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更新时间：2023-11-09 19:39:40
使用 scale（）来转换x和y使用字段
$ b
>包在你的问题：
库（akima）
库（字段）
$ b $ （20,4,3）
y x y< - scale（y）＃来重现你的错误
z -norm（20）
s 图像。情节
library（akima）
library（ggplot2）$ （20，4，3）
y x y< - scale（y）＃来重现你的错误
z
t。 < - interp（x，y，z）
t.df< - data.frame（t。）
gt< - data.frame（expand.grid（X1 = t $ x，
X2 = t。$ y），
z = c（t。$ z），
value = cut（c（t。$ z），
（a）（x1，x2，fill = value）bs = bs（min（z），max（z），0.25）））
p geom_tile ）+
geom_contour（aes（x = X1，y = X2，z = z），color =black）
p
另一个问题，解决方案也描述为在重新缩放前使用正确的原始数据值标记轴。目前只适用于 ggplot 。
I am trying to use the A true heat map in R suggestions, however I get the error:
Error in interp.old(x, y, z, xo = xo, yo = yo, ncp = 0, extrap = extrap,
: scales of x and y are too dissimilar
after the code line:
s <- interp(x,y,z)
My data was constructed expecting to get coloured heat-map like lines in a dark continuous background, and works in GNUplot using set pm3d map and set hidden3d. The data corresponds to a model of molecules production (y) in a given time (x) with the frequency of appearance denoted by z. It looks like this:
1.000000000000e+00 1e-8 0
1.000000000000e+00 5e-8 0
1.000000000000e+00 1e-7 5
1.000000000000e+00 5e-7 0
1.000000000000e+00 1e-6 0
1.000000000000e+00 5e-6 0
1.000000000000e+00 1e-5 0
1.000000000000e+00 5e-5 0
1.000000000000e+00 1e-4 0
1.000000000000e+00 5e-4 0
1.000000000000e+00 1e-3 0
1.000000000000e+00 5e-3 0
1.000000000000e+00 1e-2 0
1.000000000000e+00 5e-2 0
1.000000000000e+00 1e-1 0
1.000000000000e+00 5e-1 0
1.000000000000e+00 1e+1 0
1.000000000000e+00 5e+1 0
1.000000000000e+00 1e+2 0
1.000000000000e+00 5e+2 0
1.000000000000e+00 1e+3 0
1.000000000000e+00 5e+3 0
1.000000000000e+00 1e+4 0
1.000000000000e+00 5e+4 0
1.000000000000e+00 1e+5 0
1.000000000000e+00 5e+5 0
1.000000000000e+00 1e+6 0
1.000000000000e+00 5e+6 0
1.000000000000e+00 1e+7 0
1.000000000000e+00 5e+7 0
1.000000000000e+00 1e+8 0
1.000000000000e+00 5e+8 0
2.000000000000e+00 1e-8 0
2.000000000000e+00 5e-8 0
2.000000000000e+00 1e-7 0
2.000000000000e+00 5e-7 5
2.000000000000e+00 1e-6 0
2.000000000000e+00 5e-6 0
2.000000000000e+00 1e-5 0
2.000000000000e+00 5e-5 0
2.000000000000e+00 1e-4 0
2.000000000000e+00 5e-4 0
2.000000000000e+00 1e-3 0
2.000000000000e+00 5e-3 0
2.000000000000e+00 1e-2 0
2.000000000000e+00 5e-2 0
2.000000000000e+00 1e-1 0
2.000000000000e+00 5e-1 0
2.000000000000e+00 1e+1 0
2.000000000000e+00 5e+1 0
2.000000000000e+00 1e+2 0
2.000000000000e+00 5e+2 0
2.000000000000e+00 1e+3 0
2.000000000000e+00 5e+3 0
2.000000000000e+00 1e+4 0
2.000000000000e+00 5e+4 0
2.000000000000e+00 1e+5 0
2.000000000000e+00 5e+5 0
2.000000000000e+00 1e+6 0
2.000000000000e+00 5e+6 0
2.000000000000e+00 1e+7 0
2.000000000000e+00 5e+7 0
2.000000000000e+00 1e+8 0
2.000000000000e+00 5e+8 0
3.000000000000e+00 1e-8 0
3.000000000000e+00 5e-8 0
3.000000000000e+00 1e-7 0
3.000000000000e+00 5e-7 0
3.000000000000e+00 1e-6 5
3.000000000000e+00 5e-6 0
3.000000000000e+00 1e-5 0
3.000000000000e+00 5e-5 0
3.000000000000e+00 1e-4 0
3.000000000000e+00 5e-4 0
3.000000000000e+00 1e-3 0
3.000000000000e+00 5e-3 0
3.000000000000e+00 1e-2 0
3.000000000000e+00 5e-2 0
3.000000000000e+00 1e-1 0
3.000000000000e+00 5e-1 0
3.000000000000e+00 1e+1 0
