问如何将数据从LabVIEW连续发送到R？(代码帮助)

EN

Error in aggregate.data.frame(B, list(rep(1:(nrow(B)%/%n + 1), each = n,  :
    no rows to aggregate

getwd()
setwd("C:/Users/johnd/Desktop/R Data")

while(1) {

  A = fread("C:/Users/johnd/Desktop/R Data/a1.csv" , skip = 4  , header = FALSE , col.names = c("t1","B2","t2","AM","t3","M","t4","B1"))
  t1 = A$t1
  B2 = A$B2
  t2 = A$t2
  AM = A$AM
  t3 = A$t3
  M = A$M
  t4 = A$t4
  B1 = A$B1

  B = fread("C:/Users/johnd/Desktop/R Data/b1.csv" , skip = 4  , header = FALSE , col.names = c("T1","small","T2","big"))
  T1 = B$T1
  small = B$small
  T2 = B$T2
  big = B$big

  DJ1 = A[seq(1,nrow(A),1),c('t1','B2','AM','M','B1')]
  DJ1

  n = 16
  DJ2 = aggregate(B,list(rep(1:(nrow(B)%/%n+1),each=n,len=nrow(B))),mean)[-1]
  DJ2

  #------------------------------------------------------------------------
  DJ6 = cbind(DJ1[,'B1'],DJ2[,c('small','big')]) # creates matrix for these three indicators
  DJ6


  #--------------T2 Hand made---------------------------------------------------------------------

  new_B1 = DJ6[,'B1']
  new_small = DJ6[,'small']   ### decompose the DJ6 matrix into vectors for each indicator(temperature, big & small accelerometers)
  new_big = DJ6[,'big']

  new_B1
  new_small
  new_big

  mean_B1 = as.numeric(colMeans(DJ6[,'B1']))
  mean_small = as.numeric(colMeans(DJ6[,'small']))    ##decomposes into vectors of type numeric 
  mean_big = as.numeric(colMeans(DJ6[,'big']))

  cov_inv = data.matrix(solve(cov(DJ6)))   # obtain inverse covariance matrix 
  cov_inv

  p = ncol(DJ6) #changed to pull number of parameters by taking the number of coumns in OG matrix   #p=3   # #ofQuality Characteristics 
  m=64 # #of samples (10 seconds of data)
  a_alpha = 0.99
  f= qf(a_alpha , df1 = p,df2 = (m-p))  ### calculates the F-Statistic for our data    
  f
  UCL = (p*(m+1)*(m-1)*(f))/(m*(m-p))   ###produces upper control limit 
  UCL

  diff_B1 = new_B1-mean_B1
  diff_small = new_small-mean_small
  diff_big = new_big-mean_big

  DJ7 = cbind(diff_B1, diff_small , diff_big) #produces matrix of difference between average and observations (x-(x-bar))
  DJ7
  # DJ8 = data.matrix(DJ7[1,])
  # DJ8
  DJ9 = data.matrix(DJ7)     ### turns matrix into appropriate numeric form   
  DJ9

  # T2.1.1 = DJ8 %*% cov_inv %*% t(DJ8)
  # T2.1.1

  # T2.1 = t(as.matrix(DJ9[1,])) %*% cov_inv %*% as.matrix(DJ9[1,])
  # T2.1

  #T2 <- NULL
  for(i in 1:64){   #### creates vector of T^2 statistic 

    T2<- t(as.matrix(DJ9[i,])) %*% cov_inv %*% as.matrix(DJ9[i,])   # calculation of T^2 test statistic   ## there is no calculation of x-double bar

    write.table(T2,"C:/Users/johnd/Desktop/R Data/c1.csv",append=T,sep="," , col.names = FALSE)#
     #
    DJ12 <-fread("C:/Users/johnd/Desktop/R Data/c1.csv" , header = FALSE ) #
  }
  # DJ12

  DJ12$V1 = 1:nrow(DJ12)  
  # plot(DJ12 , type='l')

  p1 = nrow(DJ12)-m
  p2 = nrow(DJ12)

  plot(DJ12[p1:p2,], type ='o', ylim =c(0,15), ylab="T2 Chart" , xlab="Data points")  ### plots last 640 points     
  # plot(DJ12[p1:p2,], type ='o' , ylim =c(0,15) , ylab="T2 Chart" , xlab="Data points")
  abline(h=UCL , col="red") ## displays upper control limit 


  Sys.sleep(1)
}