R中有用的小功能？

Question

你写的功能是什么,不值得一个包,但你想分享？

我会投入一些我的:

destring <- function(x) {
    ## convert factor to strings
    if (is.character(x)) {
        as.numeric(x)
    } else if (is.factor(x)) {
        as.numeric(levels(x))[x]
    } else if (is.numeric(x)) {
        x
    } else {
        stop("could not convert to numeric")
    }
}

pad0 <- function(x,mx=NULL,fill=0) {
  ## pad numeric vars to strings of specified size
  lx <- nchar(as.character(x))
  mx.calc <- max(lx,na.rm=TRUE)
  if (!is.null(mx)) {
    if (mx<mx.calc) {
      stop("number of maxchar is too small")
    }
  } else {
    mx <- mx.calc
  }
  px <- mx-lx
  paste(sapply(px,function(x) paste(rep(fill,x),collapse="")),x,sep="")
}


.eval <- function(evaltext,envir=sys.frame()) {
  ## evaluate a string as R code
  eval(parse(text=evaltext), envir=envir)
}

## trim white space/tabs
## this is marek's version
trim<-function(s) gsub("^[[:space:]]+|[[:space:]]+$","",s)

Answer 1

这是一个用伪透明度绘制重叠直方图的函数:

重叠直方图http://chrisamiller.com/images/histOverlap.png

plotOverlappingHist <- function(a, b, colors=c("white","gray20","gray50"),
                            breaks=NULL, xlim=NULL, ylim=NULL){

  ahist=NULL
  bhist=NULL

  if(!(is.null(breaks))){
    ahist=hist(a,breaks=breaks,plot=F)
    bhist=hist(b,breaks=breaks,plot=F)
  } else {
    ahist=hist(a,plot=F)
    bhist=hist(b,plot=F)

    dist = ahist$breaks[2]-ahist$breaks[1]
    breaks = seq(min(ahist$breaks,bhist$breaks),max(ahist$breaks,bhist$breaks),dist)

    ahist=hist(a,breaks=breaks,plot=F)
    bhist=hist(b,breaks=breaks,plot=F)
  }

  if(is.null(xlim)){
    xlim = c(min(ahist$breaks,bhist$breaks),max(ahist$breaks,bhist$breaks))
  }

  if(is.null(ylim)){
    ylim = c(0,max(ahist$counts,bhist$counts))
  }

  overlap = ahist
  for(i in 1:length(overlap$counts)){
    if(ahist$counts[i] > 0 & bhist$counts[i] > 0){
      overlap$counts[i] = min(ahist$counts[i],bhist$counts[i])
    } else {
      overlap$counts[i] = 0
    }
  }

  plot(ahist, xlim=xlim, ylim=ylim, col=colors[1])
  plot(bhist, xlim=xlim, ylim=ylim, col=colors[2], add=T)
  plot(overlap, xlim=xlim, ylim=ylim, col=colors[3], add=T)
}

如何运行它的示例:

a = rnorm(10000,5)
b = rnorm(10000,3)
plotOverlappingHist(a,b)

更新:FWIW,有一种可能更简单的方法来实现这一点,我已经学会了透明度:

a=rnorm(1000, 3, 1)
b=rnorm(1000, 6, 1)
hist(a, xlim=c(0,10), col="red")
hist(b, add=T, col=rgb(0, 1, 0, 0.5)

Answer 2

fftR 中的(快速傅立叶变换)函数的输出处理起来可能有点繁琐.我写这个plotFFT函数是为了做FFT的频率与功率曲线.该getFFTFreqs函数(由内部使用plotFFT)返回与每个FFT值相关的频率.

这主要基于http://tolstoy.newcastle.edu.au/R/help/05/08/11236.html上非常有趣的讨论.

