cachematrix.R

# makeCacheMatrix: This function creates a special "matrix" object that can cache its inverse.
makeCacheMatrix <- function(x = matrix()) {
  # Refresh to NULL
  m<-NULL
  # Creates the cache matrix (ex: test <- makeCacheMatrix())
  set<-function(y){
    x<<-y
    m<<-NULL
  }
  # Returns the cache matrix (ex: test$getmatrix())
  get<-function() x
  setmatrix<-function(solve) m<<- solve
  getmatrix<-function() m
  list(set=set, get=get,
       setmatrix=setmatrix,
       getmatrix=getmatrix)
}

# cacheSolve: This function computes the inverse of the special "matrix" returned by makeCacheMatrix above. 
# If the inverse has already been calculated (and the matrix has not changed), 
# then the cachesolve should retrieve the inverse from the cache.
cacheSolve <- function(x, ...) {
  # Get the provided matrix
  m<-x$getmatrix()
  # Throw a message to the user that we are using the cache
  if(!is.null(m)){
    message("getting cached data")
    return(m)
  }
  matrix<-x$get()
  m<-solve(matrix, ...)
  x$setmatrix(m)
  m
}

# Instructor Provided Functions

# makeVector creates a special "vector", which is really a list containing a function to
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)
}

# cachemean 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
}