Create a Wrapper of unicorn library for RQA

[etzinis]

It would be inefficient to re implement everything from the beginning and thus it would be wise to use unicorn: https://github.com/pik-copan/pyunicorn/blob/master/examples/tutorials/recurrence_network.py

This wrapper will fully modularize the whole process of RQA baseline feature extraction.

[etzinis]

===== RQA Performance Testing =====

>Total Time: 0.115321397781 for 100 frames, RP Class: threshold
>Total Time: 0.117163896561 for 100 frames, RP Class: threshold_std
>Total Time: 0.257563591003 for 100 frames, RP Class: recurrence_rate

~~~~~ Testing for Fs=16000 Samples=320  ~~~~~
>Total Time: 0.245970010757 for 100 frames, RP Class: threshold
>Total Time: 0.248541593552 for 100 frames, RP Class: threshold_std
>Total Time: 0.88880443573 for 100 frames, RP Class: recurrence_rate

~~~~~ Testing for Fs=44100 Samples=882  ~~~~~
>Total Time: 1.37852692604 for 100 frames, RP Class: threshold
>Total Time: 1.38466095924 for 100 frames, RP Class: threshold_std
>Total Time: 7.00100374222 for 100 frames, RP Class: recurrence_rate