How can I select all parts of a vector?

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giancarlo maldonado cardenas 2022-5-11

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编辑： giancarlo maldonado cardenas 2022-5-13

hello everyone, I have a problem with my code that I cannot solve, I have a vector of 1536, what I am trying to do is select a part for each iteration for, that is, basically I divide that vector of 1536 into 64 parts of 24, and in each part of those 24 I try to discover the peak that crosses a threshold, the problem is that I only get to point 1512 of the 1536 and there is a last peak that crosses the threshold at point 1520 as shown in the image, can someone help me please?

Thank you in advance.

attached bin2.mat and pdp.mat

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回答（1 个）

Mitch Lautigar 2022-5-11

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Remove the -1 from your for loop.

for ci = 1:numel(bins)-1

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dpb 2022-5-11

编辑：dpb 2022-5-11

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Have you shown that is the problem? If it's a problem on the last group, it's also possibly an issue on the others.

If you're binning in even chunks as is, then there's no need for any rounding at all in the indices, simply use 1:24. 25:48, ... for each section.

NperG=24;                           % set your group size
NG=size(pdp,1)/NperG;               % compute number of groups
i1=1;                               % the first index
for i=1:NG-1                        % iterate over groups
  i2=i1+NperG-1;                    % end of this group
  data=pdp(i1:i2);                  % get that data set (NB: can use pdp(i1:i2) directly w/ no copy needed)
  ...do whatever here with the subsection...
  i1=i2+1;                          % increment i1 to next point after end of this group, rinse and repeat
end

If you want to continue with the bins idea, use discretize and the returned bin numbers and will be inclusive.

As far as the overall idea, if you have the Signal Processing TB, findpeaks has all this stuff builtin to return the peaks with all kinds of discrimation available; simply return the peaks and count those within a given binning would do it all...

dpb 2022-5-11

编辑：dpb 2022-5-12

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Wherever you find the index inside the binned subset, the overall index to the original array is simply that index plus the starting bin index.

For example, in

[M,I] = max(data);

I will be the location of the maximum in the subsection counting from 1; so the same value/location in the orginal vector will be the location

Ibig=i1+I-1;

Isn't that pretty self-evident since you're beginning each data segment at postion i1 in the full vector?

giancarlo maldonado cardenas 2022-5-13

the code continued without finding the last one, but I modified a line and it worked perfectly, how can I accept your question? you answered another user's question hehe

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