Temp Scripts/WorkedExampleForReadMe.R

In SOLV-Code/SPATFunctions-Package: Functions for the Salmon Pattern Analysis Tool

## SCRIPT TO TEST THE PACKAGE FUNCTIONS

library(SPATFunctions)

# Note: using built-in data set of environmental covariates
head(SPATData_EnvCov)

# Calculate correlation matrix of raw data (excluding first column with years)
M <- calcCorrMatrix(SPATData_EnvCov[,-1])
head(M$cor.mat)

# plot correlation matrix
plotCorrMatrix(M$cor.mat) # original order of variables
plotCorrMatrix(M$cor.mat,order="clustered",n.groups=4)  # clustered by correlation
plotCorrMatrix(M$cor.mat,order="clustered",n.groups=round(dim(M$cor.mat)[1]/3))
round(dim(M$cor.mat)[1]/3)

plotCorrMatrix(M$cor.mat,order="clustered",n.groups=4,plot.type = "color")
plotCorrMatrix(M$cor.mat,order="clustered",n.groups=4,plot.type = "number")
plotCorrMatrix(M$cor.mat,order="clustered",n.groups=4,plot.type = "circle")


# repeat, with modified data:
# - shift (offset) the pdo variable by 2 years (just as an illustration, this is not meaningful)
# - transform all variables to z-score (i.e. normalize)
head(SPATData_EnvCov)
data.shifted <- shiftSeries(SPATData_EnvCov, offsets=c(0,0,0,0,0,0,0,0,0,0,0,0,-2,0,0,rep(0,18)))
head(data.shifted)
data.z <- transformData(data.shifted,type="z-score",
                       cols=names(data.shifted)[names(data.shifted)!="yr"],
                       zero.convert = NA )
head(data.z)
M.z <- calcCorrMatrix(data.z[,-1])
plotCorrMatrix(M.z$cor.mat) # original order of variables
plotCorrMatrix(M.z$cor.mat,order="hclust",n.groups=4)


# pairwise correlations (cumulative and by time window)

vars.test <- c("EC_jflow","EC_pdo")

plotPair(SPATData_EnvCov[,c("yr",vars.test)],layout = "single")
plotPair(data.z[,c("yr",vars.test)],layout = "2panels")


running.corr <- comPair(SPATData_EnvCov[,c("yr",vars.test)],
                        window = 12,plot.type="print")
running.corr

running.corr.z <- comPair(data.z[,c("yr",vars.test)],
                        window = 12,plot.type="print")
running.corr.z


running.corr.z <- comPair(data.z[,c("yr",vars.test)],
                          window = 12,plot.type="shiny")
print(running.corr.z$plot)




# plotly testing
library(plotly)


dim(drop_na(SPATData_EnvCov))

test <- plotPair(SPATData_EnvCov[,c("yr",vars.test)],layout = "single",plot.type = "shiny")
print(test)

plotPair(SPATData_EnvCov[,c("yr",vars.test)],layout = "2panels",plot.type = "shiny")

plotPair(SPATData_EnvCov[,c("yr",vars.test)],layout = "2axes",plot.type = "shiny")



####################
group.out <- plotGroup(SPATData_EnvCov[,1:5],agg.idx="median",plot.type="print")
names(group.out)

group.out <- plotGroup(SPATData_EnvCov[,1:5],agg.idx="mean",plot.type="shiny")
names(group.out)
group.out$plot
group.out$agg.idx

group.out <- plotGroup(SPATData_EnvCov[,1:5],agg.idx="none",plot.type="shiny")
names(group.out)
group.out$plot
group.out$agg.idx

group.out <- plotGroup(SPATData_EnvCov[,1:5],agg.idx="mean",plot.type="shiny",idx.label = "Mean1to5")
names(group.out)
group.out$plot
group.out$agg.idx





##################
# OTHER PLOTS


plotBoxes(list.in = list(Var1 = rnorm(200,100,1),Var2 = rnorm(200,0.5,3)))



tmp.dat <- SPATData_EnvCov %>% select(RpEff_ESum_Gate,RpEff_ESum_Nadi)


scatter.spark <- function(x,y){
  par(new = TRUE)
x.vec <- unlist(x)
y.vec <- unlist(y)

plot(x.vec,y.vec,bty="n",axes=FALSE,pch=21,col="darkblue",xlab="",ylab="",cex=0.8,bty="n")
abline(lm(y.vec~x.vec),col="red")

}

scatter.spark(tmp.dat[1],tmp.dat[2])



scatter.spark2 <- function(x,y){
  par(new = TRUE)
  x.vec <- unlist(x)
  y.vec <- unlist(y)

  plot(x.vec,y.vec,bty="n",axes=FALSE,type="n",bty="n")
  abline(lm(y.vec~x.vec),col="red",lwd=3)

}


dens.spark <- function(x){
par(new = TRUE)
dens <- density(unlist(x),na.rm=TRUE)

plot(dens$x,dens$y,type="l",col="darkblue")
#lines(dens$x,dens$y,type="l",col="white")
}


dens.spark(tmp.dat[1])




pairs(tmp.dat,
lower.panel = scatter.spark  ,
upper.panel	= scatter.spark2,
diag.panel = dens.spark
)




plotSPLOM(SPATData_EnvCov[,2:5])


library(SPATFunctions)

test <- plotRanked(log(SPATData_EnvCov[,16:33]),trim = 5,maxvars=NULL,flag=names(SPATData_EnvCov)[19])

test


test <- plotRanked(log(SPATData_EnvCov[,2:5]),trim = 7,maxvars=NULL,flag=names(SPATData_EnvCov)[19])
test






plotScatter(SPATData_EnvCov[,c(1,3,4)], labels = NULL, colors = "fade",recent.window = 10)





######################
library(devtools)