请在下面查找我的数据。
nd 包含两列
> nd
lnd y
1: 0.0 0.350
2: 0.1 0.351
3: 0.2 0.353
4: 0.3 0.356
5: 0.4 0.358
---
997: 99.6 0.884
998: 99.7 0.884
999: 99.8 0.885
1000: 99.9 0.885
1001: 100.0 0.885
我已经制作了这个图(在 Stackoverflow 的帮助下)，但我很难让它正常工作。
我的问题是，下面的脚本似乎只适用于基于 nd$lnd-values 的整数。我想要蓝色的geom_polygon(范围从LND==0到~10)将y轴精确对齐nd$y==0.551 (用橙色圆圈表示)。nd$y==0.551 随后应与 x 轴 上的相应值匹配，即 >nd$lnd==9.6。
我的脚本:
library(tidyverse)
cols = c("#2C77BF", "#E38072","#6DBCC3")
polys = function(xrng, col.num) {
geom_polygon(data=nd %>%
filter(lnd>=xrng[1], lnd<=xrng[2]) %>%
bind_rows(data.frame(lnd=c(xrng[2], rep(0,2), xrng[1]),
y=c(rep(nd$y[nd$lnd==xrng[2]], 2), rep(nd$y[nd$lnd==xrng[1]], 2)))),
fill=cols[col.num],alpha=0.85)
}
as.data.frame(approx(nd$lnd, nd$y, xout=c(nd$lnd, 9.0001, 25.0001))) %>%
set_names(c("lnd", "y")) %>%
mutate(xcut = cut(lnd, c(0,9,25,100), include.lowest=TRUE)) %>%
ggplot(aes(lnd, y)) +
geom_area(aes(fill=xcut), alpha=0.3) +
polys(c(0,9),1) +
polys(c(9,25),2) +
polys(c(25,100),3) +
geom_line(size=6,color="white") +
geom_line(size=2, alpha=.9) +
geom_segment(aes(x = 0, y = nd$y[1], xend = 0, yend = 0.2), lty="solid", size=0.9, color="black") +
geom_point(aes(x = 0, y = nd$y[1]), size=4, shape=20, col="black", alpha=0.5) +
scale_fill_manual(values=cols) +
scale_colour_manual(values=cols) +
scale_x_continuous(name="", breaks=seq(0,100,by=5),
label=c(paste0("0%"), paste0(seq(5,100,5),"%"))) +
scale_y_continuous(name = "", breaks = seq(0.35,1,by=.1),
labels=c("35%","","55%","","75%","","95%")) +
coord_cartesian(ylim=c(0.25,0.95), xlim=c(0,50))
当我尝试更改上述脚本中的以下内容时，出现错误:
(...)
mutate(xcut = cut(lnd, c(0,9.6,25,100), include.lowest=TRUE)) %>%
(...)
polys(c(0,9.6),1) +
polys(c(9.6,25),2) +
(...)
