Loading arrays of different sizes into a single array - arrays

Question

I have 100 arrays with the dimension of nx1. n varies from one array to the next (e.g, n1 = 50, n2 = 52, n3 = 48 etc.). I would like to combine all these arrays into a single one with the dimension of 100 x m with m being the max of n's.
The issue I am running into is that as n varies, Matlab will throw out an error says that the dimensions mismatch. Is there a way to get around this so I can pad "missing" cell with N/A? For instance, if the first array contains 50 elements (i.e., n1 = 50) like this:
23
31
6
...
22
the second array contains 52 elements (i.e., n2 = 52) like this:
25
85
41
...
8
12
66
The result should be:
23 25
31 85
6 41
... ...
22 8
N/A 12
N/A 66
Thanks to the community in advance!

Answer 1

Here is another approach without eval.
array_lengths = cellfun(#numel, arrays);
max_length = max(array_lengths);
result = nan(max_rows, num_arrays);
for r=1:num_arrays
result(1:array_lengths(r),r) = arrays{r}(1:array_lengths(r));
end
Some explanation: I'm assuming your arrays are stored in a cell to begin with. Here is some code to generate fictitious data with the dimensions you gave:
% some dummy data for your arrays.
num_arrays = 100;
primerArrayCell = num2cell(ones(1,num_arrays)); % , 1, ones(1, num_arrays));
arrays = cellfun(#(c) rand(randi(50, 1),1), primerArrayCell, 'uniformoutput',false);
You can use cellfun with an anonymous function to get the lengths of each individual array:
% Assume your arrays are in a cell of arrays with the variable name arrays
array_lengths = cellfun(#numel, arrays);
max_length = max(array_lengths);
Allocate an array of nan values to store your result
% initialize your data to nan's.
result = nan(max_rows, num_arrays);
Then fill in the non-nan values based on the length of the arrays calculated previously.
for r=1:num_arrays
result(1:array_lengths(r),r) = arrays{r}(1:array_lengths(r));
end

Answer 2

You may want to consider using structure arrays for storing such datasets as it makes everything easier when merging them into a single array.
But to answer your question, if you have arrays like this:
a1 = 1:20; % array of size 1 x 20
n1 = numel(a1); % 20
a2 = 50:60; % array of size 1 x 11
n2 = numel(a2); % 11
... say you have nArrs arrays
Given nArrs arrays for example, you can create the desired matrix res like this:
m = max([n1, n2, .... ]);
res = ones(m,nArrs) * nan; % initialize the result matrix w/ nan
% Manually
res(1:n1,1) = a1.';
res(1:n2,2) = a2.';
% ... so on
% Or use eval instead like this
for i = 1:nArrs
eval(['res(1:n' int2str(i) ', i) = a' int2str(i) '.'';'])
end
Now bear in mind that using eval is NOT recommended but hopefully that just gives you an idea as to what to do. If you did use structures, you can replace eval with something more efficient and robust like arrayfun for instance.