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Tall Matrix Index Extraction

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Blake Van Winkle
Blake Van Winkle on 8 Jan 2021
Commented: Blake Van Winkle on 13 Jan 2021
To All:
I have a varying size model of the dimensions (L x nx)
L = number of data points
nx = number of variables per data point
In the algorithm that I am using, it moves the data around to support a search of the data space.
A small example could be this:
x = [1,2;3,4;5,6];
id =[1,6;2,4;1,5];
xnew = x(id);
disp(xnew); %[1,6;3,2;1,4];
Now while this isn't too difficult, my state "x" is in reality a tall matrix.
xtall = tall(x);
xnewtall = x(id); % crashes!
Does anyone know how to do this without having to do every individual point independently?

Answers (1)

SaiDileep Kola
SaiDileep Kola on 13 Jan 2021
Since tall matrices are challenging in terms of memory, how about parsing arrays "xtall" and "id" and using with appropriate offsets, up on that par-for would run efficiently, this could be a bit better thatn individual point independently.
Some task on similar problem is done here.
  1 Comment
Blake Van Winkle
Blake Van Winkle on 13 Jan 2021
To SaiDileep:
I appreciate the thought. This approach does reduce the time required, but it is still less efficient than if there was a total dimensional indexing solution.

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