Create r36.r

2022_r36_paired_barplot/r36.r

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+library(ggplot2)
+library(ggnewscale)
+
+oridat <-  read.csv('micro.csv', header = TRUE)
+oridat1 <- oridat[,1:2]
+oridat2 <- oridat[,c(1,3)]
+oridat1$x <-1
+oridat1$dens <- oridat1$WCH1/sum(oridat1$WCH1)
+oridat1 <- oridat1[order(oridat1$WCH1, decreasing = TRUE),]
+dat1 <- oridat1[1:20,]
+names(dat1)[1:2] <- c('lab','abun')
+dat1$y <- 20:1
+
+oridat2$x <-2
+oridat2$dens <- oridat2$WXH1/sum(oridat2$WXH1)
+oridat2 <- oridat2[order(oridat2$WXH1, decreasing = TRUE),]
+dat2 <- oridat2[1:20,]
+names(dat2)[1:2] <- c('lab','abun')
+dat2$y <- 20:1
+
+dat <- rbind(dat1,dat2)
+dat3 <- data.frame(name = c('Cigu', 'Xiangpu'),
+                   x = 1:2,
+                   y = 21.5)
+
+
+
+ggplot(dat, aes(x,y)) + geom_text(aes(label = lab, hjust = ifelse(x ==1,1,0))) + geom_line(aes(group = lab))+
+  geom_segment(data = dat2,aes(x = x+1, xend = x + 1 + (dens*30), y = y, yend = y, color = dens), size = 6) +
+  geom_segment(data = dat1,aes(x = x-1, xend = x - 1 - (dens*30), y = y, yend = y, color = dens), size = 6) +
+  scale_color_gradientn(
+    colours = c("grey90", "pink", "darkorchid4"),
+    breaks = c(0, 0.05, 0.13)
+    ) +
+  theme_void() +
+  theme(legend.position = "none") +
+  new_scale_color() +
+  geom_text(data = dat2, aes(x = x +1, y = y, label = scales::percent(dens, accuracy = .01), color = I(ifelse(dens > 0.1, 'white', 'black'))), hjust = 0) +
+  geom_text(data = dat1, aes(x = x -1, y = y, label = scales::percent(dens, accuracy = .01), color = I(ifelse(dens > 0.1, 'white', 'black'))), hjust = 1) +
+  geom_text(data = dat3,aes(label = name, hjust = ifelse(x ==1,1,0)), size = 8 )
+