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.
Visualize Sparse Matrix.
4 messages · FRANCISCO XAVIER SUMBA TORAL, Jim Lemon
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.sumba93 at 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]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
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 <drjimlemon at 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.sumba93 at 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]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Hi Francisco, Your example plot shows me what you want to do (I think). I'm guessing that you want to display the values in your matrix that are NOT zero or NA, either colored in some way, or just in one color as the example. The following example shows how to do both of these: # wtmat<-matrix(rnorm(4602*1817),nrow=4602) # use a smaller matrix to illustrate the principle wtmat<-matrix(rnorm(46*18),nrow=46) # make it "sparse" by taking out all small values # in your case this may be changing all zero values to NS wtmat[abs(wtmat)<1]<-NA library(plotrix) x11(width=5,height=13) # display all values in the matrix # colored as red->white (negative values), white (NA) # and white->black (positive values) color2D.matplot(wtmat,c(1,1,0),c(0,1,0),c(0,1,0),border=FALSE) # now do a plot just showing values that are not NA color2D.matplot(abs(wtmat),extremes=c(4,4),border=FALSE) My original example also looked "dirty", albeit colorful, because there were so many rectangles on it. With a PDF plot about 500mm high you can see the individual rectangles in a matrix plot of your original dimensions. Jim On Sat, Jun 11, 2016 at 3:29 AM, FRANCISCO XAVIER SUMBA TORAL <
xavier.sumba93 at ucuenca.ec> wrote:
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: snipped