R - ggplot - stat_contour无法生成等高线 [英] R - ggplot - stat_contour not able to generate contour lines

问题描述

我试图通过 stat_contour（）将等高线添加到我的ggplot / ggplot2-plot中。不幸的是，我不能给你真正的数据，从哪个点值应该评估。然而，另一个容易复制的例子表现相同：

I am trying to add contour lines via stat_contour() to my ggplot/ggplot2-plot. Unfortunately, I can not give you the real data from which point values should be evaluated. However, another easily repreducably example behaves the same:

testPts <- data.frame(x=rep(seq(7.08, 7.14, by=0.005), 200))
testPts$y <- runif(length(testPts$x), 50.93, 50.96)
testPts$z <- sin(testPts$y * 500)

(ggplot(data=testPts, aes(x=x, y=y, z=z))
+ geom_point(aes(colour=z))
+ stat_contour()
)

这会导致以下错误消息：

This results in the following error message:

Error in if (nrow(layer_data) == 0) return() : argument is of length zero
In addition: Warning message:
Not possible to generate contour data 

在我的官方手册/教程中，并且如果我为 stat_contour 提供更多规范，那么看起来并不重要。看起来，该函数并不传递数据（-layer）作为指出错误信息。

The example looks not different to others posted on stackoverflow or in the official manual/tutorial to me, and it seeminlgy doesn't matter if I provide more specifications to stat_contour. It seems, the function does not pass the data(-layer) as pointed ou tint the error message.

感谢您的想法和建议！

推荐答案

这个问题的一个解决方案是生成一个规则的网格，并且针对该网格插值点值。以下是我为多个数据字段中的一个完成的操作：

One solution to this problem is the generation of a regular grid and the interpolation of point values in respect to that grid. Here is how I did it for just one of multiple data fields:

pts.grid <- interp(as.data.frame(pts)$coords.x1, as.data.frame(pts)$coords.x2, as.data.frame(pts)$GWLEVEL_TI)
pts.grid2 <- expand.grid(x=pts.grid$x, y=pts.grid$y)
pts.grid2$z <- as.vector(pts.grid$z)

这个结果产生一个数据框架，当数据框架定义时，它可以在 stat_contour（）中的ggplot中使用。该函数的参数：

This results in a data frame which can be used in a ggplot in stat_contour() when defined in the data-parameter of that function:

(ggplot(as.data.frame(pts), aes(x=coords.x1, y=coords.x2, z=GWLEVEL_TI))
#+ geom_tile(data=na.omit(pts.grid2), aes(x=x, y=y, z=z, fill=z))
+ stat_contour(data=na.omit(pts.grid2), binwidth=2, colour="red", aes(x=x, y=y, z=z))
+ geom_point()
)

这个解决方案很可能包含不必要的转换，因为我还不知道更好。此外，我必须为每个数据字段单独进行同一个网格生成，然后再将它们组合到一个数据框中 - 效率并不像我想要的那样适用于更大的数据集。

This solution most likely includes unneccessary transformations because I don't know better yet. Furthermore I must make the same grid generation for every data field individually before combining them in a single data frame again - not as efficient as I would like it to be for bigger data sets.

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