Question

我目前正在研究模拟集水流对四个气候变量的响应： T，RH，Rs和uz 。我想构建一些响应曲面＆＃39;我流向两个变量， T和Rs ，具有 Rs和uz 范围的不同组合，即流量对 T和Rs的响应以 RH和uz 为条件。

然而格子中似乎没有任何函数可以用于构造具有2个条件变量的表面，或者它就像我一直在错误地使用它们一样。例如，我尝试了 levelplot（），但它给了我一个空白的情节：

# Separate input variables and define range intervals for plotting
deltaT <- as.matrix(x$X$X1)
deltaRH <- as.matrix(x$X$X2)
deltaRs <- as.matrix(x$X$X3)
deltauz <- as.matrix(x$X$X4)
responseQave <- as.matrix(t(yPenman)[,11])    

# Use 2 intervals for each conditioning variable with 10% overlap
deltaRHint <- equal.count(deltaRH,number=2,overlap=.1)
deltauzint <- equal.count(deltauz,number=2,overlap=.1)

levelplot(responseQave ~ deltaT * deltaRs | deltaRHint * deltauzint, zlim = c(-20,20),cuts=10, col.regions = colorRampPalette(c("red", "white", "blue")))

因此，我手动将Rs和uz的范围划分为区间，并尝试使用 filled.contour 为Rs和uz的每个区间组合构建表面。

这里是我开发的代码 - 很遗憾，因为我还在开发我的编码技能：

# Extract the boundaries of intervals for each conditioning variable
deltaRHI <- as.matrix(levels(deltaRHint))
deltaRHI <- c(deltaRHI[[1]][1],deltaRHI[[1]][2],deltaRHI[[2]][1],deltaRHI[[2]][2])
deltauzI <- as.matrix(levels(deltauzint))
deltauzI <- c(deltauzI[[1]][1],deltauzI[[1]][2],deltauzI[[2]][1],deltauzI[[2]][2])

# response to T and Rs
# first combination of RH and uz - interpolate irregular data using akima

grid111 <- interp(x = deltaT[deltaRH>deltaRHI[1] & deltaRH<deltaRHI[2] & deltauz>deltauzI[2]], 
              y = deltaRs[deltaRH>deltaRHI[1] & deltaRH<deltaRHI[2] & deltauz>deltauzI[2]],
              z = responseQave[deltaRH>deltaRHI[1] & deltaRH<deltaRHI[2]& deltauz>deltauzI[2]],
              duplicate="strip")
filled.contour(x = grid111$x,
           y = grid111$y,
           z = grid111$z,
           xlim = c(0,8), ylim = c(-10,10), zlim = c(-20,20),
           levels = c(seq(-20,20,by = 1)),
           color.palette = colorRampPalette(c("red", "white", "blue")))

# second combination of RH and uz
grid222 <- interp(x = deltaT[deltaRH>deltaRHI[2] & deltauz>deltauzI[2]], 
              y = deltaRs[deltaRH>deltaRHI[2] & deltauz>deltauzI[2]], 
              z = responseQave[deltaRH>deltaRHI[2]& deltauz>deltauzI[2]], 
              duplicate="strip")
filled.contour(x = grid222$x,
              y = grid222$y,
              z = grid222$z,
              xlim = c(0,8), ylim = c(-10,10), zlim = c(-20,20),
              levels = c(seq(-20,20,by = 1)),
              color.palette =
                colorRampPalette(c("red", "white", "blue")))

# third combination of RH and uz
grid333 <- interp(x = deltaT[deltaRH>deltaRHI[1] & deltaRH<deltaRHI[2] & deltauz>deltauzI[1] & deltauz<deltauzI[2]], 
              y = deltaRs[deltaRH>deltaRHI[1] & deltaRH<deltaRHI[2] & deltauz>deltauzI[1] & deltauz<deltauzI[2]],
              z = responseQave[deltaRH>deltaRHI[1] & deltaRH<deltaRHI[2]& deltauz>deltauzI[1] & deltauz<deltauzI[2]],
              duplicate="strip")
filled.contour(x = grid333$x,
              y = grid333$y,
              z = grid333$z,
              xlim = c(0,8), ylim = c(-10,10), zlim = c(-20,20),
              levels = c(seq(-20,20,by = 1)),
              color.palette =
                colorRampPalette(c("red", "white", "blue")))

# fourth combination of RH and uz
grid444 <- interp(x = deltaT[deltaRH>deltaRHI[2] & deltauz>deltauzI[1] & deltauz<deltauzI[2]], 
              y = deltaRs[deltaRH>deltaRHI[2] & deltauz>deltauzI[1] & deltauz<deltauzI[2]], 
              z = responseQave[deltaRH>deltaRHI[2]& deltauz>deltauzI[1] & deltauz<deltauzI[2]], 
              duplicate="strip")
filled.contour(x = grid444$x,
              y = grid444$y,
              z = grid444$z,
              xlim = c(0,8), ylim = c(-10,10), zlim = c(-20,20),
              levels = c(seq(-20,20,by = 1)),
              color.palette =
                colorRampPalette(c("red", "white", "blue")))

这些似乎给我提供了很好的单个表面图，如下图所示，但顶部没有条形表示调节变量的水平（就像你在使用晶格生成的标准曲面图的面板上看到的那样） em> - 所以我很难将它们组合在一起，并且这些条形显示条件变量。

任何帮助将不胜感激！：）

Answer 1

我无法告诉您如何使用未提供的数据进行操作，并且您没有通过提供正确的测试数据集来完成我们，但是有一个interaction函数可以构建一个因子来自两个输入因素。

dat <- data.frame( responseQave =rnorm(32), deltaT=rnorm(32), deltaRs=rlnorm(32), deltaRHint=a,deltazint=b)
print(levelplot(responseQave ~ deltaT * deltaRs | interaction(deltaRHint, deltazint), data=dat))

将多个fill.contour图与R中不同级别的条件变量结合起来

1 个答案: