R/app.R
In saulitalja/RR:
Defines functions
Sensitivity
Sensitivity_fractiles
Probability_of_freedom_iterations
Probability_of_freedom_fractiles
Plot_SSe_country
Plot_Pfree_country
Plot_SSe_regions
Plot_Pfree_regions
help_dl_figs
help_pert
help_csv_N_w
help_csv_n_w
help_csv_N_M
help_csv_n_M
help_csv_host_area
help_csv_entry_sites
help_PriorPfree
help_Pinv
help_n_i
help_TSe_w
help_TSe_M
help_site_w
help_site_M
help_n_w
help_n_M
help_entry_sites
help_host_area
help_d_w
help_d_M
help_survey_type
help_localDP_ie
help_localDP_ed
help_globalDP
help_max_inf_size
server
library(shiny)
library(shinythemes) # Theme
library(magrittr) # IS THIS NEEDED?
library(shinyhelper) # Pop up helps
library(ggplot2) # Plotting
library(mc2d) # Pert- probability distribution
library(ipc) # Asyc computing
library(promises) # Asyc computing
library(future) # Asyc computing
plan(multiprocess) # Asyc computing
#source("functions.R")
###################################################
# A function that calculates the sensitivities of annual surveys
Sensitivity <- function(N_wood, n_wood, p_wood, TSe_wood,
N_Monochamus, n_Monochamus, p_Monochamus, TSe_Monochamus,
Pop_data, RP, DPr_adj,
scenario, DP_wood, DP_Monochamus, DPr, max_inf_size,
n_r, n_y, n_i){
#####
# CALCULATING INSPECTION SENSITIVITY
# Deciding whether to use binomial or hypergeometric distribution
# (Binomial is appropriate when the sample size is less than 10% of the total population size)
if(max(n_wood)/min(p_wood) < 0.1){
ISe_wood = 1 - (1 - (DP_wood*TSe_wood))^n_wood
}else{
ISe_wood = 1 - (1 - ((n_wood*TSe_wood)/(p_wood - 0.5*(p_wood*DP_wood*TSe_wood-1))))^(p_wood*DP_wood)
}
if(max(n_Monochamus)/min(p_Monochamus) < 0.1){
ISe_Monochamus = 1 - (1 - (DP_Monochamus*TSe_Monochamus))^n_Monochamus
}else{
ISe_Monochamus = 1 - (1 - ((n_Monochamus*TSe_Monochamus)/(p_Monochamus - 0.5*(p_Monochamus*DP_Monochamus*TSe_Monochamus-1))))^(p_Monochamus*DP_Monochamus)
}
#####
# CALCULATING THE SENSITIVITY OF ANNUAL SURVEYS IN THE REGIONS
# (Separately for wood sampling and Monochamus trapping)
# Deciding whether to use binomial or hypergeometric distribution
if(max(N_wood)/min(Pop_data) < 0.1){
GSe_wood = 1 - (1 - (DPr_adj*ISe_wood))^N_wood
}else{
GSe_wood = 1 - (1 - ((N_wood*ISe_wood)/(Pop_data - 0.5*(Pop_data*DPr_adj*ISe_wood-1))))^(Pop_data*DPr_adj)
}
if(max(N_Monochamus)/min(Pop_data) < 0.1){
GSe_Monochamus = 1 - (1 - (DPr_adj*ISe_Monochamus))^N_Monochamus
}else{
GSe_Monochamus = 1 - (1 - ((N_Monochamus*ISe_Monochamus)/(Pop_data - 0.5*(Pop_data*DPr_adj*ISe_Monochamus-1))))^(Pop_data*DPr_adj)
}
#####
# CALCULATING THE SENSITIVITY OF ANNUAL SURVEYS IN THE REGIONS AND IN FINLAND
# (Wood sampling and Monochamus trapping combined)
# Arrays for storing the results
# w = wood, m = Monochamus, wm = wood and Monochamus
GSe_wm <- array(0,dim=c(n_y,(n_r-1),n_i))
SSe_w_FI <- array(0,dim=c(n_y,n_i))
SSe_m_FI <- array(0,dim=c(n_y,n_i))
SSe_wm_FI <- array(0,dim=c(n_y,n_i))
for (k in 1:n_i){
for(t in 1:n_y){
# Regions
GSe_wm[t,,k] = 1 - (1-GSe_wood[t,,k])*(1-GSe_Monochamus[t,,k])
# Finland
# Import-export
if(scenario == 1){
SSe_w_FI[t,k] = 1 - prod(1-GSe_wood[t,,k])
SSe_m_FI[t,k] = 1 - prod(1-GSe_Monochamus[t,,k])
SSe_wm_FI[t,k] = 1 - (1-SSe_w_FI[t,k])*(1-SSe_m_FI[t,k])
# Early detection
}else{
SSe_wm_FI[t,k] = sum(GSe_wm[t,,k]*RP[t,,k])
}
}
}
#####
# ALL THE RESULTS IN ONE ARRAY
# Regions in columns 1-(n_r-1), Finland in column n_r
Sensitivity_all <- array(0,dim=c(n_y,n_r,n_i))
Sensitivity_all[,1:(n_r-1),] = GSe_wm
Sensitivity_all[,n_r,] = SSe_wm_FI
return(Sensitivity_all)}
######################################################
# A function that returns the 2.5, 50 and 97.5% fractiles of the senitivity of annual surveys
Sensitivity_fractiles <- function(Sensitivity_all,n_r,n_y){
# Matrixes for storing the results
Se_2.5 <- matrix(0,n_y,n_r)
Se_50 <- matrix(0,n_y,n_r)
Se_97.5 <- matrix(0,n_y,n_r)
for(i in 1:n_y){
for(j in 1:n_r){
Se_2.5[i,j] = quantile(Sensitivity_all[i,j,],0.025)
Se_50[i,j] = quantile(Sensitivity_all[i,j,],0.5)
Se_97.5[i,j] = quantile(Sensitivity_all[i,j,],0.975)
}
}
# All the results in one array
Se_all <- array(0,dim=c(n_y,n_r,3))
Se_all[,,1] = Se_2.5
Se_all[,,2] = Se_50
Se_all[,,3] = Se_97.5
return(Se_all)}
#####################################################
# A function that returns the probability of freedom after the last survey
Probability_of_freedom_iterations <- function(progressMonitor1=function(h) cat("."),
progressMonitor2=function(h) cat("."),
N_wood, n_wood, p_wood, TSe_wood,
N_Monochamus, n_Monochamus, p_Monochamus, TSe_Monochamus,
Pop_data, RP, DPr_adj,
scenario, DP_wood, DP_Monochamus, DPr, max_inf_size,
Pinv_FI, PrioPfree_1,
n_r, n_y, n_i){
##########
# ARRAYS FOR STORING RESULTS
# w = wood, m = Monochamus, wm = wood and Monochamus
GSe_wm <-array(0,dim=c(n_y,(n_r-1),n_i))
SSe_w_FI <-array(0,dim=c(n_y,n_i))
SSe_m_FI <-array(0,dim=c(n_y,n_i))
SSe_wm_FI <-array(0,dim=c(n_y,n_i))
Pfree_w <-array(0,dim=c(n_y,(n_r-1),n_i))
Pfree_wm <-array(0,dim=c(n_y,(n_r-1),n_i))
Pfree_adj <-array(0,dim=c(n_y,(n_r-1),n_i))
Pfree_w_FI <-array(0,dim=c(n_y,n_i))
Pfree_wm_FI <-array(0,dim=c(n_y,n_i))
Pfree_adj_FI <-array(0,dim=c(n_y,n_i))
Pfree_all <- array(0,dim=c(length(Pinv_FI),n_r,n_i))
##########
# CALCULATING INSPECTION SENSITIVITY
# Deciding whether to use binomial or hypergeometric distribution
# (Binomial is appropriate when the sample size is less than 10% of the total population size)
if(max(n_wood)/min(p_wood) < 0.1){
ISe_wood = 1 - (1 - (DP_wood*TSe_wood))^n_wood
}else{
ISe_wood = 1 - (1 - ((n_wood*TSe_wood)/(p_wood - 0.5*(p_wood*DP_wood*TSe_wood-1))))^(p_wood*DP_wood)
}
if(max(n_Monochamus)/min(p_Monochamus) < 0.1){
ISe_Monochamus = 1 - (1 - (DP_Monochamus*TSe_Monochamus))^n_Monochamus
}else{
ISe_Monochamus = 1 - (1 - ((n_Monochamus*TSe_Monochamus)/(p_Monochamus - 0.5*(p_Monochamus*DP_Monochamus*TSe_Monochamus-1))))^(p_Monochamus*DP_Monochamus)
}
#####
# CALCULATING THE SENSITIVITY OF ANNUAL SURVEYS IN THE REGIONS
# (Separately for wood sampling and Monochamus trapping)
# Deciding whether to use binomial or hypergeometric distribution
if(max(N_wood)/min(Pop_data) < 0.1){
GSe_wood = 1 - (1 - (DPr_adj*ISe_wood))^N_wood
}else{
GSe_wood = 1 - (1 - ((N_wood*ISe_wood)/(Pop_data - 0.5*(Pop_data*DPr_adj*ISe_wood-1))))^(Pop_data*DPr_adj)
}
if(max(N_Monochamus)/min(Pop_data) < 0.1){
GSe_Monochamus = 1 - (1 - (DPr_adj*ISe_Monochamus))^N_Monochamus
}else{
GSe_Monochamus = 1 - (1 - ((N_Monochamus*ISe_Monochamus)/(Pop_data - 0.5*(Pop_data*DPr_adj*ISe_Monochamus-1))))^(Pop_data*DPr_adj)
}
#########
# CALCULATING THE SENSITIVITY OF ANNUAL SURVEYS IN THE REGIONS AND COUNTRY
# (Wood sampling and Monochamus trapping combined)
for (k in 1:n_i){
for(t in 1:n_y){
# Regions
GSe_wm[t,,k] = 1 - (1-GSe_wood[t,,k])*(1-GSe_Monochamus[t,,k])
# Finland
# Import-export
if(scenario == 1){
SSe_w_FI[t,k] = 1 - prod(1-GSe_wood[t,,k])
SSe_m_FI[t,k] = 1 - prod(1-GSe_Monochamus[t,,k])
SSe_wm_FI[t,k] = 1 - (1-SSe_w_FI[t,k])*(1-SSe_m_FI[t,k])
# Early detection
}else{
SSe_wm_FI[t,k] = sum(GSe_wm[t,,k]*RP[t,,k])
}
}
}
# CALCULATING THE PROBABILITY OF FREEDOM
for (h in 1:length(Pinv_FI)){
progressMonitor1(h)
progress$set(value = (h/length(Pinv_FI))*100)
Pinv_country = Pinv_FI[h]
# The probability of invasion in the regions
Pinv_regions = RP*Pinv_country
for(t in 1:n_y){
if(t==1){
# Probability of freedom, Finland
Pfree_wm_FI[t,] = PrioPfree_1 / (PrioPfree_1 + ((1-PrioPfree_1)*(1-SSe_wm_FI[t,])))
# Adjusted probability of freedom, Finland
Pfree_adj_FI[t,] = 1 - ( (1-Pfree_wm_FI[t,]) + Pinv_country - ((1-Pfree_wm_FI[t,])*Pinv_country) )
# Probability of freedom, Regions
Pfree_w[t,,] = PrioPfree_1 / (PrioPfree_1 + ((1-PrioPfree_1)*(1-GSe_wood[t,,])))
Pfree_wm[t,,] = Pfree_w[t,,] / (Pfree_w[t,,] + ((1-Pfree_w[t,,])*(1-GSe_Monochamus[t,,])))
# Adjusted probability of freedom, Regions
Pfree_adj[t,,] = 1 - ( (1-Pfree_wm[t,,]) + Pinv_regions[t,,] - ((1-Pfree_wm[t,,])*Pinv_regions[t,,]) )
}else{
# Probability of freedom, Finland
Pfree_wm_FI[t,] = Pfree_adj_FI[t-1,] / (Pfree_adj_FI[t-1,] + ((1-Pfree_adj_FI[t-1,])*(1-SSe_wm_FI[t,])))
# Adjusted probability of freedom, Finland
Pfree_adj_FI[t,] = 1 - ( (1-Pfree_wm_FI[t,]) + Pinv_country - ((1-Pfree_wm_FI[t,])*Pinv_country) )
# Probability of freedom, Regions
Pfree_w[t,,] = Pfree_adj[t-1,,] / (Pfree_adj[t-1,,] + ((1-Pfree_adj[t-1,,])*(1-GSe_wood [t,,])))
Pfree_wm[t,,] = Pfree_w[t,,] / (Pfree_w[t,,] + ((1-Pfree_w[t,,])*(1-GSe_Monochamus[t,,])))
# Adjusted probability of freedom, Regions
Pfree_adj[t,,] = 1 - ( (1-Pfree_wm[t,,]) + Pinv_regions[t,,] - ((1-Pfree_wm[t,,])*Pinv_regions[t,,]) )
}
}
##########
# RETURN ALL THE RESULTS IN ONE ARRAY
Pfree_all[h,1:(n_r-1),] = Pfree_wm[n_y,,]
Pfree_all[h,n_r,] = Pfree_wm_FI[n_y,]
}
#inter$destroy()
#plan(sequential)
return(Pfree_all)}
######################################################
# A function that returns tha 2.5, 50 and 97.5% fractiles of the porbability of freedom after the last survey
Probability_of_freedom_fractiles <- function(Pfree_all,Pinv_FI,n_r,n_y){
# Matrix for storing the results
PF_all <- array(0,dim=c(length(Pinv_FI),n_r,3))
for(i in 1:length(Pinv_FI)){
for(j in 1:n_r){
PF_all[i,j,1] = quantile(Pfree_all[i,j,],0.025)
PF_all[i,j,2] = quantile(Pfree_all[i,j,],0.5)
PF_all[i,j,3] = quantile(Pfree_all[i,j,],0.975)
}
}
return(PF_all)}
############################################################
# FIGURES FOR THE TAB "RESULTS"
##########
# FIGURE SSe - Country
Plot_SSe_country <- function(Y,SSe,n_r){
plot(Y,SSe[,n_r,2],
type = "p",
ylim=c(0.00,1.00),
xlab = "Years",
ylab = "Sensitivity")
arrows(Y, SSe[,n_r,1], Y, SSe[,n_r,3], length=0.01, angle=90, code=3)
}
##########
# FIGURE Pfree - Country
Plot_Pfree_country <- function(Finv_FI,Pfree,n_r){
plot(Finv_FI,Pfree[,n_r,1],
type = 'l',col = 'grey',
ylim=c(0.00,1.00),
xlab = "Mean time between invasions, years",
ylab = "Probability of freedom")
lines(Finv_FI, Pfree[,n_r,3], col='grey')
polygon(c(Finv_FI,rev(Finv_FI)), c(Pfree[,n_r,1], rev(Pfree[,n_r,3])), col='grey', border=NA)
}
##########
# FIGURE SSe - Regoins
Plot_SSe_regions <- function(Y,SSe,regions){
n_regions = length(regions)
par(mfrow=c(ceiling(n_regions/3),3))
par(pin=c(2,4))
par(mar=c(2,2,2,2))
par(mgp=c(0.5,0.75,0))
par(oma=c(2.5,3,2,1))
SetLine<--9
TitleSize<- 1
AxisSize<- 1.2
Xlabels<-seq(Y[1],Y[length(Y)],2)
Ylabels<- seq(0,1,0.2)
for(i in 1:n_regions){
plot(Y, SSe[,i,2], type = "p", pch=16, frame.plot=FALSE, ylim=c(0,1), axes=FALSE, xlab="", ylab="",main=regions[i])
arrows(Y, SSe[,i,1], Y, SSe[,i,3], length=0.01, angle=90, code=3)
title(line=SetLine, cex.main=TitleSize)
axis(side=1, at=Xlabels, labels=Xlabels, cex.axis=AxisSize)
axis(side=2, at=Ylabels, labels=Ylabels, las=1, cex.axis=AxisSize)
}
mtext('Year', side=1, outer=TRUE, line=1)
mtext('Sensitivity', side=2, outer=TRUE, line=1.5)
}
##########
# FIGURE Pfree - Regions
Plot_Pfree_regions <- function(Finv_FI,Pfree,regions){
n_regions = length(regions)
par(mfrow=c(ceiling(n_regions/3),3))
par(pin=c(2,4))
par(mar=c(2,2,2,2))
par(mgp=c(0.5,0.75,0))
par(oma=c(2.5,3,2,1))
SetLine<--9
TitleSize<-1
AxisSize<-1.2
Xlabels<-seq(0,Finv_FI[length(Finv_FI)],10)
Ylabels<-c(0.00,0.20,0.40,0.60,0.80,1.00)
for(i in 1:n_regions){
plot(Finv_FI, Pfree[,i,1], type="l", col="grey", frame.plot=FALSE,
ylim=c(0,1), xlim=c(Finv_FI[1],Finv_FI[length(Finv_FI)]),
axes=FALSE, xlab="", ylab="",main=regions[i])
lines(Finv_FI, Pfree[,i,3], col="grey")
polygon(c(Finv_FI,rev(Finv_FI)), c(Pfree[,i,1], rev(Pfree[,i,3])), col="grey", border=NA)
title(line=SetLine, cex.main=TitleSize)
axis(side=1, at=Xlabels, labels=Xlabels, cex.axis=AxisSize)
axis(side=2, at=Ylabels, labels=Ylabels, las=1, cex.axis=AxisSize)
}
mtext('The mean time between invasions to the country, years', side=1, outer=TRUE, line=1.2)
mtext('The probability of freedom', side=2, outer=TRUE, line=1.5)
}
###############################################
# HELP TEXTS FOR THE POP UP WINDOWS
help_dl_figs <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Choose a figure",
content = c("Note that the same figure cannot be downloaded and/or viewed twice in a row.
