我运行了发布在http://ggplot2.tidyverse.org/articles/extending-ggplot2.html#picking-defaults的 R 代码 ，以下是修改后的代码，添加了一些 print() 以显示每个步骤中的变量值，我的问题在代码中被标记为注释：
StatDensityCommon <- ggproto("StatDensityCommon", Stat, required_aes = "x",
setup_params = function(data, params) {
print("PARAMS BEFORE:")
print(params)
if(!is.null(params$bandwidth))
return(params)
print("DATA: ")
print(data)
#1. When and how does the data being modified and the "group" field added?
xs <- split(data$x, data$group)
print("XS: ")
print(xs)
bws <- vapply(xs, bw.nrd0, numeric(1))
print("BWS: ")
print(bws)
bw <- mean(bws)
print("BW: ")
print(bw)
message("Picking bandwidth of ", signif(bw, 3))
params$bandwidth <- bw
print("PARAMS AFTER: ")
print(params)
params
},
compute_group = function(data, scales, bandwidth = 1) {
#2. how does the bandwidth computed in setup_params passed into compute_group
#even if the bandwidth has already been set to 1 in the arguments?
d <- density(data$x, bw = bandwidth)
data.frame(x = d$x, y = d$y)
}
)
stat_density_common <- function(mapping = NULL, data = NULL, geom = "line", position = "identity", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, bandwidth = NULL, ...){
layer(stat = StatDensityCommon, data = data, mapping = mapping, geom = geom, position = position, show.legend = show.legend, inherit.aes = inherit.aes, params = list(bandwidth = bandwidth, na.rm = na.rm, ...))
}
ggplot(mpg, aes(displ, colour = drv)) + stat_density_common()
以下是除绘图外的输出：
[1] "PARAMS BEFORE:"
$bandwidth
NULL
$na.rm
[1] FALSE
[1] "DATA: "
x colour PANEL group
1 1.8 f 1 2
2 1.8 f 1 2
3 2.0 f 1 2
4 2.0 f 1 2
5 2.8 f 1 2
6 2.8 f 1 2
7 3.1 f 1 2
8 1.8 4 1 1
9 1.8 4 1 1
10 2.0 4 1 1
11 2.0 4 1 1
12 2.8 4 1 1
13 2.8 4 1 1
14 3.1 4 1 1
15 3.1 4 1 1
16 2.8 4 1 1
17 3.1 4 1 1
18 4.2 4 1 1
19 5.3 r 1 3
20 5.3 r 1 3
21 5.3 r 1 3
22 5.7 r 1 3
23 6.0 r 1 3
24 5.7 r 1 3
25 5.7 r 1 3
26 6.2 r 1 3
27 6.2 r 1 3
28 7.0 r 1 3
29 5.3 4 1 1
30 5.3 4 1 1
31 5.7 4 1 1
32 6.5 4 1 1
33 2.4 f 1 2
