##Programming Assignment 2 ####Coursera R Programming #####rprog-013, April 2015.

In this second programming assignment, it is required to write an R function that is able to cache potentially time-consuming computations.

This assignment specifically requires an R code that calculates the inverse (i.e., using solve(x)) of a static n-by-n matrix (i.e., non-square matrices do not have an inverse). Such an operation can be very time-consuming particular for large matrices.

The idea is, that if the content of a matrix are not changing throughout an analysis, that repeatedly require the inverted matrix, it may make more sense to cache the result of the matrix inversion, rather than repeatedly re-calculate it. In other words the result can be looked up in the cache.

This Programming Assignment will take advantage of the lexical scoping rules of the R language and how these can be manipulated to preserve state inside of an R object. See also Hadley Wickham's discussion of Environments in ["Advanced R"](http://adv-r.had.co.nz/Environments.html.

More details are given in the comments to the code found in "cachematrix.R".

I have furthermore added some code in the the global environment that provides a simple matrix and line by line illustrates the functionality of the two functions makeCacheMatrix and cacheSolve(i.e., doing the actual matrix inversion).

Though to get the fun going you can define your own matrix a, feed it to makeCacheMatixby v <- makeCacheMatrix(a). Note you would need to call the cacheSolvefunction to initiate the matrix inversion, e.g., ai <- cacheSolve(v)and then just to prove it works do a1 %*% a which should give you I, the unity matrix with 1's in the diagonal and zero everywhere else. Second time you call the cacheSolve (for the same matrix) you should see "getting cached data" which means that the result was retrived from the cache and no calculation where made.

Have fun!