Vinnie Monaco vmonaco

## runs_test.py
"""
Multivariate Wald-Wolfowitz test for two samples in separate CSV files.

See:
  Friedman, Jerome H., and Lawrence C. Rafsky.
  "Multivariate generalizations of the Wald-Wolfowitz and Smirnov two-sample tests."
  The Annals of Statistics (1979): 697-717.

Given multivariate sample X of length m and sample Y of length n, test the null hypothesis:

## cmu_powerlaw.py
'''
Created on May 26, 2015

@author: vinnie, vincent@vmonaco.com

Power-law results from:
"DATA FORENSIC TECHNIQUES USING BENFORD’S LAW AND ZIPF’S LAW FOR KEYSTROKE
DYNAMICS", Aamo Iorliam, Anthony T.S. Ho, Norman Poh, Santosh Tirunagari,
and Patrick Bours. IWBF 2015.

## hci_clicks_example.py
"""
Identify users by mouse click timings.
Train a POHMM for each user, one sample, and test using the remaining samples.

Using the clicks from task 3 (Star Bubbles) in the HCI dataset:
https://bitbucket.org/vmonaco/dataset-four-hci-tasks/

$ python hci_clicks_example.py data/task3.click.csv

Accuracy (88 samples): 0.375

## segment_motion.py
"""
Segment an acceleration or gyroscopic CSV file into motion/non-motion segments
using a 2-state HMM and Savitzky–Golay filter as preprocessing
"""
import sys
import pandas as pd
import matplotlib.pyplot as plt
from hmmlearn.hmm import GaussianHMM
from scipy.signal import savgol_filter