modified the IPython parallel version of the proximity forest so that
instances of a callable class can be used as distance functions. The key
is to query df.func_name as opposed to df.__name__ as instances don't
have the latter, but can easily implement the former.
Added a subclass of ProximityTree and ProximityForest for handling input
formatted as a feature matrix. Currently, this is a non-efficient
shallow layer over the base class, but the plan is to implement more
efficient vectorized distance computations when the inputs are vectors
stacked in a matrix. 

Also added some additional code comments.
Progress indicator for ProximityForestAnalysis.classifyAll method has
been improved. Confusion matrix has an option for analyzing labels that
are 1-based integers. Updated comments in some places to note that
0-based contiguous integers are assumed for the labels.