How to properly set rendering Rmarkdown to pdf? - r

I use Rmarkdown to generate reports and if my line is too long it is usually cut after rendering.
Is there a way to fix it?
I attach a screenshot in order better explain my issue.


You can use the chunk option tidy=TRUE to automatically insert line breaks in the code.
---
output: pdf_document
---
```{r, tidy = TRUE}
c(1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0)
```
The linebreaks are inserted by formatR::tidy_source(). See https://yihui.org/knitr/options/#code-decoration for more details.
chunk_content <- "c(1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0)"
formatR::tidy_source(text = chunk_content, width.cutoff = 30)
#> c(1, 2, 3, 4, 5, 6, 7, 8, 9, 0,
#> 1, 2, 3, 4, 5, 6, 7, 8, 9,
#> 0, 1, 2, 3, 4, 5, 6, 7, 8,
#> 9, 0, 1, 2, 3, 4, 5, 6, 7,
#> 8, 9, 0)

Related

Difference between fit$loadings and fit$Vaccounted for variance accounted for in factor analysis?

I am getting different values for variance accounted for by factors in factor analysis whether I check them with fit$loadings or with fit$Vaccounted. I am using the psych package with the fa() function. Why would that be the case if they're supposed to be exactly the same thing (I guess they're not or that they are calculated differently)?
The total difference is not huge, but still not trivial (about 0.7 for cumulative). I have a reprex below.
(I'm sorry for the large dataset, I was not able to replicate the issue with different datasets or a subset, so it might have to do with something funky with the data.)
data <- structure(list(X1 = c(5, 5, 5, 7, 2, 2, 2, 2, 7, 5, 4, 9, 8,
8, 6, 9, 9, 2, 2, 2, 2, 3, 2, 2, 9, 7, 8, 4, 3, 4, 6, 6, 3, 4,
4, 4, 8, 7, 6, 7, 5, 6, 6, 4, 8, 8, 8, 3, 9, 9, 6, 4, 8, 7, 8,
7, 8, 8, 8, 8), X2 = c(6, 4, 4, 6, 2, 2, 2, 2, 6, 5, 4, 8, 7,
9, 6, 9, 4, 2, 2, 2, 6, 4, 6, 7, 9, 6, 8, 4, 3, 3, 5, 5, 2, 3,
4, 7, 7, 5, 5, 6, 7, 7, 7, 3, 8, 5, 3, 2, 9, 9, 4, 4, 4, 6, 4,
4, 8, 8, 8, 8), X3 = c(7, 5, 4, 7, 2, 2, 2, 2, 7, 5, 3, 7, 8,
9, 7, 9, 2, 2, 2, 2, 4, 2, 5, 4, 9, 6, 8, 4, 3, 2, 4, 5, 3, 2,
2, 7, 7, 6, 6, 5, 7, 7, 7, 4, 8, 7, 3, 2, 9, 9, 4, 3, 4, 4, 5,
5, 8, 7, 7, 7), X5 = c(7, 6, 4, 6, 2, 2, 2, 2, 6, 4, 3, 7, 7,
9, 6, 9, 2, 2, 2, 2, 2, 2, 4, 4, 9, 8, 6, 5, 2, 2, 4, 3, 2, 2,
4, 7, 7, 6, 5, 6, 7, 7, 7, 3, 4, 5, 3, 2, 9, 9, 4, 2, 4, 4, 4,
5, 8, 4, 6, 5), X6 = c(8, 4, 3, 8, 3, 2, 2, 2, 6, 5, 3, 7, 9,
9, 7, 9, 2, 2, 2, 2, 6, 4, 6, 5, 8, 7, 6, 3, 2, 2, 2, 2, 4, 5,
8, 8, 8, 2, 3, 4, 8, 8, 5, 3, 2, 2, 2, 2, 9, 9, 4, 4, 4, 4, 4,
