How to save data using matfile Matlab - matlab

New to matlab and I need some help.
I need to create a .mat file , using matObj or save(), that has some information that will be passed from some variable. Lets say that variable x = 1,2,3,4,5
1|2|3|4|5|
Then I need to save that in test.mat
Then I need to load that file and save something like,
6|7|8|9|10|
So I get
1|2|3|4|5|
6|7|8|9|10|
and so on.
So every time I save it goes to a new row. The numbers that go inside they are not random the above numbers are just there to make things simple to see.
Can someone help me out.

You are describing two different problems here. The first is saving and loading of data.
Saving is easy:
x = 1:5;
filename = 'myFile.mat'
save(filename, 'x'); %notice that I used the string name of the variable
Likewise loading is also simple:
filename = 'myFile.mat';
data = load(filename); % loaded variables are placed in a struct to prevent overwriting workspace variables
x = data.x;
The 2nd problem can be solved using concatenation:
lets say you want to convert the vector 1 2 3 into the matrix:
1 2 3
1 2 3
You can simply call:
v = 1:3;
m = cat(1, v, v);
Likewise you can add an additional row to the existing matrix using the same command:
m = cat(1, m, v);

I'm sure any amount of googling will get you how to save a variable to a mat file - The matlab docs are absolutely spectacular, and such a simple operation will be covered along with examples showing exactly how to use the functions.
As for the second part, use the concatenation property
new = [old1 old2];
to concatenate horizontally, and
new = [old1;old2];
to concatenate vertically. Then resave the same way that you just learned via google.
Hope this helps, and in the future, i guarantee 99% of the answers to a new user's questions will be in the top two google search results if you append "matlab" to your search. The Mathworks really set the bar on documentation in my opinion. (Of course, I last used MATLAB 3 years ago)

Related

Applying (with as few loops as possible) a function to given elements/voxels (x,y,z) taken from subfields of multiple structs (nifti's) in MATLAB?

I have a dataset of n nifti (.nii) images. Ideally, I'd like to be able to get the value of the same voxel/element from each image, and apply a function to the n data points. I'd like to do this for each voxel/element across the whole image, so that I can reconvert the result back into .nii format.
I've used the Tools for NIfTI and ANALYZE image toolbox to load my images:
data(1)=load_nii('C:\file1.nii');
data(2)=load_nii('C:\file2.nii');
...
data(n)=load_nii('C:\filen.nii');
From which I obtain a struct object with each sub-field containing one loaded nifti. Each of these has a subfield 'img' corresponding to the image data I want to work on. The problem comes from trying to select a given xyz within each img field of data(1) to data(n). As I discovered, it isn't possible to select in this way:
data(:).img(x,y,z)
or
data(1:n).img(x,y,z)
because matlab doesn't support it. The contents of the first brackets have to be scalar for the call to work. The solution from googling around seems to be a loop that creates a temporary variable:
for z = 1:nz
for x = 1:nx
for y = 1:ny
for i=1:n;
points(i)=data(i).img(x,y,z);
end
[p1(x,y,z,:),~,p2(x,y,z)] = fit_data(a,points,b);
end
end
end
which works, but takes too long (several days) for a single set of images given the size of nx, ny, nz (several hundred each).
I've been looking for a solution to speed up the code, which I believe depends on removing those loops by vectorisation, preselecting the img fields (via getfield ?)and concatenating them, and applying something like arrayfun/cellfun/structfun, but i'm frankly a bit lost on how to do it. I can only think of ways to pre-select which themselves require loops, which seems to defeat the purpose of the exercise (though a solution with fewer loops, or fewer nested loops at least, might do it), or fun into the same problem that calls like data(:).img(x,y,z) dont work. googling around again is throwing up ways to select and concatenate fields within a struct, or a given field across multiple structs. But I can't find anything for my problem: select an element from a non-scalar sub-field in a sub-struct of a struct object (with the minimum of loops). Finally I need the output to be in the form of a matrix that the toolbox above can turn back into a nifti.
Any and all suggestions, clues, hints and help greatly appreciated!
You can concatenate images as a 4D array and use linear indexes to speed up calculations:
img = cat(4,data.img);
p1 = zeros(nx,ny,nz,n);
p2 = zeros(nx,ny,nz);
sz = ny*nx*nz;
for k = 1 : sz
points = img(k:sz:end);
[p1(k:sz:end),~,p2(k)] = fit_data(a,points,b);
end

