Taking the Inverse of a Tall Array To Solve a Linear System of Equations

Hi, I'm working with some large data sets and have begun using tall arrays for the first time. I was happy to hear that the inverse function (\) was available for tall arrays, but am having some trouble on implementation. Below is a none-working example (you may need to set your own output directory), if F is tall or not doesn't change anything.

function [SOL] = MinWorkExample
outDIR = 'M:\project\MATLAB Folder\PhD\TESTAREA\InterpolationForPaper\PHFtall';
fileIDX = 1;
rowsPerFile = 1e3;
rowsWritten = 0;
totalRows = 1e5;
while rowsWritten<totalRows
    rowsToWrite = min(rowsPerFile, totalRows-rowsWritten);
    datas = rand(1,totalRows);
    fname = fullfile(outDIR,sprintf('datas_%05d.mat',fileIDX));
    save(fname,'datas');
    fileIDX = 1 + fileIDX;
    rowsWritten = rowsToWrite + rowsWritten;
end
ds = fileDatastore(fullfile(outDIR, '*.mat'), ...
    'ReadFcn', @(fname) getfield(load(fname), 'datas'), ...
    'UniformRead', true);
CONMAT = tall(ds);
% Either F does not work.
% F = rand(totalRows,1);
F = tall(rand(totalRows,1));
SOL = CONMAT\F;

Answer 1

[Ayden Clay]

So! I'm a collossal idiot. The error note was incredibly well written, and described my exact problem. Turns out that if I repeat the process but write in columns rather than rows, we're all good.

In the same nomenclature as the question, here is a working version:

function [SOL] = MinWorkExample
outDIR = '\PHFtall';
fileIDX = 1;
ColsPerFile = 1e3;
ColsWritten = 0;
totalCols = 1e5;
while ColsWritten<totalCols
    colsToWrite = min(ColsPerFile, totalCols-ColsWritten);
    datas = rand(totalCols,1);
    fname = fullfile(outDIR,sprintf('datas_%05d.mat',fileIDX));
    save(fname,'datas');
    fileIDX = 1 + fileIDX;
    ColsWritten = colsToWrite + ColsWritten;
end
ds = fileDatastore(fullfile(outDIR, '*.mat'), ...
    'ReadFcn', @(fname) getfield(load(fname), 'datas'), ...
    'UniformRead', true);
CONMAT = tall(ds);
F = tall(rand(1,totalCols));
SOL = CONMAT\F;

[Ayden Clay]

Nevermind. This causes a further issue in that the data is vertically concatenated, producing a large Nx1 vector. Still working on a fix.