(9已更改为9.6)
...产生以下图:
还有我的数据:
nd <- structure(list(lnd = c(0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7,
0.8, 0.9, 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2,
2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3, 3.1, 3.2, 3.3,
3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6,
4.7, 4.8, 4.9, 5, 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9,
6, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, 7, 7.1, 7.2,
7.3, 7.4, 7.5, 7.6, 7.7, 7.8, 7.9, 8, 8.1, 8.2, 8.3, 8.4, 8.5,
8.6, 8.7, 8.8, 8.9, 9, 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7, 9.8,
9.9, 10, 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8, 10.9,
11, 11.1, 11.2, 11.3, 11.4, 11.5, 11.6, 11.7, 11.8, 11.9, 12,
12.1, 12.2, 12.3, 12.4, 12.5, 12.6, 12.7, 12.8, 12.9, 13, 13.1,
13.2, 13.3, 13.4, 13.5, 13.6, 13.7, 13.8, 13.9, 14, 14.1, 14.2,
14.3, 14.4, 14.5, 14.6, 14.7, 14.8, 14.9, 15, 15.1, 15.2, 15.3,
15.4, 15.5, 15.6, 15.7, 15.8, 15.9, 16, 16.1, 16.2, 16.3, 16.4,
16.5, 16.6, 16.7, 16.8, 16.9, 17, 17.1, 17.2, 17.3, 17.4, 17.5,
17.6, 17.7, 17.8, 17.9, 18, 18.1, 18.2, 18.3, 18.4, 18.5, 18.6,
18.7, 18.8, 18.9, 19, 19.1, 19.2, 19.3, 19.4, 19.5, 19.6, 19.7,
19.8, 19.9, 20, 20.1, 20.2, 20.3, 20.4, 20.5, 20.6, 20.7, 20.8,
20.9, 21, 21.1, 21.2, 21.3, 21.4, 21.5, 21.6, 21.7, 21.8, 21.9,
22, 22.1, 22.2, 22.3, 22.4, 22.5, 22.6, 22.7, 22.8, 22.9, 23,
23.1, 23.2, 23.3, 23.4, 23.5, 23.6, 23.7, 23.8, 23.9, 24, 24.1,
24.2, 24.3, 24.4, 24.5, 24.6, 24.7, 24.8, 24.9, 25, 25.1, 25.2,
25.3, 25.4, 25.5, 25.6, 25.7, 25.8, 25.9, 26, 26.1, 26.2, 26.3,
26.4, 26.5, 26.6, 26.7, 26.8, 26.9, 27, 27.1, 27.2, 27.3, 27.4,
27.5, 27.6, 27.7, 27.8, 27.9, 28, 28.1, 28.2, 28.3, 28.4, 28.5,
28.6, 28.7, 28.8, 28.9, 29, 29.1, 29.2, 29.3, 29.4, 29.5, 29.6,
29.7, 29.8, 29.9, 30, 30.1, 30.2, 30.3, 30.4, 30.5, 30.6, 30.7,
30.8, 30.9, 31, 31.1, 31.2, 31.3, 31.4, 31.5, 31.6, 31.7, 31.8,
31.9, 32, 32.1, 32.2, 32.3, 32.4, 32.5, 32.6, 32.7, 32.8, 32.9,
33, 33.1, 33.2, 33.3, 33.4, 33.5, 33.6, 33.7, 33.8, 33.9, 34,
34.1, 34.2, 34.3, 34.4, 34.5, 34.6, 34.7, 34.8, 34.9, 35, 35.1,
35.2, 35.3, 35.4, 35.5, 35.6, 35.7, 35.8, 35.9, 36, 36.1, 36.2,
36.3, 36.4, 36.5, 36.6, 36.7, 36.8, 36.9, 37, 37.1, 37.2, 37.3,
