From ff5dfb1c84b7f4f909b958f294df0512837651b5 Mon Sep 17 00:00:00 2001
From: Francesco Sabatini <francesco.sabatini@idiv.de>
Date: Mon, 7 Sep 2020 16:36:00 +0200
Subject: [PATCH] Corrected typo
---
02_Mesobromion_ExamineOutput.R | 245 ++++++++++++++++-----------------
1 file changed, 122 insertions(+), 123 deletions(-)
diff --git a/02_Mesobromion_ExamineOutput.R b/02_Mesobromion_ExamineOutput.R
index 25a76f5..906ef04 100644
--- a/02_Mesobromion_ExamineOutput.R
+++ b/02_Mesobromion_ExamineOutput.R
@@ -27,7 +27,7 @@ get.best <- function(x, N, labs){
traits <- read_delim("_data/Mesobromion/traits.v2.10perc.txt", delim="\t")
traits <- traits %>%
- rename(Schlerophylly=Leaf_Scleroph)
+ rename(Sclerophylly=Leaf_Scleroph)
#traits.sign.cov <- read_delim("_data/Mesobromion/traits.v2.10perc.cov.sign.txt", delim="\t")
#traits.sign.pa <- read_delim("_data/Mesobromion/traits.v2.10perc.pa.sign.txt", delim="\t")
trait.labs <- data.frame(trait.name=colnames(traits)[-1]) %>%
@@ -41,7 +41,7 @@ species.cov <- read_delim("_data/Mesobromion/species.v2.10perc.cov.txt", delim="
traits <- traits %>%
as.data.frame() %>%
- mutate_at(.vars=vars(Schlerophylly, LifeSpan, Rosette),
+ mutate_at(.vars=vars(Sclerophylly, LifeSpan, Rosette),
.funs=~as.ordered(.)) %>%
# filter(species0 %in% colnames(species)) %>%
mutate_if(~is.character(.), .funs=~as.factor(.)) %>%
@@ -617,7 +617,6 @@ ggsave(filename = "_pics/SXXX_Best_AllCombinations_CI_pa.png", dpi=400,
#species <- read_delim("_data/Mesobromion/species.out.10perc.txt", delim="\t")
species.cov <- read_delim("_data/Mesobromion/species.v2.10perc.cov.txt", delim="\t")
-#traits <- traits.backup
traits <- traits %>%
rownames_to_column("species0") %>%
mutate_if(.predicate=~is.ordered(.),
@@ -954,130 +953,130 @@ PCA3_4.sp <- basemap0 %+% tmp +
ylab(paste("PC4 (", varexpl[4], "%)", sep=""))
-ggsave("_pics/Fig6a_PCA_Beals_1-2_wSpecies.png", width=8, height=8, dpi=300, PCA1_2.sp)
-ggsave("_pics/Fig6b_PCA_Beals_3-4_wSpecies.png", width=8, height=8, dpi=300, PCA3_4.sp)
+ggsave("_pics/S10a_PCA_Beals_1-2_wSpecies.png", width=8, height=8, dpi=300, PCA1_2.sp)
+ggsave("_pics/S10b_PCA_Beals_3-4_wSpecies.png", width=8, height=8, dpi=300, PCA3_4.sp)
###### _ ######
#### 4.2 RDA of Beals ~ FWMs ####
-RDA.beals <- rda(W.beals ~ scores(pca.fuzz, choices=1:3)$sites, scale=F)
-# var explained by CONSTRAINED axes
-varexpl <- round((RDA.beals$CCA$eig)/(sum(RDA.beals$CA$eig) + sum(RDA.beals$CCA$eig))*100,1)
-
-scores.rda <- scores(RDA.beals, choices = 1:3)$sites #
-#scores.rda <- RDA.beals$CA$u[,1:3]
-(cwms.cor <- cor(CWM.wide, RDA.beals$CCA$u[,1:3]))
-env.cor <- cor(env %>%
- dplyr::select(Temp, Prec, pH=PHIPHOX, C.org=ORCDRC),
- RDA.beals$CCA$u[,1:3], use = "pairwise.complete.obs") #double check
-(fuzz.cor <- cor(pca.fuzz$CA$u, RDA.beals$CCA$u[,1:3])) #RDA.beals$CCA$biplot #
-
-myvectors.rda <- as.data.frame(env.cor) %>%
- rownames_to_column("mylab") %>%
- mutate(category="Env") %>%
- bind_rows(as.data.frame(cwms.cor) %>%
- rownames_to_column("mylab") %>%
- mutate(category="Trait")) %>%
- bind_rows(as.data.frame(fuzz.cor) %>%
- rownames_to_column("mylab") %>%
- mutate(mylab=paste0("FWM-", mylab)) %>%
