gu-mi

#include <iostream>
using namespace std;

int main()
{
  const int MAX_ROWS = 3;
  const int MAX_COLS = 4;
  
  // 2-D array of integers
  int MyInts[MAX_ROWS][MAX_COLS] = { {34, -1, 879, 22},

gu-mi

#spirographR() will produce either a hypotrochoid or an epitrochoid. 

#'A' is a circle of radius 'A.RADIUS'
#'B' is a circle of radius 'B.RADIUS' travelling around 'A'
#'C' is a point relative to the center of 'B' which rotates with the turning of 'B'.
#'BC' is the distance from the center of 'B' to 'C'
#'A.REV' is the number of revolutions that 'B' should travel around 'A'
#'N.PER.A.REV' is the number of radial increments to be calculated per revolution
#'A.CEN' is the position of the center of 'A'
#

gu-mi

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ReadImages", "reshape", "ggplot2")
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Image URL:
allImageURLs <- c("http://media.charlesleifer.com/blog/photos/thumbnails/akira_940x700.jpg",
                  "http://upload.wikimedia.org/wikipedia/commons/thumb/e/ec/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg/402px-Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg",
                  "http://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Official_portrait_of_Barack_Obama.jpg/441px-Official_portrait_of_Barack_Obama.jpg",
                  "http://cache.boston.com/universal/site_graphics/blogs/bigpicture/obama_11_05/obama22_16604051.jpg",

gu-mi

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ReadImages", "reshape", "ggplot2")
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Image URL:
allImageURLs <- c("http://media.charlesleifer.com/blog/photos/thumbnails/akira_940x700.jpg",
                  "http://upload.wikimedia.org/wikipedia/commons/thumb/e/ec/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg/402px-Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg",
                  "http://upload.wikimedia.org/wikipedia/commons/thumb/e/e9/Official_portrait_of_Barack_Obama.jpg/441px-Official_portrait_of_Barack_Obama.jpg",
                  "http://cache.boston.com/universal/site_graphics/blogs/bigpicture/obama_11_05/obama22_16604051.jpg",

gu-mi

# http://www.r-bloggers.com/example-10-7-fisher-vs-pearson/
# Author: Ken Kleinman

# In R, we'll simulate observations from a multinomial distribution 
# with the desired cell probabilities, and assemble the result into 
# a table to calculate the p-values. This will make it easier to simulate 
# tables under the alternative, as we need to do to assess power. 
# If there are empty rows or columns, the chisq.test() function produces 
# a p-value of "NaN", which will create problems later. To avoid this, 
# we'll put the table generation inside a while() function. This operates 

gu-mi

heatmap.3=function (x, Rowv = TRUE, Colv = if (symm) "Rowv" else TRUE,
    distfun = dist, hclustfun = hclust, dendrogram = c("both",
        "row", "column", "none"), symm = FALSE, scale = c("none",
        "row", "column"), na.rm = TRUE, revC = identical(Colv,
        "Rowv"), add.expr, breaks, symbreaks = max(x < 0, na.rm = TRUE) ||
        scale != "none", col = "heat.colors", colsep, rowsep,
    sepcolor = "white", sepwidth = c(0.05, 0.05), cellnote, notecex = 1,
    notecol = "cyan", na.color = par("bg"), trace = c("column",
        "row", "both", "none"), tracecol = "cyan", hline = median(breaks),
    vline = median(breaks), linecol = tracecol, margins = c(5,

gu-mi

# Simple ggplot2 heatmap, with optimal seriation

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ggplot2", "reshape2", "RColorBrewer", "seriation")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Using U.S. Judge Rating Data
myData <- as.matrix(USJudgeRatings)

gu-mi

#' Constructor
EmailClass <- function(name, email) {
	nc = list(
		name = name,
		email = email,
		get = function(x) nc[[x]],
		set = function(x, value) nc[[x]] <<- value,
		props = list(),
		history = list(),
		getHistory = function() return(nc$history),

gu-mi

# Randomly allocating observations into groups, for, e.g. cross-validation
kk <- 10  # Number of partitions, as in "kk-fold cross-validation."

# Here is a data.frame full of good data:
nn <- 1003
myData <- data.frame(matrix(rnorm(nn * 3), ncol = 3))
colnames(myData) <- LETTERS[1:3]

# This does not work:
whichK <- sample(LETTERS[1:kk], nrow(myData), replace = T)

gu-mi

# Simple ggplot2 heatmap
# with colorBrewer "spectral" palette

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ggplot2", "reshape2", "RColorBrewer")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Generate a random matrix
# This can be any type of numeric matrix,