Inherited the clear_cache method to a few more derived models and the direct view parallel model.
Merge pull request #12 from ihincks/master

Inherited the clear_cache method to a few more derived models and the direct view parallel model.
Minor bug fixes, new option to disable LW postselection.
Added the mixin ScoreMixin which numerically computes the score function q.
Minor bug fixes to score methods + example calculation notebook.
Merge pull request #13 from ihincks/feature-score

Included ability to compute the score function numerically by adding ScoreMixin
Added Python Tools for Visual Studio solution file.
Added RB example for ScoreMixin.
Changed init file to address #14.
Minor fixes to models.
Fixed mistake w/ bad A, B.
Minor changes to ScoreMixin example.
Added GPU model example, basic performance testing.
added __all__ to test_models.
Added MASMC to smc.py's __all__.
More fixes to make simple example work, new ExpSpareHeuristic.
Fixed doc errors, added details of new classes, functions.
Added more documentation, fixed dists, fixed doc issues.
Added new check to resamplers.py for zero-norm cov.

I noted in testing that sometimes an updater would get very
close to the true model, but would fail with a ResamplerError
due to the estimated norm of the error in sqrtm(cov) being nan.
This can happen either if the error term is awful, or if the
norm of cov is zero; the error is intended for the former case,
not the latter. To compensate, the LW resampler as of this commit
now checks for zero-norm cov and if detected, warns, then adds
a small artificial covariance to compensate.
Added logic to clear_cache to prevent IPython parallel memory leaks.