- mutate(category="Fuzzy-Weighted")) %>%
- mutate(fontface0=ifelse(mylab %in% best.traits.cov, "bold", "italic")) %>%
- mutate(category=as.factor(category)) %>%
- mutate(mycol=ifelse(category=="Trait", oilgreen, orange)) %>%
- mutate(mycol=ifelse(category=="Fuzzy-Weighted", myblue, mycol)) %>%
- mutate(categorical=ifelse(grepl(pattern=paste(categorical.traits, collapse="|"), mylab), 1, 0)) %>%
- rowwise() %>%
- mutate(mylab=gsub(pattern="LeafPersistence", replacement = "LeafPers", x = mylab))
-
-
-
-basemap0 <- ggplot(data=as.data.frame(scores.rda)) +
- theme_bw() +
- scale_color_identity() +
- scale_y_continuous(limits=c(-1, 1)) +
- scale_x_continuous(limits=c(-1, 1)) + coord_equal() +
- theme(panel.grid = element_blank())
-
-
-RDA1_2 <- basemap0 +
- geom_point(data=as.data.frame(scores.rda),
- aes(x=RDA1, y=RDA2), pch="+", size=2, alpha=0.8) +
- geom_segment(data=myvectors.rda %>%
- filter(categorical==0),
- aes(x=0, xend=RDA1, y=0, yend=RDA2, col=mycol),
- arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
- geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
- geom_label_repel(data=myvectors.rda,
- aes(x=RDA1, y=RDA2, label=mylab, col=mycol, fontface=fontface0), size=2,
- position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
- xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
- ylab(paste("RDA2 (", varexpl[2], "%)", sep=""))
-
-ggsave("_pics/Fig6v2_RDA_Beals_1-2.png", width=10, height=5, dpi=300, RDA1_2)
-
-
-RDA1_3 <- basemap0 +
- geom_point(data=as.data.frame(scores.rda),
- aes(x=RDA1, y=RDA3), pch="+", size=2, alpha=0.8) +
- geom_segment(data=myvectors.rda %>%
- filter(categorical==0),
- aes(x=0, xend=RDA1, y=0, yend=RDA3, col=mycol),
- arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
- geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
- geom_label_repel(data=myvectors.rda,
- aes(x=RDA1, y=RDA3, label=mylab, col=mycol, fontface=fontface0), size=2,
- position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
- xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
- ylab(paste("RDA3 (", varexpl[3], "%)", sep=""))
-
-panel.RDA_beals <- cowplot::plot_grid(RDA1_2,RDA1_3, nrow=1)
-
-ggsave("_pics/Fig6v2_RDA_Beals_1-2-3.png", width=10, height=5, dpi=300, panel.RDA_beals)
-
-#### 4.2.1 Alternative showing species scores ####
-tmp <- as.data.frame(scores(RDA.beals, choices = 1:3)$species*4) %>%
-#tmp <- as.data.frame(RDA.beals$CCA$v*4) %>%
- mutate(species0=rownames(RDA.beals$CCA$v)) %>%
- mutate(species=species0) %>%
- separate(species0, sep="_", into=c("Gen", "Spe")) %>%
- mutate(Gen=substr(Gen, 1, 3)) %>%
- mutate(Spe=substr(Spe, 1, 3)) %>%
- mutate(labels=paste(Gen, Spe, sep="_"))
-
-tmp <- fix.duplicate.labels(tmp)
-
-
-RDA1_2.sp <- basemap0 %+% tmp +
- geom_text(aes(x=RDA1, y=RDA2, label=labels), size=2, alpha=0.8) +
- geom_segment(data=myvectors.rda%>%
- filter(categorical==0),
- aes(x=0, xend=RDA1, y=0, yend=RDA2, col=mycol),
- arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
- geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
- geom_label_repel(data=myvectors.rda,
- aes(x=RDA1, y=RDA2, label=mylab, col=mycol, fontface=fontface0), size=2,
