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# Vinnie Monaco vmonaco

Created Dec 7, 2015
Segment motion using a 2-state Gaussian HMM
View 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
Created Mar 10, 2018
Finite automata and (deterministic) Turing machine running/drawing.
View fa.sty
 \NeedsTeXFormat{LaTeX2e} \ProvidesPackage{fa} [2018/03/09 v0.3 Construct finite automata and Turing machines] \RequirePackage{tikz} \RequirePackage{etoolbox} \usetikzlibrary{arrows.meta,automata,calc,chains,positioning} % Define \emptystring to \varepsilon
Last active Feb 21, 2020
CMU keystroke power law
View 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.
Created Sep 24, 2011
RSA Explained in Python
View rsa.py
 #!/usr/bin/env python # This example demonstrates RSA public-key cryptography in an # easy-to-follow manner. It works on integers alone, and uses much smaller numbers # for the sake of clarity. ##################################################################### # First we pick our primes. These will determine our keys. #####################################################################
Last active Nov 2, 2020
Performs a Pandas groupby operation in parallel
View groupyby_parallel.py
 # coding=utf-8 import pandas as pd import itertools import time import multiprocessing from typing import Callable, Tuple, Union def groupby_parallel(groupby_df: pd.core.groupby.DataFrameGroupBy, func: Callable[[Tuple[str, pd.DataFrame]], Union[pd.DataFrame, pd.Series]],
Last active Mar 8, 2021
Multivariate Wald-Wolfowitz test to compare the distributions of two samples
View 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: