Populating a spreadsheet - dlmwrite, '-append' and specifying rows and columns

Hello!

I'm trying to use a for loop to populate a spreadsheet with information from a struct, such that it pulls out each piece of information into a separate row.

My problem is arising when I try to use csvwrite - I can't append so it just gets overwritten. I switched to using dlmwrite but am now encountering another problem.

I originally tried this - but it got overwritten each time.

dlmwrite('Filename',A,rownum,1) 
dlmwrite('Filename',B,rownum,2)
dlmwrite('Filename',C,rownum,3)
dlmwrite('Filename',D,rownum,4)

I tried adding append in - but then it takes it format differently and comes back with an error stating I have an invalid attribute.

dlmwrite('Filename',A,'-append','delimiter',',',rownum,1)

Error using dlmwrite (line 118)
Invalid attribute tag: 1

Any thoughts on how I can format this so that I can still specify the row and column?

Thank you,

ML

PS. I cant really use xlswrite as I dont know the row names - (it's going to be in the thousands of rows - so Its difficult to call A1324)- unless anyone knows a workaround

Answer 1

[Joseph Cheng]

The error is that you are missing 'roffset' and 'coffset' designators for the row and column. However that will still not do what you want. Will A, B, C, D be all the same length? The problem with using -append is that it'll append it to the bottom of the file, so you will not be able to get your [A B C D] columns aligned. If they are the same length i would write them all at once with a single dlmwrite.

[Joseph Cheng]

Oh, and its late so I forgot to include this. Text files are row orientated. So to add a column to a text document you'll need to either concatenate the data first or read in whats already in there and write the data back with the new column.

[Mary]

A,B,C, and D are technically the same length (I'm pulling the data out of structs in a for loop)

Is there a way I could generate a matrix or a table from structs similarly to a dlmwrite and then have it write them all at once?