## How can I save a very large MATLAB sparse matrix to a text file?

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function is not defined for sparse inputs

I have a 30000x14000 sparse matrix in MATLAB (version 7), which I need to use in another program. Calling save won't write this as ASCII (not supported). Calling `full()`

on this monster results in an `Out of Memory`

error.
How do I export it?

You can use find to get index & value vectors:

[i,j,val] = find(data) data_dump = [i,j,val]

You can recreate data from data_dump with spconvert, which is meant to "Import from sparse matrix external format" (so I guess it's a good export format):

data = spconvert( data_dump )

You can save to ascii with:

save -ascii data.txt data_dump

But this dumps indices as double, you can write it out more nicely with fopen/fprintf/fclose:

fid = fopen('data.txt','w') fprintf( fid,'%d %d %f\n', transpose(data_dump) ) fclose(fid)

Hope this helps.

**Why am I not able to write a sparse matrix to a file using the ,** Learn more about dlmwrite, sparse, matrix, matrices, sprintf MATLAB. Perhaps using a text format to output all of the elements of a very large sparse matrix is Select a Web Site. Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .

Save the sparse matrix as a `.mat`

file. Then, in the other program, use a suitable library to read the `.mat`

file.

For instance, if the other program is written in Python, you can use the `scipy.io.mio.loadmat`

function, which supports sparse arrays and gives you a sparse numpy matrix.

**How can I write a sparse matrix's non-zero values and the ,** Learn more about MATLAB. I define a sparse identity matrix, using the SPEYE command as follows: would like to write the non-zero elements as well as the row and column information corresponding to the non-zero elements to a text file. I have a 2D matrix myMatrix of integers which I want to save its content to a text file. I did the following: save myFile.txt myMatrix -ASCII I get this message: Warning: Attempt to write an unsupported data type to an ASCII file. Variable 'myMatrix' not written to file. and nothing is written. What to do?

I saved it as text using Java within MATLAB. MATLAB Code:

pw=java.io.PrintWriter(java.io.FileWriter('c:\\retail.txt')); line=num2str(0:size(data,2)-1); pw.println(line); for index=1:length(data) disp(index); line=num2str(full(data(index,:))); pw.println(line); end pw.flush(); pw.close();

Here `data`

is an extremely large sparse matrix.

**Import from sparse matrix external format,** This MATLAB function constructs sparse matrix S from the columns of D in a manner Convert Data File to Sparse Matrix Save the file in your current directory. Partition large arrays across the combined memory of your cluster using I want to save a matrix as text file. thank you very much sir 0 Comments. Discover what MATLAB ® can do for your career.

Did you try partitioning it ?

I mean try calling full() on the 1000 first rows (or 5000) and then repeat the process if it works.

**Best way to save big matrices - MATLAB Answers,** I'm looking for the best way to save big (both full and sparse) matrices in files. The nonsparse matrices will be too big to be stored into memory as a full matrix. If your file is all zeros the solution is fairly trivial: Make a loop that prints y zeros x times. If your matrix is not all zeros, the problem is a bit more interesting. Hopefully it is quite a sparse matrix, in which case this question has some good answers: How can I save a very large MATLAB sparse matrix to a text file?

Use the `find`

function to get the indices of non-zero elements...

idcs = find(data); vals = data(idcs); ...save the index vector and value vector in whatever format you want...

If you want, you can use `ind2sub`

to convert the linear indices to row, column subscripts.

If you need to recreate a sparse matrix in matlab from subscripts + values, use `spconvert`

.

**How to save a huge matrix efficiently? - MATLAB Answers,** I want to save a huge matrix into a mat.file. If the matrices are sparse (i.e. they contain mostly zeros with a few non-zero values) then saving I can't tell much about the structure of matrix but as you can see from the storage space used on disk, it has huge number of zeros. Some entries are repeated versions of a particular entry. Such redundant entries were also not stored. But to compute eigen values or determinant, I thought I might have to construct the matrix first to give to Matlab

**Write A Sparse Matrix Out To A File In Matlab?,** Actually I downloaded a huge big scRNA-seq .txt file from paper. And How can i do this by matlab ?? I have matrix 100*100 and i get its The normal representation of a sparse matrix takes up lots of memory when the useful information can be captured with much less. A possible way to represent a sparse matrix is with a cell vector whose first element is a 2-element vector representing the size of the sparse matrix.

**Text Mining with MATLAB®,** First, it is assumed that each line of the CSV formatted file is read one at a time important format, which is commonly known as the sparse-matrix format. in general) we have to deal with huge matrices for which most of its elements are equal to zero. So, instead of saving N times M elements (where N and M can be easily In Matlab, we can create a sparse matrix by using the keyword “sparse”. The syntax which is used to represent the sparse matrix in Matlab with additional features like: i = Sparse(M) This is used to convert a normal matrix M to the sparse matrix which will squeeze out the zeroes present in the matrix and it helps in saving the memory.

**ImportMatrix - Maple Programming Help,** ImportMatrix import a Matrix from a file or URL ExportMatrix export a Matrix to a file This option applies to text files only. In most cases, ImportMatrix can automatically detect binary files created in MATLAB® MATLAB® sparse and dense arrays are imported as Maple sparse and rectangular Matrices, respectively. For example, in 32-bit MATLAB ®, a double sparse matrix with less than about 2/3 density requires less space than the same matrix in full storage. In 64-bit MATLAB, however, double matrices with fewer than half of their elements nonzero are more efficient to store as sparse matrices.

##### Comments

- The data_dump during the fprintf command should be transposed before using according the docs (mathworks.com/help/matlab/ref/fprintf.html). This happens because the data is written in collumn-order.
- I'm confused - why did you use java.io instead of MATLAB's built-in fopen and fprintf?
- probably because i knew better java than matlab, and it was a throw away code, so it didnt need to be beautiful. it just needed to work correctly :)
- yes thats always an option, it will probably take a lot of time writing ascii chunks and merging them later