Sampling and Calculation in R

Question

I have a file that contains two columns (Time , VA). The file is large and I managed to read it in R(used read and subset -not a practical for large file). Now, I want to do sampling based on the time, where each sample has a sample size and sample shift. Sample size is fixed value for the whole process of sampling e.g. sampleSize=10 second. Sample shift is the start point for each new sample (after First sample). For example, if sampleShift =4 sec and the sampleSize is 10 sec , that means the second sample will start from 5 sec and add 10 sec as the sample sample size=10 sec. For each sample I want feed the -VA- values to a function to some calculation.

Sampling <- function(values){
# Perform the sampling 
lastRowNumber<- #specify the last row manually
sampleSize<-10
lastValueInFile<-lastRowNumber-sampleSize

for (i in 1: (lastValueInFile ) ){ 
  EndOfShift<-9+i
  sample<-c(1:sampleSize)
  h<-1

  for(j in i:EndOfShift){        
    sample[h] <- values[j,1]
    h<-h+1
  }
  print(sample)
  #Perform the Calculation on the extracted sample
  #--Samp_Calculation<-SomFunctionDoCalculation(sample) 
}
}

The problems with my try are: 1) I have to specify the lastRow number manually for each file I read. 2) I was trying to do the sampling based on rows number not the Time value. Also, the shift was by one for each sample.

file sample:

Time     VA
0.00000 1.000
0.12026 2.000
0.13026 2.000
0.14026 2.000
0.14371 3.000
0.14538 4.000
 ..........
 ..........
15.51805 79.002
15.51971 79.015
15.52138 79.028
15.52304 79.040
15.52470 79.053
.............

Any suggestion for more professional way ?

Simon · Accepted Answer · 2013-02-22 02:48:03Z

1

I've generated some test data as follows:

val <- data.frame (time=seq(from=0,to=15,by=0.01),VA=c(0:1500))

... then the function:

sampTime <- function (values,sampTimeLen) 
{
    # return a data frame for a random sample of the data frame -values-
    # of length -sampTimeLen-
    minTime <- values$time[1]
    maxTime <- values$time[length(values$time)] - sampTimeLen
    startTime <- runif(1,minTime,maxTime)
    values[(values$time >= startTime) & (values$time <= (startTime+sampTimeLen)),]
}

... can be used as follows:

> sampTime(val,0.05)
    time  VA
857 8.56 856
858 8.57 857
859 8.58 858
860 8.59 859
861 8.60 860

... which I think is what you were looking for.

(EDIT)

Following the clarification that you want a sample from a specific time rather than a random time, this function should give you that:

sampTimeFrom <- function (values,sampTimeLen,startTime) 
{
    # return a data frame for sample of the data frame -values-
    # of length -sampTimeLen- from a specific -startTime-
    values[(values$time >= startTime) & (values$time <= (startTime+sampTimeLen)),]
}

... which gives:

> sampTimeFrom(val,0.05,0)
  time VA
1 0.00  0
2 0.01  1
3 0.02  2
4 0.03  3
5 0.04  4
6 0.05  5
> sampTimeFrom(val,0.05,0.05)
   time VA
6  0.05  5
7  0.06  6
8  0.07  7
9  0.08  8
10 0.09  9
11 0.10 10

If you want multiple samples, they can be delivered with sapply() like this:

> samples <- sapply(seq(from=0,to=0.15,by=0.05),function (x) sampTimeFrom(val,0.05,x))
> samples[,1]
$time
[1] 0.00 0.01 0.02 0.03 0.04 0.05

$VA
[1] 0 1 2 3 4 5

In this case the output will overlap but making the sampTimeLen very slightly smaller than the shift value (which is shown in the by= parameter of the seq) will give you non-overlapping samples. Alternatively, one or both of the criteria in the function could be changed from >= or <= to > or <.

edited Feb 22, 2013 at 2:48

answered Feb 22, 2013 at 0:45

Simon

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2 Comments

SimpleNEasy Over a year ago

Yes this almost what I was looking for. However, instead of the random sample I need to do the sampling on all of the Time content uniformly. In other words, I want to have more samples until the end of the time (no more to sample). sample 2 and 3,..... will be regulated by sampleShift. I tried to add more to your answer, However, I'm getting only one sample. ' startTime<-0 for (i in 1:maxTime){ startTime <- minTime+startTime test<-sampTime(values,sampTimeLen,startTime) cat("Sample ",i,"\n") print(test) startTime<-shiftSize }'

Simon Over a year ago

@Eng.Mohd: I've edited my answer in a way that hopefully addresses your clarification.

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