If you need to download and/or view the same figure more than once, you need
to select another figure in between the two downloads/views."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_pert <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Estimate as a probability distribution",
content = c("If the exact value of the parameter is not known or if it varies,
the parameter value can be defined as a Pert probability distribution.",
"",
"First, the minimum, maximum and mode of the parameter should be set.
Then, lambda should be defined such that the resulting probability distribution
reflects the uncertainty or the variation of the parameter value. Lambda
takes positive values and the greater its value the more
peaked is the probability distribution.",
"",
"If the exact value of the parameter is known, minimum, maximum and
mode should all be set to that known value. In this special case,
lambda must also be defined, but it can be given any value,
as it has no effect on the outcome."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_N_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"For the regions and/or years in which no survey was done, the number of inspected
sites should be zero.",
"",
"The data for the Finnish PWN surveys is in the file
1.1_N_inspected_sites_wood_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_n_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"For the regions and/or years in which no survey was done, the number of samples per
inspected site should be zero."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_N_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"For the regions and/or years in which no survey was done,
the number of inspected sites should be zero.",
"",
"The data for the Finnish PWN surveys is in the file
1.2_N_inspected_sites_Monochamus_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_n_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files and
the years should always be in ascending order.",
"",
"For the regions and/or years in which no survey was done, the number of samples per
inspected site should be zero.",
"",
"The data for the Finnish PWN surveys is in the file
1.2_n_samples_per_inspected_site_Monochamus_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_host_area <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"Even if the the area with host plants was the same for all or some of the years,
data should be given for all the considered years separately.",
"",
"The data for the Finnish PWN surveys is in the file
1.3_Area_with_host_plants_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_entry_sites <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"Even if the area of entry sites was the same for all or some of the years,
data should be given for all the considered years separately.",
"",
"The data for the Finnish PWN surveys is in the file
1.4_Area_of_entry_sites_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_PriorPfree <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Initial prior probability of freedom",
content = c("This determines the probability of freedom before the first survey.",
"",
"If no information is available about the presence/absence of PWN before
the surveys were started, the initial prior probability of freedom can be set to 0.5.",
"",
"The initial prior probability of freedom should be in line with the probability of invasion,
unless reason exists to assume that the probability of invasion was different before
the surveys were initiated. (I.e., if the probability of invasion is assumed to be high,
assuming the initial prior probability of freedom is low is not logical, and vice versa.)",
"",
"It should be noted that if the sensitivity of the annual surveys is low, even a
seemingly uninformative initial prior probability of freedom (0.5)
can have an impact on the probability of freedom for several years."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_Pinv <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Mean time between invasions",
content = c("This is the mean time
between events in which PWN enters the country,
is transferred to a host plant and manages to establish there.",
"",
"If information or estimates about the mean time between invasions are not available,
the considered range can be as wide as needed."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_n_i <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Number of iterations",
content = c("This determines the number of iterations for the Monte Carlo simulation used in the assessment.",
"",
"For preliminary runs, a small number (<1000) is suitable.
For the final assessment, 10 000 iterations are recommended.",
"",
"When the number of iterations is high, computation can take several
minutes, especially if a wide range of mean time between invasions is considered."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_TSe_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Test sensitivity",
content = c("Test sensitivity is the probability that the pest is detected
in the laboratory analysis, given that it was present in the
wood object(s) included in the sample.",
"",
"Test sensitivity is always less than one. But, if inspection site level
design prevalence is determined as apparent design prevalence,
test sensitivity should be set to one."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_TSe_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Test sensitivity",
content = c("Test sensitivity is the probability that the pest is detected
in the laboratory analysis, given that it was present in the Monochamus
beetle(s) included in the sample.",
"",
"Test sensitivity is always less than one. But, if inspection site level
design prevalence is determined as apparent design prevalence,
test sensitivity should be set to one."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_site_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The size of inspection site",
content = c("This is the area covered by one inspection as square kilometers.",
"",
"The size of inspection site should be such that the number of infested
wood objects per inspection site at the inspection site level design
prevalence would be at least one. "),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_site_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The size of inspection site",
content = c("This is the area covered by one inspection as square kilometers.",
"",
"The size of inspection site should be such that the number of infested
Monochamus adults per inspection site at the inspection site level design
prevalence would be at least one. "),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_n_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The number of wood objects sampled per inspected site",
content = c("This is the number of wood objects from which material was taken for
laboratory analysis per inspected site, irrespective of whether
the material from all the objects was pooled or analyzed separately."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_n_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The number of Monochamus sampled per inspected site",
content = c("This is the number of Monochamus collected for laboratory analysis
per inspected site, irrespective of whether all the beetles
were pooled or analyzed separately."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_entry_sites <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The area of entry sites",
content = c("This is the area of sites in with elevated probability of PWN introduction,
i.e. harbors, industrial areas and landfills, in square kilometers."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_host_area <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The area with host plants",
content = c("This is the area with PWN host plants within the area for which the results
of the surveys will be generalized, in square kilometers."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_d_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The density of wood objects suitable for sampling",
content = c("This is the number of wood objects suitable for
sampling per square kilometer in the area for which
the results of the survey will be generalized."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_d_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The density of adult Monochamus beetles",
content = c("This is the number of adult Monochamus beetles per
square kilometer in the area for which the results
of the survey will be generalized."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_survey_type <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The aim of the surveys",
content = c("The first option is referred to as import-export survey and the latter as early detection survey.
The pest populations that these two survey types aim to detect differ in two respects.",
"",
"First, for import-export surveys, PWN infestation is expected to be randomly distributed throughout
the country, while for early detection surveys, PWN infestation is expected to be restricted to one region.",
"",
"Second, the design prevalences of import-export surveys can be based merely on what is required
to facilitate trade, while those of early detection surveys should
be defined based on the size of an eradicable PWN population."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_localDP_ie <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Inspection site level design prevalence",
content = c("Inspection site level design prevalence is determined as the proportion
of PWN-infested wood objects of all wood objects suitable for sampling,
and the proportion of PWN-infested Monochamus adults of all Monochamus adults.",
"",
"Design prevalence should be such that PWN could reach it, at least at some point
in time, if it was established in the considered area. Additionally, it
must be such that it corresponds to, at least, one whole infested wood object
and Monochamus adult per inspection site.",
"",
"For import-export surveys, inspection site level design prevalences can
correspond to the prevalence that established PWN populations would likely have in the considered
conditions.",
"",
"For areas where PWN is not expected to cause symptoms and where Bursaphelenchus mucronatus is
established, inspection site level design prevalence may be set equal to observed
prevalence of B. mucronatus.",
"",
"If the prevalence of B. mucronatus has been estimated with similar sampling as that done in
the PWN surveys, inspection site level design prevalence can be determined as apparent prevalence
and test sensitivity (on the tab 'Upload data and define parameter values') can be set to one."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_localDP_ed <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Inspection site level design prevalence",
content = c("Inspection site level design prevalence is determined as the proportion
of PWN-infested wood objects of all wood objects suitable for sampling,
and the proportion of PWN-infested Monochamus adults of all Monochamus adults.",
"",
"Design prevalence should be such that PWN could reach it, at least at some point
in time, if it was established in the considered area. Additionally, it
must be such that it corresponds to, at least, one whole infested wood object
and Monochamus adult per inspection site.",
"",
"For the early detection survey, inspection site level design prevalences should
preferably correspond to a PWN population that is still growing
(i.e., has not reached its maximum prevalence).",
"",
"In areas where PWN is not expected to cause symptoms and where Bursaphelenchus mucronatus
is established, inspection site level design prevalence should be lower than the prevalence of B. mucronatus.",
"",
"If the prevalence of B. mucronatus has been estimated with similar sampling as that done in
the PWN surveys, inspection site level design prevalence can be determined as apparent prevalence
and test sensitivity (on the tab 'Upload data and define parameter values') can be set to one."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_globalDP <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Country level design prevalence",
content = c("For import-export surveys, country level design prevalence is determined as the proportion of
PWN-infested area of the total area with PWN host plants in the area
for which the results of the surveys will be generalized to.",
"",
"Country level design prevalence can be based on requirements of the trading partners,
political considerations, availability of resources, and/or biological plausibility.",
"",
"Country level design prevalence must be such that PWN could reach it, at least at some
point in time, if it was established in the country. Also, it must be such that it corresponds
to, at least, the size of one whole infested inspection site."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_max_inf_size <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Maximum acceptable size of PWN infestation at detection",
content = c("For early detection surveys, region level design prevalence is defined based on
the maximum size of an eradicable PWN infestation in square kilometers.",
"",
"The maximum area from which eradication could be attempted is limited by the financial
and physical resources available for the eradication measures (e.g., the availability of
labor and machinery). If the maximum area from which eradication could be attempted can
be estimated, it may be used as a proxy for the maximum area from which eradication could be
achieved. However, it is important to keep in mind that attempting and achieving are very different
things when it comes to eradicating invasive species.",
"",
"In EU countries, the requirements of the EU emergency measures for PWN (EU 2012) can be used to guide the definition of
the maximum size of an eradicable PWN population. The measures allow EU member states to refrain from
attempting eradication of PWN if the diameter of the infested area exceeds 20 km. Hence, it is
logical to assume that in an early detection survey, PWN should be detected before the diameter of
its infestation is more than 20 km.",
"",
"The area of a PWN infestation that has a 20 km diameter depends on the shape of the area and the proportion
of the area that is covered by PWN host plants. If the infested area is circular, it is, at maximum,
314 km2. In most cases, it is much smaller due to low coverage of PWN host plants. Again, it is important
to remember that it is not at all clear if such a large infestation could be eradicated with the resources
available for delimiting the infested area and conducting the eradication measures."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
#########################################################
ui <-
navbarPage("FinnSURV-Assess PWN",
theme = shinythemes::shinytheme("united"),
tabPanel("1. Upload data and define parameter values",
withMathJax(),
tabsetPanel(
tabPanel(h5("1.1 Wood sampling"),
fluidRow(h3("")),
fluidRow(column(3,
wellPanel(h4(tags$b("The number of inspected sites")),
tags$hr(),
help_csv_N_w(),
fileInput("file_N_w","Upload a csv file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table")),
wellPanel(help_site_w(),
numericInput(inputId = "site_w",
label = "The size of inspection site, km\\(^2\\)",
value = 0.35, min = 0, max = 5, step = 0.1)),
wellPanel(
help_TSe_w(),
numericInput(inputId = "TSe_w",
label = "Test sensitivity",
value = 1, min = 0, max = 1, step = 0.01))),
column(3,wellPanel(
fluidRow(column(11,
help_n_w(),
h4(tags$b("The number of wood objects sampled per inspected site")),
tags$hr(),
radioButtons(inputId = "select_n_w_input_type",
label = "",
choices = c("Upload a csv file" = 1,
"Estimate as a probability distribution" = 2),
selected = 2),
tags$hr(),
uiOutput(outputId = "upload_n_w_data"))))),
column(3,conditionalPanel(condition = "input.select_n_w_input_type == '2'",
wellPanel(h5(tags$i("The estimated probability distribution of the number of wood objects sampled per inspected site")),
plotOutput(outputId = "n_wood", height=300), align = "center")))
),
h5(textOutput("Table_legend_N_w")),
tableOutput("table_N_w"),
conditionalPanel(condition = "input.select_n_w_input_type == '1'",
h5(textOutput("Table_legend_n_w")),
tableOutput("table_n_w"))
),
tabPanel(h5("1.2", tags$i("Monochamus"), "trapping"),
fluidRow(h3("")),
fluidRow(column(3,
wellPanel(h4(tags$b("The number of inspected sites")),
tags$hr(),
help_csv_N_M(),
fileInput("file_N_M", "Upload a csv file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table")),
wellPanel(help_site_M(),
numericInput(inputId = "site_M",
label = "The size of inspection site, km\\(^2\\)",
value = 0.25, min = 0, max = 5, step = 0.1)),
wellPanel(help_TSe_M(),
numericInput(inputId = "TSe_M",
label = "Test sensitivity",
value = 1, min = 0, max = 1, step = 0.01))
),
column(3,wellPanel(
fluidRow(column(11,
help_n_M(),
