How can I make multiple vectors the same length?
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Hi all,
I am struggeling with an interpolation task and dont make any process.
I have calculated muscle thickness values across the total muscle length of several subjects. Now I want to compare the region specific differences between subjects but of course all subjects have different muscle length (and thus I have vectors with more values (if muscle has greater length) and smaller vectors (for short muscles).
How could I interpolate these data so that each vector has the same length? I have attached a data sheet (each subjects has an own column).
Thank you for your help!!
2 个评论
Walter Roberson
2020-9-16
Do you want the interpolation to be done at intervals that are the same for each muscle (for example 2mm), or do you want the interpolation to be at intervals that are equal proportions of the muscle (e.g., every 1/8th of the length) ?
Christoph Centner
2020-9-16
采纳的回答
Because each of the input columns has their own domain, you will have to loop over the columns and interpolate each column separately, something like this:
inp = xlsread('Sample.xlsx');
out = inp; % preallocate
num = size(out,1);
for k = 1:size(out,2)
idx = ~isnan(inp(:,k));
xi = 1:nnz(idx);
xo = linspace(1,nnz(idx),num);
out(:,k) = interp1(xi,inp(idx,k),xo);
end
Giving:
>> inp % raw data
inp =
0.3487 0.6447 0.8550 0.6123 0.4617 0.7680 0.8120 0.4800 0.9830
0.7033 0.5983 0.8143 0.7540 0.6167 0.6230 0.6570 0.6357 0.7357
0.7700 0.6753 0.2363 0.7473 0.7600 0.6143 0.8490 0.8643 0.6917
0.7583 0.7740 0.7683 0.9083 0.7167 0.5497 0.8620 0.8520 0.8227
0.8963 0.8700 0.8983 0.9853 0.8053 0.6887 0.9170 0.9657 0.9020
0.8990 1.0077 0.9497 0.9460 0.8480 0.7230 0.8993 1.0130 0.9747
0.9040 0.9130 0.9560 1.0037 0.8913 0.7640 0.9340 1.1217 1.0367
0.8550 0.9693 0.9565 1.0513 0.8900 0.7763 1.0707 1.1203 1.0160
0.9277 0.9963 0.9220 NaN 0.9037 0.8657 1.1093 1.1407 1.0457
0.9290 1.0790 0.8823 NaN 0.8880 0.8247 1.0657 1.1763 1.0410
NaN 0.9413 0.7607 NaN 1.0247 NaN 1.0347 1.1750 1.0693
NaN NaN NaN NaN 0.9120 NaN 1.0880 1.2743 1.0937
NaN NaN NaN NaN NaN NaN 1.1810 1.0443 1.1110
NaN NaN NaN NaN NaN NaN 1.2476 NaN NaN
NaN NaN NaN NaN NaN NaN 1.3207 NaN NaN
>> out % interpolated data
out =
0.3487 0.6447 0.8550 0.6123 0.4617 0.7680 0.8120 0.4800 0.9830
0.5767 0.6116 0.8260 0.6832 0.5835 0.6748 0.6570 0.6134 0.7710
0.7224 0.6313 0.5666 0.7540 0.6986 0.6205 0.8490 0.7990 0.7042
0.7652 0.6894 0.3123 0.7507 0.7445 0.6150 0.8620 0.8573 0.7665
0.7633 0.7599 0.6923 0.7473 0.7293 0.5774 0.9170 0.9007 0.8567
0.7879 0.8289 0.8426 0.8278 0.7990 0.5795 0.8993 0.9792 0.9228
0.8766 0.9093 0.9130 0.9083 0.8358 0.6688 0.9340 1.0285 0.9835
0.8977 1.0077 0.9497 0.9468 0.8697 0.7058 1.0707 1.1217 1.0367
0.8997 0.9400 0.9542 0.9853 0.8910 0.7289 1.1093 1.1205 1.0190
0.9029 0.9371 0.9562 0.9657 0.8910 0.7552 1.0657 1.1349 1.0372
0.8830 0.9732 0.9515 0.9460 0.9017 0.7693 1.0347 1.1610 1.0430
0.8602 0.9925 0.9269 0.9748 0.8936 0.7827 1.0880 1.1758 1.0531
0.9069 1.0436 0.8993 1.0037 0.9466 0.8401 1.1810 1.2034 1.0763
0.9281 1.0397 0.8476 1.0275 1.0005 0.8510 1.2476 1.2415 1.0961
0.9290 0.9413 0.7607 1.0513 0.9120 0.8247 1.3207 1.0443 1.1110
>>
4 个评论
Christoph Centner
2020-9-16
编辑：Christoph Centner
2020-9-16
Ameer Hamza
2020-9-16
Just change these two lines
out = inp; % preallocate
num = size(out,1);
with
num = 10;
out = zeros(num, size(inp,2)); % preallocate
Christoph Centner
2020-9-16
"Thank you Steven!"
Thank you Ameer Hamza.
"Do you also know how to make them all a length of 10 data points? Then I could easily compare all subjects on 10%, 20%, 30% - 100% of muscle length?"
If you sample every 10% along the length, i.e. at 0%, 10%, 20%, ... 90%, 100% of the length, then this requires eleven sample points, not ten. If you sample the length with only ten points, then this gives samples at 0%, 11.111..%, 22.222..%, ... 88.888...%, 100% of the length.
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