34 2.4 f 1 2
35 3.1 f 1 2
36 3.5 f 1 2
37 3.6 f 1 2
38 2.4 f 1 2
39 3.0 f 1 2
40 3.3 f 1 2
41 3.3 f 1 2
42 3.3 f 1 2
43 3.3 f 1 2
44 3.3 f 1 2
45 3.8 f 1 2
46 3.8 f 1 2
47 3.8 f 1 2
48 4.0 f 1 2
49 3.7 4 1 1
50 3.7 4 1 1
51 3.9 4 1 1
52 3.9 4 1 1
53 4.7 4 1 1
54 4.7 4 1 1
55 4.7 4 1 1
56 5.2 4 1 1
57 5.2 4 1 1
58 3.9 4 1 1
59 4.7 4 1 1
60 4.7 4 1 1
61 4.7 4 1 1
62 5.2 4 1 1
63 5.7 4 1 1
64 5.9 4 1 1
65 4.7 4 1 1
66 4.7 4 1 1
67 4.7 4 1 1
68 4.7 4 1 1
69 4.7 4 1 1
70 4.7 4 1 1
71 5.2 4 1 1
72 5.2 4 1 1
73 5.7 4 1 1
74 5.9 4 1 1
75 4.6 r 1 3
76 5.4 r 1 3
77 5.4 r 1 3
78 4.0 4 1 1
79 4.0 4 1 1
80 4.0 4 1 1
81 4.0 4 1 1
82 4.6 4 1 1
83 5.0 4 1 1
84 4.2 4 1 1
85 4.2 4 1 1
86 4.6 4 1 1
87 4.6 4 1 1
88 4.6 4 1 1
89 5.4 4 1 1
90 5.4 4 1 1
91 3.8 r 1 3
92 3.8 r 1 3
93 4.0 r 1 3
94 4.0 r 1 3
95 4.6 r 1 3
96 4.6 r 1 3
97 4.6 r 1 3
98 4.6 r 1 3
99 5.4 r 1 3
100 1.6 f 1 2
101 1.6 f 1 2
102 1.6 f 1 2
103 1.6 f 1 2
104 1.6 f 1 2
105 1.8 f 1 2
106 1.8 f 1 2
107 1.8 f 1 2
108 2.0 f 1 2
109 2.4 f 1 2
110 2.4 f 1 2
111 2.4 f 1 2
112 2.4 f 1 2
113 2.5 f 1 2
114 2.5 f 1 2
115 3.3 f 1 2
116 2.0 f 1 2
117 2.0 f 1 2
118 2.0 f 1 2
119 2.0 f 1 2
120 2.7 f 1 2
121 2.7 f 1 2
122 2.7 f 1 2
123 3.0 4 1 1
124 3.7 4 1 1
125 4.0 4 1 1
126 4.7 4 1 1
127 4.7 4 1 1
128 4.7 4 1 1
129 5.7 4 1 1
130 6.1 4 1 1
131 4.0 4 1 1
132 4.2 4 1 1
133 4.4 4 1 1
134 4.6 4 1 1
135 5.4 r 1 3
136 5.4 r 1 3
137 5.4 r 1 3
138 4.0 4 1 1
139 4.0 4 1 1
140 4.6 4 1 1
141 5.0 4 1 1
142 2.4 f 1 2
143 2.4 f 1 2
144 2.5 f 1 2
145 2.5 f 1 2
146 3.5 f 1 2
147 3.5 f 1 2
148 3.0 f 1 2
149 3.0 f 1 2
150 3.5 f 1 2
151 3.3 4 1 1
152 3.3 4 1 1
153 4.0 4 1 1
154 5.6 4 1 1
155 3.1 f 1 2
156 3.8 f 1 2
157 3.8 f 1 2
158 3.8 f 1 2
159 5.3 f 1 2
160 2.5 4 1 1
161 2.5 4 1 1
162 2.5 4 1 1
163 2.5 4 1 1
164 2.5 4 1 1
165 2.5 4 1 1
166 2.2 4 1 1
167 2.2 4 1 1
168 2.5 4 1 1
169 2.5 4 1 1
170 2.5 4 1 1
171 2.5 4 1 1
172 2.5 4 1 1
173 2.5 4 1 1
174 2.7 4 1 1
175 2.7 4 1 1
176 3.4 4 1 1
177 3.4 4 1 1
178 4.0 4 1 1