- position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
- xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
- ylab(paste("RDA2 (", varexpl[2], "%)", sep=""))
-
-RDA1_3.sp <- basemap0 %+% tmp +
- geom_text(aes(x=RDA1, y=RDA3, label=labels), size=2, alpha=0.8) +
- geom_segment(data=myvectors.rda%>%
- filter(categorical==0),
- aes(x=0, xend=RDA1, y=0, yend=RDA3, col=mycol),
- arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
- geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
- geom_label_repel(data=myvectors.rda,
- aes(x=RDA1, y=RDA3, label=mylab, col=mycol, fontface=fontface0), size=2,
- position = position_dodge(1), segment.alpha=0.8, segment.colour=gray(0.7), segment.size = 0.5) +
- xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
- ylab(paste("RDA3 (", varexpl[3], "%)", sep=""))
-
-
-ggsave("_pics/Fig6v2a_RDA_Beals_1-2_wSpecies.png", width=8, height=8, dpi=300, RDA1_2.sp)
-ggsave("_pics/Fig6v2b_RDA_Beals_1-3_wSpecies.png", width=8, height=8, dpi=300, RDA1_3.sp)
-
+# RDA.beals <- rda(W.beals ~ scores(pca.fuzz, choices=1:3)$sites, scale=F)
+# # var explained by CONSTRAINED axes
+# varexpl <- round((RDA.beals$CCA$eig)/(sum(RDA.beals$CA$eig) + sum(RDA.beals$CCA$eig))*100,1)
+#
+# scores.rda <- scores(RDA.beals, choices = 1:3)$sites #
+# #scores.rda <- RDA.beals$CA$u[,1:3]
+# (cwms.cor <- cor(CWM.wide, RDA.beals$CCA$u[,1:3]))
+# env.cor <- cor(env %>%
+# dplyr::select(Temp, Prec, pH=PHIPHOX, C.org=ORCDRC),
+# RDA.beals$CCA$u[,1:3], use = "pairwise.complete.obs") #double check
+# (fuzz.cor <- cor(pca.fuzz$CA$u, RDA.beals$CCA$u[,1:3])) #RDA.beals$CCA$biplot #
+#
+# myvectors.rda <- as.data.frame(env.cor) %>%
+# rownames_to_column("mylab") %>%
+# mutate(category="Env") %>%
+# bind_rows(as.data.frame(cwms.cor) %>%
+# rownames_to_column("mylab") %>%
+# mutate(category="Trait")) %>%
+# bind_rows(as.data.frame(fuzz.cor) %>%
+# rownames_to_column("mylab") %>%
+# mutate(mylab=paste0("FWM-", mylab)) %>%
+# mutate(category="Fuzzy-Weighted")) %>%
+# mutate(fontface0=ifelse(mylab %in% best.traits.cov, "bold", "italic")) %>%
+# mutate(category=as.factor(category)) %>%
+# mutate(mycol=ifelse(category=="Trait", oilgreen, orange)) %>%
+# mutate(mycol=ifelse(category=="Fuzzy-Weighted", myblue, mycol)) %>%
+# mutate(categorical=ifelse(grepl(pattern=paste(categorical.traits, collapse="|"), mylab), 1, 0)) %>%
+# rowwise() %>%
+# mutate(mylab=gsub(pattern="LeafPersistence", replacement = "LeafPers", x = mylab))
+#
+#
+#
+# basemap0 <- ggplot(data=as.data.frame(scores.rda)) +
+# theme_bw() +
+# scale_color_identity() +
+# scale_y_continuous(limits=c(-1, 1)) +
+# scale_x_continuous(limits=c(-1, 1)) + coord_equal() +
+# theme(panel.grid = element_blank())
+#
+#
+# RDA1_2 <- basemap0 +
+# geom_point(data=as.data.frame(scores.rda),
+# aes(x=RDA1, y=RDA2), pch="+", size=2, alpha=0.8) +
+# geom_segment(data=myvectors.rda %>%
+# filter(categorical==0),
+# aes(x=0, xend=RDA1, y=0, yend=RDA2, col=mycol),
+# arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
+# geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
+# geom_label_repel(data=myvectors.rda,