Numerical Matrix CSV -> Covariance Matrix

I have a CSV file containing a numerical matrix with over two thousand New York Stock Exchange listed companies' value over two years.
It seems like it should be really simple - I want to attain a covariance matrix formed from the CSV matrix.
As far as I'm aware I simply need to:
Import the data as numerical matrix (just the data no headings etc) using the MATLAB Import Data button.
Press save as on the workspace variable and make e.g. NYSE.mat.
In my function call cov(NYSE.mat);
This should access the matrix and return a large covariance matrix from my data. The cov() function works when i manually input an example matrix of for example:
[5 0 3 7; 1 -5 7 3; 4 9 8 10];
But for some reason whenever I try to call cov(NYSE.mat); only one number is returned, rather than a covariance matrix.
Can anyone tell me where I'm going wrong? I've been trying to figure this out for a while now and I feel the answer should be really simple.
I'm running on MATLAB R2016a.
Not sure you need to manually save the workspace name in step 2. As part of your import process you once you click the import button the variable should be loaded into workspace with the name of the file (maybe NYSE)
Try Load('NYSE.mat') and see what appears in your workspace.
Once you figure out the name of the variable, calling the function with that.
If your CSV file is without any header lines (not sure if any CSV file needs them) and contains only numbers, you can simply call
x = importdata('<nameofyourcsv>.csv');
and then
c = cov(x);
or even do it in one step:
c = cov(importdata('nameofcsv.csv'));
This function is equivalent of clicking on the button you mention. However, if your file contains header lines, you have to specify its number and call this function with more parameters:
x = importdata('nameofcsv.csv',',', nh); % nh is a number of header lines
x will no longer be a regular MATLAB matrix but a structure with following fields: data, textdata, and colheaders. cov(x.data) will calculate covariance. Not sure why you would need to save anything in a mat file, though. If you wish, you would probably need to assign a value from a data field to a regular variable and then save such variable. Otherwise, you will save the whole x structure.
For instance, the following file, test.csv:
95.01,76.21,61.54,40.57,5.79,20.28,1.53
23.11,45.65,79.19,93.55,35.29,19.87,74.68
60.68,1.85,92.18,91.69,81.32,60.38,44.51
48.60,82.14,73.82,41.03,0.99,27.22,93.18
89.13,44.47,17.63,89.36,13.89,19.88,46.60
can be imported by calling importdata:
>> x = importdata('test.csv')
x =