4, 5, 3, 4, 5), X7 = c(6, 6, 4, 4, 2, 2, 2, 2, 7, 4, 3, 7, 6,
7, 4, 6, 2, 2, 2, 2, 2, 2, 4, 2, 7, 4, 8, 2, 2, 2, 4, 3, 3, 3,
2, 5, 8, 4, 6, 7, 6, 6, 4, 2, 4, 8, 7, 2, 8, 8, 3, 3, 5, 5, 6,
6, 5, 8, 8, 8), X8 = c(6, 6, 4, 4, 2, 2, 2, 2, 7, 4, 3, 7, 5,
7, 6, 6, 2, 2, 2, 2, 2, 2, 2, 2, 6, 3, 7, 3, 2, 2, 4, 2, 2, 2,
2, 4, 7, 4, 4, 6, 6, 6, 5, 2, 2, 7, 3, 2, 8, 7, 3, 3, 4, 5, 5,
5, 4, 6, 8, 8), X10 = c(9, 9, 9, 8, 9, 9, 9, 9, 4, 6, 8, 3, 6,
5, 6, 4, 9, 9, 9, 9, 8, 7, 8, 8, 2, 8, 3, 9, 9, 9, 9, 7, 7, 8,
7, 7, 4, 3, 7, 6, 9, 6, 9, 9, 9, 9, 9, 9, 4, 4, 8, 9, 9, 6, 8,
8, 9, 9, 9, 9), X11 = c(5, 6, 4, 7, 2, 3, 2, 3, 7, 6, 2, 3, 8,
7, 6, 7, 2, 2, 2, 2, 3, 2, 2, 3, 9, 4, 8, 2, 2, 2, 6, 5, 3, 2,
2, 2, 5, 7, 4, 6, 8, 5, 8, 2, 7, 7, 2, 2, 8, 8, 4, 4, 5, 4, 5,
4, 5, 3, 5, 3), X12 = c(8, 6, 4, 6, 2, 2, 2, 2, 2, 5, 2, 2, 3,
3, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 9, 4, 4, 2, 2, 3, 6, 2, 3,
3, 3, 4, 4, 8, 7, 5, 8, 6, 4, 5, 8, 2, 2, 2, 4, 4, 3, 5, 5, 4,
4, 7, 4, 6, 6), X13 = c(9, 8, 8, 8, 2, 2, 2, 2, 3, 5, 3, 2, 7,
5, 8, 5, 2, 2, 2, 2, 2, 2, 2, 2, 2, 8, 3, 3, 2, 2, 5, 6, 7, 7,
8, 6, 3, 4, 8, 6, 4, 6, 6, 6, 9, 9, 9, 4, 3, 5, 6, 8, 8, 8, 8,
9, 7, 8, 9, 9), X14 = c(7, 5, 6, 8, 2, 2, 2, 2, 7, 5, 3, 9, 8,
8, 6, 9, 2, 2, 2, 2, 5, 2, 3, 3, 9, 6, 8, 2, 5, 4, 6, 4, 4, 5,
5, 6, 6, 8, 3, 5, 9, 7, 6, 8, 9, 9, 4, 3, 9, 9, 4, 4, 6, 7, 6,
7, 8, 8, 8, 9), X15 = c(7, 6, 4, 6, 2, 2, 2, 2, 6, 5, 3, 8, 9,
7, 6, 5, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 3, 3, 4, 4, 5, 3,
4, 7, 2, 3, 5, 2, 6, 5, 6, 3, 4, 7, 5, 3, 8, 8, 3, 4, 5, 5, 6,
6, 8, 7, 6, 7), X16 = c(7, 6, 4, 6, 2, 3, 2, 2, 7, 5, 3, 8, 9,
9, 7, 9, 2, 2, 2, 2, 2, 2, 7, 5, 9, 7, 8, 2, 2, 2, 4, 4, 5, 4,
4, 6, 9, 8, 6, 6, 6, 5, 6, 3, 8, 7, 3, 3, 8, 8, 4, 4, 4, 5, 5,
5, 8, 7, 5, 7), X17 = c(9, 4, 3, 7, 3, 3, 2, 2, 2, 2, 2, 2, 9,
8, 7, 4, 2, 2, 2, 2, 2, 2, 2, 2, 9, 5, 8, 3, 2, 2, 7, 6, 4, 2,
3, 3, 4, 7, 6, 6, 8, 7, 7, 3, 2, 2, 3, 3, 2, 7, 5, 4, 4, 4, 4,
4, 4, 4, 4, 3), X18 = c(8, 5, 7, 7, 2, 2, 2, 2, 2, 5, 3, 7, 9,
8, 9, 9, 2, 2, 2, 2, 4, 4, 5, 3, 9, 8, 9, 3, 3, 2, 5, 4, 3, 4,
6, 5, 6, 8, 8, 8, 4, 5, 3, 2, 9, 8, 7, 3, 6, 8, 4, 2, 2, 4, 4,
3, 6, 4, 3, 6), X19 = c(4, 5, 7, 8, 2, 2, 2, 2, 7, 4, 3, 8, 9,
8, 7, 9, 2, 2, 2, 2, 2, 2, 4, 2, 9, 6, 8, 2, 2, 2, 5, 4, 3, 2,
2, 2, 8, 9, 3, 7, 6, 6, 2, 2, 8, 5, 2, 3, 7, 9, 3, 3, 5, 3, 4,
2, 7, 5, 4, 5), X20 = c(8, 7, 7, 7, 5, 6, 6, 6, 4, 3, 4, 4, 8,
5, 6, 7, 6, 6, 6, 6, 4, 2, 4, 4, 9, 4, 7, 6, 5, 5, 5, 5, 6, 6,
6, 6, 8, 5, 6, 5, 5, 3, 2, 2, 8, 9, 9, 9, 9, 9, 6, 7, 8, 8, 8,
9, 9, 8, 9, 8), X21 = c(9, 8, 7, 7, 4, 4, 5, 5, 9, 3, 8, 9, 9,
9, 9, 9, 4, 4, 4, 4, 8, 7, 7, 4, 9, 8, 9, 9, 4, 5, 5, 5, 5, 6,
5, 6, 9, 7, 7, 7, 6, 6, 6, 6, 9, 9, 9, 9, 9, 9, 6, 8, 8, 8, 8,
9, 9, 8, 9, 9), X23 = c(4, 4, 3, 6, 3, 2, 2, 2, 2, 2, 2, 2, 6,
7, 4, 7, 3, 3, 3, 3, 3, 2, 2, 2, 7, 5, 7, 4, 2, 2, 2, 2, 4, 6,
8, 7, 4, 2, 5, 4, 2, 2, 2, 2, 2, 2, 2, 2, 8, 9, 5, 5, 4, 6, 5,
5, 5, 3, 5, 8), X24 = c(4, 3, 6, 3, 2, 2, 2, 4, 2, 2, 2, 2, 8,
8, 7, 7, 2, 2, 2, 2, 7, 8, 5, 5, 3, 2, 3, 2, 2, 2, 2, 2, 2, 2,
2, 2, 7, 5, 6, 5, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 8, 2, 2, 2,
2, 2, 2, 2, 2), X25 = c(6, 6, 6, 7, 3, 5, 3, 3, 7, 5, 3, 5, 8,
8, 9, 9, 2, 2, 2, 2, 6, 7, 6, 5, 7, 2, 3, 2, 2, 2, 2, 2, 2, 3,
3, 4, 5, 4, 6, 6, 7, 9, 7, 4, 2, 2, 2, 2, 5, 6, 2, 9, 2, 5, 4,
3, 4, 3, 3, 6), X26 = c(8, 7, 5, 7, 3, 5, 3, 4, 4, 5, 3, 6, 7,
6, 7, 4, 2, 2, 2, 2, 2, 6, 5, 4, 2, 9, 9, 3, 2, 2, 2, 2, 4, 6,
7, 4, 5, 6, 8, 6, 6, 6, 7, 3, 3, 7, 5, 4, 4, 5, 3, 5, 4, 5, 5,
4, 4, 4, 5, 6), X28 = c(6, 4, 5, 6, 2, 2, 2, 2, 7, 4, 2, 5, 8,
6, 7, 5, 3, 3, 3, 3, 2, 2, 2, 2, 7, 4, 6, 2, 2, 2, 2, 2, 3, 3,
2, 4, 5, 7, 7, 6, 5, 3, 6, 5, 2, 8, 2, 2, 5, 5, 7, 7, 4, 4, 4,
5, 4, 3, 4, 7), X29 = c(5, 8, 6, 6, 9, 9, 9, 9, 5, 6, 9, 5, 3,
4, 4, 6, 8, 8, 8, 8, 9, 8, 9, 8, 5, 8, 8, 8, 8, 8, 6, 7, 6, 7,
7, 5, 4, 3, 4, 4, 6, 4, 6, 5, 8, 5, 8, 8, 7, 7, 4, 5, 7, 7, 6,
7, 8, 8, 9, 8), X30 = c(3, 3, 4, 5, 2, 2, 2, 2, 5, 4, 2, 5, 8,
7, 7, 6, 2, 2, 2, 2, 2, 2, 2, 2, 6, 5, 6, 3, 3, 2, 2, 2, 2, 2,
4, 3, 7, 8, 7, 6, 2, 2, 2, 2, 2, 9, 3, 2, 4, 3, 6, 5, 3, 2, 4,
3, 2, 2, 2, 4), X32 = c(2, 3, 3, 3, 2, 4, 2, 3, 3, 2, 2, 6, 8,
7, 8, 8, 2, 2, 2, 2, 2, 2, 2, 2, 8, 5, 8, 2, 2, 2, 2, 2, 3, 2,
2, 3, 2, 6, 4, 6, 9, 9, 9, 5, 2, 9, 2, 2, 5, 4, 6, 7, 2, 2, 2,
2, 5, 6, 5, 6), X34 = c(2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 4,
3, 4, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2,
6, 6, 2, 2, 3, 2, 6, 8, 7, 2, 2, 2, 3, 2, 6, 4, 3, 3, 3, 4, 3,
3, 4, 3, 4, 2)), class = "data.frame", row.names = c(NA, 60L))
Now that we defined the dataset, let's jump in with the code.
library(psych)
fit <- fa(data, nfactors = 4)
#> Loading required namespace: GPArotation
print(fit$loadings)
#>
#> [Loadings truncated for brevity]
#>
#> MR1 MR2 MR3 MR4
#> SS loadings 9.464 3.571 2.171 1.682
#> Proportion Var 0.338 0.128 0.078 0.060
#> Cumulative Var 0.338 0.466 0.543 0.603
print(fit$Vaccounted, digits = 3)
#> MR1 MR2 MR3 MR4
#> SS loadings 10.392 4.328 2.324 1.8283
#> Proportion Var 0.371 0.155 0.083 0.0653
#> Cumulative Var 0.371 0.526 0.609 0.6740
Created on 2022-02-10 by the reprex package (v2.0.1)
We can see the values differ. Any ideas why?