179 4.7 4 1 1
180 2.2 f 1 2
181 2.2 f 1 2
182 2.4 f 1 2
183 2.4 f 1 2
184 3.0 f 1 2
185 3.0 f 1 2
186 3.5 f 1 2
187 2.2 f 1 2
188 2.2 f 1 2
189 2.4 f 1 2
190 2.4 f 1 2
191 3.0 f 1 2
192 3.0 f 1 2
193 3.3 f 1 2
194 1.8 f 1 2
195 1.8 f 1 2
196 1.8 f 1 2
197 1.8 f 1 2
198 1.8 f 1 2
199 4.7 4 1 1
200 5.7 4 1 1
201 2.7 4 1 1
202 2.7 4 1 1
203 2.7 4 1 1
204 3.4 4 1 1
205 3.4 4 1 1
206 4.0 4 1 1
207 4.0 4 1 1
208 2.0 f 1 2
209 2.0 f 1 2
210 2.0 f 1 2
211 2.0 f 1 2
212 2.8 f 1 2
213 1.9 f 1 2
214 2.0 f 1 2
215 2.0 f 1 2
216 2.0 f 1 2
217 2.0 f 1 2
218 2.5 f 1 2
219 2.5 f 1 2
220 2.8 f 1 2
221 2.8 f 1 2
222 1.9 f 1 2
223 1.9 f 1 2
224 2.0 f 1 2
225 2.0 f 1 2
226 2.5 f 1 2
227 2.5 f 1 2
228 1.8 f 1 2
229 1.8 f 1 2
230 2.0 f 1 2
231 2.0 f 1 2
232 2.8 f 1 2
233 2.8 f 1 2
234 3.6 f 1 2
[1] "XS: "
$`1`
[1] 1.8 1.8 2.0 2.0 2.8 2.8 3.1 3.1 2.8 3.1 4.2 5.3 5.3 5.7 6.5 3.7 3.7 3.9 3.9 4.7 4.7 4.7 5.2 5.2
[25] 3.9 4.7 4.7 4.7 5.2 5.7 5.9 4.7 4.7 4.7 4.7 4.7 4.7 5.2 5.2 5.7 5.9 4.0 4.0 4.0 4.0 4.6 5.0 4.2
[49] 4.2 4.6 4.6 4.6 5.4 5.4 3.0 3.7 4.0 4.7 4.7 4.7 5.7 6.1 4.0 4.2 4.4 4.6 4.0 4.0 4.6 5.0 3.3 3.3
[73] 4.0 5.6 2.5 2.5 2.5 2.5 2.5 2.5 2.2 2.2 2.5 2.5 2.5 2.5 2.5 2.5 2.7 2.7 3.4 3.4 4.0 4.7 4.7 5.7
[97] 2.7 2.7 2.7 3.4 3.4 4.0 4.0
$`2`
[1] 1.8 1.8 2.0 2.0 2.8 2.8 3.1 2.4 2.4 3.1 3.5 3.6 2.4 3.0 3.3 3.3 3.3 3.3 3.3 3.8 3.8 3.8 4.0 1.6
[25] 1.6 1.6 1.6 1.6 1.8 1.8 1.8 2.0 2.4 2.4 2.4 2.4 2.5 2.5 3.3 2.0 2.0 2.0 2.0 2.7 2.7 2.7 2.4 2.4
[49] 2.5 2.5 3.5 3.5 3.0 3.0 3.5 3.1 3.8 3.8 3.8 5.3 2.2 2.2 2.4 2.4 3.0 3.0 3.5 2.2 2.2 2.4 2.4 3.0
[73] 3.0 3.3 1.8 1.8 1.8 1.8 1.8 2.0 2.0 2.0 2.0 2.8 1.9 2.0 2.0 2.0 2.0 2.5 2.5 2.8 2.8 1.9 1.9 2.0
[97] 2.0 2.5 2.5 1.8 1.8 2.0 2.0 2.8 2.8 3.6
$`3`
[1] 5.3 5.3 5.3 5.7 6.0 5.7 5.7 6.2 6.2 7.0 4.6 5.4 5.4 3.8 3.8 4.0 4.0 4.6 4.6 4.6 4.6 5.4 5.4 5.4
[25] 5.4
[1] "BWS: "
1 2 3
0.4056219 0.2482564 0.3797632
[1] "BW: "
[1] 0.3445472
Picking bandwidth of 0.345
[1] "PARAMS AFTER: "
$bandwidth
[1] 0.3445472
$na.rm
[1] FALSE
提前致谢！