95.0100 76.2100 61.5400 40.5700 5.7900 20.2800 1.5300
23.1100 45.6500 79.1900 93.5500 35.2900 19.8700 74.6800
60.6800 1.8500 92.1800 91.6900 81.3200 60.3800 44.5100
48.6000 82.1400 73.8200 41.0300 0.9900 27.2200 93.1800
89.1300 44.4700 17.6300 89.3600 13.8900 19.8800 46.6000
EDIT
I downloaded the file and copy pasted this command from your answer:
c = importdata('nyse_data_matrix_no_tags.csv');
Then, I opened the file in a text editor and copied 1st and 20th row of numbers in the file and created a matrix in MATLAB:
x = [46.09,24.69,156.78,5.95,21.14,76.17,55.51,7.04,38.87,19.58,47.57,7.73,119.44,1.61,44.55,24.9,50.89,4.87,26.25,15.95,15.96,39.14,121.27,15.7,25.91,25.8,69.7,16.32,12.86,7.89,247.4,27.11,41.6,5.14,47.77,40.98,13.78,26.058,14.56,41.05,24.27,47.13,40.92,27,85.04,15.06,5.05,29.14,7.51,67.5,67.79,42.68,124.86,24.28,27.82,18.08,100.67,109.07,12.59,50.34,18.64,4.75,6.06,16.63,109.86,14.1,54.48,13.9,59.98,16.24,45.53,4.06,67.99,18.22,4.2,117.23,158.75,5.7,2.46,76.39,77.79,6.17,16.95,5.27,12.74,14.7,19.14,14.4,42.77,26.4,14.17,76.57,12.4,42.07,77.47,41.27,60.53,16.97,65.71,56.13,258.4,28.96,760.07,60.46,34.77,133.1,14.19,29.41,11.78,154.55,44.75,15.18,17.52,24.86,36.18,14.1,30.1,47.65,22.92,47.37,61.84,226.52,10.2,65.14,7.88,16.34,170.23,9.6,34.42,15.0999,20.34,58.7,16.6,14.72,14.32,20.89,14.32,13.2,6.05,422.96,21.43,47.55,13.28,27.98,8.16,45.15,15.1665,41.65,17.45,25.73,63.03,16.07,17.56,11.54,6.54,33.18,15.01,357.96,74.88,15.24,27.24,69.08,36.29,76.55,65.72,50.93,72.73,16.13,23.81,52.14,16.05,12.19,71.77,14.97,11.82,33.04,7.86,15.26,72.46,15.42,24.49,15.75,63.78,32.43,36.57,16.24,7.08,26.08,15.74,14.78,16.22,16.85,23.32,31.14,12.72,6.7,26.65,24,12.95,129.92,20.07,11.28,34.66,12.86,17.5,26.5,0.7038,1.22,128.98,23.33,19.2,15.64,8.34,45.01,38.14,50.31,13.11,17.4,47.15,79.29,8.24,28.92,24.97,1.92,77.16,126.5,8.97,3.97,12.85,30.75,37.82,2.36,10.37,52.28,1.56,53,47.33,41.32,10.65,15.24,39.5,94.42,12,54.25,48.03,3.72,6.34,18.5,23.47,26.74,8.74,6.7,7.08,70.92,27.3,65.43,18.776,7.82,16.8,12.0625,124.24,29.79,22.88,29.4,66.44,28.88,1.505,0.8642,10.37,47.14,99.83,133.87,46.41,4.88,57.63,14.45,11.2,34.99,11.06,129.25,7.71,35.2,2.29,2.53,1.65,13.74,15.6,11.84,59.79,33.85,62.48,72.34,25.15,131.2,61.13,2.17,5.1,53.35,26.9,43.15,10.8,63.61,130.91,81.42,45.29,17.58,415.79,118.64,73.88,9.85,79.22,43.39,4.86,32.18,68.36,60.21,34.15,19.47,23.39,29.96,39.58,14.66,5.98,70.87,25.9,38.64,90.45,165.2,46.57,83.18,16.48,134.15,54.68,62.51,12.25,24.33,17.69,60.73,11.51,15.6,85.99,80.81,59.9,17.48,30.73,104.34,0.94,86.03,82.73,14.41,34.05,17.2,11.98,13,52.5,39.2,19.58,101.59,26.38,44.13,18.72,23.3,32.05,27,26.12