separate column into several using descriptive variable
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I would like to split up a cell array that I have using a grouping variable. I have not found an applicable group function. I have a column of numbers say x = 123456789 and y = c1 c2 c1 c3 c4 c3 c1 c3 c4 I would like to split it up into 4 separate arrays with the values from x. Any help would be greatly appreciated. I have about 10 000 samples so manually going through would not be an option.
Cheers
4 comentarios
Stephen23
el 25 de En. de 2016
It sounds like you need to use some indexing to pick those.
But your explanation is not very clear: please edit your question and provide us with exact input and output arrays for us to try out. How is x = 123456789 a "column of numbers"? x is a scalar numeric. What are x and y? What is the input that will be used to pick these columns?
Brandon MacKinnon
el 25 de En. de 2016
Image Analyst
el 25 de En. de 2016
I'm just as confused as Stephen. It doesn't look like Brandon has read this yet. Like Stephen says, x = 123456789 means x is a single number, not a column of numbers. So when you say "values from x", what values would those be? There is only one value and that is 123456789. What are the other values???????????????????
And assuming the c in your definition of y means column, I can't see any pattern to the numbers in y, either by themselves or by looking at x. What is the rule for assembling y like that???
Brandon MacKinnon
el 25 de En. de 2016
Respuestas (1)
x = 100*rand(1000,1); %your data
groups = [0:10:100]; %your bins to group the data into
group_id = discretize(x,bins);
If you don't have groups and want every unique value of x instead, try unique instead with the third return option.
3 comentarios
Brandon MacKinnon
el 25 de En. de 2016
jgg
el 25 de En. de 2016
This code works fine for me. What are you calling that it giving you the error exactly? Are you using an older version of Matlab?
The documentation is here:
jgg
el 25 de En. de 2016
If you have an older version of Matlab this should work instead:
x = 100*rand(1000,1); %your data
groups = [0:10:100]; %your bins to group the data into
[~,group_id] = histc(x,groups);
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