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#######  GCP/GCloud VM setup running R/Python using Anaconda  ########

	# Prepared as part of a guest lecture series in parallel programming and GCloud setup
	# at Pepperdine University for their inaugural ML class on 3/16/2018.
	# Rights: MIT Licence

## 10 easy steps: Running R/Python in the cloud

1) Log into GCP 
2) Create a project (if not done already), and log into <your project> from top of screen

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Creating Zips

import shutil
import os

cwd = os.getcwd()

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### Likelihood of getting 3 heads out of 8 flips given a fair coin
n = 8
k = 3
steps = 10001 # Non zero ending to get likelihood; best if > 10000
p_grid = seq(0,1,length.out = steps)
prior = rep(1, steps)
likelihood = dbinom(k, n, prob = p_grid)
  # unstd.posterior = likelihood*prior
  # posterior = unstd.posterior/sum(unstd.posterior)
  # plot(p_grid, posterior)

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library(mosaic)

f <- makeFun(x^2 + y ~ x & y)
g <- makeFun(x^2 - y^2 ~ x & y)

  # levelset <- 10
  # plotFun(f(x,y) ~ x & y, xlim = range(-10, 10),
  #         levels = levelset, ylim = range(-10, 10), filled = F)
  # plotFun(g(x,y) ~ x & y, levels = levelset,  xlim = range(-10, 10),

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packages <- c("twitteR", "dismo", "maps", "ggplot2")
installAll <- packageList[!packages %in% rownames(installed.packages())]
if(installAll){install.packages(installAll, repos = "http://cran.us.r-project.org")} else {print("No Packages Installed")}
lapply(packages, library, character.only = TRUE)

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binomProbs <- function(w, n, propStep){

  # print(w)
  # print(n)
  # print(propStep)
  
  plot(seq(0, 1, propStep), dbinom(w, n, prob = seq(0,1, propStep)), xlim = c(0, 1),
       xlab = "", ylab = "")
 points(seq(0, 1, propStep), 

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Game explained https://www.scientificamerican.com/article/the-3-door-monty-hall-problem/

##### Play the game ######

# Example
# sampleSpaceDoorPick = c("ABC","ACB","BCA","BAC","CAB","CBA")

# Prep combinations table

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# Function
xylist <- function(start, finish){
  
  x <- seq(start, finish)
  y <- seq(start, finish)^2
  
  return(list("x" = x, "y" = y))
  
}

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