https://www.researchgate.net/post/How_can_of_Variance_of_factors_in_exploratory_factor_analysis_be_calculated_when_factors_are_correlated
I am not familiar with factor analysis, but as shown here, it seems that SS loading cannot be calculated as a sum of squares because of inter-factor correlations when oblique rotation is used. Perhaps, fit$Vaccounted takes this problem into account but fit$loadings is simply the sum of squares. I think this difference appears.
Note that the default rotation in the fa package is oblimin which is obliqu rotation, so I think this difference will appear.

How can I add edges into an existing plot?

I am wanting to plot graph clusters that I define by myself. I am using the simplified undirected enron data.
library(igraphdata)
data("enron")
g <- as.undirected(enron)
g <- simplify(g)
rm("enron")
member <- c(1, 8, 9, 9, 10, 10, 8, 7, 4, 1, 2, 6, 3, 1, 2, 8, 7, 2, 1, 5,
1, 7, 6, 4, 8, 4, 8, 10, 3, 6, 1, 4, 7, 4, 3, 7, 9, 10, 3, 8, 1,
9, 8, 2, 7, 2, 9, 5, 1, 2, 6, 10, 3, 3, 2, 1, 9, 10, 3, 5, 6, 5,
5, 3, 7, 6, 9, 10, 8, 10, 8, 8, 10, 10, 10, 8, 7, 7, 9, 1, 9, 2, 9,
7, 2, 7, 7, 3, 2, 5, 2, 1, 6, 5, 10, 4, 3, 2, 4, 6, 4, 9, 5, 4,
1, 10, 2, 3, 4, 3, 6, 3, 6, 4, 6, 8, 2, 4, 5, 1, 5, 1, 4, 10, 4, 7,
5, 9, 10, 1, 2, 1, 5, 7, 5, 3, 5, 8, 7, 9, 5, 8, 1, 5, 3, 3, 3, 10,
1, 7, 8, 4, 1, 10, 9, 6, 9, 9, 4, 2, 6, 4, 6, 3, 5, 6, 9, 7, 6, 6,
4, 8, 6, 8, 8, 2, 5, 4, 3, 2, 9, 10, 2, 7)
I have tried many ways but none looks good. The best I can make is
edges_data_frame <- get.data.frame(g, what = "edges")
w.mem <- rep(0, length(E(g)))
for (i in 1:length(E(g))){
w.mem[i] <- ifelse(member[edges_data_frame$from[i]] == member[edges_data_frame$to[i]], 500, 1)
}
mem <- make_clusters(g,member)
E(g)$weight <- w.mem
colors <- rainbow(max(membership(mem)))
layout <- layout.fruchterman.reingold(g, weights=w.mem)
set.seed(1234)
plot(g, vertex.color=colors[mem$membership],
mark.groups=communities(mem),
vertex.label = NA,
edge.width = 1, edge.color = "lightgray", vertex.size = 5)
my first trial
I found that the "deleting edges plot" looks much cleaner
coGrph <- delete_edges(g, E(g)[crossing(mem, g)])
col_vector <- c('#e6194b', '#3cb44b', '#ffe119', '#4363d8', '#f58231', '#911eb4', '#46f0f0', '#f032e6', '#bcf60c', '#fabebe', '#008080', '#e6beff', '#9a6324', '#fffac8', '#800000', '#aaffc3', '#808000', '#ffd8b1', '#000075', '#808080', '#ffffff', '#000000')
temp <- sapply(1:length(V(g)), FUN = function(i) {col_vector[member[i]]})
V(coGrph)$color <- temp
plot(coGrph, vertex.label = NA, vertex.size = 5)
my second trial
