MATLAB: How to make multiple vectors the same length

interpolation

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!!

Best Answer

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
>>
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