Initial implementation.

Author: robmoore

.gitignore

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+.Rproj.user
+.Rhistory
+.RData

ProgrammingAssignment2.Rproj

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+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX

cachematrix.R

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-## Put comments here that give an overall description of what your
-## functions do
-
-## Write a short comment describing this function
+## Functions for memoization (http://en.wikipedia.org/wiki/Memoization) of
+## inverted matrices (http://en.wikipedia.org/wiki/Invertible_matrix).
 
+## Caches or memoizes matrix inversion
 makeCacheMatrix <- function(x = matrix()) {
-
+  # Initialize the inverted matrix to a value that an be used
+  # for testing if inverted matrix has been calculated.
+  s <- NULL
+  # Set the matrix value to something other than the initial value
+  # provided when creating the function.
+  set <- function(y) {
+    x <<- y
+    s <<- NULL
+  }
+  # Return the matrix to be inverted
+  get <- function() x
+  # Set the inverted matrix
+  sets <- function(solve) s <<- solve
+  # Returns the cached inverted matrix
+  gets <- function() s
+  list(set = set, get = get,
+       sets = sets,
+       gets = gets)
 }
 
-
-## Write a short comment describing this function
-
+## Returns a matrix that is the inverse of 'x'
 cacheSolve <- function(x, ...) {
-        ## Return a matrix that is the inverse of 'x'
+  # Check if inverted matrix already exists
+  s <- x$gets()
+  if(!is.null(s)) {
+    message("Found inverted matrix")
+    return(s)
+  }
+  # Retrieve original matrix
+  data <- x$get()
+  # Generate inverse
+  s <- solve(data, ...)
+  # Store inverse
+  x$sets(s)
+  s
 }
+

cachemean.R

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+## Creates a special "vector", which is really a list containing a function to
+## - set the value of the vector
+## - get the value of the vector
+## - set the value of the mean
+## - get the value of the mean
+makeVector <- function(x = numeric()) {
+  m <- NULL
+  set <- function(y) {
+    x <<- y
+    m <<- NULL
+  }
+  get <- function() x
+  setmean <- function(mean) m <<- mean
+  getmean <- function() m
+  list(set = set, get = get,
+       setmean = setmean,
+       getmean = getmean)
+}
+
+## In this example we introduce the <<- operator which can be used to assign 
+## a value to an object in an environment that is different from the current 
+## environment. Below are two functions that are used to create a special 
+## object that stores a numeric vector and caches its mean.
+
+##  The following function calculates the mean of the special "vector" created 
+## with the above function. However, it first checks to see if the mean has 
+## already been calculated. 
+##
+## If so, it gets the mean from the cache and skips the computation. Otherwise, 
+## it calculates the mean of the data and sets the value of the mean in the 
+## cache via the setmean function.
+cachemean <- function(x, ...) {
+  m <- x$getmean()
+  if(!is.null(m)) {
+    message("getting cached data")
+    return(m)
+  }
+  data <- x$get()
+  m <- mean(data, ...)
+  x$setmean(m)
+  m
+}

test.R

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+# From the http://www.mathsisfun.com/algebra/matrix-inverse.html page
+mat <- matrix(c(4, 2, 7, 6), 2, 2)
+inv <- solve(mat)
+ide <- mat %*% inv
+
+# See also http://www.purplemath.com/modules/mtrxmult.htm
+# for nice matrix multiplication algorithm graphic.
+
+# Generate a random 2 x 2 matrix of integers from 1 to 10
+di <- 2
+mat <- matrix(sample(1:10, di * di), di, di)
+# Invert matrix
+inv <- solve(mat)
+# General identity matrix
+ide <- mat %*% inv
+# Should be true
+identical(ide, matrix(c(1, 0, 0, 1), 2, 2))
+
+cm <- makeCacheMatrix(mat)
+# Should be true
+is.null(cm$gets())
+cs <- cacheSolve(cm)
+# Should be false
+is.null(cm$gets())
+
+identical(inv, cacheSolve(cm))