Unfolding work

Work on understanding the unfolding so far. Changes as per commit names.
Some findings:
- manual fake subtraction ([click](https://github.com/senkin/DailyPythonScripts/commit/532c2f239a37da0786cf82656c713276cb7b71bd#diff-c9993a899d3916df38befe89edef875bR82)) has no effect in TSVDUnfold. Not sure why.
- tau values behave much better when the response matrix includes fakes — closure tests pass fine:
![screen shot 2014-03-06 at 17 25 54](https://f.cloud.github.com/assets/2600844/2348141/9a47ce98-a554-11e3-8e86-bcb8b6ac5fca.png)
- manually loading fakes histogram results in reasonable output of k value determination script for RooUnfoldSvd, i.e. Impl()->GetD() function works and returns sensible results, however, there's an extra empty bin in d_i (?)
- not loading fakes still gives k-values of 1 for RooUnfoldSvd.
- if fakes are included in the response matrix, TSVDUnfold method returns inconsistent d_i results (only 1 first bin for HT and MET, OK for other variables). Closure tests look good though.
- if fakes are not included in response matrix, closure tests fail in TSVDUnfold.

Main conclusion:
- unfolding is still a black box; not sure which method to use for k value determination.