,13.13,18.58,6.07,73.74,3.53,42.4,12.21,15.72,16.71,26.27,26.69,4.52,35.99,26.1,17.31,45.61,67.9,11.15,13.08,1.1,9.7001,17.51,59.8,26.27,86.95,18.95,26.75,34.33,66.72,107.98,9.7,18.27,24.16,56.8,46.56,91.69,21.43,78.75,3.37,13.71,31.73,100.39,5.65,6.98,85.21,97.84,13.5,26.19,42.43,26.73,10.11,47.95,102.84,66.95,28.35,14.07,5.25,23.68,127.43,11.41,10.43,4.19,25.48,19.78,72.08,53.59,17.41,36.57,92.37,127.48,23.98,16.46,5.28,24.76,9.1,68.33,64.45,8.15,18.54,8.85,119.72,3.62,20.49,2.57,94.05,16.99,25.93,25.12,25.71,9.68,81.26,16.7,77.21,37.45,80.43,6.95,24.95,87.1,20.74,31.82,25.44,25.48,25.5515,46.96,19.11,43.49,10,8.68,16.99,120.79,3.95,1.91,76.54,7.8,33.71,14.59,13.5,15.99,42.6,38.86,46.76,8.1,23.14,23.04,17.39,15.4399,13.62,14,125.94,13.92,22.98,48.68,4.62,68.17,1.14,9.82,29.75,73.66,6.51,92.28,25.53,25.6,25.63,7.59,72.9,25.23,10.41,27.87,10.81,48.76,11.38,3.76,71.78,13.21,53.59,25.55,42.43,68.21,66.25,37.2,6.1,6.24,84.58,13.17,13.2,22.92,82.95,28.9,6.07,74.57,29.35,74.89,64.46,77.91,30.21,11.09,6.34,21.69,56.88,15.25,41.44,1.77,67.42,209.26,11.24,15.8,13.53,15.09,32.8,9.78,12.99,62.77,21.8,39.11,78.68,14.75,10.67,20.6,10.57,36.39,7.24,6.1,13.61,14.58,51.04,20.36,102.48,35.14,12.31,8.98,3.7,81.22,89.67,27.32,13.26,1.54,37.84,11.29,8.98,24.08,4.43,8.54,15.51,36.26,9.33,6.56,43.38,13.04,10.9,54.68,160,164.11,34.25,15.87,14.65,18.72,10.57,13.25,21.08,62.55,6.08,22.72,17.25,14.1,11.91,16.5,17.36,4.93,31.46,75.14,32.84,55.65,21.39,18.76,53.36,52.27,150,11.51,50.35,4.77,16.2,13.83,43.24,94.4,37.89,13.18,35.9,70.65,14.16,11.8273,12.67,22.93,11.11,13.55,9.55,14.24,26.44,13.49,69.92,9.88,157.12,14.93,6.53,13.5,6.83,28.27,13.07,48.33,59,9.67,2.04,28.2,5.82,31.87,65.9,33.14,36.14,30.08,8.49,64.92,4.76,141.98,8.63,10.11,17.27,19.65,30.24,26.53,40.67,26.87,26.25,39.18,1.54,33.93,16.59,7.33,15.36,13.91,1.1,17.12,4.47,15.67,18.68,1.79,15.54,81.13,21.34,27.59,7.46,10.77,503.01,19.74,18.46,15.26,47.57,30.24,6.55,65.34,4.13,13.2,21.55,21.03,29.36,27.27,47.72,10,26.17,7.45,7.62,3.48,18.15,8.2,20.66,97.23,59.46,13.37,7.8,76.6,19.31,9.21,24.18,77.53,0.9,10.8,153.17,23.32,1.18,25.83,42.06,1.48,11.49,24.78,18.24,21.24,6.59,44.54,33.28,64.61,227.17,30,48.14,29.72,45.5,79.45,26.83,4.96,81.03,30.76,72.15,34.48,129.3,65.48,33.48,67.43,34.31,15.05,60.38,32.59,26.84,1.7,32.48,2.31,113.96,1.13,7.3,31.13,12.27,44.48,163.75,4.55,4.93,49.64,7,0.42,4.66,62.44,41.56,21.6,8.18,26.89,33.78,3.79,47.23,27.86,0.5199,45.15,117.21,9.51,74.52,1.8,67.24,22.28,22.735,28.48,13.84,19.61,26.62,25.78,18.95,33.53,21.54,51.22,13.79,34.9,81.22,6.86,15.59,96.42,18.49,31.21,24.57,21.23,22.93,16.32,10.63,11.18,188.35,16.08,18.39,18.17,43.96,62.54,8.82,1.87,33.38,14.9,10.47,16.69,3.2,8.89,3.95,50.02,153.42,7.65,35.53,0.54,18.36,5.24,262.52,4.07,74.98,12.53,13.66,86.82,129.8,24.78,9.8,7.03,21.68,8.1,17.1,7.5,38.4,118.45,6.47,26.92,17.2,7.6,35.32,1.72,25.83,9.11,26.27,13,12.18,12.29,44.75,26.