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  key_t key;
  int id;
  char *msg;
  int write_mode = 0644;

  /**
   * Make a key!
   * This Key will be used to 
   * keep track of the datas
   * location in memory

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  int    fd;
  char * mapped_memory;

  /**
   * Open a file and map it to memory,
   * once it is mapped to memory we can close
   * the file because we have access.
   */
  fd = open(argv[1], O_RDWR | O_CREAT);
  mapped_memory = mmap(NULL, MAX, PROT_READ | PROT_WRITE, MAP_SHARED, fd, 0);

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  int pfds[2];
  int SIZE = 30;
  char buf[SIZE];
  char * msg = "This is a pipe example!";

  /** Generates two pipe file descriptors **/
  pipe(pfds);

  /** writer **/
  if (!fork()) {

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  /* Creates fifo */
  mkfifo(argv[1], S_IRWXU | S_IRWXG | S_IRWXO);
  int fifo = open(argv[1], O_RDONLY);

  /* Duplicate the file 'fifo', so that file descriptor 0 points to it.
   * Note that 0 is the file descriptor of stdin. */
  dup2(fifo, 0);

  char line[1024];
  int i = 0;

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package main

import (
   "image"
   "image/color"
   "image/draw"
   "image/png"
   "code.google.com/p/draw2d/draw2d"

   "log"

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/**
 * Producer-Comsumer example, written in C++ May 4, 2014
 * Compiled on OSX 10.9, using:
 * g++ -std=c++11 producer_consumer.cpp
 **/

#include <iostream>           
#include <thread>             
#include <mutex>              
#include <condition_variable> 

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/**
 * Semaphore example, written in C++ May 4, 2014
 * Compiled on OSX 10.9, using:
 * g++ -std=c++11 semaphore.cpp
 **/

#include <iostream>      
#include <thread>        
#include <mutex>         
#include <condition_variable>

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import numpy as np

def func1(x, y):
    return x*x + x*y + y*y

def func2(y, x):
    return x**3 + y**3 + y*x**2 + y**2 + 2

def monte(func, n, ymin, ymax, xmin, xmax):

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/* version 2.4 of openCV */
using namespace cv;

/**
 * Takes in a RGB image and outputs
 * a Lab space image.
 **/
Mat BGR2LAB(Mat const &imgRGB){
	Mat imgLab;
	cvtColor(imgRGB, imgLab, CV_RGB2Lab);

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/**
 * Description:
 * Finds the gradient between two images, searches the Red channel in RGB
 *  
 * @param: img - image to find gradient on
 * @param: prune - the cut off for the pruning (difference between two steps
 * @param: step - How many pixels apart to check
 * @Return: Mat grad - the image with gradients colored
 **/
Mat findGradient(Mat &img, unsigned int prune, unsigned int step){