3.000000000000e+00 5e+1 0
3.000000000000e+00 1e+2 0
3.000000000000e+00 5e+2 0
3.000000000000e+00 1e+3 0
3.000000000000e+00 5e+3 0
3.000000000000e+00 1e+4 0
3.000000000000e+00 5e+4 0
3.000000000000e+00 1e+5 0
3.000000000000e+00 5e+5 0
3.000000000000e+00 1e+6 0
3.000000000000e+00 5e+6 0
3.000000000000e+00 1e+7 0
3.000000000000e+00 5e+7 0
3.000000000000e+00 1e+8 0
3.000000000000e+00 5e+8 0
4.000000000000e+00 1e-8 0
4.000000000000e+00 5e-8 0
4.000000000000e+00 1e-7 0
4.000000000000e+00 5e-7 0
4.000000000000e+00 1e-6 0
4.000000000000e+00 5e-6 5
4.000000000000e+00 1e-5 0
4.000000000000e+00 5e-5 0
4.000000000000e+00 1e-4 0
4.000000000000e+00 5e-4 0
4.000000000000e+00 1e-3 0
4.000000000000e+00 5e-3 0
4.000000000000e+00 1e-2 0
4.000000000000e+00 5e-2 0
4.000000000000e+00 1e-1 0
4.000000000000e+00 5e-1 0
4.000000000000e+00 1e+1 0
4.000000000000e+00 5e+1 0
4.000000000000e+00 1e+2 0
4.000000000000e+00 5e+2 0
4.000000000000e+00 1e+3 0
4.000000000000e+00 5e+3 0
4.000000000000e+00 1e+4 0
4.000000000000e+00 5e+4 0
4.000000000000e+00 1e+5 0
4.000000000000e+00 5e+5 0
4.000000000000e+00 1e+6 0
4.000000000000e+00 5e+6 0
4.000000000000e+00 1e+7 0
4.000000000000e+00 5e+7 0
4.000000000000e+00 1e+8 0
4.000000000000e+00 5e+8 0
The first suggestion gave me some ugly results similar the ones obtained at first in A true heat map in R which is a plot with some horizontal lines full of dots in different gray-scale tones. The second seems to crash. I got this message from it:
>Traceback:
1: .Fortran("idsfft", as.integer(1), as.integer(ncp), as.integer(n), as.double(x), as.double(y), as.double(z), as.integer(nx), as.integer(ny), x = as.double(xo), y = as.double(yo), z = zo, integer((31 + ncp) * n + nx * ny), double(5 * n), misso = as.logical(misso), PACKAGE = "akima")
2: interp.old(x, y, z, xo = xo, yo = yo, ncp = 0, extrap = extrap, duplicate = duplicate, dupfun = dupfun)
3: interp(x, y, z)
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
I just included more data in case it is helpful. I am calling the columns from the data frame this way:
coso <- read.table("/home/libertad/mygraphs/two/two_1_90/coso.txt", header = FALSE,sep = "\t")
>x <-coso[[1]]
>y <-coso[[2]]
This is one of my graphs in GNUplot, I expected to get nicer ones with R.
Use scale() to transform x and y to comparable scales.
Using the fields package as in your question:
library(akima)
library(fields)
x <- rnorm(20, 4, 3)
y <- rnorm(20, 5e-5, 1e-5)
x <- scale(x) # comment out these two lines
y <- scale(y) # to reproduce your error
z <- rnorm(20)
s <- interp(x,y,z)
image.plot(s)
Using ggplot2, adapted from my other answer here:
library(akima)
library(ggplot2)
x <- rnorm(20, 4, 3)
y <- rnorm(20, 5e-5, 1e-5)
x <- scale(x) # comment out these two lines
y <- scale(y) # to reproduce your error
z <- rnorm(20)
t. <- interp(x,y,z)
t.df <- data.frame(t.)
gt <- data.frame( expand.grid(X1=t.$x,
X2=t.$y),
z=c(t.$z),
value=cut(c(t.$z),
breaks=seq(min(z),max(z),0.25)))
p <- ggplot(gt) +
geom_tile(aes(X1,X2,fill=value)) +
geom_contour(aes(x=X1,y=X2,z=z), colour="black")
p
In another question, the solution is also described for labeling the axes with the correct values of the original data before the re-scaling. This currently only applies to ggplot.