package_test.R

In Pacific-salmon-assess/WSP-Metrics-Pkg: WSPMetrics Package: R package to calculate and use metrics for status assessments under Canada's Wild Salmon Policy (WSP)

library(tidyverse)
library(WSPMetrics)
library(R2jags)


#ls(getNamespace("MetricsTest"), all.names=TRUE)


# TEST LONG-TERM TREND  AND PERC CHANGE - Simple versions for single vector from example Data. Perc change calculated over entire time period.

lt.trend.single <- calcLongTermTrendSimple(vec.in = exampleData$Stock1 ,
            gen.in = 4,min.lt.yrs = 20, avg.type = "geomean",
            tracing=FALSE,
            recent.excl = FALSE)

lt.trend.single

calcPercChangeSimple(vec.in = exampleData$Stock1)
calcPercChangeSimple(vec.in = exampleData$Stock2)
calcPercChangeSimple(vec.in = exampleData$Stock3)



# TEST LONG-TERM TREND AND PERC CHANGE - data frame version. Perc change calculated over 3 generations


lt.trend <- calcLongTermTrend(X = exampleData,gen.in = 4, recent.num.gen = 1, extra.yrs = 0,
                               min.yrs.used = 20, avg.type = "geomean", tracing=FALSE,
                               recent.excl = FALSE)

lt.trend

perc.change <- calcPercChange(X = exampleData,gen.in = 4,
                  slope.num.gen = 3, extra.yrs = 0,
                  genmean.smoothing = TRUE,
                  log.transform = TRUE,
                  out.exp = TRUE, tracing=FALSE)

perc.change



# TEST BAYESIAN PERC CHANGE

pdf("ProbDecl_Fits.pdf",onefile=TRUE,height=8.5, width=11)

# Smooth the first 15 years of the Example Data- Stock1
vec.use <- smoothSeries(exampleData[1:15,1], gen=4, filter.sides=1, log.transform = TRUE, out.exp = TRUE,na.rm=FALSE)
vec.use <- vec.use[4:15] # Removing intial NAs

slope.mcmc.fit <- calcPercChangeMCMC(vec.in= vec.use,model.in = NULL ,
                                     perc.change.bm = -25 , na.skip=FALSE,
                                     out.type = "long", mcmc.plots = TRUE)
dev.off()

names(slope.mcmc.fit)
slope.mcmc.fit$pchange
slope.mcmc.fit$probdecl
slope.mcmc.fit$summary







###########
?calcLongTermTrendSimple


#################
# Testing Manual Generation


library(devtools)

setwd("../") # have to be outside the package folder

build_manual(pkg = "WSP-Metrics-Pkg") # takes a while (first time only? installs some stuff)

setwd("WSP-Metrics-Pkg") # move back into pkg folder




########################
# testing NA fix

test.vec <- c(1,2,3,4,5,NA,NA,-Inf,0,8,9)
test.vec


inf.idx <- !is.finite(test.vec)
inf.idx
inf.idx[is.na(inf.idx)] <- FALSE



######################
# Testing calcMetrics()

head(exampleData)

yrs.vec <- 1:length(exampleData$Stock1) + 1979 # if your data doesn't have yrs, need to generate a yr vector

plot(yrs.vec, exampleData$Stock1,type="o")



test.out <- calcMetrics (  series.in = exampleData$Stock1 , # vector of values
                          yrs.in  = yrs.vec,
                          gen.in = 4, # avg generation time
                          stk.label = "Stock 1", # used for labeling output
                          species.label = "Species", # used for labeling output
                          series.label = "DataVersion", # used for labeling output
                          slope.specs = list(num.gen = 3, extra.yrs = 0,filter.sides=1, slope.smooth=TRUE,
                                             log.transform = TRUE, out.exp = TRUE,na.rm=FALSE),
                          avg.specs = list(avg.type = "geomean",recent.excl=FALSE,
                                           lt.smooth=TRUE, rel.avg.type="regular",
                                           min.lt.yrs =20,min.perc.yrs =20),
                          metric.bm =  list(RelAbd = c(30,50),   # set these at arbitrary numbers for the illustration
                                            AbsAbd = c(1000,10000),
                                            LongTrend = c(0.5,0.75),
                                            PercChange = c(-25,-15),
                                            ProbDeclBelowLBM = c(NA,NA),
                                            Percentile = c(0.25,0.5)),
                          retro.start = NULL,
                          tracing = TRUE)



head(test.out)