adding synthesizer as the main loop of the program

looks like this is going to be fast - can run ipf for households and population in a small county in about 15 seconds
pep8
synthpop not popsynth!
adding a function to convert to frequency table for use in ipu

still need to work out exactly how all these data gets pass around though
forgot to check pep8
this is a *very* intermediate commit

It should have everything plugged in to the ipu OK, and format the frequency tables appropraitely, but it's not pretty and probably needs a moderate reorg.  Still, I don't want this code just sitting on my laptop.
appears to be running through the ipf and ipu see if we can get the tests running
pep8
pep8
probably don't need this tracts_to_pumas function anymore
converted to synthpop dir structure

also added a few parameters for zero marginals and zero constraints

and set_index to the cat_ids rather than reset_index

getting closer...
implemented a random draw
forgot to update test to get rid of SynthPop object
the tests are passing on my local machine

trying again on travis with a few tweaks
presumably a groupby(level=0) is better than a reindex followed by a groupby of the first column

Presumably this is caused by a hierarchical column name that breaks when I drop the index into the dataframe.  I think this is a pandas bug only in the version that travis is running and not on my mac.
Merge pull request #9 from synthicity/add-synthesizer

Add synthesizer - you can pass in a county and get out a dataframe of households.  More work to do, but this is a draft of the minimum useful functionality.
Use NumPy arrays internally in IPU

Pretty much *all* the time in the IPU was being spent doing
Pandas indexing. NumPy arrays are much simpler and much faster,
so at the beginning of the IPU I get the internal values of
the passed DataFrames and Series so I can work with pure NumPy
arrays.

Result: test function execution went from 4.1 to 0.16 seconds.