h4(tags$b("The number of", tags$i("Monochamus"), "sampled per inspected site")),
tags$hr(),
radioButtons(inputId = "select_n_M_input_type",
label = "",
choices = c("Upload a csv file" = 1, "Estimate as a probability distribution" = 2),
selected = 1),
tags$hr(),
uiOutput(outputId = "upload_n_M_data"))))),
column(3,conditionalPanel(condition = "input.select_n_M_input_type == '2'",
wellPanel(h5(tags$i("The estimated probability distribution of the number of", tags$i("Monochamus"), "sampled per inspected site")),
plotOutput(outputId = "n_Monochamus",height=300),align = "center")))
),
h5(textOutput("Table_legend_N_M")),
tableOutput("table_N_M"),
conditionalPanel(condition = "input.select_n_M_input_type == '1'",
h5(textOutput("Table_legend_n_M")),
tableOutput("table_n_M"))
),
tabPanel(h5("1.3 Target population"),
fluidRow(h3("")),
fluidRow(column(6,h4("At the level of inspection sites"), align = "center"),
column(3,h4("At the level of regions"), align = "center")),
fluidRow(column(3,
wellPanel(fluidRow(column (11,help_d_w(),
h4(tags$b("The density of wood objects suitable for sampling")),
tags$hr(),
radioButtons(inputId = "select_d_w_input_type",
label = "",
choices = c("Use the estimate from Hannunen and Tuomola (2020)" = 1, "Estimate as a probability distribution" = 2),
selected = 1),
tags$hr(),
uiOutput(outputId = "upload_d_w_data"))))),
column(3,
wellPanel(fluidRow(column(11,help_d_M(),
h4(tags$b("The density of adult", tags$i("Monochamus"), "beetles")),
tags$hr(),
radioButtons(inputId = "select_d_M_input_type",
label = "",
choices = c("Use the estimate from Hannunen and Tuomola (2020)" = 1, "Estimate as a probability distribution" = 2),
selected = 1),
tags$hr(),
uiOutput(outputId = "upload_d_M_data"))))),
column(3,
wellPanel(help_host_area(),
h4(tags$b("The area with host plants, km", tags$sup("2"))),
hr(),
help_csv_host_area(),
fileInput("file_host_area", "Upload a csv file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table")))
),
fluidRow(column(3,
wellPanel(
h5(tags$i("The estimated probability distribution of the density of wood objects suitable for sampling")),
plotOutput("d_wood", height=300), align = "center")),
column(3,
wellPanel(
h5(tags$i("The estimated probability distribution of the density of Monochamus adults")),
plotOutput("d_Monochamus", height=300), align = "center"))),
fluidRow(column(12,
h5(textOutput("Table_legend_host_area")),
tableOutput("table_host_area")))
),
tabPanel(h5("1.4 Entry sites"),
fluidRow(h3("")),
fluidRow(column(3,
wellPanel(help_entry_sites(),
h4(tags$b("The area of entry sites, km",tags$sup("2"))),
tags$hr(),
help_csv_entry_sites(),
fileInput("file_entry_sites", "Upload a csv file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table")))),
fluidRow(column(12,
h5(textOutput("Table_legend_entry_sites")),
tableOutput("table_entry_sites")))
))),
tabPanel("2. Define the aim of the survey",
fluidRow(
column(3,
wellPanel(help_survey_type(),
h4(tags$b("The aim of the surveys is")),
tags$hr(),
radioButtons(inputId = "select_survey_type",
label = "",
choices = c("to provide evidence to justify import requirements related to PWN and
to facilitate export to countries with corresponding requirements" = 1,
"to detect possible PWN invasions early enough to enable successful eradication" = 2),
selected = ""))),
column(3,
uiOutput(outputId = "localDP")),
column(3,
uiOutput(outputId = "globalDP")))),
tabPanel("3. View results",
fluidRow(column(2,
wellPanel(help_PriorPfree(),
numericInput(inputId = "Prior_Pfree",
label = "Initial prior probability of freedom",
value = 0.5, min = 0, max = 1, step = 0.05)),
wellPanel(help_Pinv(),
h5(tags$b("Mean time between invasions, years")),
numericInput(inputId = "Finv_min",
label = "Min",
value = 2, min = 2, max = 100, step = 1),
numericInput(inputId = "Finv_max",
label = "Max",
value = 50, min = 2, max = 10000, step = 10)),
wellPanel(help_n_i(),
numericInput(inputId = "n_i",
label = "Number of iterations",
value = 10, min = 100, max = 10000, step = 100))),
column(1,
actionButton(inputId = "run", label = "RUN"),
tags$hr(),
actionButton(inputId = "cancel", label = "CANCEL")),
column(8,
tabsetPanel(
tabPanel("Sensitivity - Country",
p(),
plotOutput(outputId = "SSe_c"),
tags$hr(),
helpText("The dots denote the medians and the bars the 95% confidence intervals of the assessment results")),
tabPanel("Probability of freedom - Country",
p(),
plotOutput(outputId = "Pfree_c"),
tags$hr(),
helpText("The colored area shows the 95% confidence intervals of the assessment results")),
tabPanel("Sensitivity - Regions",
p(),
plotOutput(outputId = "SSe_r", height = "1000px"),
tags$hr(),
helpText("The dots denote the medians and the bars the 95% confidence intervals of the assessment results")),
tabPanel("Probability of freedom - Regions",
p(),
plotOutput(outputId = "Pfree_r", height = "1000px"),
tags$hr(),
helpText("The colored area shows the 95% confidence intervals of the assessment results"))
)))),
tabPanel("4. Download results",
fluidRow(column(3,
wellPanel(h4(tags$b("The sensitivity of the annual surveys")),
tags$hr(),
selectInput("SSe_table_to_dl","2.5, 50 and 97.5% fractiles as separate csv files",
choices = c("2.5%",
"50%",
"97.5%")),
downloadButton("download_SSe_tables", "Download"),
tags$hr(),
h5(tags$b("All the fractiles as a rds file")),
downloadButton("download_SSe_fractiles", "Download"),
tags$hr(),
h5(tags$b("All iterations as a rds file")),
downloadButton("download_SSe_iterations", "Download")
)),
column(3,
wellPanel(h4(tags$b("The probability of freedom after the last survey")),
tags$hr(),
selectInput("Pfree_table_to_dl","2.5, 50 and 97.5% fractiles as separate csv files",
choices = c("2.5%",
"50%",
"97.5%")),
downloadButton("download_Pfree_tables", "Download"),
tags$hr(),
h5(tags$b("All the fractiles as a rds file")),
downloadButton("download_Pfree_fractiles", "Download"),
tags$hr(),
h5(tags$b("All iterations as a rds file")),
downloadButton("download_Pfree_iterations", "Download")
)),
column(3,
wellPanel(h4(tags$b("Download figures")),
tags$hr(),
help_dl_figs(),
selectInput("fig_to_dl", "Choose a figure",
choices = c("Sensitivity - Country",
"Probability of freedom - Country",
"Sensitivity - Regions",
"Probability of freedom - Regions")),
downloadButton("download_fig", "Download"))
))),
tabPanel("About FinnSURV-Assess PWN",
fluidRow(column(5,
tags$br(),
wellPanel(
p(tags$b("FinnSURV-Assess PWN is a tool for assessing the confidence in freedom from pine wood nematode
(PWN",",", tags$i("Bursaphelenchus xylophilus"),") gained in official quarantine pest surveys
in areas where PWN is not expected to cause symptoms.")),
p(),
p("FinnSURV-Assess PWN can be used to assess both the sensitivity of annual surveys and the probability
of freedom achieved in multiannual surveys. It assumes that a) the surveys are composed of inspections
that cover a fixed sized area and b) in the inspections one or more wood or Monochamus samples are collected.
If all the needed data is provided separately for all regions of a country, the assessment will be done
separately for each region and for the whole country."),
p(),
p("FinnSURV-Assess PWN was developed in the Risk Assessment Unit of the Finnish Food Authority
by Salla Hannunen and Juha Tuomola in 2020. The methodology used in it is described in detail in
Hannunen and Tuomola (2020) and references therein, especially",
tags$a("Cannon (2002)", href = "https://doi.org/10.1016/S0167-5877(01)00262-8", target = "_blank"),",",
tags$a("Martin et al. (2007)", href = "https://doi.org/10.1016/j.prevetmed.2006.09.008", target = "_blank"),",",
tags$a("Efsa (2012)", href = "https://doi.org/10.2903/sp.efsa.2012.EN-366", target = "_blank"),"and",
tags$a("Efsa (2018)", href = "https://doi.org/10.2903/sp.efsa.2018.EN-1399", target = "_blank"),
".")
)
),
column(1),
column(5,
tabsetPanel(
tabPanel("Glossary",
tags$br(),
p("Apparent prevalence = The proportion of samples testing positive"),
p(),
p("Design prevalence = Roughly, design prevalence determines the minimum prevalence that the
survey is aimed to detect. If the pest prevalence is equal to or greater than the design prevalence,
at least one infested individual will be detected in the survey, with the probability equal to the
sensitivity of the survey."),
p(),
p("Early detection survey = A survey that aims to detect possible PWN invasions early enough to
enable successful eradication"),
p(),
p("Entry site = A site where the probability of PWN introduction is elevated, i.e. harbors,
industrial areas and landfills"),
p(),
p("Import-export survey = A survey that aims to provide evidence to justify import requirements
related to PWN and to facilitate export to countries with corresponding requirements"),
p(),
p("Initial prior probability of freedom = The probability that the prevalence of the pest is
below the design prevalence before the first survey"),
p(),
p("Probability of freedom = The probability that the prevalence of the pest is below the design
prevalence if the pest is not detected in the surveys"),
p(),
p("Sensitivity = Roughly, sensitivity determines the probability with which a survey is expected
to succeed in its aim. If the pest prevalence is equal to or greater than the design prevalence,
at least one infested individual will be detected in the survey, with the probability equal to
the sensitivity of the survey."),
p(),
p("Target population at the level of inspection site = Wood objects suitable for sampling / Monochamus adults"),
p(),
p("Target population at the level of regions = The area with PWN host plants in the
area for which the results of the survey will be generalized"),
p(),
p("Test sensitivity = The probability that the pest is detected in the laboratory analysis, given that it
was present in the wood object(s) / Monochamus beetle(s) included in the sample")
),
tabPanel("References",
tags$br(),
p(tags$a("Cannon RM (2002) Demonstrating disease freedom - Combining confidence levels.
Preventive Veterinary Medicine 52: 227-249.",
href = "https://doi.org/10.1016/S0167-5877(01)00262-8", target="_blank")),
p("Corine..."),
p(tags$a("European Food Safety Authority (2012)
A framework to substantiate absence of disease: the risk based estimate
of system sensitivity tool (RiBESS) using data collated according to the EFSA Standard Sample Description -
An example on", tags$i("Echinococcus multilocularis"),". Supporting Publications 2012 9(12):EN-366: 1-44.",
href = "https://doi.org/10.2903/sp.efsa.2012.EN-366", target="_blank")),
p(tags$a("European Food Safety Authority, Ciubotaru RM, Cortinas Abrahantes J, Oyedele J,
Parnell S, Schrader G, Zancanaro G, Vos S (2018) Work-plan and methodology for EFSA
to develop plant pest survey guidelines for EU Member States. EFSA supporting publication 2018 15(3):EN-1399: 1-36",
href = "https://doi.org/10.2903/sp.efsa.2018.EN-1399", target="_blank")),
p(tags$a("European Union (2012) Commission Implementing Decision of 26 September 2012 on
emergency measures to prevent the spread within the Union of",
tags$i("Bursaphelenchus xylophilus"),"(Steiner et Buhrer) Nickle et al. (the pine wood nematode)
(notified under document C(2012) 6543) (2012/535/EU).
Official Journal of the European Union L 266 2.10.2012: 42-52.",
href = "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:02012D0535-20170310", target="_blank")),
p("Hannunen S and Tuomola J (2020)
Assessing the probability of freedom
from pine wood nematode based on 19 years of surveys. NeoBiota..."),
p(tags$a("Martin PAJ, Cameron AR, Greiner M (2007)
Demonstrating freedom from disease using multiple complex data sources
1: A new methodology based on scenario trees.
Preventive Veterinary Medicine 79: 71-97.",
href = "https://doi.org/10.1016/j.prevetmed.2006.09.008", target="_blank"))
),
tabPanel("Copyright",
tags$br(),
p("Please refer to FinnSURV-Assess PWN as:"),
p("Hannunen S and Tuomola J 2020. FinnSURV-Assess PWN - A tool for assessing
the confidence of freedom from the pine wood nematode gained in official surveys.
Finnish Food Authority, Helsinki, Finland. Available at..."),
tags$br(),
p("FinnSURV-Assess PWN is published under", tags$a(href="https://creativecommons.org/licenses/by-nc-sa/4.0/","the Creative Commons Attribution-NonCommercial-ShareAlike 4.0
International", target="_blank"), "license.")
)
)
)))
)
#####################################################
server <- function(input,output,session){
observe_helpers()
# Stop session when the window is closed
session$onSessionEnded(stopApp)
##########
# INTERACTIVE PARTS OF THE UI (RENDER UI)
# Inspection site level design prevalences of the different survey types
output$localDP <- renderUI({
req(input$select_survey_type)
switch(input$select_survey_type,
"1" = wellPanel(help_localDP_ie(),
h4(tags$b("Inspection site level design prevalence")),
tags$hr(),
numericInput(inputId = "DP_w",
label = "Wood",
value = 0.12, min = 0, max = 0.12, step = 0.01),
numericInput(inputId = "DP_M",
label = tags$i("Monochamus"),
value = 0.09, min = 0, max = 0.09, step = 0.01)),
"2" = wellPanel(help_localDP_ed(),
h4(tags$b("Inspection site level design prevalence")),
tags$hr(),
numericInput(inputId = "DP_w",
label = "Wood",
value = 0.06, min = 0, max = 0.12, step = 0.01),
numericInput(inputId = "DP_M",
label = tags$i("Monochamus"),
value = 0.045, min = 0, max = 0.09, step = 0.01)))
})
# Region/country level design prevalences of the different survey types
output$globalDP <- renderUI({
req(input$select_survey_type)
switch(input$select_survey_type,
"1" = wellPanel(help_globalDP(),
h4(tags$b("Country level design prevalence")),
tags$hr(),
numericInput(inputId = "DPr",
label = "",
value = 0.01, min = 0, max = 1, step = 0.001)),
"2" = wellPanel(help_max_inf_size(),
h4(tags$b("Maximum acceptable size of PWN infestation at detection, km",tags$sup("2"))),
tags$hr(),
numericInput(inputId = "max_inf_size",
label = "",
value = 314, min = 1, max = 5000, step = 10)))
})
# Number of wood objects sampled per inspected site: upload data or define as probability distribution
output$upload_n_w_data <- renderUI({
switch(input$select_n_w_input_type,
"1" = fluidRow(column(12,
help_csv_n_w(),
fileInput("file_n_w", "",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table"))),
"2" = fluidRow(
help_pert(),
column(6,
numericInput(inputId = "n_w_min",
label = "Min",
value = 1, min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_w_max",
label = "Max",
value = 5, min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_w_mode",
label = "Mode",
value = 2, min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_w_lambda",
label = "Lambda",
value = 1, min = 1, max =20, step = 1)),
column(12,helpText("See the plot on the right for the distribution")))
)})
# Number of Monochamus sampled per inspected site: upload data or define as probability distribution
output$upload_n_M_data <- renderUI({
switch(input$select_n_M_input_type,
"1"= fluidRow(column(12,
help_csv_n_M(),
fileInput("file_n_M", "",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table"))),
"2" = fluidRow(
help_pert(),
column(6,
numericInput(inputId = "n_M_min",
label = "Min",
value = "", min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_M_max",
label = "Max",
value = "", min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_M_mode",
label = "Mode",
value = "", min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_M_lambda",
label = "Lambda",
value = "", min = 1, max =20, step = 1)),
column(12,helpText("See the plot on the right for the distribution")))
)})
# Density of wood objects suitable for sampling: upload data or define as porbability distribution
output$upload_d_w_data <- renderUI({
switch(input$select_d_w_input_type,
"1" = fluidRow(column(12,
helpText("See the plot below for the distribution"))),
"2" = fluidRow(
column(11,h5(tags$b("Number per km", tags$sup("2")))),
help_pert(),
column(6,
numericInput(inputId = "d_w_min",
label = "Min",
value = 1, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_w_max",
label = "Max",
value = 60, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_w_mode",
label = "Mode",
value = 30, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_w_lambda",
label = "Lambda",
value = 1, min = 1, max = 10, step = 1)),
column(12,helpText("See the plot below for the distribution")))
)})
# Density of Monochamus adults: upload data or define as probability distribution
output$upload_d_M_data <- renderUI({
switch(input$select_d_M_input_type,
"1"= fluidRow(column(12,
helpText("See the plot below for the distribution"))),
"2" = fluidRow(column(11,h5(tags$b("Number per km", tags$sup("2")))),
help_pert(),
column(6,
numericInput(inputId = "d_M_min",
label = "Min",
value = 1, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_M_max",
label = "Max",
value = 60, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_M_mode",
label = "Mode",
value = 30, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_M_lambda",
label = "Lambda",
value = 1, min = 1, max = 10, step = 1)),
column(12,helpText("See the plot below for the distribution")))
