【发布时间】：2013-10-30 05:25:37
【问题描述】：
这应该是一个超级简单的问题，但我还在学习 ggplot 并不能让它工作。
我想修复此图中颜色条的最小值和最大值，以图形方式与其他图进行比较，我的意思是图例中的最小值为例如-2，最大值为 4。
我尝试了limits，但无法成功。
require(ggmap)
colormap <- c("Violet","Blue","Green","Yellow","Red","White")
map.in <- get_map(location = c(24.9072, 60.1477, 24.9623, 60.1752), source = "osm")
sim.data <- ggmap(map.in) %+% samplesnnsp +
aes(x = samplesnnsp[,1],
y = samplesnnsp[,2],
z = samplesnnsp[,3])+
stat_summary2d(fun = median,
binwidth = c(.0005, .0005),
alpha = 0.4) +
scale_fill_gradientn(name = "Median",
colours = colormap,
space = "Lab") +
labs(x = "Longitude",
y = "Latitude") +
coord_map()
print(sim.data)
一些数据可能是
samplesnnsp <-
lon lat var1.pred var1.var
1 24.90720 60.1477 -0.459263483 NA
2 24.90734 60.1477 -1.470819439 NA
3 24.90748 60.1477 0.341401207 NA
4 24.90761 60.1477 -0.627459141 NA
5 24.90775 60.1477 -0.945025977 NA
6 24.90789 60.1477 1.593166965 NA
7 24.90803 60.1477 1.388875605 NA
8 24.90817 60.1477 1.573702349 NA
9 24.90830 60.1477 -1.456883473 NA
10 24.90844 60.1477 -0.044724669 NA
11 24.90858 60.1477 0.492260162 NA
12 24.90872 60.1477 1.301121758 NA
13 24.90886 60.1477 -0.995094857 NA
14 24.90900 60.1477 -0.134303726 NA
15 24.90913 60.1477 0.742252392 NA
16 24.90927 60.1477 -1.252147160 NA
17 24.90941 60.1477 -0.526063594 NA
18 24.90955 60.1477 0.244057093 NA
19 24.90969 60.1477 -0.509438179 NA
20 24.90982 60.1477 0.240845774 NA
21 24.90996 60.1477 1.214138185 NA
22 24.91010 60.1477 0.169762721 NA
23 24.91024 60.1477 0.064761291 NA
24 24.91038 60.1477 2.135645208 NA
25 24.91051 60.1477 -0.320435955 NA
26 24.91065 60.1477 0.192032441 NA
27 24.91079 60.1477 1.717479829 NA
28 24.91093 60.1477 0.917301565 NA
29 24.91107 60.1477 -0.532562593 NA
30 24.91120 60.1477 0.963605718 NA
31 24.91134 60.1477 0.397451616 NA
32 24.91148 60.1477 1.818823108 NA
33 24.91162 60.1477 0.345882622 NA
34 24.91176 60.1477 -0.655113243 NA
35 24.91190 60.1477 -0.052475131 NA
36 24.91203 60.1477 -0.533822804 NA
37 24.91217 60.1477 -1.192470544 NA
38 24.91231 60.1477 -1.004180985 NA
39 24.91245 60.1477 -1.531023312 NA
40 24.91259 60.1477 -0.629444162 NA
41 24.91272 60.1477 0.282512182 NA
42 24.91286 60.1477 0.560439088 NA
43 24.91300 60.1477 -0.922094517 NA
44 24.91314 60.1477 -0.121183201 NA
45 24.91328 60.1477 0.897210951 NA
46 24.91341 60.1477 1.598458357 NA
47 24.91355 60.1477 -0.023978283 NA
48 24.91369 60.1477 0.979520714 NA
49 24.91383 60.1477 -1.558292167 NA
50 24.91397 60.1477 -0.857758865 NA
51 24.91410 60.1477 2.436103790 NA
52 24.91424 60.1477 -0.716014292 NA
53 24.91438 60.1477 -1.509418144 NA
54 24.91452 60.1477 0.421319628 NA
55 24.91466 60.1477 0.134673030 NA
56 24.91480 60.1477 0.236527420 NA
57 24.91493 60.1477 -0.131870867 NA
58 24.91507 60.1477 -0.764709492 NA
59 24.91521 60.1477 -1.125855959 NA
60 24.91535 60.1477 -0.835676397 NA
61 24.91549 60.1477 -0.010050297 NA
62 24.91562 60.1477 -0.689060241 NA
63 24.91576 60.1477 -0.255953439 NA
64 24.91590 60.1477 1.503940499 NA
65 24.91604 60.1477 -0.647302524 NA
66 24.91618 60.1477 0.032949746 NA
67 24.91631 60.1477 -0.302106163 NA
68 24.91645 60.1477 -0.869169561 NA
69 24.91659 60.1477 -1.125110141 NA
70 24.91673 60.1477 0.028541911 NA
71 24.91687 60.1477 -0.519090322 NA
72 24.91700 60.1477 -0.029579821 NA
73 24.91714 60.1477 0.208527926 NA
74 24.91728 60.1477 0.893646836 NA
75 24.91742 60.1477 -0.887658105 NA
76 24.91756 60.1477 1.304644066 NA
77 24.91770 60.1477 -2.235914148 NA
78 24.91783 60.1477 -0.732714812 NA
79 24.91797 60.1477 -1.068315393 NA
80 24.91811 60.1477 0.989133329 NA
81 24.91825 60.1477 -0.658703883 NA
82 24.91839 60.1477 1.174113274 NA
83 24.91852 60.1477 -2.435087039 NA
84 24.91866 60.1477 -1.462809655 NA
85 24.91880 60.1477 0.433320476 NA
86 24.91894 60.1477 0.203231497 NA
87 24.91908 60.1477 -0.654920115 NA
88 24.91921 60.1477 -0.247426889 NA
89 24.91935 60.1477 -1.282573973 NA
90 24.91949 60.1477 -0.189281908 NA
91 24.91963 60.1477 0.004738164 NA
92 24.91977 60.1477 0.619994186 NA
93 24.91990 60.1477 -1.553654198 NA
94 24.92004 60.1477 -0.260587710 NA
95 24.92018 60.1477 -0.316618098 NA
96 24.92032 60.1477 -0.617153029 NA
97 24.92046 60.1477 -1.496197677 NA
98 24.92060 60.1477 -1.433603039 NA
99 24.92073 60.1477 -0.549665645 NA
100 24.92087 60.1477 -0.315078410 NA
【问题讨论】：
-
如果您提供minimal, reproducible example，您更有可能收到有用的答案。
ggmap(map.in) %+% samplesnnspError in ggmap(map.in) : object 'map.in' not found。ggmap(samplesnnsp)Error: ggmap plots objects of class ggmap, see ?get_map。干杯。 -
糟糕，我没注意到，让我修复它。
标签： r colors ggplot2 legend ggmap