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#! /usr/bin/python
#
# This program will take a file name from the command line and analyze its entropy, using many of the same algorithms
# as the ent program from hotbits
import sys
import struct
import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab

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//    FILE: RandomCardDraw.ino
//  AUTHOR: Rob Tillaart and Walter Anderson
// VERSION: 1.0.0
// PURPOSE: generate random sequence (optimized)
//    DATE: April 24, 2014
//     URL: 

// The Entropy library provides true random numbers and can be obtained from:
// http://code.google.com/p/avr-hardware-random-number-generation/wiki/WikiAVRentropy
#include <Entropy.h>

wandrson

#! /usr/bin/python

import sys
import struct

try:
    infilename = sys.argv[1]
    outfilename = sys.argv[2]
    maxsize = int(sys.argv[3])
except:

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// due_hwrng_speed_test.ino
//  by Walter Anderson
//  April 5, 2014
//
//  This is a speed test run on an Arduino Due with an ATSAM3X8E-AU chip dated 1317, it produced the following
//  output:
//     Starting time test for speed of generation of hardware randrom number gebnrator.
//     It took 262 milliseconds to generato 1,048,576 bytes of entropy!
//  This equates to 4,002,198 bytes per second!
//

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// DUE's TRNG  32 bits every 84 ticks
#include <sam.h>
#include <sam3xa/include/component/component_trng.h>

uint32_t test_hwrng()
{
    static bool enabled = false;
    if (!enabled) {
        pmc_enable_periph_clk(ID_TRNG);
        TRNG->TRNG_IDR = 0xFFFFFFFF;

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// TrueRandomSeed.ino
// This example sketch shows how to provide a truly random seed value to the built in
// library pseudo random number generator. This ensures that your sketch will be
// using a different sequence of random numbers every time it runs. Unlike the
// usually suggested randomSeed(analogRead(0)) this method will provide a much more
// uniform and varied seed value. For more information about the basic technique used
// here to produce a random number or if you need more than one such number you can
// find a library, Entropy from the following web site along with documentation of how
// the library has been tested to provide TRUE random numbers on a variety of AVR
// chips and arduino environments.

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# Analyze dice data to establish if it is random
setwd("~/Development/hardware-rng/avr-hardware-random-number-generation/Entropy/examples/Dice")
library(foreign)
library(prettyR)
sink("analysis.prn")
Dice.data <- read.csv("dice.txt")
Dice.data$Sum <- Dice.data$Die1 + Dice.data$Die2
png(filename="cumulative.png", width=800, height=600)
hist(Dice.data$Sum,
freq=FALSE,

wandrson

#!/usr/bin/env python

import socket
from time import sleep
from blinkt import set_clear_on_exit, set_pixel, show

colors = [
[  0,  0,  0],#0 black
[ 32, 32,  0],#1 brown
[255,  0,  0],#2 red