How to perform the following data splitting?

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M
M am 1 Okt. 2023
Kommentiert: M am 2 Okt. 2023
How to perform the following data splitting?
There are vectors X,Y,T all of these have the same size
I want to split these 3 vectors and store the splitted data in 3 arraies X_array y_array T_array
The splitting will be according to a specific range
for example:
split X and Y according to T
T contains time data from 5.2 to 10 (i,e T=[5.2,5.2002,.........................5.202, ................10])
I want to split these vectors every 0.002 of T
for example include all the data of X in one vector until T reach 5.202 then store in the first cell in the array,then include all the data of X in one vector until T reach 5.204 then store in the 2nd cell in the array,,, and so on
similar to Y and T

Akzeptierte Antwort

Dyuman Joshi
Dyuman Joshi am 1 Okt. 2023
%Random data
t = 5.2:0.002:5.3;
x = 1:numel(t);
%Define bins to group data into
cats = min(t):0.02:max(t);
%Group the data according to the bins defined
idx = discretize(t,cats);
%Split the data according to groups and store in a cell array
%Do the same for y as well
X = splitapply(@(k) {k}, x, idx)
X = 1×5 cell array
{[1 2 3 4 5 6 7 8 9 10]} {[11 12 13 14 15 16 17 18 19 20]} {[21 22 23 24 25 26 27 28 29 30]} {[31 32 33 34 35 36 37 38 39 40]} {1×11 double}
X'
ans = 5×1 cell array
{[ 1 2 3 4 5 6 7 8 9 10]} {[ 11 12 13 14 15 16 17 18 19 20]} {[ 21 22 23 24 25 26 27 28 29 30]} {[ 31 32 33 34 35 36 37 38 39 40]} {[41 42 43 44 45 46 47 48 49 50 51]}
  2 Kommentare
Walter Roberson
Walter Roberson am 1 Okt. 2023
We probably should not count on the input T starting from 5.2 so we should probably not use min() for the lower bound. We are told to start from 5.2 so that should be the lower bound.
M
M am 2 Okt. 2023
@Dyuman Joshi, Thanks, your solution worked with me and the splitting was correct

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Weitere Antworten (1)

Walter Roberson
Walter Roberson am 1 Okt. 2023
idx = round((T(:)-5.2)/0.02) + 1;
Xgrouped = accumarray(idx, X(:), [], @(vals){vals});
Ygrouped = accumarray(idx, Y(:), [], @(vals){vals});
Tgrouped = accumarray(idx, T(:), [], @(vals){vals});
  3 Kommentare
M
M am 2 Okt. 2023
Bearbeitet: M am 2 Okt. 2023
idx = round((Time(:)-Time(1,1))/0.002) + 1;
Unrecognized function or variable 'Time'.
Xgrouped = accumarray(idx, X(:), [], @(vals){vals});
Ygrouped = accumarray(idx, Y(:), [], @(vals){vals});
Tgrouped = accumarray(idx, Time(:), [], @(vals){vals});
M
M am 2 Okt. 2023
@Walter Roberson Dyuman solution worked with me,but I am wondered why your solution didn't work

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