37.4, 37.5, 37.6, 37.7, 37.8, 37.9, 38, 38.1, 38.2, 38.3, 38.4,
38.5, 38.6, 38.7, 38.8, 38.9, 39, 39.1, 39.2, 39.3, 39.4, 39.5,
39.6, 39.7, 39.8, 39.9, 40, 40.1, 40.2, 40.3, 40.4, 40.5, 40.6,
40.7, 40.8, 40.9, 41, 41.1, 41.2, 41.3, 41.4, 41.5, 41.6, 41.7,
41.8, 41.9, 42, 42.1, 42.2, 42.3, 42.4, 42.5, 42.6, 42.7, 42.8,
42.9, 43, 43.1, 43.2, 43.3, 43.4, 43.5, 43.6, 43.7, 43.8, 43.9,
44, 44.1, 44.2, 44.3, 44.4, 44.5, 44.6, 44.7, 44.8, 44.9, 45,
45.1, 45.2, 45.3, 45.4, 45.5, 45.6, 45.7, 45.8, 45.9, 46, 46.1,
46.2, 46.3, 46.4, 46.5, 46.6, 46.7, 46.8, 46.9, 47, 47.1, 47.2,
47.3, 47.4, 47.5, 47.6, 47.7, 47.8, 47.9, 48, 48.1, 48.2, 48.3,
48.4, 48.5, 48.6, 48.7, 48.8, 48.9, 49, 49.1, 49.2, 49.3, 49.4,
49.5, 49.6, 49.7, 49.8, 49.9, 50, 50.1, 50.2, 50.3, 50.4, 50.5,
50.6, 50.7, 50.8, 50.9, 51, 51.1, 51.2, 51.3, 51.4, 51.5, 51.6,
51.7, 51.8, 51.9, 52, 52.1, 52.2, 52.3, 52.4, 52.5, 52.6, 52.7,
52.8, 52.9, 53, 53.1, 53.2, 53.3, 53.4, 53.5, 53.6, 53.7, 53.8,
53.9, 54, 54.1, 54.2, 54.3, 54.4, 54.5, 54.6, 54.7, 54.8, 54.9,
55, 55.1, 55.2, 55.3, 55.4, 55.5, 55.6, 55.7, 55.8, 55.9, 56,
56.1, 56.2, 56.3, 56.4, 56.5, 56.6, 56.7, 56.8, 56.9, 57, 57.1,
57.2, 57.3, 57.4, 57.5, 57.6, 57.7, 57.8, 57.9, 58, 58.1, 58.2,
58.3, 58.4, 58.5, 58.6, 58.7, 58.8, 58.9, 59, 59.1, 59.2, 59.3,
59.4, 59.5, 59.6, 59.7, 59.8, 59.9, 60, 60.1, 60.2, 60.3, 60.4,
60.5, 60.6, 60.7, 60.8, 60.9, 61, 61.1, 61.2, 61.3, 61.4, 61.5,
61.6, 61.7, 61.8, 61.9, 62, 62.1, 62.2, 62.3, 62.4, 62.5, 62.6,
62.7, 62.8, 62.9, 63, 63.1, 63.2, 63.3, 63.4, 63.5, 63.6, 63.7,
63.8, 63.9, 64, 64.1, 64.2, 64.3, 64.4, 64.5, 64.6, 64.7, 64.8,
64.9, 65, 65.1, 65.2, 65.3, 65.4, 65.5, 65.6, 65.7, 65.8, 65.9,
66, 66.1, 66.2, 66.3, 66.4, 66.5, 66.6, 66.7, 66.8, 66.9, 67,
67.1, 67.2, 67.3, 67.4, 67.5, 67.6, 67.7, 67.8, 67.9, 68, 68.1,
68.2, 68.3, 68.4, 68.5, 68.6, 68.7, 68.8, 68.9, 69, 69.1, 69.2,
69.3, 69.4, 69.5, 69.6, 69.7, 69.8, 69.9, 70, 70.1, 70.2, 70.3,
70.4, 70.5, 70.6, 70.7, 70.8, 70.9, 71, 71.1, 71.2, 71.3, 71.4,
71.5, 71.6, 71.7, 71.8, 71.9, 72, 72.1, 72.2, 72.3, 72.4, 72.5,
72.6, 72.7, 72.8, 72.9, 73, 73.1, 73.2, 73.3, 73.4, 73.5, 73.6,
73.7, 73.8, 73.9, 74, 74.1, 74.2, 74.3, 74.4, 74.5, 74.6, 74.7,
74.8, 74.9, 75, 75.1, 75.2, 75.3, 75.4, 75.5, 75.6, 75.7, 75.8,
