Assignment rdpeng#3

README.md

@@ -1,23 +1,23 @@
 ### Introduction
 
 This second programming assignment will require you to write an R
-function is able to cache potentially time-consuming computations. For
-example, taking the mean of a numeric vector is typically a fast
+function that is able to cache potentially time-consuming computations.
+For example, taking the mean of a numeric vector is typically a fast
 operation. However, for a very long vector, it may take too long to
 compute the mean, especially if it has to be computed repeatedly (e.g.
 in a loop). If the contents of a vector are not changing, it may make
 sense to cache the value of the mean so that when we need it again, it
 can be looked up in the cache rather than recomputed. In this
-Programming Assignment will take advantage of the scoping rules of the R
-language and how they can be manipulated to preserve state inside of an
-R object.
+Programming Assignment you will take advantage of the scoping rules of
+the R language and how they can be manipulated to preserve state inside
+of an R object.
 
 ### Example: Caching the Mean of a Vector
 
 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 cache's its mean.
+special object that stores a numeric vector and caches its mean.
 
 The first function, `makeVector` creates a special "vector", which is
 really a list containing a function to
@@ -64,8 +64,8 @@ function.
 
 ### Assignment: Caching the Inverse of a Matrix
 
-Matrix inversion is usually a costly computation and their may be some
-benefit to caching the inverse of a matrix rather than compute it
+Matrix inversion is usually a costly computation and there may be some
+benefit to caching the inverse of a matrix rather than computing it
 repeatedly (there are also alternatives to matrix inversion that we will
 not discuss here). Your assignment is to write a pair of functions that
 cache the inverse of a matrix.
@@ -76,8 +76,8 @@ Write the following functions:
     that can cache its inverse.
 2.  `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.
+    already been calculated (and the matrix has not changed), then
+    `cacheSolve` should retrieve the inverse from the cache.
 
 Computing the inverse of a square matrix can be done with the `solve`
 function in R. For example, if `X` is a square invertible matrix, then
@@ -88,13 +88,16 @@ invertible.
 
 In order to complete this assignment, you must do the following:
 
-1.  Clone the GitHub repository containing the stub R files at
+1.  Fork the GitHub repository containing the stub R files at
     [https://github.com/rdpeng/ProgrammingAssignment2](https://github.com/rdpeng/ProgrammingAssignment2)
-2.  Edit the R file contained in the git repository and place your
+    to create a copy under your own account.
+2.  Clone your forked GitHub repository to your computer so that you can
+    edit the files locally on your own machine.
+3.  Edit the R file contained in the git repository and place your
     solution in that file (please do not rename the file).
-3.  Commit your completed R file into YOUR git repository and push your
-    git branch to your GitHub account.
-4.  Submit to Coursera the URL to your GitHub repository that contains
+4.  Commit your completed R file into YOUR git repository and push your
+    git branch to the GitHub repository under your account.
+5.  Submit to Coursera the URL to your GitHub repository that contains
     the completed R code for the assignment.
 
 ### Grading

cachematrix.R

@@ -1,10 +1,35 @@
-## [Put comments here that describe what your functions do]
+## Caching the Inverse of a Matrix:
+## Instead of computing the inverse of a matrix repeatedly, it is more beneficial to cache the inverse of a matrix since the computation of a matrix is usually a costly computation
 
-makeCacheMatrix <- function(x = matrix()) {
+## This function creates a special matrix object that can cache its inverse
 
+makeCacheMatrix <- function(x = matrix()) {
+	inv <- NULL
+	set <- function(y) {
+		x <<- y
+		inv <<- NULL 
+	}
+	get <- function() x
+	setInverse <- function(inverse) inv <<- inverse
+	getInverse <- function() inv
+	list(set = set,
+		 get = get,
+		 setInverse = setInverse,
+		 getInverse = getInverse)
 }
 
+## The following function calculates the inverse of the special matrix created by the above function. However, it firs checks to see if the inverse has already been calculated. If so, it gets the inverse from the cache and skips the computation. Otherwise, it calculates the inverse of the data and sets the value of the minverse in the cache via the setInverse function.
 
 cacheSolve <- function(x, ...) {
         ## Return a matrix that is the inverse of 'x'
+        inv <- x$getInverse()
+        if (!is.null(inv)) {
+        	message("getting cached data")
+        	return(inv)
+        }
+        mat <- x$get()
+        inv <- solve(mat, ...)
+        x$setInverse(inv)
+        inv
 }
+