Hi Jim,
Thanks for your answer.
I try your code example, but it is basically the same that I had it. I want to
visualise my matrix something like this image:
With the graphics that I already have is difficult to visualise my data. I am
getting this results:
1) With my first code, I got this:
2) With Jim’s code. I got this:
Ho can I make my graphs more observable as in the first figure? My graphs shows
points as if my screen was dirty.
Cheers.
> On Jun 10, 2016, at 04:39, Jim Lemon <drjimle...@gmail.com> wrote:
>
> Hi Francisco,
> I tried this just to see if it would work. It did, after a while.
>
> wtmat<-matrix(rnorm(4602*1817),nrow=4602)
> library(plotrix)
> x11(width=5,height=13)
> color2D.matplot(wtmat,c(1,1,0),c(0,1,0),0,border=FALSE)
>
> Jim
>
> On Fri, Jun 10, 2016 at 8:27 AM, FRANCISCO XAVIER SUMBA TORAL
> <xavier.sumb...@ucuenca.ec> wrote:
>> Hi,
>>
>> First of all, sorry for my question it could be so basic for a common user
>> in R, but I am starting with this new environment.
>>
>> I have done a clustering job and I would like to visualize my vectors. I
>> have a matrix of TF-IDF weights of 4602 x 1817. I store the values in a CSV
>> file. How can I visualize my vectors in a 2D-space?
>>
>> After that, I execute a clustering algorithm and I got a label for each
>> cluster. How can I visualize my vectors resulting base on a color or figure
>> for each cluster?
>>
>> This is the code that I am having trying to accomplish my graphs:
>>
>> data <- read.csv(pathFile,header = FALSE, sep = ",”)
>> dMatrix <- matrix(unlist(data), ncol = 4602, byrow = TRUE) # Use a matrix to
>> use melt.
>> # Graph my data
>> ggplot(melt(dMatrix), aes(Var1,Var2, fill=value)) + geom_raster() +
>> scale_fill_gradient2(low='red', high=‘black', mid=‘white') + theme_bw() +
>> xlab("x1") + ylab("x2")
>>
>>
>> Cheers.
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
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>> and provide commented, minimal, self-contained, reproducible code.
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