75.9, 76, 76.1, 76.2, 76.3, 76.4, 76.5, 76.6, 76.7, 76.8, 76.9,
77, 77.1, 77.2, 77.3, 77.4, 77.5, 77.6, 77.7, 77.8, 77.9, 78,
78.1, 78.2, 78.3, 78.4, 78.5, 78.6, 78.7, 78.8, 78.9, 79, 79.1,
79.2, 79.3, 79.4, 79.5, 79.6, 79.7, 79.8, 79.9, 80, 80.1, 80.2,
80.3, 80.4, 80.5, 80.6, 80.7, 80.8, 80.9, 81, 81.1, 81.2, 81.3,
81.4, 81.5, 81.6, 81.7, 81.8, 81.9, 82, 82.1, 82.2, 82.3, 82.4,
82.5, 82.6, 82.7, 82.8, 82.9, 83, 83.1, 83.2, 83.3, 83.4, 83.5,
83.6, 83.7, 83.8, 83.9, 84, 84.1, 84.2, 84.3, 84.4, 84.5, 84.6,
84.7, 84.8, 84.9, 85, 85.1, 85.2, 85.3, 85.4, 85.5, 85.6, 85.7,
85.8, 85.9, 86, 86.1, 86.2, 86.3, 86.4, 86.5, 86.6, 86.7, 86.8,
86.9, 87, 87.1, 87.2, 87.3, 87.4, 87.5, 87.6, 87.7, 87.8, 87.9,
88, 88.1, 88.2, 88.3, 88.4, 88.5, 88.6, 88.7, 88.8, 88.9, 89,
89.1, 89.2, 89.3, 89.4, 89.5, 89.6, 89.7, 89.8, 89.9, 90, 90.1,
90.2, 90.3, 90.4, 90.5, 90.6, 90.7, 90.8, 90.9, 91, 91.1, 91.2,
91.3, 91.4, 91.5, 91.6, 91.7, 91.8, 91.9, 92, 92.1, 92.2, 92.3,
92.4, 92.5, 92.6, 92.7, 92.8, 92.9, 93, 93.1, 93.2, 93.3, 93.4,
93.5, 93.6, 93.7, 93.8, 93.9, 94, 94.1, 94.2, 94.3, 94.4, 94.5,
94.6, 94.7, 94.8, 94.9, 95, 95.1, 95.2, 95.3, 95.4, 95.5, 95.6,
95.7, 95.8, 95.9, 96, 96.1, 96.2, 96.3, 96.4, 96.5, 96.6, 96.7,
96.8, 96.9, 97, 97.1, 97.2, 97.3, 97.4, 97.5, 97.6, 97.7, 97.8,
97.9, 98, 98.1, 98.2, 98.3, 98.4, 98.5, 98.6, 98.7, 98.8, 98.9,
99, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, 99.9, 100
), y = c(0.35, 0.351, 0.353, 0.356, 0.358, 0.361, 0.363, 0.366,
0.369, 0.371, 0.374, 0.377, 0.379, 0.382, 0.384, 0.387, 0.39,
0.392, 0.395, 0.397, 0.4, 0.402, 0.404, 0.407, 0.409, 0.411,
0.413, 0.416, 0.418, 0.42, 0.422, 0.424, 0.426, 0.428, 0.43,
0.431, 0.433, 0.435, 0.437, 0.439, 0.44, 0.442, 0.444, 0.446,
0.447, 0.449, 0.451, 0.452, 0.454, 0.456, 0.457, 0.459, 0.461,
0.462, 0.464, 0.466, 0.467, 0.469, 0.471, 0.473, 0.474, 0.476,
0.478, 0.48, 0.482, 0.484, 0.486, 0.488, 0.49, 0.492, 0.494,
0.496, 0.498, 0.5, 0.502, 0.504, 0.506, 0.508, 0.511, 0.513,
0.515, 0.517, 0.519, 0.522, 0.524, 0.526, 0.528, 0.531, 0.533,
0.535, 0.537, 0.54, 0.542, 0.544, 0.547, 0.549, 0.551, 0.554,
0.556, 0.558, 0.56, 0.563, 0.565, 0.567, 0.57, 0.572, 0.574,
0.576, 0.579, 0.581, 0.583, 0.585, 0.587, 0.59, 0.592, 0.594,
