add documentation, some code cleanup, and a bug fix

After seeing Jasper Snoek talk in cambridge I was inspired to try this bayesian optimization package.  It seems well written and well commented, but without much documentation.  I had a some difficulty trying to understand what all the variables meant and what all the routines were doing.  So while I was going through the  code in detail I added some documentation for my own benefit.  Maybe you guys will appreciate it.  But please go over my documentation carefully.  The only thing worse then no documentation is incorrect documentation.

I also made some other changes.

1. I did a bit of code cleanup, like removing tabs, removing unused imports, changing 2-space indents to 4-space, shortening long lines, etc.

2. I added a new example for noisy functions.  This is simply the branin function with some added noise.

3. I added a file make_plots.py to the simple branin example.  Using your README I was able to easily run the example, but I had no idea what to do then.  I didn't know how to access the data or make predictions or find the best guess for the minimum, or show uncertainties.  make_plots.py is basically my solution to that, though it may be a bit hacky.  You may want to update it if there are more elegant ways of doing this.  I wrote it in a general way so it can be called from any experiment directory with a 2-dimensional function (e.g. examples/noisy)  

4. I restructured main.py, separating out the part that reads in the options.  I did this mostly because I wanted to re-use it for make_plots.py

5. I renamed some variables because I found it really hard to know if variable `tasks` referred to a list of `Task` objects or a list of task names (strings).  This confused me a lot and I only changed a few of the examples.

Finally, thanks for the great code
yes, but it is still able to find a good solution :).   The branin function over the input data runs from about 0 to 300 so it's actually not too bad.  Feel free to reduce it though