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.3,112.64,26.1,44.12,5.27,8.25,22.99,68.65,75.61,9.07,53.28,10.89,87.69,7.53,5.49,28.77,16.93,31.76,56.22,26.5,25.85,25.7401,6.03,8.52,73.39,17.69,37.86,20.07,20.07,38.7,29.07,148.17,37.66,43.78,7.71,8.06,21.2,15.01,7.65,36.81,27.64,25.07,37.7,41.81,20.87,133.29,56.32,7.4,45.66,1.77,9.84,44.71,111.33,129.74,33.85,83.84,12.96,101.79,60.87,4.87,41.94,27.98,38.29,20.16,3.28,39.63,101.46,18.22,55.85,25.52,26.35,77.89,58.71,106.91,106.8875,82.26,18.76,74.11,14.07,22.74,9.85,32.93,60.84,3.9,14.49,14.35,21.27,1.82,12.3,13.61,54.78,46.51,13.6,9.1,116.12,134.97,14.18,56.62,96.69,3.28,13.6,14.19,47.52,24.93,12.36,27.7,10.77,15.9,66.72,50.39,30.56,4.05,51.47,27.54,37.84,79.17,4.41,34.21,134.96,105.34,35.36,55.08,92.92,69.47039835,24.05,19.76,12.71,60.18,48.91,90.11,26.55,49.2,5.82,2.9,68.28,20.82,40.56,56.32,171.54,11.4,11.94,10.99,11.91,13.69,45.01,10.93,61.78,19.05,9.11,46.67,23.65,66.85,14.14,21.6,30.4,35.89,63.93,10.56,14.96,9.02,29.15,52.18,56.31,29.22,38.54,54.51,133.93,13.7,71.27,2.27,825.61,32.84,56.14,13.07,19.25,17.79,17.89,31.23,69.13,14.81,1.75,115.34,41.85,4.97,33.71,89.67,24.5,27.18,5.98,53.57,9.24,43.24,526.42,3.48,20.92,81.57,5.13,117.44,23.66,12.76,14.3,32.23,12.09,46.25,4.9,5.77,6.24,11.94,8.45,6,38.21,2.05,1.18,1.19,2.17,0.73,3.23,3.05,1.46,2.06,4.68,18.27,0.3199,31.48,2.59,16.44,16.85,16.9,11.91,1.74,122.34,0.82,3.33,0.55,13.02,19.46,2.6,55.43,18.83,28.86,34.75,11.76,10.8,9.5,48.62,12.54,12.8,16.6,16.22,2.9,2.33,16.09,14.56,0.5024,0.24,9.84,0.15,13.19,13.82,14.1466,13.15,13.88,14.07,13.68,14.38,14.85,7.69,0.7663,0.324,1.89,5.35,0.9,0.77,23.7,1.2863,11.39,11.24,6.43,0.97,4.2127,0.3302,2.21,3.5,1.54,0.6,2.65,27.28,2.75,1.78,9.52,2.35,0.11,0.1212,5.68,13.86,31.34,7.6,0.42,1.56,0.6299,12.7,1.05,0.94,2.37,17.12,3.66,0.21,12.61,13.18,1.52,0.3221,0.6634,10.9,63.43,16.37,10.54,16.52,7.5,14.62,5.24,2,3.53,4.53,0.3581,4.75,2.59,0.7299,6.13,0.165,16.42,15.63,9.37,15.04,14.15,10.95,31.46,17.57,6.71,0.525,89.54,0.225,2.27,15.71,2.89,0.84,0.79,30.57,0.2603,8.49,7.26,19.76,44.32,0.6701,2930.11,0.51,2.29,12.6,2.07,0.49,0.5058,1.06,17.75,0.3579,63.51,0.8301,0.75,0.78,0.4875,0.7495,2.52,4.35,0.82,7.66,12.36,12.96,10.735];
I compared matrix x with the 1st and 20th row of c and they are equal:
isequal(x,c([1 20],:))
ans =
1
importdata seems to be working as expected.

