构build复杂情节的手册图例

我不知道如何手动设置这个情节的图例。 所有我真正想要的是一个简单的传说,右边使用三种颜色,每个都有一个名字。

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当前的代码如下所示:

a <-c("S1","S2","S3","S4","S5","S6","S7","S8","S9") #names b <-c(0.23,0.26,0.55,0.56,0.36,0.23,0.18,0.06,0.04) #mean t0 c <-c(0.64,0.6,0.81,1.4,0.89,0.55,0.48,0.22,0.09) #mean t1 d <-c(0.20,0.23,0.52,0.53,0.33,0.20,0.15,0.04,0.03) #SD low t0 e <-c(0.26,0.29,0.58,.59,0.39,0.26,0.21,0.08,0.05) #SD high t0 f <-c(0.67,0.63,0.86,1.44,0.93,0.59,0.51,0.25,0.10) #SD high t1 g <-c(0.61,0.57,0.78,1.36,0.85,0.53,0.45,0.19,0.08) #SD low t1 h <-c(0.41,0.34,0.26,0.84,0.53,0.32,0.30,0.16,0.05) #absolute change data <- data.frame(a,b,c,d,e,f,g,h) ggplot(data=data,aes(a)) + geom_bar(stat="identity", aes(y=h),fill="#62c76b",colour="#333333")+ #green geom_line(aes(y=b,group=1),size=1.0,colour="#f04546") + #red geom_point(aes(y=b),size=3, colour="#f04546") + #red geom_errorbar(aes(ymin=d, ymax=e), colour="#f04546", width=0.1, size=.8) + geom_line(aes(y=c,group=1),size=1.0,colour="#3591d1") + #blue geom_point(aes(y=c),size=3, colour="#3591d1") + #blue geom_errorbar(aes(ymin=f, ymax=g), colour="#3591d1", width=0.1, size=.8) + ylab("Symptom severity") + xlab("PHQ-9 symptoms") + ylim(0,1.6) + theme_bw() + theme(axis.title.x = element_text(size = 15, vjust=-.2)) + theme(axis.title.y = element_text(size = 15, vjust=0.3)) 

您需要将属性映射到美学(aes语句中的颜色)以生成图例。

 cols <- c("LINE1"="#f04546","LINE2"="#3591d1","BAR"="#62c76b") ggplot(data=data,aes(x=a)) + geom_bar(stat="identity", aes(y=h, fill = "BAR"),colour="#333333")+ #green geom_line(aes(y=b,group=1, colour="LINE1"),size=1.0) + #red geom_point(aes(y=b, colour="LINE1"),size=3) + #red geom_errorbar(aes(ymin=d, ymax=e, colour="LINE1"), width=0.1, size=.8) + geom_line(aes(y=c,group=1,colour="LINE2"),size=1.0) + #blue geom_point(aes(y=c,colour="LINE2"),size=3) + #blue geom_errorbar(aes(ymin=f, ymax=g,colour="LINE2"), width=0.1, size=.8) + scale_colour_manual(name="Error Bars",values=cols) + scale_fill_manual(name="Bar",values=cols) + ylab("Symptom severity") + xlab("PHQ-9 symptoms") + ylim(0,1.6) + theme_bw() + theme(axis.title.x = element_text(size = 15, vjust=-.2)) + theme(axis.title.y = element_text(size = 15, vjust=0.3)) 

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我知道罗兰是从哪里来的,但是由于这只是3个属性,并且由叠加条和错误条引起了复杂性,所以将数据保持为宽格式是合理的。 通过使用geom_pointrange可以稍微降低复杂度。


要更改原始图像中的误差线图例的背景颜色,请将+ theme(legend.key = element_rect(fill = "white",colour = "white"))到绘图规范中。 要合并不同的图例,通常需要为所有元素都有一个一致的映射,但是它目前正在为我生成黑色背景的工件。 我以为guide = guide_legend(fill = NULL,colour = NULL)会将图例的背景设置为null,但是没有。 也许值得另一个问题。

 ggplot(data=data,aes(x=a)) + geom_bar(stat="identity", aes(y=h,fill = "BAR", colour="BAR"))+ #green geom_line(aes(y=b,group=1, colour="LINE1"),size=1.0) + #red geom_point(aes(y=b, colour="LINE1", fill="LINE1"),size=3) + #red geom_errorbar(aes(ymin=d, ymax=e, colour="LINE1"), width=0.1, size=.8) + geom_line(aes(y=c,group=1,colour="LINE2"),size=1.0) + #blue geom_point(aes(y=c,colour="LINE2", fill="LINE2"),size=3) + #blue geom_errorbar(aes(ymin=f, ymax=g,colour="LINE2"), width=0.1, size=.8) + scale_colour_manual(name="Error Bars",values=cols, guide = guide_legend(fill = NULL,colour = NULL)) + scale_fill_manual(name="Bar",values=cols, guide="none") + ylab("Symptom severity") + xlab("PHQ-9 symptoms") + ylim(0,1.6) + theme_bw() + theme(axis.title.x = element_text(size = 15, vjust=-.2)) + theme(axis.title.y = element_text(size = 15, vjust=0.3)) 

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为了摆脱图例中的黑色背景,您需要在guide_legend使用override.aes参数。 这样做的目的是让您指定图例中可能没有被正确分配的特定方面。

 ggplot(data=data,aes(x=a)) + geom_bar(stat="identity", aes(y=h,fill = "BAR", colour="BAR"))+ #green geom_line(aes(y=b,group=1, colour="LINE1"),size=1.0) + #red geom_point(aes(y=b, colour="LINE1", fill="LINE1"),size=3) + #red geom_errorbar(aes(ymin=d, ymax=e, colour="LINE1"), width=0.1, size=.8) + geom_line(aes(y=c,group=1,colour="LINE2"),size=1.0) + #blue geom_point(aes(y=c,colour="LINE2", fill="LINE2"),size=3) + #blue geom_errorbar(aes(ymin=f, ymax=g,colour="LINE2"), width=0.1, size=.8) + scale_colour_manual(name="Error Bars",values=cols, guide = guide_legend(override.aes=aes(fill=NA))) + scale_fill_manual(name="Bar",values=cols, guide="none") + ylab("Symptom severity") + xlab("PHQ-9 symptoms") + ylim(0,1.6) + theme_bw() + theme(axis.title.x = element_text(size = 15, vjust=-.2)) + theme(axis.title.y = element_text(size = 15, vjust=0.3)) 

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