cachematrix_0.3.R

## ver 0.2
## Calculate Inverse of a Matrix using cache.
## If cached Inverse of a Matrix exists in the memory, then display it.
## Or, there is no one, calculate it.
## To do this, use a special function containing 4 sub-functions.

## "makeCacheMatrix": This function contains 4 sub-functions in it.
## Why use this complicating function? To hold the calculation results in memory without noticing it.

makeCacheMatrix <- function(x = matrix()) {
        m <- NULL
        y <- NULL
        # set <- function(y) {
        #        x <<- y
        #        #m <<- NULL
        #}
        get <- function() {
          x
        }
        setInverse <- function(x, Inverse) {
          y <<- x
          m <<- Inverse          
        }
        getInverse <- function() {
          m
        }
        getOriginal <- function() {
          y
        }  
        list(#set = set, 
             get = get, 
             setInverse = setInverse,
             getInverse = getInverse)
}

## Cacalute the inverse of of a matrix .
## If it was already calculated and cashed,  then the cached results are simply returned.

cacheSolve <- function(x, ...) {
        ## Return a matrix that is the inverse of 'x'
        m <- x$getInverse()  # get the cashed data
        y <- x$getOriginal()  # get the original matrix
        if(!is.null(m) && y == x) {    # If cashed and not changed, 
            message("getting cached data")
            return(m)
        }
        data <- x$get()      # If there is no cashed data, then use the new data
        m <- solve(data, ...)
        x$setInverse(m, x)      # Cashe the solved matrix into memory.
        m
}

## An example how to use the functions
matrix.1 <- c(0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0) 
matrix.1 <- matrix(matrix.1, ncol=5, byrow=TRUE) 
fx.inverse <- makeCacheMatrix(matrix.1)
matrix.1                          #original matrix
cacheSolve(fx.inverse)            #solved matrix   
matrix.1%*%cacheSolve(fx.inverse) #check whether the solved matrix is correct (diagnonal matrix).


matrix.1 <- c(0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0) 
matrix.1 <- matrix(matrix.1, ncol=5, byrow=TRUE)