[R] Visualize Sparse Matrix.

[FRANCISCO XAVIER SUMBA TORAL]

Hi, 

Thanks for your help.

I used the SparseM package http://www.econ.uiuc.edu/~roger/research/sparse/SparseM.pdf <http://www.econ.uiuc.edu/~roger/research/sparse/SparseM.pdf>
First of all, I create a class for sparse matrices stored in Compressed Sparse Row (CSR) with as.matrix.csr(matrix).
After that, I plot the non-zero entries of a matrix of class matrix.csr with image(m.csr)


This is my code:

library(SparseM)
data <- read.csv(pathCSV, header = FALSE, sep = ",")
numcol <- ncol(data)
dMatrix <- matrix(unlist(data), ncol = numcol, byrow = TRUE)
dMatrix.csr <- as.matrix.csr(dMatrix)
image(dMatrix.csr, col=c("white","blue"))

After clustering, I will have the same matrix but each row (vector) has a tag to represent a cluster id. So, how could I plot my matrix to show a different color for cluster id?

This is an example of my results:

213	0	0 	0 	0.213	0.3423  
345	0	0 	0.32 0		0  
84	0	0.4 	0 	0.54		0  
84	0.86	0 	0 	0		0  
213	0	0.98 0 	0		0.45  
345	0	0.57 0 	0		0.4  

Cheers.

> On Jun 10, 2016, at 18:51, Amos Elberg <amos.elberg at gmail.com> wrote:
> 
> Sparse matrix visualization is a feature of my largeVis package:  https://github.com/elbamos/largeVis/tree/0.1.6 <https://github.com/elbamos/largeVis/tree/0.1.6>
> 
> 
> 
> On Thu, Jun 9, 2016 at 6:27 PM, FRANCISCO XAVIER SUMBA TORAL <xavier.sumba93 at ucuenca.ec <mailto: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.
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> 
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