)})
##########
# UPLOADING DATA AND PRINTING IT AS TABLES
# The number of inspected sites in the wood sampling component of the survey
df_N_w <- reactive({
req(input$file_N_w)
A <- read.csv(input$file_N_w$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_N_w <- eventReactive(input$file_N_w,{
"The number of inspected sites"})
output$table_N_w <- renderTable({
req(input$file_N_w)
df_N_w()})
# The number of wood objects sampled per inspected site
df_n_w <- reactive({
req(input$file_n_w)
A <- read.csv(input$file_n_w$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_n_w <- eventReactive(input$file_n_w,{
"The mean number of wood objects sampled per inspected site"})
output$table_n_w <- renderTable({
req(input$file_n_w)
df_n_w()})
# The number of inspected sites in the Monochamsu trapping component of the survey
df2 <- reactive({
req(input$file_N_M)
A <- read.csv(input$file_N_M$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_N_M <- eventReactive(input$file_N_M,{
"The number of inspected sites"})
output$table_N_M <- renderTable({
req(input$file_N_M)
df2()})
# The number of Monochamus sampled per inspected site
df2.1 <- reactive({
req(input$file_n_M)
A <- read.csv(input$file_n_M$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_n_M <- eventReactive(input$file_n_M,{
"The mean number of beetles sampled per inspected site"})
output$table_n_M <- renderTable({
req(input$file_n_M)
df2.1()})
# The area with host plants
df_host_area <- reactive({
req(input$file_host_area)
A <- read.csv(input$file_host_area$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_host_area <- eventReactive(input$file_host_area,{
"The area with host plants, km2"})
output$table_host_area <- renderTable({
req(input$file_host_area)
df_host_area()})
# The area of entry sites
df_entry_sites <- reactive({
req(input$file_entry_sites)
A <- read.csv(input$file_entry_sites$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_entry_sites <- eventReactive(input$file_entry_sites,{
"The area of entry sites, km2"})
output$table_entry_sites <- renderTable({
req(input$file_entry_sites)
df_entry_sites()})
##########
# VECTORS NEEDED IN THE CALCULATIONS AND FIGURES
# The considered mean times between invasions
Finv_FI <- eventReactive(input$run,{
seq(input$Finv_min,input$Finv_max,1)
})
# The years when surveys were conducted
Y <- eventReactive(input$run,{
a = data.matrix(df_N_w())
seq(a[1,1],a[nrow(a),1],1)
})
# The number of years when surveys were conducted
n_y <- eventReactive(input$run,{
length(Y())
})
# The names of the regions included in the survey
region_names <- eventReactive(input$run,{
A <- read.csv(input$file_N_w$datapath,
header = TRUE,
sep = ",",
quote = "'")
colnames(A[2:ncol(A)])
})
# The number of regions included in the survey + 1 (to include the whole country)
n_r <- eventReactive(input$run,{
ncol(df_N_w())
})
##########
# UPLOADED DATA FOR THE CALCULATIONS
# The number of inspected sites in the wood sampling component of the survey
N_wood <- reactive({
a = data.matrix(df_N_w())
b = a[,2:ncol(a)]
array(b, dim=c(nrow(b),ncol(b),input$n_i))
})
# The number of inspected sites in the Monochamus trapping component of the survey
N_Monochamus <- reactive({
a = data.matrix(df2())
b = a[,2:ncol(a)]
array(b, dim=c(nrow(b),ncol(b),input$n_i))
})
# The number of wood objects sampled per inspected site
n_wood <- reactive({
if(input$select_n_w_input_type == 1){
a = data.matrix(df_n_w())
b = a[,2:ncol(a)]
A <- array(b, dim=c(nrow(b),ncol(b),input$n_i))
}else{
req(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max)
A <- round(rpert(input$n_i,input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda))
}
A
})
# The number of Monochamus adults sampled per inspected site
n_Monochamus <- reactive({
if(input$select_n_M_input_type == 1){
a = data.matrix(df2.1())
b = a[,2:ncol(a)]
A <- array(b, dim=c(nrow(b),ncol(b),input$n_i))
}else{
req(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max)
A<- round(rpert(input$n_i,input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda))
}
A
})
# The density of wood objects suitable for sampling
d_wood <- reactive({
if(input$select_d_w_input_type == 1){
# The number of Monochamus-suitable dead wood objects per km2
obj <- round(rpert(input$n_i,166,288,398,1))
# The proportion of Monochamus-suitable dead wood objects that is suitable for sampling
psam <- runif(input$n_i,0.05,0.95)
# The density of wood objects suitable for sampling, number/km2
round(obj*psam)
}else{
req(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max)
round(rpert(input$n_i,input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda))
}
})
# The number of wood objects suitable for sampling per inspection site
p_wood <- reactive({
b <- array(d_wood(),dim=c(n_y(),n_r()-1,input$n_i))
c = round(b*input$site_w)
c[c < ceiling(1/input$DP_w)] <- ceiling(1/input$DP_w)
c
})
# The density of Monochamus adults
d_Monochamus <- reactive({
if(input$select_d_M_input_type == 1){
# The number of dead wood objects occupied by Monochamus per km2
obju <- round(rpert(input$n_i,13.28,28.8,47.76,1))
# The number of Monochamus eggs laid per Monochamus-suitable dead-wood object
fobj <- rpert(input$n_i,6,31,88,1)
# The proportion of Monochamus surviving from egg to egg-laying adults
surv <- rpert(input$n_i,0.1,0.25,0.4,1)
# The density of Monochamus adults, number/km2
obju*fobj*surv
}else{
req(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max)
round(rpert(input$n_i,input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda))
}
})
# The number of Monochamus adults per inspection site
p_Monochamus <- reactive({
b <- array(d_Monochamus(),dim=c(n_y(),n_r()-1,input$n_i))
c = round(b*input$site_M)
c[c < ceiling(1/input$DP_M)] <- ceiling(1/input$DP_M)
c
})
# The area with host plants
host_area <- reactive({
a = data.matrix(df_host_area())
b = a[,2:ncol(a)]
array(b, dim=c(nrow(b),ncol(b),input$n_i))
})
# The area of entry sites
entry_sites <- reactive({
a = data.matrix(df_entry_sites())
b = a[,2:ncol(a)]
matrix(b, nrow(b), ncol(b))
})
# The relative probability of invasion to the regions
RP <- reactive({
a = entry_sites()/rowSums(entry_sites())
array(a, dim=c(nrow(a),ncol(a),input$n_i))
})
# The effective probability of infestation for the import-export survey
# and the regional-level design prevalence for the early detection survey
DPr_adj <- reactive({
# The proportion of the target population in the regions
PropPop = host_area()/rowSums(host_area()[,,1])
# Weighted probability of invasion in the regions
WR = RP()/rowSums(PropPop[,,1]*RP()[,,1])
# Effective probability of infestation for the import-export survey
if(input$select_survey_type == 1){
A = input$DPr*WR
# Regional-level design prevalence for the early detection survey
}else{
A = input$max_inf_size/host_area()
}
A
})
##########
# FIGURES FOR THE TABS "UPLOAD DATA"
# The number of wood objects sampled per inspected site
output$n_wood <- renderPlot({
validate(
need(all(input$n_w_min<=input$n_w_mode,
input$n_w_min<=input$n_w_max,
input$n_w_mode<=input$n_w_max,
input$n_w_min >= 0,
input$n_w_mode >= 0,
input$n_w_max >= 0,
input$n_w_lambda >= 0),
"Make sure that min, mode, max and lambda are logical"),
need(any(input$n_w_min!=input$n_w_mode,
input$n_w_min!=input$n_w_max,
input$n_w_mode!=input$n_w_max),
"Cannot present a probability distribution if min, mode and max are the same, but analysis can be run if min, max and lambda are all defined")
)
x <- seq(input$n_w_min,input$n_w_max,0.1)
dist = dpert(x,input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda)
plot(x,dist,type = 'l',
xlab = "Number per inspection", ylab = "Probability")
})
# the number of Monochamus sampled per inspected site
output$n_Monochamus <- renderPlot({
validate(
need(all(input$n_M_min<=input$n_M_mode,
input$n_M_min<=input$n_M_max,
input$n_M_mode<=input$n_M_max,
input$n_M_min >= 0,
input$n_M_mode >= 0,
input$n_M_max >= 0,
input$n_M_lambda >= 0),
"Make sure that min, mode, max and lambda are logical"),
need(any(input$n_M_min!=input$n_M_mode,
input$n_M_min!=input$n_M_max,
input$n_M_mode!=input$n_M_max),
"Cannot present a probability distribution if min, mode and max are the same, but analysis can be run if min, max and lambda are all defined")
)
x <- seq(input$n_M_min,input$n_M_max,0.1)
dist = dpert(x,input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda)
plot(x,dist,type = 'l',
xlab = "Number per inspection", ylab = "Probability")
})
# The density of wood objects suitable for sampling
output$d_wood <- renderPlot({
if(input$select_d_w_input_type == 2){
validate(
need(all(input$d_w_min<=input$d_w_mode,
input$d_w_min<=input$d_w_max,
input$d_w_mode<=input$d_w_max,
input$d_w_min >= 0,
input$d_w_mode >= 0,
input$d_w_max >= 0,
input$d_w_lambda >= 0),
"Make sure that min, mode, max and lambda are logical"),
need(any(input$d_w_min!=input$d_w_mode,
input$d_w_min!=input$d_w_max,
input$d_w_mode!=input$d_w_max),
"Cannot present a probability distribution if min, mode and max are the same, but analysis can be run if min, max and lambda are all defined")
)
x <- seq(input$d_w_min,input$d_w_max,0.1)
dist = dpert(x,input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)
plot(x,dist,type = 'l',
xlab = expression(paste("Number per" ~ km^{2})),
ylab = "Probability")}
else{
dist = round(rpert(600000,166,288,398,1))*runif(600000,0.05,0.95)
res <- hist(dist, freq = FALSE, breaks = 80, xlim=c(0,400))
a = res$breaks+res$breaks[2]/2
x = a[1:length(a)-1]
plot(x,res$density,'l',
xlab = expression(paste("Number per" ~ km^{2})),
ylab = "Probability", main = "")
}
})
# The density of Monochamus adults
output$d_Monochamus <- renderPlot({
if(input$select_d_M_input_type == 2){
validate(
need(all(input$d_M_min<=input$d_M_mode,
input$d_M_min<=input$d_M_max,
input$d_M_mode<=input$d_M_max,
input$d_M_min >= 0,
input$d_M_mode >= 0,
input$d_M_max >= 0,
input$d_M_lambda >= 0),
"Make sure that min, mode, max and lambda are logical"),
need(any(input$d_M_min!=input$d_M_mode,
input$d_M_min!=input$d_M_max,
input$d_M_mode!=input$d_M_max),
"Cannot present a probability distribution if min, mode and max are the same, but analysis can be run if min, max and lambda are all defined")
)
x <- seq(input$d_M_min,input$d_M_max,0.1)
dist = dpert(x,input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)
plot(x,dist,type = 'l',
xlab = expression(paste("Number per" ~ km^{2})),
ylab = "Probability")}
else{
dist = round(rpert(100000,13.28,28.8,47.76,1))*rpert(100000,6,31,88,1)*rpert(100000,0.1,0.25,0.4,1)
res <- hist(dist, freq = FALSE, breaks = 50, xlim=c(0,1600))
a = res$breaks+res$breaks[2]/2
x = a[1:length(a)-1]
plot(x,res$density,'l',
xlab = expression(paste("Number per" ~ km^{2})),
ylab = "Probability", main = "")
}
})
##########
# CALCULATING THE SENSITIVITY OF THE ANNUAL SURVEYS
# All iterations
SSe_iterations <- eventReactive(input$run, {
Sensitivity(N_wood(), n_wood(), p_wood(), input$TSe_w,
N_Monochamus(), n_Monochamus(), p_Monochamus(), input$TSe_M,
host_area(), RP(), DPr_adj(),
input$select_survey_type, input$DP_w, input$DP_M, input$DPr, input$max_inf_size,
n_r(), n_y(), input$n_i)
})
# 2.5, 50,97.5% fractiles
SSe <- eventReactive(input$run, {
Sensitivity_fractiles(SSe_iterations(),n_r(),n_y())
})
#####################
# CALCULATING THE PROBABILITY OF FREEDOM AFTER THE LAST SURVEY (iterations as an Async operation)
nclicks <- reactiveVal(0)
Pfree_iterations_val <- reactiveVal()
inter <- AsyncInterruptor$new()
observeEvent(input$run,{
req(N_wood(), n_wood(), p_wood(), input$TSe_w,
N_Monochamus(),n_Monochamus(),p_Monochamus(),input$TSe_M,
host_area(), entry_sites(),
input$select_survey_type, input$DP_w, input$DP_M, any(input$DPr!="", input$max_inf_size!=""),
input$Prior_Pfree, Finv_FI(), input$n_i)
# Start progress monitor
if(nclicks() == 0){
progress <- AsyncProgress$new(session, min=1, max=100, message = "Computing")
progress$set(message = "Computing", value = 1)
}
# If "Run" is clicked several times, don't do anything as analysis is already running
if(nclicks() != 0){
showNotification("Already running analysis")
return(NULL)
}
# Increment clicks and prevent concurrent analyses
nclicks(nclicks() + 1)
Pfree_iterations_val(NULL)
# Create variables that can be imported to the async operation (since reactive values and input$xxs cannot)
N_wood <- N_wood()
n_wood <- n_wood()
p_wood <- p_wood()
TSe_w = input$TSe_w
N_Monochamus <- N_Monochamus()
n_Monochamus <- n_Monochamus()
p_Monochamus <- p_Monochamus()
TSe_M = input$TSe_M
host_area <- host_area()
RP <- RP()
DPr_adj <- DPr_adj()
n_r <- n_r()
n_y <- n_y()
Pinv_FI <- 1/Finv_FI()
select_survey_type = input$select_survey_type
DP_w = input$DP_w
DP_M = input$DP_M
DPr = input$DPr
max_inf_size = input$max_inf_size
Prior_Pfree = input$Prior_Pfree
n_i = input$n_i
# Compute the iterations as an async operation
Pfree_iterations <- future({
Probability_of_freedom_iterations(progressMonitor1 = function(h) inter$execInterrupts(),
progressMonitor2 = function(h) progress$set(),
N_wood, n_wood, p_wood,TSe_w,
N_Monochamus, n_Monochamus, p_Monochamus,TSe_M,
host_area, RP, DPr_adj,
select_survey_type, DP_w, DP_M, DPr, max_inf_size,
Pinv_FI, Prior_Pfree,
n_r, n_y, n_i)
}) %...>% Pfree_iterations_val()
# After the promise has been evaluated set nclicks to 0 to allow for anlother run
# and close the progress monitor
Pfree_iterations <- finally(Pfree_iterations,
function(){
nclicks(0)
progress$close()
})
# Return something other than the promise so shiny remains responsive
NULL
})
# If cancell is clicked, interrupt computing and show notification
observeEvent(input$cancel,{
inter$interrupt("Error: Stop Future")
showNotification("Analysis cancelled")
})
# Get the 2.5, 50 and 97.5% fractiles
Pfree <- reactive({
req(Pfree_iterations_val())
Pinv_FI <- 1/Finv_FI()
Probability_of_freedom_fractiles(Pfree_iterations_val(),Pinv_FI,n_r(),n_y())
})
#############
# FIGURES FOR THE TAB "VIEW RESULTS"
# SSe - Country
output$SSe_c <- renderPlot({
# Validate and if not valid show an error message
# (need(all(input$file_n_w, any(input$1, input$2,input$3)),"Error message") did not work, so I had to use if...else...)
if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}
req(Pfree_iterations_val())
Plot_SSe_country(Y(),SSe(),n_r())
})
# Pfree - Country
output$Pfree_c <- renderPlot({
if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}
req(Pfree_iterations_val())
Plot_Pfree_country(Finv_FI(),Pfree(),n_r())
})
# Pfree - Regions
output$Pfree_r <- renderPlot({
if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}
req(Pfree_iterations_val())
Plot_Pfree_regions(Finv_FI(),Pfree(),region_names())
})
# SSe - Regions
output$SSe_r <- renderPlot({
if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}
req(Pfree_iterations_val())
Plot_SSe_regions(Y(),SSe(),region_names())
})
##########
# DOWNLOAD RESULTS
# SSe tables
SSetableInput <- reactive({
a <- as.data.frame(SSe()[,,1])
b <- as.data.frame(SSe()[,,2])
c <- as.data.frame(SSe()[,,3])
colnames(a)[seq(1,ncol(a)-1,1)] <- c(region_names())
colnames(a)[ncol(a)] <- "Country"
colnames(b) <- colnames(a)
colnames(c) <- colnames(a)
switch(input$SSe_table_to_dl,
"2.5%" = a,
"50%" = b,
"97.5%" = c
)
})
output$download_SSe_tables <- downloadHandler(
filename = function(){
paste(input$SSe_table_to_dl, 'csv', sep = ".")},
content = function(file){
write.csv(SSetableInput(), file, row.names = c(Y()))
})
output$download_SSe_fractiles <- downloadHandler(
filename = function(){
paste("SSe_fractiles.rds")},
content = function(file){
saveRDS(SSe(), file=file)
})
output$download_SSe_iterations <- downloadHandler(
filename = function(){
paste("SSe_iterations.rds")},
content = function(file){
saveRDS(SSe_iterations(), file=file)
})
# Pfree tables
PfreetableInput <- reactive({
a <- as.data.frame(Pfree()[,,1])
b <- as.data.frame(Pfree()[,,2])
c <- as.data.frame(Pfree()[,,3])
colnames(a)[seq(1,ncol(a)-1,1)] <- c(region_names())
colnames(a)[ncol(a)] <- "Country"
colnames(b) <- colnames(a)
colnames(c) <- colnames(a)
switch(input$Pfree_table_to_dl,
"2.5%" = a,
"50%" = b,
"97.5%" = c)
})
output$download_Pfree_tables <- downloadHandler(
filename = function(){
paste(input$Pfree_table_to_dl,"csv", sep = ".")},
content = function(file){
write.csv(PfreetableInput(), file, row.names = c(Finv_FI()))
})
output$download_Pfree_fractiles <- downloadHandler(
filename = function(){
paste("Pfree_fractiles.rds")},
content = function(file){
saveRDS(Pfree(), file=file)
})
output$download_Pfree_iterations <- downloadHandler(
filename = function(){
paste("Pfree_iterations.rds")},
content = function(file){
saveRDS(Pfree_iterations_val(), file=file)
})
# Download figures
FigInput <- reactive({
switch(input$fig_to_dl,
"Sensitivity - Country" = Plot_SSe_country(Y(),SSe(),n_r()),
"Probability of freedom - Country" = Plot_Pfree_country(Finv_FI(),Pfree(),n_r()),
"Sensitivity - Regions" = Plot_SSe_regions(Y(),SSe(),region_names()),
"Probability of freedom - Regions" = Plot_Pfree_regions(Finv_FI(),Pfree(),region_names())
)})
output$download_fig <- downloadHandler(
filename = function(){
paste(input$fig_to_dl,"png",sep = ".")
