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Hi I have the following data recorded with 15Hz and I want to resample it using linear interpolation to 25 Hz. What is the best way to achieve this? Here is the first second of my data set:

     RecordFile YTSIMTMD RBDDLO_0  RBDDGS_0 IDLWMWC1    time timeNF
864 2C01MUC.txx 85535.10    -0.31 -0.348873        1 0.00000      0
865 2C01MUC.txx 85535.17    -0.31 -0.348873        1 0.06667   6667
866 2C01MUC.txx 85535.23    -0.31 -0.348873        0 0.13334  13334
867 2C01MUC.txx 85535.30    -0.31 -0.348832        0 0.20000  20000
868 2C01MUC.txx 85535.37    -0.31 -0.348832        0 0.26667  26667
869 2C01MUC.txx 85535.43    -0.31 -0.348832        0 0.33334  33334
870 2C01MUC.txx 85535.50    -0.31 -0.348832        1 0.40000  40000
871 2C01MUC.txx 85535.57    -0.31 -0.348796        1 0.46667  46667
872 2C01MUC.txx 85535.63    -0.31 -0.348796        1 0.53334  53334
873 2C01MUC.txx 85535.70    -0.31 -0.348796        1 0.60000  60000
874 2C01MUC.txx 85535.77    -0.31 -0.348796        0 0.66667  66667
875 2C01MUC.txx 85535.83    -0.31 -0.348767        0 0.73334  73334
876 2C01MUC.txx 85535.90    -0.31 -0.348767        0 0.80000  80000
877 2C01MUC.txx 85535.97    -0.31 -0.348767        0 0.86667  86667
878 2C01MUC.txx 85536.03    -0.31 -0.348767        1 0.93334  93334
879 2C01MUC.txx 85536.10    -0.31 -0.348735        1 1.00000 100000

After that I want to match it with this data set recorded with 25 Hz

  vpName vpID origIndex areaNum areaName startMS endMS durationMS startF endF durationF accumIndex
1   2C01    1         1       2      ATT       0   560        560      0   14        14          1
2   2C01    1         1       2      ATT       0   560        560      0   14        14          1
3   2C01    1         1       2      ATT       0   560        560      0   14        14          1
4   2C01    1         1       2      ATT       0   560        560      0   14        14          1
5   2C01    1         1       2      ATT       0   560        560      0   14        14          1
6   2C01    1         1       2      ATT       0   560        560      0   14        14          1

I found that approx seems to be the linear interpolation for linear interpolation in R, however I am not sure which parameters to use to upsample my data from 15 to 25 Hz?

There seem to be explicit packages for handling time series in R like zoo and xts, but I am not sure whether I need them. Both data sets start at the same time, so after upsampling I could simply match by rownumber.

Thank your for your help!

florian
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  • The help page for `approx` is pretty explicit about how to specify the `x`-values at which you want interpolations! If you prefer, use `lm` to create the equation for the linear fit, and feed it a vector of data. – Carl Witthoft Aug 09 '14 at 11:52
  • Can you go a little bit more into details plz? I think I have a general understanding problem of the approx functionality...maybe there is also a better function to achieve what I want. – florian Aug 09 '14 at 12:00

2 Answers2

1

Here's an example, using approxfun to create a function with the linear fit to the input data:

xin<-seq(1,26,by=5)
 yin<-2.5+3*xin
 myfun<-approxfun(xin,yin)
 plot(xin,yin)
 newy<-myfun(seq(3,18,by=5))
 points(seq(3,18,by=5),newy)
 points(seq(3,18,by=5),newy,col='red')

In your case, the inputs aretime for x-values and whatever you are working with for y-values. Then just feed a sequence of "new" x values at 25Hz intervals (0.04 seconds) to get the fitted values you want.

Carl Witthoft
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1

I'll make some assumptions - first, that data columns "YTSIMTMD" "RBDDLO_0" and "RBDDGS_0" contain continuous data so linear interpolation can be used. Second, that column IDLWMWC1 contains binary data so we will interpolate using method=constant which selects the data value at the last data time prior to the interpolation time. Given this, the following uses approx to do the interpolations and combine them into a data frame. The interpolation times are generated at a time interval of 1/freq. I put your data into a data frame called xx.

t_seq <- seq(min(xx$time), max(xx$time),1/25)
ap <- cbind(t_seq, sapply(xx[,c("YTSIMTMD", "RBDDLO_0","RBDDGS_0")], 
                      function(y, x, nout) approx(x, y, nout, method="linear")$y, x=xx$time, nout=t_seq ))
ap <- cbind(ap,IDLWMWC1=approx(xx$time, xx$IDLWMWC1, t_seq, method="constant")$y)

I don't quite understand how your second set of data relates to the first but if it's just additional information at intervals of 1/25 starting at the same time, you could just combine the two data frame using cbind.

WaltS
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  • Your assumptions are correct - I just realized how bad I am at asking questions - sorry for that I think it was because of my misunderstanding of approx functionality which I realized during lunch. The really relevant variables for me are "RBDDLO_0","RBDDGS_0" but is cool to see, how it would have been done for the others! So if I understand your code correctly you first create a time sequence with 40ms steps in the first line...then you use approx to fit to that sequence. cbind and sapply become necessary as you want to achieve all variables within one line, instead doing it var by var? – florian Aug 09 '14 at 14:01
  • That's right. If you're going to user R very much, it's probably worth becoming familiar with the "apply" functions. sapply is one of the more common ones. – WaltS Aug 09 '14 at 14:21