# Gets the frequencies returned by the FFT function
getFFTFreqs <- function(Nyq.Freq, data)
    {
    if ((length(data) %% 2) == 1) # Odd number of samples
        {
        FFTFreqs <- c(seq(0, Nyq.Freq, length.out=(length(data)+1)/2), 
               seq(-Nyq.Freq, 0, length.out=(length(data)-1)/2))
        }
    else # Even number
        {
        FFTFreqs <- c(seq(0, Nyq.Freq, length.out=length(data)/2), 
               seq(-Nyq.Freq, 0, length.out=length(data)/2))
        }

    return (FFTFreqs)
    }

# FFT plot
# Params:
# x,y -> the data for which we want to plot the FFT 
# samplingFreq -> the sampling frequency
# shadeNyq -> if true the region in [0;Nyquist frequency] will be shaded
# showPeriod -> if true the period will be shown on the top
# Returns a list with:
# freq -> the frequencies
# FFT -> the FFT values
# modFFT -> the modulus of the FFT
plotFFT <- function(x, y, samplingFreq, shadeNyq=TRUE, showPeriod = TRUE)
    {
    Nyq.Freq <- samplingFreq/2
    FFTFreqs <- getFFTFreqs(Nyq.Freq, y)

    FFT <- fft(y)
    modFFT <- Mod(FFT)
    FFTdata <- cbind(FFTFreqs, modFFT)
    plot(FFTdata[1:nrow(FFTdata)/2,], t="l", pch=20, lwd=2, cex=0.8, main="",
        xlab="Frequency (Hz)", ylab="Power")
    if (showPeriod == TRUE)
        {
        # Period axis on top        
        a <- axis(3, lty=0, labels=FALSE)
        axis(3, cex.axis=0.6, labels=format(1/a, digits=2), at=a)
        }
    if (shadeNyq == TRUE)
        {
        # Gray out lower frequencies
        rect(0, 0, 2/max(x), max(FFTdata[,2])*2, col="gray", density=30)
        }

    ret <- list("freq"=FFTFreqs, "FFT"=FFT, "modFFT"=modFFT)
    return (ret)
    }

作为一个例子,你可以试试这个

# A sum of 3 sine waves + noise
x <- seq(0, 8*pi, 0.01)
sine <- sin(2*pi*5*x) + 0.5 * sin(2*pi*12*x) + 0.1*sin(2*pi*20*x) + 1.5*runif(length(x))
par(mfrow=c(2,1))
plot(x, sine, "l")
res <- plotFFT(x, sine, 100)

要么

linearChirp <- function(fr=0.01, k=0.01, len=100, samplingFreq=100)
    {
    x <- seq(0, len, 1/samplingFreq)
    chirp <- sin(2*pi*(fr+k/2*x)*x) 

    ret <- list("x"=x, "y"=chirp)
    return(ret)
    }

chirp <- linearChirp(1, .02, 100, 500)
par(mfrow=c(2,1))
plot(chirp, t="l")
res <- plotFFT(chirp$x, chirp$y, 500, xlim=c(0, 4))

哪个给

正弦波的 FFT图http://www.nicolaromano.net/misc/sine.jpg线性啁啾的FFT图http://www.nicolaromano.net/misc/chirp.jpg

Answer 3

非常简单,但我经常使用它:

setdiff2 <- function(x,y) {
    #returns a list of the elements of x that are not in y 
     #and the elements of y that are not in x (not the same thing...)

    Xdiff = setdiff(x,y)
    Ydiff = setdiff(y,x)
    list(X_not_in_Y=Xdiff, Y_not_in_X=Ydiff)
}

Answer 4

# Create a circle with n number of "sides" (kudos to Barry Rowlingson, r-sig-geo).
circle <-  function(x = 0, y = 0, r = 100, n = 30){
    t <- seq(from = 0, to = 2 * pi, length = n + 1)[-1]
    t <- cbind(x = x + r * sin(t), y = y + r * cos(t))
    t <- rbind(t, t[1,])
    return(t)
}
# To run it, use
plot(circle(x = 0, y = 0, r = 50, n = 100), type = "l")

Answer 5

对我来说很烦人的是如何data.frame打印很多列,我的意思是这个列分裂.所以我写了自己的版本:

print.data.frame <- function(x, ...) {
    oWidth <- getOption("width")
    oMaxPrint <- getOption("max.print")
    on.exit(options(width=oWidth, max.print=oMaxPrint))
    options(width=10000, max.print=300)
    base::print.data.frame(x, ...)
}