},
content = function(file){
ggsave(FigInput(), file = file)
})
}
############################################################
shinyApp(ui=ui,server=server)
saulitalja/RR documentation built on March 14, 2020, 1:19 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions Sensitivity Sensitivity_fractiles Probability_of_freedom_iterations Probability_of_freedom_fractiles Plot_SSe_country Plot_Pfree_country Plot_SSe_regions Plot_Pfree_regions help_dl_figs help_pert help_csv_N_w help_csv_n_w help_csv_N_M help_csv_n_M help_csv_host_area help_csv_entry_sites help_PriorPfree help_Pinv help_n_i help_TSe_w help_TSe_M help_site_w help_site_M help_n_w help_n_M help_entry_sites help_host_area help_d_w help_d_M help_survey_type help_localDP_ie help_localDP_ed help_globalDP help_max_inf_size server
library(shiny)
library(shinythemes) # Theme
library(magrittr) # IS THIS NEEDED?
library(shinyhelper) # Pop up helps
library(ggplot2) # Plotting
library(mc2d) # Pert- probability distribution
library(ipc) # Asyc computing
library(promises) # Asyc computing
library(future) # Asyc computing
plan(multiprocess) # Asyc computing
#source("functions.R")
###################################################
# A function that calculates the sensitivities of annual surveys
Sensitivity <- function(N_wood, n_wood, p_wood, TSe_wood,
N_Monochamus, n_Monochamus, p_Monochamus, TSe_Monochamus,
Pop_data, RP, DPr_adj,
scenario, DP_wood, DP_Monochamus, DPr, max_inf_size,
n_r, n_y, n_i){
#####
# CALCULATING INSPECTION SENSITIVITY
# Deciding whether to use binomial or hypergeometric distribution
# (Binomial is appropriate when the sample size is less than 10% of the total population size)
if(max(n_wood)/min(p_wood) < 0.1){
ISe_wood = 1 - (1 - (DP_wood*TSe_wood))^n_wood
}else{
ISe_wood = 1 - (1 - ((n_wood*TSe_wood)/(p_wood - 0.5*(p_wood*DP_wood*TSe_wood-1))))^(p_wood*DP_wood)
}
if(max(n_Monochamus)/min(p_Monochamus) < 0.1){
ISe_Monochamus = 1 - (1 - (DP_Monochamus*TSe_Monochamus))^n_Monochamus
}else{
ISe_Monochamus = 1 - (1 - ((n_Monochamus*TSe_Monochamus)/(p_Monochamus - 0.5*(p_Monochamus*DP_Monochamus*TSe_Monochamus-1))))^(p_Monochamus*DP_Monochamus)
}
#####
# CALCULATING THE SENSITIVITY OF ANNUAL SURVEYS IN THE REGIONS
# (Separately for wood sampling and Monochamus trapping)
# Deciding whether to use binomial or hypergeometric distribution
if(max(N_wood)/min(Pop_data) < 0.1){
GSe_wood = 1 - (1 - (DPr_adj*ISe_wood))^N_wood
}else{
GSe_wood = 1 - (1 - ((N_wood*ISe_wood)/(Pop_data - 0.5*(Pop_data*DPr_adj*ISe_wood-1))))^(Pop_data*DPr_adj)
}
if(max(N_Monochamus)/min(Pop_data) < 0.1){
GSe_Monochamus = 1 - (1 - (DPr_adj*ISe_Monochamus))^N_Monochamus
}else{
GSe_Monochamus = 1 - (1 - ((N_Monochamus*ISe_Monochamus)/(Pop_data - 0.5*(Pop_data*DPr_adj*ISe_Monochamus-1))))^(Pop_data*DPr_adj)
}
#####
# CALCULATING THE SENSITIVITY OF ANNUAL SURVEYS IN THE REGIONS AND IN FINLAND
# (Wood sampling and Monochamus trapping combined)
# Arrays for storing the results
# w = wood, m = Monochamus, wm = wood and Monochamus
GSe_wm <- array(0,dim=c(n_y,(n_r-1),n_i))
SSe_w_FI <- array(0,dim=c(n_y,n_i))
SSe_m_FI <- array(0,dim=c(n_y,n_i))
SSe_wm_FI <- array(0,dim=c(n_y,n_i))
for (k in 1:n_i){
for(t in 1:n_y){
# Regions
GSe_wm[t,,k] = 1 - (1-GSe_wood[t,,k])*(1-GSe_Monochamus[t,,k])
# Finland
# Import-export
if(scenario == 1){
SSe_w_FI[t,k] = 1 - prod(1-GSe_wood[t,,k])
SSe_m_FI[t,k] = 1 - prod(1-GSe_Monochamus[t,,k])
SSe_wm_FI[t,k] = 1 - (1-SSe_w_FI[t,k])*(1-SSe_m_FI[t,k])
# Early detection
}else{
SSe_wm_FI[t,k] = sum(GSe_wm[t,,k]*RP[t,,k])
}
}
}
#####
# ALL THE RESULTS IN ONE ARRAY
# Regions in columns 1-(n_r-1), Finland in column n_r
Sensitivity_all <- array(0,dim=c(n_y,n_r,n_i))
Sensitivity_all[,1:(n_r-1),] = GSe_wm
Sensitivity_all[,n_r,] = SSe_wm_FI
return(Sensitivity_all)}
######################################################
# A function that returns the 2.5, 50 and 97.5% fractiles of the senitivity of annual surveys
Sensitivity_fractiles <- function(Sensitivity_all,n_r,n_y){
# Matrixes for storing the results
Se_2.5 <- matrix(0,n_y,n_r)
Se_50 <- matrix(0,n_y,n_r)
Se_97.5 <- matrix(0,n_y,n_r)
for(i in 1:n_y){
for(j in 1:n_r){
Se_2.5[i,j] = quantile(Sensitivity_all[i,j,],0.025)
Se_50[i,j] = quantile(Sensitivity_all[i,j,],0.5)
Se_97.5[i,j] = quantile(Sensitivity_all[i,j,],0.975)
}
}
# All the results in one array
Se_all <- array(0,dim=c(n_y,n_r,3))
Se_all[,,1] = Se_2.5
Se_all[,,2] = Se_50
Se_all[,,3] = Se_97.5
return(Se_all)}
#####################################################
# A function that returns the probability of freedom after the last survey
Probability_of_freedom_iterations <- function(progressMonitor1=function(h) cat("."),
progressMonitor2=function(h) cat("."),
N_wood, n_wood, p_wood, TSe_wood,
N_Monochamus, n_Monochamus, p_Monochamus, TSe_Monochamus,
Pop_data, RP, DPr_adj,
scenario, DP_wood, DP_Monochamus, DPr, max_inf_size,
Pinv_FI, PrioPfree_1,
n_r, n_y, n_i){
##########
# ARRAYS FOR STORING RESULTS
# w = wood, m = Monochamus, wm = wood and Monochamus
GSe_wm <-array(0,dim=c(n_y,(n_r-1),n_i))
SSe_w_FI <-array(0,dim=c(n_y,n_i))
SSe_m_FI <-array(0,dim=c(n_y,n_i))
SSe_wm_FI <-array(0,dim=c(n_y,n_i))
Pfree_w <-array(0,dim=c(n_y,(n_r-1),n_i))
Pfree_wm <-array(0,dim=c(n_y,(n_r-1),n_i))
Pfree_adj <-array(0,dim=c(n_y,(n_r-1),n_i))
Pfree_w_FI <-array(0,dim=c(n_y,n_i))
Pfree_wm_FI <-array(0,dim=c(n_y,n_i))
Pfree_adj_FI <-array(0,dim=c(n_y,n_i))
Pfree_all <- array(0,dim=c(length(Pinv_FI),n_r,n_i))
##########
# CALCULATING INSPECTION SENSITIVITY
# Deciding whether to use binomial or hypergeometric distribution
# (Binomial is appropriate when the sample size is less than 10% of the total population size)
if(max(n_wood)/min(p_wood) < 0.1){
ISe_wood = 1 - (1 - (DP_wood*TSe_wood))^n_wood
}else{
ISe_wood = 1 - (1 - ((n_wood*TSe_wood)/(p_wood - 0.5*(p_wood*DP_wood*TSe_wood-1))))^(p_wood*DP_wood)
}
if(max(n_Monochamus)/min(p_Monochamus) < 0.1){
ISe_Monochamus = 1 - (1 - (DP_Monochamus*TSe_Monochamus))^n_Monochamus
}else{
ISe_Monochamus = 1 - (1 - ((n_Monochamus*TSe_Monochamus)/(p_Monochamus - 0.5*(p_Monochamus*DP_Monochamus*TSe_Monochamus-1))))^(p_Monochamus*DP_Monochamus)
}
#####
# CALCULATING THE SENSITIVITY OF ANNUAL SURVEYS IN THE REGIONS
# (Separately for wood sampling and Monochamus trapping)
# Deciding whether to use binomial or hypergeometric distribution
if(max(N_wood)/min(Pop_data) < 0.1){
GSe_wood = 1 - (1 - (DPr_adj*ISe_wood))^N_wood
}else{
GSe_wood = 1 - (1 - ((N_wood*ISe_wood)/(Pop_data - 0.5*(Pop_data*DPr_adj*ISe_wood-1))))^(Pop_data*DPr_adj)
}
if(max(N_Monochamus)/min(Pop_data) < 0.1){
GSe_Monochamus = 1 - (1 - (DPr_adj*ISe_Monochamus))^N_Monochamus
}else{
GSe_Monochamus = 1 - (1 - ((N_Monochamus*ISe_Monochamus)/(Pop_data - 0.5*(Pop_data*DPr_adj*ISe_Monochamus-1))))^(Pop_data*DPr_adj)
}
#########
# CALCULATING THE SENSITIVITY OF ANNUAL SURVEYS IN THE REGIONS AND COUNTRY
# (Wood sampling and Monochamus trapping combined)
for (k in 1:n_i){
for(t in 1:n_y){
# Regions
GSe_wm[t,,k] = 1 - (1-GSe_wood[t,,k])*(1-GSe_Monochamus[t,,k])
# Finland
# Import-export
if(scenario == 1){
SSe_w_FI[t,k] = 1 - prod(1-GSe_wood[t,,k])
SSe_m_FI[t,k] = 1 - prod(1-GSe_Monochamus[t,,k])
SSe_wm_FI[t,k] = 1 - (1-SSe_w_FI[t,k])*(1-SSe_m_FI[t,k])
# Early detection
}else{
SSe_wm_FI[t,k] = sum(GSe_wm[t,,k]*RP[t,,k])
}
}
}
# CALCULATING THE PROBABILITY OF FREEDOM
for (h in 1:length(Pinv_FI)){
progressMonitor1(h)
progress$set(value = (h/length(Pinv_FI))*100)
Pinv_country = Pinv_FI[h]
# The probability of invasion in the regions
Pinv_regions = RP*Pinv_country
for(t in 1:n_y){
if(t==1){
# Probability of freedom, Finland
Pfree_wm_FI[t,] = PrioPfree_1 / (PrioPfree_1 + ((1-PrioPfree_1)*(1-SSe_wm_FI[t,])))
# Adjusted probability of freedom, Finland
Pfree_adj_FI[t,] = 1 - ( (1-Pfree_wm_FI[t,]) + Pinv_country - ((1-Pfree_wm_FI[t,])*Pinv_country) )
# Probability of freedom, Regions
Pfree_w[t,,] = PrioPfree_1 / (PrioPfree_1 + ((1-PrioPfree_1)*(1-GSe_wood[t,,])))
Pfree_wm[t,,] = Pfree_w[t,,] / (Pfree_w[t,,] + ((1-Pfree_w[t,,])*(1-GSe_Monochamus[t,,])))
# Adjusted probability of freedom, Regions
Pfree_adj[t,,] = 1 - ( (1-Pfree_wm[t,,]) + Pinv_regions[t,,] - ((1-Pfree_wm[t,,])*Pinv_regions[t,,]) )
}else{
# Probability of freedom, Finland
Pfree_wm_FI[t,] = Pfree_adj_FI[t-1,] / (Pfree_adj_FI[t-1,] + ((1-Pfree_adj_FI[t-1,])*(1-SSe_wm_FI[t,])))
# Adjusted probability of freedom, Finland
Pfree_adj_FI[t,] = 1 - ( (1-Pfree_wm_FI[t,]) + Pinv_country - ((1-Pfree_wm_FI[t,])*Pinv_country) )
# Probability of freedom, Regions
Pfree_w[t,,] = Pfree_adj[t-1,,] / (Pfree_adj[t-1,,] + ((1-Pfree_adj[t-1,,])*(1-GSe_wood [t,,])))
Pfree_wm[t,,] = Pfree_w[t,,] / (Pfree_w[t,,] + ((1-Pfree_w[t,,])*(1-GSe_Monochamus[t,,])))
# Adjusted probability of freedom, Regions
Pfree_adj[t,,] = 1 - ( (1-Pfree_wm[t,,]) + Pinv_regions[t,,] - ((1-Pfree_wm[t,,])*Pinv_regions[t,,]) )
}
}
##########
# RETURN ALL THE RESULTS IN ONE ARRAY
Pfree_all[h,1:(n_r-1),] = Pfree_wm[n_y,,]
Pfree_all[h,n_r,] = Pfree_wm_FI[n_y,]
}
#inter$destroy()
#plan(sequential)
return(Pfree_all)}
######################################################
# A function that returns tha 2.5, 50 and 97.5% fractiles of the porbability of freedom after the last survey
Probability_of_freedom_fractiles <- function(Pfree_all,Pinv_FI,n_r,n_y){
# Matrix for storing the results
PF_all <- array(0,dim=c(length(Pinv_FI),n_r,3))
for(i in 1:length(Pinv_FI)){
for(j in 1:n_r){
PF_all[i,j,1] = quantile(Pfree_all[i,j,],0.025)
PF_all[i,j,2] = quantile(Pfree_all[i,j,],0.5)
PF_all[i,j,3] = quantile(Pfree_all[i,j,],0.975)
}
}
return(PF_all)}
############################################################
# FIGURES FOR THE TAB "RESULTS"
##########
# FIGURE SSe - Country
Plot_SSe_country <- function(Y,SSe,n_r){
plot(Y,SSe[,n_r,2],
type = "p",
ylim=c(0.00,1.00),
xlab = "Years",
ylab = "Sensitivity")
arrows(Y, SSe[,n_r,1], Y, SSe[,n_r,3], length=0.01, angle=90, code=3)
}
##########
# FIGURE Pfree - Country
Plot_Pfree_country <- function(Finv_FI,Pfree,n_r){
plot(Finv_FI,Pfree[,n_r,1],
type = 'l',col = 'grey',
ylim=c(0.00,1.00),
xlab = "Mean time between invasions, years",
ylab = "Probability of freedom")
lines(Finv_FI, Pfree[,n_r,3], col='grey')
polygon(c(Finv_FI,rev(Finv_FI)), c(Pfree[,n_r,1], rev(Pfree[,n_r,3])), col='grey', border=NA)
}
##########
# FIGURE SSe - Regoins
Plot_SSe_regions <- function(Y,SSe,regions){
n_regions = length(regions)
par(mfrow=c(ceiling(n_regions/3),3))
par(pin=c(2,4))
par(mar=c(2,2,2,2))
par(mgp=c(0.5,0.75,0))
par(oma=c(2.5,3,2,1))
SetLine<--9
TitleSize<- 1
AxisSize<- 1.2
Xlabels<-seq(Y[1],Y[length(Y)],2)
Ylabels<- seq(0,1,0.2)
for(i in 1:n_regions){
plot(Y, SSe[,i,2], type = "p", pch=16, frame.plot=FALSE, ylim=c(0,1), axes=FALSE, xlab="", ylab="",main=regions[i])
arrows(Y, SSe[,i,1], Y, SSe[,i,3], length=0.01, angle=90, code=3)
title(line=SetLine, cex.main=TitleSize)
axis(side=1, at=Xlabels, labels=Xlabels, cex.axis=AxisSize)
axis(side=2, at=Ylabels, labels=Ylabels, las=1, cex.axis=AxisSize)
}
mtext('Year', side=1, outer=TRUE, line=1)
mtext('Sensitivity', side=2, outer=TRUE, line=1.5)
}
##########
# FIGURE Pfree - Regions
Plot_Pfree_regions <- function(Finv_FI,Pfree,regions){
n_regions = length(regions)
par(mfrow=c(ceiling(n_regions/3),3))
par(pin=c(2,4))
par(mar=c(2,2,2,2))
par(mgp=c(0.5,0.75,0))
par(oma=c(2.5,3,2,1))
SetLine<--9
TitleSize<-1
AxisSize<-1.2
Xlabels<-seq(0,Finv_FI[length(Finv_FI)],10)
Ylabels<-c(0.00,0.20,0.40,0.60,0.80,1.00)
for(i in 1:n_regions){
plot(Finv_FI, Pfree[,i,1], type="l", col="grey", frame.plot=FALSE,
ylim=c(0,1), xlim=c(Finv_FI[1],Finv_FI[length(Finv_FI)]),
axes=FALSE, xlab="", ylab="",main=regions[i])
lines(Finv_FI, Pfree[,i,3], col="grey")
polygon(c(Finv_FI,rev(Finv_FI)), c(Pfree[,i,1], rev(Pfree[,i,3])), col="grey", border=NA)
title(line=SetLine, cex.main=TitleSize)
axis(side=1, at=Xlabels, labels=Xlabels, cex.axis=AxisSize)
axis(side=2, at=Ylabels, labels=Ylabels, las=1, cex.axis=AxisSize)
}
mtext('The mean time between invasions to the country, years', side=1, outer=TRUE, line=1.2)
mtext('The probability of freedom', side=2, outer=TRUE, line=1.5)
}
###############################################
# HELP TEXTS FOR THE POP UP WINDOWS
help_dl_figs <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Choose a figure",
content = c("Note that the same figure cannot be downloaded and/or viewed twice in a row.