MATLAB loading data from multiple .mat files

My data is x,y co-ordinates in multiple files
a=dir('*.mat')
b={a(:).name}
to load the filenames in a cell array
How do I use a loop to sequentially load one column of data from each file into consecutive rows of a new/separate array......?
I've been doing it individually using e.g.
Load(example1.mat)
A(:,1)=AB(:,1)
Load(example2.mat)
A(:,2)=AB(:,1)
Load(example3.mat)
A(:,3)=AB(:,1)
Obviously very primitive and time consuming!!
My Matlab skills are weak so any advice gratefully received
Cheers
Many thanks again, I'm still figuring out how to read the code but I used it like this;
a=dir('*.mat');
b={a(:).name};
test1=zeros(numel(b),1765);
for k=1:numel(b) S=load(b{k});
I then used the following code to create a PCA cluster plot
test1(k,:)=S.AB(:,2); end [wcoeff,score,latent,tsquared,explained] = pca(test1,... 'VariableWeights','variance');
c3 = wcoeff(:,1:3) coefforth = inv(diag(std(test1)))*wcoeff; I = c3'*c3 cscores = zscore(test1)*coefforth;
figure() plot(score(:,1),score(:,2),'+') xlabel('1st Principal Component') ylabel('2nd Principal Component') –
I was using 'gname' to label the points on the cluster plot but found that the point were simply labelled from 1 to the number of rows in the array.....I was going to ask you about this but I found out simply through trial and error if I used 'gname(b)' this labels the points with the .names listed in b.....
However the clusterplot starts to look very busy/messy once I have labelled quite a few points so now I am wondering is is possible to extract the filenames into a list by dragging round or selecting a few points, I think it is possible as I have read a few related topics.....but any tips/advice around gname or labelled/extracting labels from clusterplots would be greatly appreciated. Apologies again for my formatting I'm still getting used to this website!!!
Here is a way to do it. Hopefully I got what you wanted correctly :)
The code is commented but please ask any questions if something is unclear.
a=dir('*.mat');
b={a(:).name};
%// Initialize the output array. Here SomeNumber depends on the size of your data in AB.
A = zeros(numel(b),SomeNumber);
%// Loop through each 'example.mat' file
for k = 1:numel(b)
%// ===========
%// Here you could do either of the following:
1)
%// Create a name to load with sprintf. It does not require a or b.
NameToLoad = sprintf('example%i.mat',k);
%// Load the data
S = load(NameToLoad);
2)
%// Load directly from b:
S = load(b{k});
%// ===========
%// Now S is a structure containing every variable from the exampleX.mat file.
%// You can access the data using dot notation.
%// Store the data into rows of A
A(k,:) = S.AB(:,1);
end
Hope that is what you meant!

Extracting variables while reading in data files

I am quite new to data analysis, so if this is a rookie question, I'm sorry, I am learning as I go.
I have just started doing some work in variable star astronomy. I have about 100 files for every night of observation that all contain the same basic information (star coordinates, magnitude, etc.). I am loading all of the files into my workspace as arrays using a for-loop
files = dir('*.out');
for i=1:length(files)
eval(['load ' files(i).name ' -ascii']);
end
I'm only really interested in two columns in each file. Is there a way to extract a column and set it to a vector while this for-loop is running? I'm sure that it's possible, but the actual syntax for it is escaping me.
try using load as a function and save it's output to a variable
files = dir('*.out');
twoCols = {};
for ii=1:length(files)
data = load( files(ii).name, '-ascii' ); % load file into "data"
twoCols{ii} = data(:,1:2); % take only two columns
end
Now variable twoCols holds the two columns of each file in a different cell.
You have to assign the load result to a new variable. Then if lets say your variable is starsInfo you can use
onlyTwoFirst = starsInfo(:,1:2)
That means take all the rows, but only columns 1 and 2.

Import multiple tab delimited files into matlab from different subdirectories

Sorry I am new to matlab.
What I have: A folder containing about 80 subfolders, labeled Day01, Day02, Day03, etc. Each subfolder has a file called "sample_ids.txt" It is a n x m matrix in a tab delimited format.
What I need: 1 data structure that is an array of matrices, where each matrix is the data from "sample_ids.txt" and it should be in the alphabetical order of Day01, Day02, Day03, etc.
I have no idea how to get from point A to point B. Any guidance would be greatly appreciated.
You can decompose this problem into two parts: finding the files, and reading them into memory.
Finding the files is pretty easy, and has already been covered on StackOverflow.
For loading them into memory, you want a multidimensional array, which is as simple as creating a regular array and start using more index dimensions: A = ones(2); A(:,:,2) = ones(2); will, for example, give you a 3-dimensional array of size 2-by-2-by-2, with ones all over.
What you want, is probably want something like this:
A = [] % No prealocation. Fix for speed-up.
files = dir('./Day*/sample_ids.txt');
for file = files
temp = load(file.name);
A(:,:,size(A,3)+1) = temp;
end
disp(A) % display the contents of A afterards...
I haven't tested this code extensively, but it should work OK.
A few important points:
All files must contain matrices of the exact same dimensions - MATLAB can't handle arrays that have different dimensions in different layers (at least not with regular arrays - you could use cell arrays, but that quickly becomes more complicated...). Think of it as trying to build a matrix from vectors of different lengths.
If you have a lot of data, and you know how much, you can save a lot of time by pre-allocating A. This is as easy as A = zeros(k,l,m) for m datafiles with k rows and l columns in each. If you do this, you'll also have to figure out the index of the current file, so you can use that as the third index in the assignment (on the second line in the loop block). I leave this as an internet research excersize :)