0.596, 0.598, 0.6, 0.602, 0.604, 0.606, 0.608, 0.61, 0.612, 0.614,
0.616, 0.618, 0.62, 0.622, 0.624, 0.626, 0.628, 0.63, 0.632,
0.633, 0.635, 0.637, 0.639, 0.64, 0.642, 0.644, 0.646, 0.647,
0.649, 0.651, 0.652, 0.654, 0.656, 0.657, 0.659, 0.66, 0.662,
0.663, 0.665, 0.666, 0.668, 0.669, 0.671, 0.672, 0.674, 0.675,
0.676, 0.678, 0.679, 0.681, 0.682, 0.683, 0.684, 0.686, 0.687,
0.688, 0.69, 0.691, 0.692, 0.693, 0.694, 0.696, 0.697, 0.698,
0.699, 0.7, 0.701, 0.703, 0.704, 0.705, 0.706, 0.707, 0.708,
0.709, 0.71, 0.711, 0.712, 0.713, 0.714, 0.715, 0.716, 0.717,
0.718, 0.719, 0.719, 0.72, 0.721, 0.722, 0.723, 0.724, 0.725,
0.726, 0.726, 0.727, 0.728, 0.729, 0.73, 0.73, 0.731, 0.732,
0.733, 0.733, 0.734, 0.735, 0.735, 0.736, 0.737, 0.737, 0.738,
0.739, 0.739, 0.74, 0.741, 0.741, 0.742, 0.742, 0.743, 0.744,
0.744, 0.745, 0.745, 0.746, 0.746, 0.747, 0.748, 0.748, 0.749,
0.749, 0.75, 0.75, 0.751, 0.751, 0.752, 0.752, 0.752, 0.753,
0.753, 0.754, 0.754, 0.755, 0.755, 0.755, 0.756, 0.756, 0.757,
0.757, 0.757, 0.758, 0.758, 0.759, 0.759, 0.759, 0.76, 0.76,
0.76, 0.761, 0.761, 0.761, 0.762, 0.762, 0.762, 0.763, 0.763,
0.763, 0.764, 0.764, 0.764, 0.764, 0.765, 0.765, 0.765, 0.765,
0.766, 0.766, 0.766, 0.767, 0.767, 0.767, 0.767, 0.768, 0.768,
0.768, 0.768, 0.768, 0.769, 0.769, 0.769, 0.769, 0.77, 0.77,
0.77, 0.77, 0.77, 0.771, 0.771, 0.771, 0.771, 0.771, 0.772, 0.772,
0.772, 0.772, 0.772, 0.773, 0.773, 0.773, 0.773, 0.773, 0.774,
0.774, 0.774, 0.774, 0.774, 0.775, 0.775, 0.775, 0.775, 0.775,
0.776, 0.776, 0.776, 0.776, 0.776, 0.776, 0.777, 0.777, 0.777,
0.777, 0.777, 0.778, 0.778, 0.778, 0.778, 0.778, 0.778, 0.779,
0.779, 0.779, 0.779, 0.779, 0.78, 0.78, 0.78, 0.78, 0.78, 0.781,
0.781, 0.781, 0.781, 0.781, 0.781, 0.782, 0.782, 0.782, 0.782,
0.782, 0.783, 0.783, 0.783, 0.783, 0.783, 0.783, 0.784, 0.784,
0.784, 0.784, 0.784, 0.785, 0.785, 0.785, 0.785, 0.785, 0.785,
0.786, 0.786, 0.786, 0.786, 0.786, 0.787, 0.787, 0.787, 0.787,
0.787, 0.787, 0.788, 0.788, 0.788, 0.788, 0.788, 0.789, 0.789,
0.789, 0.789, 0.789, 0.789, 0.79, 0.79, 0.79, 0.79, 0.79, 0.791,
0.791, 0.791, 0.791, 0.791, 0.791, 0.792, 0.792, 0.792, 0.792,
0.792, 0.793, 0.793, 0.793, 0.793, 0.793, 0.793, 0.794, 0.794,
0.794, 0.794, 0.794, 0.795, 0.795, 0.795, 0.795, 0.795, 0.795,