If you need to download and/or view the same figure more than once, you need
to select another figure in between the two downloads/views."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_pert <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Estimate as a probability distribution",
content = c("If the exact value of the parameter is not known or if it varies,
the parameter value can be defined as a Pert probability distribution.",
"",
"First, the minimum, maximum and mode of the parameter should be set.
Then, lambda should be defined such that the resulting probability distribution
reflects the uncertainty or the variation of the parameter value. Lambda
takes positive values and the greater its value the more
peaked is the probability distribution.",
"",
"If the exact value of the parameter is known, minimum, maximum and
mode should all be set to that known value. In this special case,
lambda must also be defined, but it can be given any value,
as it has no effect on the outcome."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_N_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"For the regions and/or years in which no survey was done, the number of inspected
sites should be zero.",
"",
"The data for the Finnish PWN surveys is in the file
1.1_N_inspected_sites_wood_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_n_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"For the regions and/or years in which no survey was done, the number of samples per
inspected site should be zero."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_N_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"For the regions and/or years in which no survey was done,
the number of inspected sites should be zero.",
"",
"The data for the Finnish PWN surveys is in the file
1.2_N_inspected_sites_Monochamus_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_n_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files and
the years should always be in ascending order.",
"",
"For the regions and/or years in which no survey was done, the number of samples per
inspected site should be zero.",
"",
"The data for the Finnish PWN surveys is in the file
1.2_n_samples_per_inspected_site_Monochamus_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_host_area <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"Even if the the area with host plants was the same for all or some of the years,
data should be given for all the considered years separately.",
"",
"The data for the Finnish PWN surveys is in the file
1.3_Area_with_host_plants_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_csv_entry_sites <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Upload a csv file",
content = c("Data should be uploaded as a comma separated csv file.",
"",
"In the file, data for each region should be in a separate column
and data for each year should be in a separate row. The first row
should have the names of the regions and the first column
should have the years considered.",
"",
"All uploaded files should have the same number of columns and rows.
The order of the regions should be the same in all the files
and the years should always be in ascending order.",
"",
"Even if the area of entry sites was the same for all or some of the years,
data should be given for all the considered years separately.",
"",
"The data for the Finnish PWN surveys is in the file
1.4_Area_of_entry_sites_FI.csv."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_PriorPfree <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Initial prior probability of freedom",
content = c("This determines the probability of freedom before the first survey.",
"",
"If no information is available about the presence/absence of PWN before
the surveys were started, the initial prior probability of freedom can be set to 0.5.",
"",
"The initial prior probability of freedom should be in line with the probability of invasion,
unless reason exists to assume that the probability of invasion was different before
the surveys were initiated. (I.e., if the probability of invasion is assumed to be high,
assuming the initial prior probability of freedom is low is not logical, and vice versa.)",
"",
"It should be noted that if the sensitivity of the annual surveys is low, even a
seemingly uninformative initial prior probability of freedom (0.5)
can have an impact on the probability of freedom for several years."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_Pinv <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Mean time between invasions",
content = c("This is the mean time
between events in which PWN enters the country,
is transferred to a host plant and manages to establish there.",
"",
"If information or estimates about the mean time between invasions are not available,
the considered range can be as wide as needed."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_n_i <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Number of iterations",
content = c("This determines the number of iterations for the Monte Carlo simulation used in the assessment.",
"",
"For preliminary runs, a small number (<1000) is suitable.
For the final assessment, 10 000 iterations are recommended.",
"",
"When the number of iterations is high, computation can take several
minutes, especially if a wide range of mean time between invasions is considered."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_TSe_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Test sensitivity",
content = c("Test sensitivity is the probability that the pest is detected
in the laboratory analysis, given that it was present in the
wood object(s) included in the sample.",
"",
"Test sensitivity is always less than one. But, if inspection site level
design prevalence is determined as apparent design prevalence,
test sensitivity should be set to one."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_TSe_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Test sensitivity",
content = c("Test sensitivity is the probability that the pest is detected
in the laboratory analysis, given that it was present in the Monochamus
beetle(s) included in the sample.",
"",
"Test sensitivity is always less than one. But, if inspection site level
design prevalence is determined as apparent design prevalence,
test sensitivity should be set to one."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_site_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The size of inspection site",
content = c("This is the area covered by one inspection as square kilometers.",
"",
"The size of inspection site should be such that the number of infested
wood objects per inspection site at the inspection site level design
prevalence would be at least one. "),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_site_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The size of inspection site",
content = c("This is the area covered by one inspection as square kilometers.",
"",
"The size of inspection site should be such that the number of infested
Monochamus adults per inspection site at the inspection site level design
prevalence would be at least one. "),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_n_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The number of wood objects sampled per inspected site",
content = c("This is the number of wood objects from which material was taken for
laboratory analysis per inspected site, irrespective of whether
the material from all the objects was pooled or analyzed separately."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_n_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The number of Monochamus sampled per inspected site",
content = c("This is the number of Monochamus collected for laboratory analysis
per inspected site, irrespective of whether all the beetles
were pooled or analyzed separately."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_entry_sites <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The area of entry sites",
content = c("This is the area of sites in with elevated probability of PWN introduction,
i.e. harbors, industrial areas and landfills, in square kilometers."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_host_area <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The area with host plants",
content = c("This is the area with PWN host plants within the area for which the results
of the surveys will be generalized, in square kilometers."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_d_w <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The density of wood objects suitable for sampling",
content = c("This is the number of wood objects suitable for
sampling per square kilometer in the area for which
the results of the survey will be generalized."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_d_M <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The density of adult Monochamus beetles",
content = c("This is the number of adult Monochamus beetles per
square kilometer in the area for which the results
of the survey will be generalized."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_survey_type <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "The aim of the surveys",
content = c("The first option is referred to as import-export survey and the latter as early detection survey.
The pest populations that these two survey types aim to detect differ in two respects.",
"",
"First, for import-export surveys, PWN infestation is expected to be randomly distributed throughout
the country, while for early detection surveys, PWN infestation is expected to be restricted to one region.",
"",
"Second, the design prevalences of import-export surveys can be based merely on what is required
to facilitate trade, while those of early detection surveys should
be defined based on the size of an eradicable PWN population."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_localDP_ie <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Inspection site level design prevalence",
content = c("Inspection site level design prevalence is determined as the proportion
of PWN-infested wood objects of all wood objects suitable for sampling,
and the proportion of PWN-infested Monochamus adults of all Monochamus adults.",
"",
"Design prevalence should be such that PWN could reach it, at least at some point
in time, if it was established in the considered area. Additionally, it
must be such that it corresponds to, at least, one whole infested wood object
and Monochamus adult per inspection site.",
"",
"For import-export surveys, inspection site level design prevalences can
correspond to the prevalence that established PWN populations would likely have in the considered
conditions.",
"",
"For areas where PWN is not expected to cause symptoms and where Bursaphelenchus mucronatus is
established, inspection site level design prevalence may be set equal to observed
prevalence of B. mucronatus.",
"",
"If the prevalence of B. mucronatus has been estimated with similar sampling as that done in
the PWN surveys, inspection site level design prevalence can be determined as apparent prevalence
and test sensitivity (on the tab 'Upload data and define parameter values') can be set to one."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_localDP_ed <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Inspection site level design prevalence",
content = c("Inspection site level design prevalence is determined as the proportion
of PWN-infested wood objects of all wood objects suitable for sampling,
and the proportion of PWN-infested Monochamus adults of all Monochamus adults.",
"",
"Design prevalence should be such that PWN could reach it, at least at some point
in time, if it was established in the considered area. Additionally, it
must be such that it corresponds to, at least, one whole infested wood object
and Monochamus adult per inspection site.",
"",
"For the early detection survey, inspection site level design prevalences should
preferably correspond to a PWN population that is still growing
(i.e., has not reached its maximum prevalence).",
"",
"In areas where PWN is not expected to cause symptoms and where Bursaphelenchus mucronatus
is established, inspection site level design prevalence should be lower than the prevalence of B. mucronatus.",
"",
"If the prevalence of B. mucronatus has been estimated with similar sampling as that done in
the PWN surveys, inspection site level design prevalence can be determined as apparent prevalence
and test sensitivity (on the tab 'Upload data and define parameter values') can be set to one."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_globalDP <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Country level design prevalence",
content = c("For import-export surveys, country level design prevalence is determined as the proportion of
PWN-infested area of the total area with PWN host plants in the area
for which the results of the surveys will be generalized to.",
"",
"Country level design prevalence can be based on requirements of the trading partners,
political considerations, availability of resources, and/or biological plausibility.",
"",
"Country level design prevalence must be such that PWN could reach it, at least at some
point in time, if it was established in the country. Also, it must be such that it corresponds
to, at least, the size of one whole infested inspection site."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
help_max_inf_size <- function(){
tags$i()%>%
helper(type="inline",
size = "m",
title = "Maximum acceptable size of PWN infestation at detection",
content = c("For early detection surveys, region level design prevalence is defined based on
the maximum size of an eradicable PWN infestation in square kilometers.",
"",
"The maximum area from which eradication could be attempted is limited by the financial
and physical resources available for the eradication measures (e.g., the availability of
labor and machinery). If the maximum area from which eradication could be attempted can
be estimated, it may be used as a proxy for the maximum area from which eradication could be
achieved. However, it is important to keep in mind that attempting and achieving are very different
things when it comes to eradicating invasive species.",
"",
"In EU countries, the requirements of the EU emergency measures for PWN (EU 2012) can be used to guide the definition of
the maximum size of an eradicable PWN population. The measures allow EU member states to refrain from
attempting eradication of PWN if the diameter of the infested area exceeds 20 km. Hence, it is
logical to assume that in an early detection survey, PWN should be detected before the diameter of
its infestation is more than 20 km.",
"",
"The area of a PWN infestation that has a 20 km diameter depends on the shape of the area and the proportion
