Question

我知道这个问题有几个答案，但我找不到任何适用于我的问题。任何人都可以帮助我解决这个错误，这个S4类在这段代码的底部不是子集。我不确定这个错误来自哪里。输出结果应该是DWT的阈值系数。

xx <- list(list(c(1,2,3,4,5,6,7,5,4,3,2,4,3,2,3,5,4,3,2,3,4,5,6,3,4,3,3),
         c(0,3,1,4,1,2,7,5,4,1,3,4,9,2,7,5,1,3,2,2,1,1,1,5,1,3,1)),
      list(c(0,3,1,4,1,2,7,5,4,1,3,4,9,2,2,4,7,6,4,2,1,1,1,5,1,3,1),
         c(1,2,3,4,5,6,7,5,4,3,5,4,3,2,3,4,5,6,3,2,1,2,3,5,4,3,3)),
      list(c(0,3,1,4,1,2,7,5,4,1,3,4,3,2,2,4,7,6,4,2,1,1,1,5,1,3,1),
         c(1,2,3,4,5,6,4,3,2,3,5,4,3,2,3,4,5,6,3,2,1,2,3,5,4,3,3)))

# Select Filter.  
library(wavelets)
filter <- c    ("d2","d4","d6", "c6","d8","la8","la10","d12","c12","la12","la14","d14","d16","la16","d18","c18","la18") 
boundary <- c("periodic","reflection")
g <- seq(1:length(xx))
fun <- function (x) seq(1: as.integer (floor (logb ((length(xx[[x]][[1]])),base=2))))   
nlevel <- lapply( g,fun)
fun <-  function(x) expand.grid(filter=filter,nlevel=nlevel[[x]],boundary=boundary, stringsAsFactors=FALSE) 
w3<- lapply(g,fun)
z <- c(seq(1:length(w3)))                                                
mapply3 <- function(i) {
w4 <- w3[[i]]
mapply ( function ( m,k,p,x ) modwt ( x, filter = m, n.levels = k, boundary=p) , w3[[i]]$filter, w3[[i]]$nlevel, w3[[i]]$boundary , MoreArgs = list(x = (xx[[i]][[1]])) )
}
DWT <- lapply ( z, mapply3 )

#---------------------------------------------------------------------------    
vscale <-  c("level")
# smooth.levels  <-  c(nlevel)
prior <- c("laplace")
a  <-  c(0.1,0.3) 
bayesfac  <-  c("TRUE")
threshrule  <-  c("median","mean")

#---------------------------------------------------------------------------

X <-   seq(1:length(DWT))
fun <-   function (x) DWT[x]
u  <-   lapply(X,fun)
fun <-   function (x) seq(1:length(DWT[[x]]))
U <-   lapply(X,fun)
L1   <-   expand.grid (  vscale = vscale, prior = prior, a = a , bayesfac = bayesfac , threshrule = threshrule , stringsAsFactors = FALSE  )
# --------------------------------------------------------------------------   
library ( EbayesThresh )
mapply2  <- function ( DWTi , LL )                                                                                                  {
mapply (  function ( c,e,f,g,h,x ) ebayesthresh.wavelet ( x, vscale = c, prior = e, a = f, bayesfac = g, threshrule = h ) , LL$vscale , LL$prior , LL$a , LL$bayesfac , LL$threshrule , MoreArgs  =   list  (  x   =   DWTi )  )
} 
mapply3 <-  function(  i, L1, DWT  )  {  
DWTi      <-   DWT      [[i]][U[[i]]]         
w3          <-   L1 
lapply( DWTi, mapply2, w3 )    
} 
M1 <-   lapply(z, mapply3, L1, DWT) 
# Error in x.dwt[[j]] : this S4 class is not subsettable

Answer 1

这可能是＆＃34;小波＆＃34;中的一个错误。包。我查找了ebayesthresh.wavelet的源代码，复制了它，并添加了一些＆＃34; print＆＃34;调试：

#------------------------------------------------------------------------
# The same as "ebayesthresh.wavelet.dwt" plus some "print" for debugging:

ebayesthresh.wvlt.dwt <-
function (x.dwt, vscale = "independent", smooth.levels = Inf, 
          prior = "laplace", a = 0.5, bayesfac = FALSE, threshrule = "median") 
{
  nlevs <- length(x.dwt) - 1
  slevs <- min(nlevs, smooth.levels)

print("nlevs:")
print(nlevs)
print("slevs")
print(slevs)

  if (is.character(vscale)) {
    vs <- substring(vscale, 1, 1)
    if (vs == "i") 
      vscale <- mad(x.dwt[[1]])
    if (vs == "l") 
      vscale <- NA
  }

print("1:slevs:")
print(1:slevs)

  for (j in 1:slevs) {

print("j:")    
print(j)

    x.dwt[[j]] <- ebayesthresh(x.dwt[[j]], prior, a, bayesfac, 
                               vscale, FALSE, threshrule)
print("OK")
  }
  return(x.dwt)
}

#----------------------------------------------------------------------------
# The same as "ebayesthresh.wavelet",
# but it calls "ebayesthresh.wvlt.dwt" instead of "ebayesthresh.wavelet.dwt":

ebayesthresh.wvlt <-
function (xtr, vscale = "independent", smooth.levels = Inf, prior = "laplace", 
          a = 0.5, bayesfac = FALSE, threshrule = "median") 
{
  xcl <<- class(xtr)
  if (class(xcl) == "dwt " && length(xcl) > 1) {
    xtr <- ebayesthresh.wavelet.splus(xtr, vscale, smooth.levels, 
                                      prior, a, bayesfac, threshrule)
    return(xtr)
  }
  if (xcl == "wd") {
    xtr <- ebayesthresh.wavelet.wd(xtr, vscale, smooth.levels, 
                                   prior, a, bayesfac, threshrule)
    return(xtr)
  }
  if (xcl == "dwt" || xcl == "modwt") {
    xtr <- ebayesthresh.wvlt.dwt(xtr, vscale, smooth.levels, 
                                    prior, a, bayesfac, threshrule)
    return(xtr)
  }
  print("Unknown wavelet transform type; no smoothing performed")
  return(xtr)
}

功能mapply2现在调用ebayesthresh.wvlt而不是ebayesthresh.wavelet：

mapply2  <- function ( DWTi , LL )                                                                                                  
{
  mapply (  function ( c,e,f,g,h,x ) ebayesthresh.wvlt ( x, 
                                                         vscale = c, 
                                                         prior = e, 
                                                         a = f, 
                                                         bayesfac = g, 
                                                         threshrule = h ) , 
            LL$vscale , 
            LL$prior , 
            LL$a , 
            LL$bayesfac , 
            LL$threshrule, 
            list(x=DWTi )  )
}

让我们看看：

> M1 <-   lapply(z, mapply3, L1, DWT) 
[1] "nlevs:"
[1] 0
[1] "slevs"
[1] 0
[1] "1:slevs:"
[1] 1 0
[1] "j:"
[1] 1
Error in x.dwt[[j]] : this S4 class is not subsettable
>

在R中for - 循环

for (j in 1:n) {...}

不为空， 如果n为0或为负数。（避免for - 循环的另一个原因？）j以1为步长从1到n。我发现了类似的错误here.

如果我们用for循环替换ebayesthresh.wvlt.dwt中的while - 循环，则错误消息会消失：

  j <- 1

  while (j<=slevs) {
    x.dwt[[j]] <- ebayesthresh(x.dwt[[j]], prior, a, bayesfac, 
                               vscale, FALSE, threshrule)
    j <- j+1
  }

错误 - 此S4类不是子集

1 个答案: