loop through structures and find the correlation

The following example resembles a similar problem that I'm dealing with, although the code below is merely an example, it is structured in the same format as my actual data set.

clear all

England = struct('AirT',rand(320,1),'SolRad',rand(320,1),'Rain',rand(320,1));
Wales = struct('AirT',rand(320,1),'SolRad',rand(320,1),'Rain',rand(320,1));
Ireland = struct('AirT',rand(320,1),'SolRad',rand(320,1),'Rain',rand(320,1));
Scotland = struct('AirT',rand(320,1),'SolRad',rand(320,1),'Rain',rand(320,1));

Location = struct('England',England,'Wales', Wales, 'Ireland',Ireland,'Scotland',Scotland);

FieldName={'England','Wales','Scotland','Ireland'};
Data = {England.AirT,Wales.AirT,Scotland.AirT,Ireland.AirT};
Data = [FieldName;Data];
Data = struct(Data{:});
Data = cell2mat(struct2cell(Data)');
[R,P] = corrcoef(Data,'rows','pairwise');
R_Value= [FieldName(nchoosek(1:size(R,1),2)) num2cell(nonzeros(tril(R,-1)))];

So, this script would show the correlation between pairs of Air Temperature of 4 locations. I'm looking for a way of also looking at the correlation between 'SolRad' and 'Rain' between the locations (same process as for AirT) or any variables denoted in the structure. I could do this by replacing the inputs into 'Data' but this seems rather long winded especially when involving many different variables. Any ideas on how to do this? I've tried using a loop but it seems harder than I though to try and get the data into the same format as the example.

Answer 1

[Oleg Komarov]

I would do it slightly differently:

fakeData = @(location) struct('Location',location,'AirT',rand(320,1),'SolRad',rand(320,1),'Rain',rand(320,1));
s(1) = fakeData('England');
s(2) = fakeData('Wales');
s(3) = fakeData('Scotland');
s(4) = fakeData('Ireland');

Repeating your example:

FieldName = {s.Location};
R         = corrcoef([s.AirT],'rows','pairwise');

Going further (SolRad vs Rain):

R = corrcoef([[s.SolRad] [s.Rain]],'rows','pairwise');

You're interested in matrix R(1:4,5:end)

[Richard]

very good.