of the area that is covered by PWN host plants. If the infested area is circular, it is, at maximum,
314 km2. In most cases, it is much smaller due to low coverage of PWN host plants. Again, it is important
to remember that it is not at all clear if such a large infestation could be eradicated with the resources
available for delimiting the infested area and conducting the eradication measures."),
buttonLabel = "OK",
easyClose = TRUE,
icon = "question-circle",
colour = "orangered",
fade = FALSE)
}
#########################################################
ui <-
navbarPage("FinnSURV-Assess PWN",
theme = shinythemes::shinytheme("united"),
tabPanel("1. Upload data and define parameter values",
withMathJax(),
tabsetPanel(
tabPanel(h5("1.1 Wood sampling"),
fluidRow(h3("")),
fluidRow(column(3,
wellPanel(h4(tags$b("The number of inspected sites")),
tags$hr(),
help_csv_N_w(),
fileInput("file_N_w","Upload a csv file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table")),
wellPanel(help_site_w(),
numericInput(inputId = "site_w",
label = "The size of inspection site, km\\(^2\\)",
value = 0.35, min = 0, max = 5, step = 0.1)),
wellPanel(
help_TSe_w(),
numericInput(inputId = "TSe_w",
label = "Test sensitivity",
value = 1, min = 0, max = 1, step = 0.01))),
column(3,wellPanel(
fluidRow(column(11,
help_n_w(),
h4(tags$b("The number of wood objects sampled per inspected site")),
tags$hr(),
radioButtons(inputId = "select_n_w_input_type",
label = "",
choices = c("Upload a csv file" = 1,
"Estimate as a probability distribution" = 2),
selected = 2),
tags$hr(),
uiOutput(outputId = "upload_n_w_data"))))),
column(3,conditionalPanel(condition = "input.select_n_w_input_type == '2'",
wellPanel(h5(tags$i("The estimated probability distribution of the number of wood objects sampled per inspected site")),
plotOutput(outputId = "n_wood", height=300), align = "center")))
),
h5(textOutput("Table_legend_N_w")),
tableOutput("table_N_w"),
conditionalPanel(condition = "input.select_n_w_input_type == '1'",
h5(textOutput("Table_legend_n_w")),
tableOutput("table_n_w"))
),
tabPanel(h5("1.2", tags$i("Monochamus"), "trapping"),
fluidRow(h3("")),
fluidRow(column(3,
wellPanel(h4(tags$b("The number of inspected sites")),
tags$hr(),
help_csv_N_M(),
fileInput("file_N_M", "Upload a csv file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table")),
wellPanel(help_site_M(),
numericInput(inputId = "site_M",
label = "The size of inspection site, km\\(^2\\)",
value = 0.25, min = 0, max = 5, step = 0.1)),
wellPanel(help_TSe_M(),
numericInput(inputId = "TSe_M",
label = "Test sensitivity",
value = 1, min = 0, max = 1, step = 0.01))
),
column(3,wellPanel(
fluidRow(column(11,
help_n_M(),
h4(tags$b("The number of", tags$i("Monochamus"), "sampled per inspected site")),
tags$hr(),
radioButtons(inputId = "select_n_M_input_type",
label = "",
choices = c("Upload a csv file" = 1, "Estimate as a probability distribution" = 2),
selected = 1),
tags$hr(),
uiOutput(outputId = "upload_n_M_data"))))),
column(3,conditionalPanel(condition = "input.select_n_M_input_type == '2'",
wellPanel(h5(tags$i("The estimated probability distribution of the number of", tags$i("Monochamus"), "sampled per inspected site")),
plotOutput(outputId = "n_Monochamus",height=300),align = "center")))
),
h5(textOutput("Table_legend_N_M")),
tableOutput("table_N_M"),
conditionalPanel(condition = "input.select_n_M_input_type == '1'",
h5(textOutput("Table_legend_n_M")),
tableOutput("table_n_M"))
),
tabPanel(h5("1.3 Target population"),
fluidRow(h3("")),
fluidRow(column(6,h4("At the level of inspection sites"), align = "center"),
column(3,h4("At the level of regions"), align = "center")),
fluidRow(column(3,
wellPanel(fluidRow(column (11,help_d_w(),
h4(tags$b("The density of wood objects suitable for sampling")),
tags$hr(),
radioButtons(inputId = "select_d_w_input_type",
label = "",
choices = c("Use the estimate from Hannunen and Tuomola (2020)" = 1, "Estimate as a probability distribution" = 2),
selected = 1),
tags$hr(),
uiOutput(outputId = "upload_d_w_data"))))),
column(3,
wellPanel(fluidRow(column(11,help_d_M(),
h4(tags$b("The density of adult", tags$i("Monochamus"), "beetles")),
tags$hr(),
radioButtons(inputId = "select_d_M_input_type",
label = "",
choices = c("Use the estimate from Hannunen and Tuomola (2020)" = 1, "Estimate as a probability distribution" = 2),
selected = 1),
tags$hr(),
uiOutput(outputId = "upload_d_M_data"))))),
column(3,
wellPanel(help_host_area(),
h4(tags$b("The area with host plants, km", tags$sup("2"))),
hr(),
help_csv_host_area(),
fileInput("file_host_area", "Upload a csv file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table")))
),
fluidRow(column(3,
wellPanel(
h5(tags$i("The estimated probability distribution of the density of wood objects suitable for sampling")),
plotOutput("d_wood", height=300), align = "center")),
column(3,
wellPanel(
h5(tags$i("The estimated probability distribution of the density of Monochamus adults")),
plotOutput("d_Monochamus", height=300), align = "center"))),
fluidRow(column(12,
h5(textOutput("Table_legend_host_area")),
tableOutput("table_host_area")))
),
tabPanel(h5("1.4 Entry sites"),
fluidRow(h3("")),
fluidRow(column(3,
wellPanel(help_entry_sites(),
h4(tags$b("The area of entry sites, km",tags$sup("2"))),
tags$hr(),
help_csv_entry_sites(),
fileInput("file_entry_sites", "Upload a csv file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table")))),
fluidRow(column(12,
h5(textOutput("Table_legend_entry_sites")),
tableOutput("table_entry_sites")))
))),
tabPanel("2. Define the aim of the survey",
fluidRow(
column(3,
wellPanel(help_survey_type(),
h4(tags$b("The aim of the surveys is")),
tags$hr(),
radioButtons(inputId = "select_survey_type",
label = "",
choices = c("to provide evidence to justify import requirements related to PWN and
to facilitate export to countries with corresponding requirements" = 1,
"to detect possible PWN invasions early enough to enable successful eradication" = 2),
selected = ""))),
column(3,
uiOutput(outputId = "localDP")),
column(3,
uiOutput(outputId = "globalDP")))),
tabPanel("3. View results",
fluidRow(column(2,
wellPanel(help_PriorPfree(),
numericInput(inputId = "Prior_Pfree",
label = "Initial prior probability of freedom",
value = 0.5, min = 0, max = 1, step = 0.05)),
wellPanel(help_Pinv(),
h5(tags$b("Mean time between invasions, years")),
numericInput(inputId = "Finv_min",
label = "Min",
value = 2, min = 2, max = 100, step = 1),
numericInput(inputId = "Finv_max",
label = "Max",
value = 50, min = 2, max = 10000, step = 10)),
wellPanel(help_n_i(),
numericInput(inputId = "n_i",
label = "Number of iterations",
value = 10, min = 100, max = 10000, step = 100))),
column(1,
actionButton(inputId = "run", label = "RUN"),
tags$hr(),
actionButton(inputId = "cancel", label = "CANCEL")),
column(8,
tabsetPanel(
tabPanel("Sensitivity - Country",
p(),
plotOutput(outputId = "SSe_c"),
tags$hr(),
helpText("The dots denote the medians and the bars the 95% confidence intervals of the assessment results")),
tabPanel("Probability of freedom - Country",
p(),
plotOutput(outputId = "Pfree_c"),
tags$hr(),
helpText("The colored area shows the 95% confidence intervals of the assessment results")),
tabPanel("Sensitivity - Regions",
p(),
plotOutput(outputId = "SSe_r", height = "1000px"),
tags$hr(),
helpText("The dots denote the medians and the bars the 95% confidence intervals of the assessment results")),
tabPanel("Probability of freedom - Regions",
p(),
plotOutput(outputId = "Pfree_r", height = "1000px"),
tags$hr(),
helpText("The colored area shows the 95% confidence intervals of the assessment results"))
)))),
tabPanel("4. Download results",
fluidRow(column(3,
wellPanel(h4(tags$b("The sensitivity of the annual surveys")),
tags$hr(),
selectInput("SSe_table_to_dl","2.5, 50 and 97.5% fractiles as separate csv files",
choices = c("2.5%",
"50%",
"97.5%")),
downloadButton("download_SSe_tables", "Download"),
tags$hr(),
h5(tags$b("All the fractiles as a rds file")),
downloadButton("download_SSe_fractiles", "Download"),
tags$hr(),
h5(tags$b("All iterations as a rds file")),
downloadButton("download_SSe_iterations", "Download")
)),
column(3,
wellPanel(h4(tags$b("The probability of freedom after the last survey")),
tags$hr(),
selectInput("Pfree_table_to_dl","2.5, 50 and 97.5% fractiles as separate csv files",
choices = c("2.5%",
"50%",
"97.5%")),
downloadButton("download_Pfree_tables", "Download"),
tags$hr(),
h5(tags$b("All the fractiles as a rds file")),
downloadButton("download_Pfree_fractiles", "Download"),
tags$hr(),
h5(tags$b("All iterations as a rds file")),
downloadButton("download_Pfree_iterations", "Download")
)),
column(3,
wellPanel(h4(tags$b("Download figures")),
tags$hr(),
help_dl_figs(),
selectInput("fig_to_dl", "Choose a figure",
choices = c("Sensitivity - Country",
"Probability of freedom - Country",
"Sensitivity - Regions",
"Probability of freedom - Regions")),
downloadButton("download_fig", "Download"))
))),
tabPanel("About FinnSURV-Assess PWN",
fluidRow(column(5,
tags$br(),
wellPanel(
p(tags$b("FinnSURV-Assess PWN is a tool for assessing the confidence in freedom from pine wood nematode
(PWN",",", tags$i("Bursaphelenchus xylophilus"),") gained in official quarantine pest surveys
in areas where PWN is not expected to cause symptoms.")),
p(),
p("FinnSURV-Assess PWN can be used to assess both the sensitivity of annual surveys and the probability
of freedom achieved in multiannual surveys. It assumes that a) the surveys are composed of inspections
that cover a fixed sized area and b) in the inspections one or more wood or Monochamus samples are collected.
If all the needed data is provided separately for all regions of a country, the assessment will be done
separately for each region and for the whole country."),
p(),
p("FinnSURV-Assess PWN was developed in the Risk Assessment Unit of the Finnish Food Authority
by Salla Hannunen and Juha Tuomola in 2020. The methodology used in it is described in detail in
Hannunen and Tuomola (2020) and references therein, especially",
tags$a("Cannon (2002)", href = "https://doi.org/10.1016/S0167-5877(01)00262-8", target = "_blank"),",",
tags$a("Martin et al. (2007)", href = "https://doi.org/10.1016/j.prevetmed.2006.09.008", target = "_blank"),",",
tags$a("Efsa (2012)", href = "https://doi.org/10.2903/sp.efsa.2012.EN-366", target = "_blank"),"and",
tags$a("Efsa (2018)", href = "https://doi.org/10.2903/sp.efsa.2018.EN-1399", target = "_blank"),
".")
)
),
column(1),
column(5,
tabsetPanel(
tabPanel("Glossary",
tags$br(),
p("Apparent prevalence = The proportion of samples testing positive"),
p(),
p("Design prevalence = Roughly, design prevalence determines the minimum prevalence that the
survey is aimed to detect. If the pest prevalence is equal to or greater than the design prevalence,
at least one infested individual will be detected in the survey, with the probability equal to the
sensitivity of the survey."),
p(),
p("Early detection survey = A survey that aims to detect possible PWN invasions early enough to
enable successful eradication"),
p(),
p("Entry site = A site where the probability of PWN introduction is elevated, i.e. harbors,
industrial areas and landfills"),
p(),
p("Import-export survey = A survey that aims to provide evidence to justify import requirements
related to PWN and to facilitate export to countries with corresponding requirements"),
p(),
p("Initial prior probability of freedom = The probability that the prevalence of the pest is
below the design prevalence before the first survey"),
p(),
p("Probability of freedom = The probability that the prevalence of the pest is below the design
prevalence if the pest is not detected in the surveys"),
p(),
p("Sensitivity = Roughly, sensitivity determines the probability with which a survey is expected
to succeed in its aim. If the pest prevalence is equal to or greater than the design prevalence,
at least one infested individual will be detected in the survey, with the probability equal to
the sensitivity of the survey."),
p(),
p("Target population at the level of inspection site = Wood objects suitable for sampling / Monochamus adults"),
p(),
p("Target population at the level of regions = The area with PWN host plants in the
area for which the results of the survey will be generalized"),
p(),
p("Test sensitivity = The probability that the pest is detected in the laboratory analysis, given that it
was present in the wood object(s) / Monochamus beetle(s) included in the sample")
),
tabPanel("References",
tags$br(),
p(tags$a("Cannon RM (2002) Demonstrating disease freedom - Combining confidence levels.
Preventive Veterinary Medicine 52: 227-249.",
href = "https://doi.org/10.1016/S0167-5877(01)00262-8", target="_blank")),
p("Corine..."),
p(tags$a("European Food Safety Authority (2012)
A framework to substantiate absence of disease: the risk based estimate
of system sensitivity tool (RiBESS) using data collated according to the EFSA Standard Sample Description -
An example on", tags$i("Echinococcus multilocularis"),". Supporting Publications 2012 9(12):EN-366: 1-44.",
href = "https://doi.org/10.2903/sp.efsa.2012.EN-366", target="_blank")),
p(tags$a("European Food Safety Authority, Ciubotaru RM, Cortinas Abrahantes J, Oyedele J,
Parnell S, Schrader G, Zancanaro G, Vos S (2018) Work-plan and methodology for EFSA
to develop plant pest survey guidelines for EU Member States. EFSA supporting publication 2018 15(3):EN-1399: 1-36",
href = "https://doi.org/10.2903/sp.efsa.2018.EN-1399", target="_blank")),
p(tags$a("European Union (2012) Commission Implementing Decision of 26 September 2012 on
emergency measures to prevent the spread within the Union of",
tags$i("Bursaphelenchus xylophilus"),"(Steiner et Buhrer) Nickle et al. (the pine wood nematode)
(notified under document C(2012) 6543) (2012/535/EU).
Official Journal of the European Union L 266 2.10.2012: 42-52.",
href = "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:02012D0535-20170310", target="_blank")),
p("Hannunen S and Tuomola J (2020)
Assessing the probability of freedom
from pine wood nematode based on 19 years of surveys. NeoBiota..."),
p(tags$a("Martin PAJ, Cameron AR, Greiner M (2007)
Demonstrating freedom from disease using multiple complex data sources
1: A new methodology based on scenario trees.
Preventive Veterinary Medicine 79: 71-97.",
href = "https://doi.org/10.1016/j.prevetmed.2006.09.008", target="_blank"))
),
tabPanel("Copyright",
tags$br(),
p("Please refer to FinnSURV-Assess PWN as:"),
p("Hannunen S and Tuomola J 2020. FinnSURV-Assess PWN - A tool for assessing
the confidence of freedom from the pine wood nematode gained in official surveys.
Finnish Food Authority, Helsinki, Finland. Available at..."),
tags$br(),
p("FinnSURV-Assess PWN is published under", tags$a(href="https://creativecommons.org/licenses/by-nc-sa/4.0/","the Creative Commons Attribution-NonCommercial-ShareAlike 4.0
International", target="_blank"), "license.")