0.796, 0.796, 0.796, 0.796, 0.796, 0.797, 0.797, 0.797, 0.797,
0.797, 0.797, 0.798, 0.798, 0.798, 0.798, 0.798, 0.799, 0.799,
0.799, 0.799, 0.799, 0.799, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.801,
0.801, 0.801, 0.801, 0.801, 0.802, 0.802, 0.802, 0.802, 0.802,
0.802, 0.803, 0.803, 0.803, 0.803, 0.803, 0.804, 0.804, 0.804,
0.804, 0.804, 0.804, 0.805, 0.805, 0.805, 0.805, 0.805, 0.805,
0.806, 0.806, 0.806, 0.806, 0.806, 0.807, 0.807, 0.807, 0.807,
0.807, 0.807, 0.808, 0.808, 0.808, 0.808, 0.808, 0.808, 0.809,
0.809, 0.809, 0.809, 0.809, 0.809, 0.81, 0.81, 0.81, 0.81, 0.81,
0.811, 0.811, 0.811, 0.811, 0.811, 0.811, 0.812, 0.812, 0.812,
0.812, 0.812, 0.812, 0.813, 0.813, 0.813, 0.813, 0.813, 0.814,
0.814, 0.814, 0.814, 0.814, 0.814, 0.815, 0.815, 0.815, 0.815,
0.815, 0.815, 0.816, 0.816, 0.816, 0.816, 0.816, 0.816, 0.817,
0.817, 0.817, 0.817, 0.817, 0.817, 0.818, 0.818, 0.818, 0.818,
0.818, 0.819, 0.819, 0.819, 0.819, 0.819, 0.819, 0.82, 0.82,
0.82, 0.82, 0.82, 0.82, 0.821, 0.821, 0.821, 0.821, 0.821, 0.821,
0.822, 0.822, 0.822, 0.822, 0.822, 0.822, 0.823, 0.823, 0.823,
0.823, 0.823, 0.823, 0.824, 0.824, 0.824, 0.824, 0.824, 0.824,
0.825, 0.825, 0.825, 0.825, 0.825, 0.825, 0.826, 0.826, 0.826,
0.826, 0.826, 0.827, 0.827, 0.827, 0.827, 0.827, 0.827, 0.828,
0.828, 0.828, 0.828, 0.828, 0.828, 0.829, 0.829, 0.829, 0.829,
0.829, 0.829, 0.83, 0.83, 0.83, 0.83, 0.83, 0.83, 0.831, 0.831,
0.831, 0.831, 0.831, 0.831, 0.832, 0.832, 0.832, 0.832, 0.832,
0.832, 0.833, 0.833, 0.833, 0.833, 0.833, 0.833, 0.834, 0.834,
0.834, 0.834, 0.834, 0.834, 0.835, 0.835, 0.835, 0.835, 0.835,
0.835, 0.835, 0.836, 0.836, 0.836, 0.836, 0.836, 0.836, 0.837,
0.837, 0.837, 0.837, 0.837, 0.837, 0.838, 0.838, 0.838, 0.838,
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0.884, 0.884, 0.884, 0.885, 0.885, 0.885)), row.names = c(NA,
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最佳答案
使用您的数据，我只需更改 cut 和 polys 函数即可获得您正在寻找的图。
在你的代码上，我只改变:
mutate(xcut = cut(lnd, c(0,9.6,25,100), include.lowest=TRUE))
和
polys(c(0,9.6),1) +
polys(c(9.6,25),2) +
polys(c(25,100),3) +
要得到这个:
这对你来说是正确的情节吗？
关于r - 为什么这个 geom_polygon 只包含整数而不包含小数？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/59546720/