However, this plot has some missing edges and does not reflect the true connection of the plot. I want to use this plot and add the deleted edges back to the plot without changing the positions I have right now. Is it possible?
Thank you very much I really appreciate your help.

Yes. Use your coGrph to create a layout, but then plot the original graph.
Continuing your "second trial"
set.seed(1234)
LOcG = layout_nicely(coGrph)
V(g)$color <- temp
plot(g, layout=LOcG, vertex.label = NA, vertex.size = 5)

How to convert a stem and leaf plot into a data set in R?

The stem and leaf plot that I need to convert is given below-
24|9
23|
22|1
21|7
20|2, 2, 5, 5, 6, 9, 9, 9
19|0, 0, 0, 0, 0, 1, 1, 2, 4, 4, 5, 8
18|0, 1, 1, 2, 2, 2, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 7, 9, 9, 9
17|1, 1, 1, 2, 3, 3, 4, 4, 4, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 9
16|0, 0, 1, 1, 1, 1, 2, 4, 5, 5, 6, 6, 8, 8, 8, 8
15|0, 1, 1, 1, 1, 1, 1, 5, 5, 5, 5, 6, 6, 6, 7, 7, 8, 9
14|0, 0, 0, 1, 2, 3, 4, 5, 6, 7, 7, 7, 8, 9, 9
13|0, 0, 0, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 4, 5, 5, 6, 6, 6, 6, 7, 7, 8, 8, 8, 9, 9, 9
12|1, 1, 1, 2, 2, 2, 3, 4, 4, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 9, 9, 9
11|0, 1, 1, 2, 2, 2, 2, 3, 3, 4, 4, 5, 5, 6, 9, 9
10|0, 2, 3, 3, 3, 4, 4, 5, 7, 7, 8
9|0, 0, 9
8|6

Here's maybe one way. If your data looks like this
stem <- "24|9
23|
22|1
21|7
20|2, 2, 5, 5, 6, 9, 9, 9
19|0, 0, 0, 0, 0, 1, 1, 2, 4, 4, 5, 8
18|0, 1, 1, 2, 2, 2, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 7, 9, 9, 9
17|1, 1, 1, 2, 3, 3, 4, 4, 4, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 9
16|0, 0, 1, 1, 1, 1, 2, 4, 5, 5, 6, 6, 8, 8, 8, 8
15|0, 1, 1, 1, 1, 1, 1, 5, 5, 5, 5, 6, 6, 6, 7, 7, 8, 9
14|0, 0, 0, 1, 2, 3, 4, 5, 6, 7, 7, 7, 8, 9, 9
13|0, 0, 0, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 4, 5, 5, 6, 6, 6, 6, 7, 7, 8, 8, 8, 9, 9, 9
12|1, 1, 1, 2, 2, 2, 3, 4, 4, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 9, 9, 9
11|0, 1, 1, 2, 2, 2, 2, 3, 3, 4, 4, 5, 5, 6, 9, 9
10|0, 2, 3, 3, 3, 4, 4, 5, 7, 7, 8
9|0, 0, 9
8|6"
Then we can split up the rows and for each row we split by the pipe. Then we split the right side by commas and join each of those values to the value to the left of the pipe.
rows <- strsplit(stem,"\n")[[1]]
values <- unlist(lapply(strsplit(rows,"\\|"), function(x) {
end_digits <- strsplit(x[2], ", ")[[1]]
if (!all(is.na(end_digits))) {
paste0(x[1], end_digits)
} else {
NULL
}
}
))
This will return character values, but you could convert to numeric with
as.numeric(values)