+# aes(x=RDA1, y=RDA2, label=mylab, col=mycol, fontface=fontface0), size=2,
+# position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
+# xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
+# ylab(paste("RDA2 (", varexpl[2], "%)", sep=""))
+#
+# ggsave("_pics/Fig6v2_RDA_Beals_1-2.png", width=10, height=5, dpi=300, RDA1_2)
+#
+#
+# RDA1_3 <- basemap0 +
+# geom_point(data=as.data.frame(scores.rda),
+# aes(x=RDA1, y=RDA3), pch="+", size=2, alpha=0.8) +
+# geom_segment(data=myvectors.rda %>%
+# filter(categorical==0),
+# aes(x=0, xend=RDA1, y=0, yend=RDA3, col=mycol),
+# arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
+# geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
+# geom_label_repel(data=myvectors.rda,
+# aes(x=RDA1, y=RDA3, label=mylab, col=mycol, fontface=fontface0), size=2,
+# position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
+# xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
+# ylab(paste("RDA3 (", varexpl[3], "%)", sep=""))
+#
+# panel.RDA_beals <- cowplot::plot_grid(RDA1_2,RDA1_3, nrow=1)
+#
+# ggsave("_pics/Fig6v2_RDA_Beals_1-2-3.png", width=10, height=5, dpi=300, panel.RDA_beals)
+#
+# #### 4.2.1 Alternative showing species scores ####
+# tmp <- as.data.frame(scores(RDA.beals, choices = 1:3)$species*4) %>%
+# #tmp <- as.data.frame(RDA.beals$CCA$v*4) %>%
+# mutate(species0=rownames(RDA.beals$CCA$v)) %>%
+# mutate(species=species0) %>%
+# separate(species0, sep="_", into=c("Gen", "Spe")) %>%
+# mutate(Gen=substr(Gen, 1, 3)) %>%
+# mutate(Spe=substr(Spe, 1, 3)) %>%
+# mutate(labels=paste(Gen, Spe, sep="_"))
+#
+# tmp <- fix.duplicate.labels(tmp)
+#
+#
+# RDA1_2.sp <- basemap0 %+% tmp +
+# geom_text(aes(x=RDA1, y=RDA2, label=labels), size=2, alpha=0.8) +
+# geom_segment(data=myvectors.rda%>%
+# filter(categorical==0),
+# aes(x=0, xend=RDA1, y=0, yend=RDA2, col=mycol),
+# arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
+# geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
+# geom_label_repel(data=myvectors.rda,
+# aes(x=RDA1, y=RDA2, label=mylab, col=mycol, fontface=fontface0), size=2,
+# position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
+# xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
+# ylab(paste("RDA2 (", varexpl[2], "%)", sep=""))
+#
+# RDA1_3.sp <- basemap0 %+% tmp +
+# geom_text(aes(x=RDA1, y=RDA3, label=labels), size=2, alpha=0.8) +
+# geom_segment(data=myvectors.rda%>%
+# filter(categorical==0),
+# aes(x=0, xend=RDA1, y=0, yend=RDA3, col=mycol),
+# arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
+# geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
+# geom_label_repel(data=myvectors.rda,
+# aes(x=RDA1, y=RDA3, label=mylab, col=mycol, fontface=fontface0), size=2,
+# position = position_dodge(1), segment.alpha=0.8, segment.colour=gray(0.7), segment.size = 0.5) +
+# xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
+# ylab(paste("RDA3 (", varexpl[3], "%)", sep=""))
+#
+#
+# ggsave("_pics/Fig6v2a_RDA_Beals_1-2_wSpecies.png", width=8, height=8, dpi=300, RDA1_2.sp)
+# ggsave("_pics/Fig6v2b_RDA_Beals_1-3_wSpecies.png", width=8, height=8, dpi=300, RDA1_3.sp)
+#
--
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