**R – Opiniomics**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

You have a matrix in R, and you want to visualise it – say, for example, with each cell coloured according to the value in the cell. Not a heatmap, per se, as that requires clustering; just a simple, visual image.

Well, the answer is image() – however, there is the slightly bizarre coding choice buried in the help:

Notice that

`image`

interprets the`z`

matrix as a table of`f(x[i], y[j])`

values, so that the x axis corresponds to row number and the y axis to column number, with column 1 at the bottom, i.e.a 90 degree counter-clockwise rotation of the conventional printed layout of a matrix.

Let’s look at that:

```
mat <- matrix(c(1,1,1,0,0,0,1,0,1), nrow=3, byrow=TRUE)
mat
[,1] [,2] [,3]
[1,] 1 1 1
[2,] 0 0 0
[3,] 1 0 1
image(mat)
```

This produces:

We can clearly see the 1,0,1 row is now the right-hand column i.e. the matrix has in fact been rotated 90 degrees anti-clockwise.

To counteract this we need to rotate the input matrix clockwise before passing to image:

```
rotate <- function(x) t(apply(x, 2, rev))
image(rotate(mat))
```

This now produces what we might expect:

Easy

**leave a comment**for the author, please follow the link and comment on their blog:

**R – Opiniomics**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.