Here is a different approach. Using #MrFlick's stem and rows objects:
rows <- strsplit(stem,"\n")[[1]]
rows.lst <- strsplit(rows,"\\|")
tens <- as.numeric(sapply(rows.lst, "[", 1)) * 10
ones <- sapply(strsplit(sapply(rows.lst, "[", 2), ","), as.numeric)
vals <- unlist(mapply("+", tens, ones))
vals <- vals[!is.na(vals)]

Error reading dataset in R

I have problem in reading a dataset
My code :
require(igraph)
g <- graph(c(0, 1, 1, 2, 2, 0, 1, 3, 3, 4,
4, 5, 5, 3, 4, 6, 6, 7, 7, 8,
8, 6, 9, 10, 10, 11, 11, 9))
Error :
Error in graph(c(0, 1, 1, 2, 2, 0, 1, 3, 3, 4, 4, 5, 5, 3, 4, 6, 6, 7, :
At structure_generators.c:84 : Invalid (negative) vertex id, Invalid vertex id

The problem seems to be vertex of name 0
yourgraph <- c(0, 1, 1, 2, 2, 0, 1, 3, 3, 4,
4, 5, 5, 3, 4, 6, 6, 7, 7, 8,
8, 6, 9, 10, 10, 11, 11, 9)
g <- graph(yourgraph + 1)

Visualization of Cayley tables in random colors?

I've got the following data which I can visualize like this
A = matrix(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 2, 1, 5, 6, 3, 4, 9, 10, 7, 8, 12, 11, 3, 5, 1, 7, 2, 9, 4, 11, 6, 12, 8, 10, 4, 6, 7, 8, 9, 10, 11, 1, 12, 2, 3, 5, 5, 3, 2, 9, 1, 7, 6, 12, 4, 11, 10, 8, 6, 4, 9, 10, 7, 8, 12, 2, 11, 1, 5, 3, 7, 9, 4, 11, 6, 12, 8, 3, 10, 5, 1, 2, 8, 10, 11, 1, 12, 2, 3, 4, 5, 6, 7, 9, 9, 7, 6, 12, 4, 11, 10, 5, 8, 3, 2, 1, 10, 8, 12, 2, 11, 1, 5, 6, 3, 4, 9, 7, 11, 12, 8, 3, 10, 5, 1, 7, 2, 9, 4, 6, 12, 11, 10, 5, 8, 3, 2, 9, 1, 7, 6, 4),nrow=12,ncol=12,byrow=TRUE)
require(plotrix)
color2D.matplot(A)
(A could be any square matrix of whole numbers)
I need to make it display with random colors which aren't too similar. Here's an example of what I am trying to achieve:
I've been unable to get randomized colors to work. Is matplot the function for this? Can anyone show me how to randomize the colors?

Per #DWin's comment, try:
plot(NULL, type= "n", xlim = c(1,ncol(A)), ylim = c(1, nrow(A)), xlab = "column", ylab = "row",
main = "HCL colors, pseudo-random hue, scaled chroma and luminance")
rect(col(A)-.5,row(A)-.5,col(A)+.5,row(A)+.5,
col = hcl(h = round(runif(length(A))*360), c = 60*A/max(A)+20, l = 60*A/max(A)+20)
)
I guessed that you still wanted the values in your matrix to still determine the 'darkness' of the colors, as was the case in the grayscale image. The only thing random here is the hue- i.e. a randomly picked angle from a color wheel.

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