是否有一种简单的方法来为R中的2d直方图(hist2d)定义中断而不是nbins?
我想为2D直方图定义x轴和y轴的范围以及每个尺寸的bin数。
我的例子:
# example data
x <- sample(-1:100, 2000, replace=T)
y <- sample(0:89, 2000, replace=T)
# create 2d histogram
h2 <- hist2d(x,y,nbins=c(23,19),xlim=c(-1,110), ylim=c(0,95),xlab='x',ylab='y',main='hist2d')
这导致这个2D直方图输出1
----------------------------
2-D Histogram Object
----------------------------
Call: hist2d(x = x, y = y, nbins = c(23, 19), xlab = "x", ylab = "y",
xlim = c(-1, 110), ylim = c(0, 95), main = "hist2d")
Number of data points: 2000
Number of grid bins: 23 x 19
X range: ( -1 , 100 )
Y range: ( 0 , 89 )
我需要
X range: ( -1 , 110 )
Y range: ( 0 , 95 )
代替。
我尝试定义xlim和ylim只会扩展绘图,但不会定义直方图的轴范围。我知道附加箱中没有数据。
有没有办法定义
xbreaks = seq(-1,110,5)
ybreaks = seq(0,95,5)
而不是使用nbins,它将范围从最小值到最大值分成给定的箱数?
感谢您的帮助
答案 0 :(得分:0)
按如下方式修改“hist2d”
hist2d_range<-function (x, y = NULL, nbins = 200, same.scale = TRUE, na.rm = TRUE,
show = TRUE, col = c("black", heat.colors(12)), FUN = base::length,
xlab, ylab,range=NULL, ...)
{
if (is.null(y)) {
if (ncol(x) != 2)
stop("If y is ommitted, x must be a 2 column matirx")
y <- x[, 2]
x <- x[, 1]
}
if (length(nbins) == 1)
nbins <- rep(nbins, 2)
nas <- is.na(x) | is.na(y)
if (na.rm) {
x <- x[!nas]
y <- y[!nas]
}
else stop("missinig values not permitted if na.rm=FALSE")
if (same.scale) {
if(is.null(range))
{
x.cuts <- seq(from = min(x, y), to = max(x, y), length = nbins[1] +
1)
y.cuts <- seq(from = min(x, y), to = max(x, y), length = nbins[2] +
1)
}else{
x.cuts <- seq(from = range[1], to = range[2], length = nbins[1] + 1)
y.cuts <- seq(from = range[1], to = range[2], length = nbins[1] + 1)
}
}
else {
x.cuts <- seq(from = min(x), to = max(x), length = nbins[1] +
1)
y.cuts <- seq(from = min(y), to = max(y), length = nbins[2] +
1)
}
index.x <- cut(x, x.cuts, include.lowest = TRUE)
index.y <- cut(y, y.cuts, include.lowest = TRUE)
m <- tapply(x, list(index.x, index.y), FUN)
if (identical(FUN, base::length))
m[is.na(m)] <- 0
if (missing(xlab))
xlab <- deparse(substitute(xlab))
if (missing(ylab))
ylab <- deparse(substitute(ylab))
if (show)
image(x.cuts, y.cuts, m, col = col, xlab = xlab, ylab = ylab,
...)
midpoints <- function(x) (x[-1] + x[-length(x)])/2
retval <- list()
retval$counts <- m
retval$x.breaks = x.cuts
retval$y.breaks = y.cuts
retval$x = midpoints(x.cuts)
retval$y = midpoints(y.cuts)
retval$nobs = length(x)
retval$call <- match.call()
class(retval) <- "hist2d"
retval
}
此函数有一个附加参数“range”。 修订点如下。
if(is.null(range))
{
x.cuts <- seq(from = min(x, y), to = max(x, y), length = nbins[1] +
1)
y.cuts <- seq(from = min(x, y), to = max(x, y), length = nbins[2] +
1)
}else{
x.cuts <- seq(from = range[1], to = range[2], length = nbins[1] + 1)
y.cuts <- seq(from = range[1], to = range[2], length = nbins[1] + 1)
}
答案 1 :(得分:0)
我稍微更改了代码,这个版本应该可以明确定义两个轴的中断。首先,您必须加载该功能。然后,您可以使用x.breaks
提供y.breaks
和x.breaks=seq(0,10,0.1)
选项。
如果same.scale
为真,则只需x.breaks
返回值addionaly包含bin的数量和相对计数。
此外,如果需要,您可以通过设置legend=TRUE
来添加图例。为此,您需要拥有包Fields
hist2d_breaks = function (x, y = NULL, nbins = 200,same.scale = FALSE, na.rm = TRUE,
show = TRUE, col = c("black", heat.colors(12)), FUN = base::length,
xlab, ylab,x.breaks,y.breaks, ...)
{
if (is.null(y)) {
if (ncol(x) != 2)
stop("If y is ommitted, x must be a 2 column matirx")
y <- x[, 2]
x <- x[, 1]
}
if (length(nbins) == 1)
nbins <- rep(nbins, 2)
nas <- is.na(x) | is.na(y)
if (na.rm) {
x <- x[!nas]
y <- y[!nas]
}
else stop("missinig values not permitted if na.rm=FALSE")
if(same.scale){
x.cuts = x.breaks;
y.cuts = x.breaks;
}else{
x.cuts <- x.breaks
y.cuts <- y.breaks
}
index.x <- cut(x, x.cuts, include.lowest = TRUE)
index.y <- cut(y, y.cuts, include.lowest = TRUE)
m <- tapply(x, list(index.x, index.y), FUN)
if (identical(FUN, base::length))
m[is.na(m)] <- 0
if (missing(xlab))
xlab <- deparse(substitute(xlab))
if (missing(ylab))
ylab <- deparse(substitute(ylab))
if (show){
if(legend){
image.plot(x.cuts, y.cuts, m, col = col, xlab = xlab, ylab = ylab,
...)
}else{
image(x.cuts, y.cuts, m, col = col, xlab = xlab, ylab = ylab,
...)
}
}
midpoints <- function(x) (x[-1] + x[-length(x)])/2
retval <- list()
retval$counts <- m
retval$counts_rel <- m/max(m)
retval$x.breaks = x.cuts
retval$y.breaks = y.cuts
retval$x = midpoints(x.cuts)
retval$y = midpoints(y.cuts)
retval$nobs = length(x)
retval$bins = c(length(x.cuts),length(y.cuts))
retval$call <- match.call()
class(retval) <- "hist2d"
retval
}
(我的数据)的调用然后带来以下内容:
hist2d_breaks(df,x.breaks=seq(0,10,1),y.breaks=seq(-10,10,1),legend=TRUE)
提出以下情节
2D Histogram with breaks