Initial work on scipy.sparse backend

Some very basic stuff is working, still needs a lot of other things implemented.
Implement more core methods

Including:

- getRow/getCol
- transpose
- copy
- items
- iteritems
Add __eq__ and __ne__
Add __setitem__ and __getitem__
Make shape and dtype properties

Instead of attributes
Add conversion factories
Add ScipySparseMat to backend loader
Add missing imports
Add support for empty sparse matrices.

Ugly but necessary...
Remove zeros in data cleansing step

All tests now pass. We have an efficiency warning to still take care of.
Add lil conversion for efficiency

Tests all pass without any warnings!
Add results fp option to bench.sh

Also reports errors when running bench scripts
Fix several bench scripts

Many were erroring out, likely due to changes in biom-format API since they were originally written.
Add some performance improvements
Merge branch 'master' into scipy-sparse-backend

Conflicts:
	INSTALL
	biom/__init__.py
Fix scipysparse import; move file
Add commented out performance improvement

Need to do some refactoring before being able to add these performance improvements though.
Update header with license
Add sum as backend requirement

Summing is now several orders of magnitude faster for both CSMat and ScipySparseMat.
Add convertVectorToDense to sparse backends

Used in _conv_to_np, allows more efficient use of ScipySparseMat when iterating over rows/cols