graphalign (sandbox/collect-variants.py), streaming error correction (sandbox/correct-errors.py), and streaming error trimming (sandbox/trim-low-abund.py).  The k-mer spectral error analysis and error profile/trimming is part of the 2014-streaming paper (https://github.com/ctb/2014-streaming).
Sure. But the second loop advances the same iterator, so it doesn't increase the time complexity of the code; and this code was considerably simpler than the alternatives I tried.  Note that the unit tests are pretty stringent for this bit of code because I made so many mistakes; I found it to be tricky stuff.