我用ggplot函数绘制图形, 这是我的绘图代码,它结合了三种不同的数据集。
pp<-ggplot(model_mean_homo,aes(x=m_tau,y=track_err,colour=model,group=model))+geom_line(size=2)
pp<-pp+geom_line(data=model_topN,aes(x=model_topN$m_tau,y=model_topN$track_err,colour=top_N,group=top_N))
pp<-pp+geom_point(data=model_mem,aes(x=model_mem$m_tau,y=model_mem$track_err,colour=model))
我想换行和点的颜色。 我尝试了以下代码:
pp<-scale_color_manual(values = c("ECMWF"="red","NCEP"="blue","ECMWF+NCEP"="green","5"="red1","10"="orange","15"="yello3","20"="green3","15"="black"),limits = c("ECMWF","NCEP","ECMWF+NCEP","5","10","15","20"))
但控制台只显示:
<ggproto object: Class ScaleDiscrete, Scale>
aesthetics: colour
break_info: function
break_positions: function
breaks: waiver
call: call
clone: function
dimension: function
drop: TRUE
expand: waiver
get_breaks: function
get_breaks_minor: function
get_labels: function
get_limits: function
guide: legend
is_discrete: function
is_empty: function
labels: waiver
limits: ECMWF NCEP ECMWF+NCEP 5 10 15 20
map: function
map_df: function
na.value: NA
name: waiver
palette: function
range: <ggproto object: Class RangeDiscrete, Range>
range: NULL
reset: function
train: function
super: <ggproto object: Class RangeDiscrete, Range>
reset: function
scale_name: manual
train: function
train_df: function
transform: function
transform_df: function
super: <ggproto object: Class ScaleDiscrete, Scale>
如何更改此类情节的颜色?
以下是数据集样本:
head(model_mean_homo)
YY model filetype m_tau track_err datano
1 2015 ECMWF+NCEP ensemble 0 35.44013 307
2 2015 ECMWF+NCEP ensemble 6 36.92316 300
3 2015 ECMWF+NCEP ensemble 12 43.44246 297
4 2015 ECMWF+NCEP ensemble 18 48.68222 284
5 2015 ECMWF+NCEP ensemble 24 57.60609 280
6 2015 ECMWF+NCEP ensemble 30 64.35638 268
head(model_topN)
YY model filetype m_tau track_err datano top_N
1 2015 NCEP ensemble 0 26.67671 618 5
2 2015 NCEP ensemble 6 27.97913 609 5
3 2015 NCEP ensemble 12 31.18090 594 5
4 2015 NCEP ensemble 18 34.23283 575 5
5 2015 NCEP ensemble 24 37.31816 557 5
6 2015 NCEP ensemble 30 43.25841 541 5
head(model_mem)
YY model filetype m_member m_tau track_err datano
1 2015 ECMWF ensemble 0 0 44.96796 397
2 2015 ECMWF ensemble 0 6 47.30694 390
3 2015 ECMWF ensemble 0 12 55.97534 383
4 2015 ECMWF ensemble 0 18 61.36752 367
5 2015 ECMWF ensemble 0 24 69.96123 363
6 2015 ECMWF ensemble 0 30 79.56475 345
答案 0 :(得分:1)
你的意思是:
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