Best way to seperate a very large array of numbers into different variables based on a value tat is given in the first column?

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Marissa Holden
Marissa Holden 2017-10-17
评论： Marissa Holden 2017-10-17
I have a variable that contains experimental data, it is 96x300001. (however the size will change every time I run my script). The first column gives a value which represents a certain group (e.g group 1, group 2 group 3 etc. The variable kinda looks like this =
1 0.021 0.0433 0.656,
2 0.00321 0.335 0.605,
3 0.1 0.035 0.625. etc etc
I want to tell MATLAB "numbers next to the number 1 go into variable "group1" and numbers next to the number 2 go into a variable called "group2" and so on, but I have no idea how to do this!
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Marissa Holden
Marissa Holden 2017-10-17
编辑：Marissa Holden 2017-10-17
For anyone looking to answer this question in the future I ended up using the "find" function. "data" is the variable containing my data -
idx_group3 = find(data(:,1)==3); -- this will output a variable with the number of each row that starts with the number 3.
Then, I tell matlab to put the data from those particular rows (from 2 to the end of the array) into a different variable.
data_group3 = data(idx_group3,2:end);

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Cedric
Cedric 2017-10-17
Here is an example: we build a fake data set:
>> data = [sort(randi(3,10,1)), rand(10,5)]
data =
1.0000 0.9727 0.6504 0.8675 0.9329 0.2748
1.0000 0.9217 0.1238 0.1572 0.7492 0.7884
1.0000 0.7864 0.9880 0.6371 0.8526 0.8418
1.0000 0.2187 0.6194 0.9931 0.9952 0.9586
2.0000 0.1218 0.9761 0.8390 0.6048 0.2233
2.0000 0.5117 0.0724 0.9759 0.2118 0.7046
3.0000 0.6800 0.3582 0.4349 0.8793 0.8167
3.0000 0.8622 0.4866 0.7729 0.8863 0.8443
3.0000 0.6063 0.8812 0.5100 0.6926 0.9223
3.0000 0.7486 0.0681 0.4883 0.6132 0.4820
and we group it this way:
>> groups = splitapply( @(x){x(:,2:end)}, data, data(:,1) )
groups =
3×1 cell array
{4×5 double}
{2×5 double}
{4×5 double}
Now groups is a cell array that we can index using the group ID:
>> groups{1}
ans =
0.9727 0.6504 0.8675 0.9329 0.2748
0.9217 0.1238 0.1572 0.7492 0.7884
0.7864 0.9880 0.6371 0.8526 0.8418
0.2187 0.6194 0.9931 0.9952 0.9586
>> groups{2}
ans =
0.1218 0.9761 0.8390 0.6048 0.2233
0.5117 0.0724 0.9759 0.2118 0.7046
>> groups{3}
ans =
0.6800 0.3582 0.4349 0.8793 0.8167
0.8622 0.4866 0.7729 0.8863 0.8443
0.6063 0.8812 0.5100 0.6926 0.9223
0.7486 0.0681 0.4883 0.6132 0.4820
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Cedric
Cedric 2017-10-17
编辑：Cedric 2017-10-17
Yes, try the following instead:
groups = mat2cell( data(:,2:end), accumarray( data(:,1), 1 )) ;
If you evaluate
accumarray( data(:,1), 1 )
you will see that it computes the length of each group, and then reading the doc of MAT2CELL, you'll understand what we do here.

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Image Analyst
Image Analyst 2017-10-17
You may not need to do that. Whether you do or not depends on what you're going to do next. For example if you just wanted the means or other simple stats, you could use grpstats() without creating variables group1, group2, group3, .... groupn. Or if you just wanted to loop over all groups, you could just extract rows one group at a time into a single variable "thisGroup" and then process that within the loop. So, assuming you know what groups each row belongs to (and you do already know this), what do you plan on doing next?
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Image Analyst
Image Analyst 2017-10-17
Marissa: Do you have the Statistics and Machine Learning Toolbox? This is exactly what it does, with no need to create a bunch of separately named variables!

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