r - 使用 ggplot2 的 Hodogram

Question

我想使用 ggplot2 创建一个多面图，代表每月的风向图。

我最近阅读了以下帖子:How to map wind direction and speed (velocity plot) with R 。我想这对我来说可能是一个好的开始。以下数据集将风值表示为 u 和 v 分量，时间步长为 3 小时。我想将其表示为一个hodogram，这意味着每个向量都遵循前一个向量。

                u             v
 [1,]  -4.0000000 -6.928203e+00
 [2,]  -6.1283555 -5.142301e+00
 [3,]  -5.0000000  1.224647e-15
 [4,]  -3.7587705  1.368081e+00
 [5,]   4.0000000 -4.898587e-16
 [6,]   4.6984631 -1.710101e+00
 [7,]   5.6381557  2.052121e+00
 [8,]   6.1283555  5.142301e+00
 [9,]  -9.1925333 -7.713451e+00
[10,]  -6.5778483  2.394141e+00
[11,]  -5.3623111  4.499513e+00
[12,]  -4.5962667  3.856726e+00
[13,]  -7.0000000  1.714506e-15
[14,]  -6.5778483 -2.394141e+00
[15,]   6.0000000 -7.347881e-16
[16,]  -6.5778483 -2.394141e+00
[17,]  -6.0000000  1.469576e-15
[18,]  -8.0000000  1.959435e-15
[19,]  -5.6381557  2.052121e+00
[20,]  -6.0000000  1.469576e-15
[21,]  -4.5962667  3.856726e+00
[22,]   2.0000000 -3.464102e+00
[23,]   5.6381557 -2.052121e+00
[24,]   6.0000000 -7.347881e-16
[25,]   5.6381557 -2.052121e+00
[26,]  -5.3623111 -4.499513e+00
[27,]  -4.5962667 -3.856726e+00
[28,]  -6.1283555 -5.142301e+00
[29,]  -4.6984631 -1.710101e+00
[30,]   0.8682409 -4.924039e+00
[31,]   2.5000000 -4.330127e+00
[32,]  -0.8682409 -4.924039e+00
[33,]  -6.0000000  1.469576e-15
[34,]  -5.3623111 -4.499513e+00
[35,]  -3.8302222 -3.213938e+00
[36,]  -4.5962667 -3.856726e+00
[37,]  -3.5000000 -6.062178e+00
[38,]   1.0418891 -5.908847e+00
[39,]   5.3623111 -4.499513e+00
[40,]   4.5962667 -3.856726e+00
[41,]   3.8302222 -3.213938e+00
[42,]   3.0000000 -5.196152e+00
[43,]   5.3623111 -4.499513e+00
[44,]   5.3623111 -4.499513e+00
[45,]   4.5962667 -3.856726e+00
[46,]   3.0000000 -5.196152e+00
[47,]   4.5962667 -3.856726e+00
[48,]   3.8302222 -3.213938e+00
[49,]   1.0418891 -5.908847e+00
[50,]   3.8302222 -3.213938e+00

您可以在这里找到一个hodogram示例: (就像左下角的那个)。

有了这些 Hodograms(每月 1 个)，我想用 ggplot2 绘制一个多面图，但我认为(我希望)我可以管理这部分。

如有任何帮助，我们将不胜感激。

提前非常感谢您!

Answer 1

我得到了一些东西，我还在努力......

u <- mydata$u
v <- mydata$v
x <- cumsum(mydata$u[56297:56704]*10.8)
y <- cumsum(mydata$v[56297:56704]*10.8)
wind <- cbind(x,y)
wind <- data.frame(wind)
p <- ggplot(wind) + geom_path(aes(x, y, colour = x))

未完待续...不要犹豫发表评论!)