How can i interpolate this data?

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Gabriel Luca Pugliese Borges 2022-4-19

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评论： Star Strider 2022-4-19

采纳的回答： Star Strider

Greetings to you all.

I'm trying to analise some data from an ADCP (Acoustic Doppler Current Profiler). For that, i must process the data.

My matrix works on this way:

Each Row has intensity values

Each column has a certain height in relation to the bottom of the water column.

example:

0 NaN 0.5 0.3 0.7 0.9

0 NaN 0.7 0.4 0.5 0.8

0 NaN 0.9 0.1 0.4 0.5

0 NaN 1.0 0.4 0.3 0.2

The second column is equivalent a 1m height from the bottom and the instrument has not registered those values because of an error. I want to interpolate them.

Appreciate any kind of help.

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Answer 1

Star Strider 2022-4-19

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If I understand the problem correctly, use the fillmissing function across the rows —

A = [0     NaN     0.5     0.3     0.7     0.9
     0     NaN     0.7     0.4     0.5     0.8
     0     NaN     0.9     0.1     0.4     0.5
     0     NaN     1.0     0.4     0.3     0.2];
B = fillmissing(A, 'linear', 2)
B = 4×6
         0    0.2500    0.5000    0.3000    0.7000    0.9000
         0    0.3500    0.7000    0.4000    0.5000    0.8000
         0    0.4500    0.9000    0.1000    0.4000    0.5000
         0    0.5000    1.0000    0.4000    0.3000    0.2000

The fillmissing function was introduced in R2016b.

.

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Gabriel Luca Pugliese Borges 2022-4-19

interesting! In my real matrix i have more than 1 page, how should i proceed?

A = 112254x12x6

Star Strider 2022-4-19

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I was away doing other things for a few minutes.

I thought of a more efficient way to do this, as well as being able to do more than one page in one operation —

A = [0     NaN     0.5     0.3     0.7     0.9
     0     NaN     0.7     0.4     0.5     0.8
     0     NaN     0.9     0.1     0.4     0.5
     0     NaN     1.0     0.4     0.3     0.2];
A = cat(3, A, A.*(1+randn(size(A))/100))
A = 
A(:,:,1) =

         0       NaN    0.5000    0.3000    0.7000    0.9000
         0       NaN    0.7000    0.4000    0.5000    0.8000
         0       NaN    0.9000    0.1000    0.4000    0.5000
         0       NaN    1.0000    0.4000    0.3000    0.2000


A(:,:,2) =

         0       NaN    0.5088    0.2997    0.7131    0.8894
         0       NaN    0.7053    0.4002    0.4915    0.7957
         0       NaN    0.8982    0.1012    0.3961    0.4958
         0       NaN    0.9938    0.4026    0.3011    0.2003
B = A;                                                      % Copy 'A' To 'B'
B(:,2,:) = mean(B(:,[1 3],:),2)                             % Column 2 Is The Mean Of Colums 1 & 3
B = 
B(:,:,1) =

         0    0.2500    0.5000    0.3000    0.7000    0.9000
         0    0.3500    0.7000    0.4000    0.5000    0.8000
         0    0.4500    0.9000    0.1000    0.4000    0.5000
         0    0.5000    1.0000    0.4000    0.3000    0.2000


B(:,:,2) =

         0    0.2544    0.5088    0.2997    0.7131    0.8894
         0    0.3526    0.7053    0.4002    0.4915    0.7957
         0    0.4491    0.8982    0.1012    0.3961    0.4958
         0    0.4969    0.9938    0.4026    0.3011    0.2003

The second ‘page’ or ‘A’ is a slightly altered version of the first page to demonstrate that this works, providing that a linear interpolation is desired, and the column 2 of every page is the NaN column.

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Answer 2

Keegan Carvalho 2022-4-19

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编辑：Keegan Carvalho 2022-4-19

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I'd assume "fillmissing" function would be best since you want to inteprolate the data row-wise (and this is not gridded interpolation).

Try this:

mydata = [0     NaN     0.5     0.3     0.7     0.9
          0     NaN     0.7     0.4     0.5     0.8
          0     NaN     0.9     0.1     0.4     0.5
          0     NaN     1.0     0.4     0.3     0.2];
mydata=fillmissing(mydata,"linear",2) 
% linear is one of the inteprolation methods you can use. There are others like spline, nearest, etc.
% 2 means inteprolation of data in each row of mydata. 1 - column