Getting statistics from a struct
显示 更早的评论
I have a struct with experimental data in it. The fields in the struct are input settings and measurement results. For all possible input settings I have a lot of measurement results, but they are not organized.
So for example I have myResults(1).Inputsetting1 and myResults(1).Inputsetting2 as input settings for one experiment and myResults(1).MeasurementA and myResults(1).MeasurementB as measurement results for that experiment. And then there exist e.g. 20 different elements which all share the same input settings. Now I want to know what the mean, standard deviation, etc. is of myResults.MeasurementA and myResults.MeasurementB of all the elements which share the same inputsettings. Is there a simple way to do this?
2 个评论
dpb
2014-7-29
Think need some more detail to have specifics, but -- look at
doc structfun
and the section on structures with addressing them, particularly the portion to create hyper-rectangles or arrays of similar data types from various fields. Then you can process those arrays selected by various characteristics.
If you have the Statistics Toolbox, look at
doc struc2dataset
Patrik Ek
2014-7-30
Try to parse the struct with functions like fieldnames and so. If you know where to find the data, a recursive parser might do the trick.
采纳的回答
Sara
2014-7-29
If measurementA is just one value, you can do:
mean([myResults.MeasurementA])
Try it for your data and look at the results and adjust.
7 个评论
Merijn
2014-7-30
dpb
2014-7-30
The question isn't the problem; it's the exact form in which you've stored the data that's not clear (enough) from which to write actual code lines.
Merijn
2014-7-30
Merijn
2014-7-30
Sara
2014-7-30
Ok, now it's clearer. Can you attach your data (or a subset) so we can play with it?
Sara
2014-7-30
Look at the code below. Is that what you are looking for?
clc
clearvars
close all
load('partofresult.mat');
drop_array = [partofresult.Droplet_spacing];
gap_array = [partofresult.Gap];
area_array = [partofresult.Area];
drop = unique([partofresult.Droplet_spacing]);
gap = unique([partofresult.Gap]);
averages = zeros(numel(drop),numel(gap));
for i = 1:numel(drop)
for j = 1:numel(gap)
k = find(drop_array == drop(i) & gap_array == gap(j));
averages(i,j) = mean(area_array(k));
end
end
[drop,gap] = meshgrid(drop,gap);
plot3(drop,gap,averages','o')
更多回答（1 个）
类别
在 帮助中心 和 File Exchange 中查找有关 Structures 的更多信息
Translated by 
