#####################################################
# Marco FW Gauger
# 2021/08/23
#
# This is the script to obtain tab S 2 of supplemental material of the manuscript submitted to PeerJ Gauger et al 2021 Diel influences on bottlenose dolphin acoustic detection in a coastal lagoon in the southwestern Gulf of California
#####################################################

ifelse("mgcv" %in% rownames(installed.packages()) == FALSE, 
       install.packages("mgcv", dependencies = T),
       ("mgcv is already installed"))
ifelse("broom" %in% rownames(installed.packages()) == FALSE, 
       install.packages("broom", dependencies = T),
       ("broom is already installed"))

require(mgcv)
require(broom)

Sys.setlocale("LC_ALL","English")
#Sys.setenv(TZ='UTC')

analysed_data_hour <- read.csv("Supplemental Data S1.csv", sep=";")
analysed_data_hour$cluster_hcpc <- as.factor(analysed_data_hour$cluster_hcpc)

dp10m_mod_cluster_I_h <-
  gam(dp10m_ELAP1~ 
        s(lunar_phase, bs="cc") + 
        te(derivate_tide, tide, bs=c("tp","tp"),
           k=c(10,10)) + 
        s(SST, k=10, bs="tp") +
        s(h, by= cluster_hcpc,  bs="cc") + 
        effort +
        s(depth, k=4) +
        s(distance_BLAP, k=4)+
        s(cluster_hcpc, bs="re"),
      data=analysed_data_hour, method="REML",family="poisson",
      knots=list(h = c(0,24)))

table1 <- as.data.frame(cbind(cbind(unlist(summary(dp10m_mod_cluster_I_h)[c(1)])),cbind(unlist(summary(dp10m_mod_cluster_I_h)[c(2)])[1:2]),cbind(unlist(summary(dp10m_mod_cluster_I_h)[c(3)])),cbind(unlist(summary(dp10m_mod_cluster_I_h)[c(4)]))))
table2 <- as.data.frame(tidy(dp10m_mod_cluster_I_h))

table <- 
  as.data.frame(cbind(c("coefficients","intercept","effort","smooth",table2[,1]),
               rbind(c("estimation",	"error est.",	"t",	"p")	,
      rbind(formatC(as.matrix(table1), format="fg",digits=3), 
      c("edf",	"Redf",	"ChiČ",	"p"),	
      formatC(as.matrix(table2[,2:5]), format="fg",digits=3)))))
colnames(table) <- rep("", 5)

table$significance <- as.character(rep("", nrow(table)))
table$significance[as.character(table[,5]) < 0.05]  <- "*"
table$significance[as.character(table[,5]) < 0.01]  <- "**"
table$significance[as.character(table[,5]) < 0.001] <- "***"
table$significance[table[,5] =="p"] <- "significance"
row.names(table) <- table[,1] 
colnames(table) <- "" 
(table <- table[,2:6])

write.csv(table, "clipboard", sep=";")