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How can I separate data into multiple groups?

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Jayden Yeo
Jayden Yeo 2023 年 3 月 3 日
コメント済み: Jayden Yeo 2023 年 3 月 8 日
Hi,
I have a csv with more than 50,000 rows (an extract is provide in the attached csv file).
I need to group the data as highlighted in yellow in the attached file. The numbers in each group are either very close to each other (difference of less than 1) or they are multiple of the smaller number (with tolerance of +/- 0.3).
How can I write the code such that it can name the highlighted group as 1, 2, 3 and so on? For those number that don't belong to a group, 0 will be their default group number.
Thanks for the help in advance.
  2 件のコメント
Jan
Jan 2023 年 3 月 3 日
CSV-files are text files. There are no colored elements.
Can you import the file already? Then you could start from "I have a vector" or "matrix".
Jayden Yeo
Jayden Yeo 2023 年 3 月 3 日
Hi,
The colour is only to help to explain my question. The csv file (with more data) that I am working on does not have any coloured elements.

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回答 (1 件)

Jan
Jan 2023 年 3 月 3 日
編集済み: Jan 2023 年 3 月 3 日
data = [2416.015, 127.402, 382.165, 127.425, 127.3387, 127.406, 637.001, 127.405, 2240.913, ...
2257.54, 241.801, 3064.636, 441.559, 220.805, 220.799, 1204.011, 1547.622, 322.37, ...
322.43, 6482.511, 558.603, 279.301, 2234.423, 279.307, 279.31, 279.295, 3901.168, ...
3595.353, 90.315];
m = [true, abs(diff(data)) < 1]; % Distance is small
ini = strfind(m, [0, 1]); % Index where blocks are starting
p = zeros(size(data));
p(ini) = 1;
p = cumsum(p); % Count starts
m(ini) = true;
result = m .* p; % Use m as mask
format long g
disp([data.', result.'])
2416.015 0 127.402 0 382.165 0 127.425 1 127.3387 1 127.406 1 637.001 0 127.405 0 2240.913 0 2257.54 0 241.801 0 3064.636 0 441.559 0 220.805 2 220.799 2 1204.011 0 1547.622 0 322.37 3 322.43 3 6482.511 0 558.603 0 279.301 0 2234.423 0 279.307 4 279.31 4 279.295 4 3901.168 0 3595.353 0 90.315 0
  8 件のコメント
Jan
Jan 2023 年 3 月 7 日
@Jayden Yeo: Yes, I've simplified my example. With the real data considering the tolerances will even increase the complexity.
If the desciption of the process is such tricky already, this is usually a hint, that the view on the problem is to indirect or contains too complicated assumptions. Therefore I ask, which real world problem you want to solve. Maybe there is a simpler solution to define groups.
Jayden Yeo
Jayden Yeo 2023 年 3 月 8 日
@Jan: I have to admit that the problem is tricky, but the data I have is what I have shown as an extract in the csv file. I think your answer above is the best that I have, and thanks a lot for your help. Once the groups are defined, I will remove those groups that are zero, and then plot groups 1, 2, 3...and so on.

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