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Loop only storing last run in nested for loop ... should be easy indixing easy for the experienced eye

Asked by mashtine on 6 Aug 2014
Latest activity Commented on by mashtine on 26 Aug 2014
This is a bit complex to explain without an essay but in point form, I have:
A large matrix with two parameters for 6 heights I want to bin the data by one parameter and then store this data in a struct for each bin I then was to do this for each height
The data is arranged in the following order date x y x2 y2 x3 y3 ... where the different levels represent the parameters at different heights.
Here is the code I have thus for but the loop is making the structure of the struct (names etc) perfectly but not iteratively saving the data:
inpdata = tower_wind_GF_allyrs;
inpdata = inpdata(~any(isnan(inpdata),2),:);
inpdata = inpdata(~any(isinf(inpdata),2),:);
bin = 0:0.51444:40;%maxws;
names = strtrim(cellstr(num2str([1:(length(bin)-1)]'))');
names = strrep(strcat('bin',names),'.','');
names2 = {'height10m' 'height20m' 'height40m' 'height80m' 'height120m' 'height200m'};
ind = cell(6,(length(bin)-1));
for k = linspace(2,12,6)
for l = linspace(3,13,6)
for i = 1:(length(bin)-1)
for varname = 1:length(names2)
search = find(inpdata(:,k) >= bin(i) & inpdata(:,k) < bin(i+1));
ind{varname,i} = search
binned_wind_allyrs.(names2{1,varname}).(names{1,i}) = cell(1,(length(bin)-1));
binned_wind_allyrs.(names2{1,varname}).(names{1,i}) = [inpdata(ind{varname,i}(:,1),k),inpdata(ind{varname,i}(:,1),l)];
Would LOVE to figure this out. Thanks in advance


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2 Answers

Answer by Kelly Kearney
on 6 Aug 2014
Edited by Kelly Kearney
on 6 Aug 2014
 Accepted Answer

You could simplify the syntax quite a bit using histc and accumarray:
inpdata = [datenum(2014,1,1)+(1:100)' rand(100,12)*39];
nheight = (size(inpdata,2)-1)/2;
bin = 0:0.51444:40;
nbin = length(bin);
xdata = inpdata(:,2:2:end);
ydata = inpdata(:,3:2:end);
% Bin the data
[n, idx] = histc(xdata, bin);
idx(idx == nbin+1) = nbin;
bindata = cell(nbin, nheight);
for ii = 1:nheight
x = accumarray(idx(:,ii), xdata(:,ii), [nbin 1], @(x) {x});
y = accumarray(idx(:,ii), ydata(:,ii), [nbin 1], @(x) {x});
bindata(:,ii) = cellfun(@(x,y) [x y], x, y, 'uni', 0);
% Structure output
bname = cellstr(num2str((1:nbin)', 'bin%02d'));
hname = {'height10m' 'height20m' 'height40m' 'height80m' 'height120m' 'height200m'};
for ib = 1:nbin
for ih = 1:nheight
S.(bname{ib}).(hname{ih}) = bindata{ib,ih};


Here is a link to download my dataset as I cannot upload here. Really appreciate the help!
Empty bins are not a problem. But data points that don't fit into a bin are. You have NaNs in your dataset, and histc assigns those data points to bin zero. So you'll have to decide what you want to do with those data points. This modification to the code above throws out any points where the x-data is NaN (it seems you have several data points with a valid x but NaN y; those points are left alone).
bindata = cell(nbin, nheight);
for ii = 1:nheight
isn = isnan(xdata(:,ii));
xtmp = xdata(~isn,ii);
ytmp = ydata(~isn,ii);
x = accumarray(idx(~isn,ii), xtmp, [nbin 1], @(x) {x});
y = accumarray(idx(~isn,ii), ytmp, [nbin 1], @(x) {x});
bindata(:,ii) = cellfun(@(x,y) [x y], x, y, 'uni', 0);
Sorry for the late reply Kelly. Thank you very much for this!
Have a great week

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Answer by Iain
on 6 Aug 2014

Simple answer is on the left hand side, you need to index with k, l, i and varname.
So, this ought to work:
binned_wind_allyrs(k,l,i,varname) = {[inpdata(ind{varname,i}(:,1),k),inpdata(ind{varname,i}(:,1),l)]};
But you might need
binned_wind_allyrs(k,l,i,varname, 1:(numel(bin)-1)) = {[inpdata(ind{varname,i}(:,1),k),inpdata(ind{varname,i}(:,1),l)]};

  1 Comment

Like this you mean:
binned_wind_allyrs(k,l,i,varname, 1:(numel(bin)-1)).(names2{1,varname}).(names{1,i}) = [inpdata(ind{varname,i},k),inpdata(ind{varname,i},l)];
When I put this, I am getting the following:
Scalar index required for this type of multi-level indexing.

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