ProgrammingAssignment2/cachematrix.R at master · kajinic/ProgrammingAssignment2 · GitHub

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## Caching the Inverse of a Matrix

## makeCacheMatrix: This function creates a special
## "matrix" object that can cache its inverse.
## makeCacheMatrix function.
##
## Usage example:
## x <- matrix(1:9, nrow=3, ncol=3)
## m <- makeCacheMatrix(x)

makeCacheMatrix <- function(x = matrix()) {

    # Initially set it to NULL

    inv_matrix <- NULL

    # Set a function
    # It sets the matrix itself but not its inverse

    set <- function(y) {
        x <<- y
        inv_matrix <<- NULL
    }

    # Get the function
    # It gets the matrix itself but not its inverse

    get <- function() x

    # Set the inverse manually

    setinverse <- function(inverse) inv_matrix <<- inverse

    # Get the inverse

    getinverse <- function() inv_matrix

    # Encapsulate into a list

    list(set=set, get=get, setinverse=setinverse, getinverse=getinverse)
}

## cacheSolve: This function computes the inverse of the special
## "matrix" returned by makeCacheMatrix function.
##
## If the user tries to use cacheSolve again on the same special
## matrix, then the pre-computed result is returned.
##

cacheSolve <- function(x, ...) {

    # Get the current state of the inverse and check if it
    # has already been computed

    inv_matrix <- x$getinverse()

    if(!is.null(inv_matrix)) {

        # Return the computed inverse

        message("Getting cached matrix")
        return(inv_matrix)
    }

    # Otherwise get the matrix itself

    data <- x$get()

    # Calculate the inverse

    inv_matrix <- solve(data, ...)

    # Cache this result in the object

    x$setinverse(inv_matrix)

    # Return theresult

    inv_matrix
}

## Usage example:
## x <- matrix(1:4, nrow=2, ncol=2)
## m <- makeCacheMatrix(x)
## solution_1 <- cacheSolve(m)
## print(solution_1)
##
## solution_1 should return:
##
##      [,1] [,2]
## [1,]   -2  1.5
## [2,]    1 -0.5
##
##
## solution_2 <- cacheSolve(m)
## This should display a "Getting cached matrix" message
## print(solution_2)

## solution_2 should return
##
##      [,1] [,2]
## [1,]   -2  1.5
## [2,]    1 -0.5
##