)
)
)))
)
#####################################################
server <- function(input,output,session){
observe_helpers()
# Stop session when the window is closed
session$onSessionEnded(stopApp)
##########
# INTERACTIVE PARTS OF THE UI (RENDER UI)
# Inspection site level design prevalences of the different survey types
output$localDP <- renderUI({
req(input$select_survey_type)
switch(input$select_survey_type,
"1" = wellPanel(help_localDP_ie(),
h4(tags$b("Inspection site level design prevalence")),
tags$hr(),
numericInput(inputId = "DP_w",
label = "Wood",
value = 0.12, min = 0, max = 0.12, step = 0.01),
numericInput(inputId = "DP_M",
label = tags$i("Monochamus"),
value = 0.09, min = 0, max = 0.09, step = 0.01)),
"2" = wellPanel(help_localDP_ed(),
h4(tags$b("Inspection site level design prevalence")),
tags$hr(),
numericInput(inputId = "DP_w",
label = "Wood",
value = 0.06, min = 0, max = 0.12, step = 0.01),
numericInput(inputId = "DP_M",
label = tags$i("Monochamus"),
value = 0.045, min = 0, max = 0.09, step = 0.01)))
})
# Region/country level design prevalences of the different survey types
output$globalDP <- renderUI({
req(input$select_survey_type)
switch(input$select_survey_type,
"1" = wellPanel(help_globalDP(),
h4(tags$b("Country level design prevalence")),
tags$hr(),
numericInput(inputId = "DPr",
label = "",
value = 0.01, min = 0, max = 1, step = 0.001)),
"2" = wellPanel(help_max_inf_size(),
h4(tags$b("Maximum acceptable size of PWN infestation at detection, km",tags$sup("2"))),
tags$hr(),
numericInput(inputId = "max_inf_size",
label = "",
value = 314, min = 1, max = 5000, step = 10)))
})
# Number of wood objects sampled per inspected site: upload data or define as probability distribution
output$upload_n_w_data <- renderUI({
switch(input$select_n_w_input_type,
"1" = fluidRow(column(12,
help_csv_n_w(),
fileInput("file_n_w", "",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table"))),
"2" = fluidRow(
help_pert(),
column(6,
numericInput(inputId = "n_w_min",
label = "Min",
value = 1, min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_w_max",
label = "Max",
value = 5, min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_w_mode",
label = "Mode",
value = 2, min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_w_lambda",
label = "Lambda",
value = 1, min = 1, max =20, step = 1)),
column(12,helpText("See the plot on the right for the distribution")))
)})
# Number of Monochamus sampled per inspected site: upload data or define as probability distribution
output$upload_n_M_data <- renderUI({
switch(input$select_n_M_input_type,
"1"= fluidRow(column(12,
help_csv_n_M(),
fileInput("file_n_M", "",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
helpText("Scroll down to see the uploaded table"))),
"2" = fluidRow(
help_pert(),
column(6,
numericInput(inputId = "n_M_min",
label = "Min",
value = "", min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_M_max",
label = "Max",
value = "", min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_M_mode",
label = "Mode",
value = "", min = 1, max = 1000, step = 1)),
column(6,
numericInput(inputId = "n_M_lambda",
label = "Lambda",
value = "", min = 1, max =20, step = 1)),
column(12,helpText("See the plot on the right for the distribution")))
)})
# Density of wood objects suitable for sampling: upload data or define as porbability distribution
output$upload_d_w_data <- renderUI({
switch(input$select_d_w_input_type,
"1" = fluidRow(column(12,
helpText("See the plot below for the distribution"))),
"2" = fluidRow(
column(11,h5(tags$b("Number per km", tags$sup("2")))),
help_pert(),
column(6,
numericInput(inputId = "d_w_min",
label = "Min",
value = 1, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_w_max",
label = "Max",
value = 60, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_w_mode",
label = "Mode",
value = 30, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_w_lambda",
label = "Lambda",
value = 1, min = 1, max = 10, step = 1)),
column(12,helpText("See the plot below for the distribution")))
)})
# Density of Monochamus adults: upload data or define as probability distribution
output$upload_d_M_data <- renderUI({
switch(input$select_d_M_input_type,
"1"= fluidRow(column(12,
helpText("See the plot below for the distribution"))),
"2" = fluidRow(column(11,h5(tags$b("Number per km", tags$sup("2")))),
help_pert(),
column(6,
numericInput(inputId = "d_M_min",
label = "Min",
value = 1, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_M_max",
label = "Max",
value = 60, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_M_mode",
label = "Mode",
value = 30, min = 1, max = 10000, step = 1)),
column(6,
numericInput(inputId = "d_M_lambda",
label = "Lambda",
value = 1, min = 1, max = 10, step = 1)),
column(12,helpText("See the plot below for the distribution")))
)})
##########
# UPLOADING DATA AND PRINTING IT AS TABLES
# The number of inspected sites in the wood sampling component of the survey
df_N_w <- reactive({
req(input$file_N_w)
A <- read.csv(input$file_N_w$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_N_w <- eventReactive(input$file_N_w,{
"The number of inspected sites"})
output$table_N_w <- renderTable({
req(input$file_N_w)
df_N_w()})
# The number of wood objects sampled per inspected site
df_n_w <- reactive({
req(input$file_n_w)
A <- read.csv(input$file_n_w$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_n_w <- eventReactive(input$file_n_w,{
"The mean number of wood objects sampled per inspected site"})
output$table_n_w <- renderTable({
req(input$file_n_w)
df_n_w()})
# The number of inspected sites in the Monochamsu trapping component of the survey
df2 <- reactive({
req(input$file_N_M)
A <- read.csv(input$file_N_M$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_N_M <- eventReactive(input$file_N_M,{
"The number of inspected sites"})
output$table_N_M <- renderTable({
req(input$file_N_M)
df2()})
# The number of Monochamus sampled per inspected site
df2.1 <- reactive({
req(input$file_n_M)
A <- read.csv(input$file_n_M$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_n_M <- eventReactive(input$file_n_M,{
"The mean number of beetles sampled per inspected site"})
output$table_n_M <- renderTable({
req(input$file_n_M)
df2.1()})
# The area with host plants
df_host_area <- reactive({
req(input$file_host_area)
A <- read.csv(input$file_host_area$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_host_area <- eventReactive(input$file_host_area,{
"The area with host plants, km2"})
output$table_host_area <- renderTable({
req(input$file_host_area)
df_host_area()})
# The area of entry sites
df_entry_sites <- reactive({
req(input$file_entry_sites)
A <- read.csv(input$file_entry_sites$datapath,
header = TRUE,
sep = ",",
quote = "")
A})
output$Table_legend_entry_sites <- eventReactive(input$file_entry_sites,{
"The area of entry sites, km2"})
output$table_entry_sites <- renderTable({
req(input$file_entry_sites)
df_entry_sites()})
##########
# VECTORS NEEDED IN THE CALCULATIONS AND FIGURES
# The considered mean times between invasions
Finv_FI <- eventReactive(input$run,{
seq(input$Finv_min,input$Finv_max,1)
})
# The years when surveys were conducted
Y <- eventReactive(input$run,{
a = data.matrix(df_N_w())
seq(a[1,1],a[nrow(a),1],1)
})
# The number of years when surveys were conducted
n_y <- eventReactive(input$run,{
length(Y())
})
# The names of the regions included in the survey
region_names <- eventReactive(input$run,{
A <- read.csv(input$file_N_w$datapath,
header = TRUE,
sep = ",",
quote = "'")
colnames(A[2:ncol(A)])
})
# The number of regions included in the survey + 1 (to include the whole country)
n_r <- eventReactive(input$run,{
ncol(df_N_w())
})
##########
# UPLOADED DATA FOR THE CALCULATIONS
# The number of inspected sites in the wood sampling component of the survey
N_wood <- reactive({
a = data.matrix(df_N_w())
b = a[,2:ncol(a)]
array(b, dim=c(nrow(b),ncol(b),input$n_i))
})
# The number of inspected sites in the Monochamus trapping component of the survey
N_Monochamus <- reactive({
a = data.matrix(df2())
b = a[,2:ncol(a)]
array(b, dim=c(nrow(b),ncol(b),input$n_i))
})
# The number of wood objects sampled per inspected site
n_wood <- reactive({
if(input$select_n_w_input_type == 1){
a = data.matrix(df_n_w())
b = a[,2:ncol(a)]
A <- array(b, dim=c(nrow(b),ncol(b),input$n_i))
}else{
req(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max)
A <- round(rpert(input$n_i,input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda))
}
A
})
# The number of Monochamus adults sampled per inspected site
n_Monochamus <- reactive({
if(input$select_n_M_input_type == 1){
a = data.matrix(df2.1())
b = a[,2:ncol(a)]
A <- array(b, dim=c(nrow(b),ncol(b),input$n_i))
}else{
req(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max)
A<- round(rpert(input$n_i,input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda))
}
A
})
# The density of wood objects suitable for sampling
d_wood <- reactive({
if(input$select_d_w_input_type == 1){
# The number of Monochamus-suitable dead wood objects per km2
obj <- round(rpert(input$n_i,166,288,398,1))
# The proportion of Monochamus-suitable dead wood objects that is suitable for sampling
psam <- runif(input$n_i,0.05,0.95)
# The density of wood objects suitable for sampling, number/km2
round(obj*psam)
}else{
req(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max)
round(rpert(input$n_i,input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda))
}
})
# The number of wood objects suitable for sampling per inspection site
p_wood <- reactive({
b <- array(d_wood(),dim=c(n_y(),n_r()-1,input$n_i))
c = round(b*input$site_w)
c[c < ceiling(1/input$DP_w)] <- ceiling(1/input$DP_w)
c
})
# The density of Monochamus adults
d_Monochamus <- reactive({
if(input$select_d_M_input_type == 1){
# The number of dead wood objects occupied by Monochamus per km2
obju <- round(rpert(input$n_i,13.28,28.8,47.76,1))
# The number of Monochamus eggs laid per Monochamus-suitable dead-wood object
fobj <- rpert(input$n_i,6,31,88,1)
# The proportion of Monochamus surviving from egg to egg-laying adults
surv <- rpert(input$n_i,0.1,0.25,0.4,1)
# The density of Monochamus adults, number/km2
obju*fobj*surv
}else{
req(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max)
round(rpert(input$n_i,input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda))
}
})
# The number of Monochamus adults per inspection site
p_Monochamus <- reactive({
b <- array(d_Monochamus(),dim=c(n_y(),n_r()-1,input$n_i))
c = round(b*input$site_M)
c[c < ceiling(1/input$DP_M)] <- ceiling(1/input$DP_M)
c
})
# The area with host plants
host_area <- reactive({
a = data.matrix(df_host_area())
b = a[,2:ncol(a)]
array(b, dim=c(nrow(b),ncol(b),input$n_i))
})
# The area of entry sites
entry_sites <- reactive({
a = data.matrix(df_entry_sites())
b = a[,2:ncol(a)]
matrix(b, nrow(b), ncol(b))
})
# The relative probability of invasion to the regions
RP <- reactive({
a = entry_sites()/rowSums(entry_sites())
array(a, dim=c(nrow(a),ncol(a),input$n_i))
})
# The effective probability of infestation for the import-export survey
# and the regional-level design prevalence for the early detection survey
DPr_adj <- reactive({
# The proportion of the target population in the regions
PropPop = host_area()/rowSums(host_area()[,,1])
# Weighted probability of invasion in the regions
WR = RP()/rowSums(PropPop[,,1]*RP()[,,1])
# Effective probability of infestation for the import-export survey
if(input$select_survey_type == 1){
A = input$DPr*WR
# Regional-level design prevalence for the early detection survey
}else{
A = input$max_inf_size/host_area()
}
A
})
##########
# FIGURES FOR THE TABS "UPLOAD DATA"
# The number of wood objects sampled per inspected site
output$n_wood <- renderPlot({
validate(
need(all(input$n_w_min<=input$n_w_mode,
input$n_w_min<=input$n_w_max,
input$n_w_mode<=input$n_w_max,
input$n_w_min >= 0,
input$n_w_mode >= 0,
input$n_w_max >= 0,
input$n_w_lambda >= 0),
"Make sure that min, mode, max and lambda are logical"),
need(any(input$n_w_min!=input$n_w_mode,
input$n_w_min!=input$n_w_max,
input$n_w_mode!=input$n_w_max),
"Cannot present a probability distribution if min, mode and max are the same, but analysis can be run if min, max and lambda are all defined")
)
x <- seq(input$n_w_min,input$n_w_max,0.1)
dist = dpert(x,input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda)
plot(x,dist,type = 'l',
xlab = "Number per inspection", ylab = "Probability")
})
# the number of Monochamus sampled per inspected site
output$n_Monochamus <- renderPlot({
validate(
need(all(input$n_M_min<=input$n_M_mode,
input$n_M_min<=input$n_M_max,
input$n_M_mode<=input$n_M_max,
input$n_M_min >= 0,
input$n_M_mode >= 0,
input$n_M_max >= 0,
input$n_M_lambda >= 0),
"Make sure that min, mode, max and lambda are logical"),
need(any(input$n_M_min!=input$n_M_mode,
input$n_M_min!=input$n_M_max,
input$n_M_mode!=input$n_M_max),
"Cannot present a probability distribution if min, mode and max are the same, but analysis can be run if min, max and lambda are all defined")
)
x <- seq(input$n_M_min,input$n_M_max,0.1)
dist = dpert(x,input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda)
plot(x,dist,type = 'l',
xlab = "Number per inspection", ylab = "Probability")
})
# The density of wood objects suitable for sampling
output$d_wood <- renderPlot({
if(input$select_d_w_input_type == 2){
validate(
need(all(input$d_w_min<=input$d_w_mode,
input$d_w_min<=input$d_w_max,
input$d_w_mode<=input$d_w_max,
input$d_w_min >= 0,
input$d_w_mode >= 0,
input$d_w_max >= 0,
input$d_w_lambda >= 0),
"Make sure that min, mode, max and lambda are logical"),
need(any(input$d_w_min!=input$d_w_mode,
input$d_w_min!=input$d_w_max,
input$d_w_mode!=input$d_w_max),
"Cannot present a probability distribution if min, mode and max are the same, but analysis can be run if min, max and lambda are all defined")
)
x <- seq(input$d_w_min,input$d_w_max,0.1)
dist = dpert(x,input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)
plot(x,dist,type = 'l',
xlab = expression(paste("Number per" ~ km^{2})),
ylab = "Probability")}
else{
dist = round(rpert(600000,166,288,398,1))*runif(600000,0.05,0.95)
res <- hist(dist, freq = FALSE, breaks = 80, xlim=c(0,400))
a = res$breaks+res$breaks[2]/2
x = a[1:length(a)-1]
plot(x,res$density,'l',
xlab = expression(paste("Number per" ~ km^{2})),
ylab = "Probability", main = "")
}
})
# The density of Monochamus adults
output$d_Monochamus <- renderPlot({
if(input$select_d_M_input_type == 2){
validate(
need(all(input$d_M_min<=input$d_M_mode,
input$d_M_min<=input$d_M_max,
input$d_M_mode<=input$d_M_max,
input$d_M_min >= 0,
input$d_M_mode >= 0,
input$d_M_max >= 0,
input$d_M_lambda >= 0),
"Make sure that min, mode, max and lambda are logical"),
need(any(input$d_M_min!=input$d_M_mode,
input$d_M_min!=input$d_M_max,
input$d_M_mode!=input$d_M_max),
"Cannot present a probability distribution if min, mode and max are the same, but analysis can be run if min, max and lambda are all defined")
)
x <- seq(input$d_M_min,input$d_M_max,0.1)
dist = dpert(x,input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)
plot(x,dist,type = 'l',
xlab = expression(paste("Number per" ~ km^{2})),
ylab = "Probability")}
else{
dist = round(rpert(100000,13.28,28.8,47.76,1))*rpert(100000,6,31,88,1)*rpert(100000,0.1,0.25,0.4,1)
res <- hist(dist, freq = FALSE, breaks = 50, xlim=c(0,1600))
a = res$breaks+res$breaks[2]/2
x = a[1:length(a)-1]
plot(x,res$density,'l',
xlab = expression(paste("Number per" ~ km^{2})),
ylab = "Probability", main = "")
}
})
##########
# CALCULATING THE SENSITIVITY OF THE ANNUAL SURVEYS
# All iterations
SSe_iterations <- eventReactive(input$run, {
Sensitivity(N_wood(), n_wood(), p_wood(), input$TSe_w,
N_Monochamus(), n_Monochamus(), p_Monochamus(), input$TSe_M,
host_area(), RP(), DPr_adj(),
input$select_survey_type, input$DP_w, input$DP_M, input$DPr, input$max_inf_size,
n_r(), n_y(), input$n_i)
})
# 2.5, 50,97.5% fractiles
SSe <- eventReactive(input$run, {
Sensitivity_fractiles(SSe_iterations(),n_r(),n_y())
})
#####################
# CALCULATING THE PROBABILITY OF FREEDOM AFTER THE LAST SURVEY (iterations as an Async operation)
nclicks <- reactiveVal(0)
Pfree_iterations_val <- reactiveVal()
inter <- AsyncInterruptor$new()
observeEvent(input$run,{
req(N_wood(), n_wood(), p_wood(), input$TSe_w,
N_Monochamus(),n_Monochamus(),p_Monochamus(),input$TSe_M,
host_area(), entry_sites(),
input$select_survey_type, input$DP_w, input$DP_M, any(input$DPr!="", input$max_inf_size!=""),
input$Prior_Pfree, Finv_FI(), input$n_i)
# Start progress monitor
if(nclicks() == 0){
progress <- AsyncProgress$new(session, min=1, max=100, message = "Computing")
progress$set(message = "Computing", value = 1)
}
# If "Run" is clicked several times, don't do anything as analysis is already running
if(nclicks() != 0){
showNotification("Already running analysis")
return(NULL)
}
# Increment clicks and prevent concurrent analyses
nclicks(nclicks() + 1)
Pfree_iterations_val(NULL)
# Create variables that can be imported to the async operation (since reactive values and input$xxs cannot)
N_wood <- N_wood()
n_wood <- n_wood()
p_wood <- p_wood()
TSe_w = input$TSe_w
N_Monochamus <- N_Monochamus()
n_Monochamus <- n_Monochamus()
p_Monochamus <- p_Monochamus()
TSe_M = input$TSe_M
host_area <- host_area()
RP <- RP()
DPr_adj <- DPr_adj()
n_r <- n_r()
n_y <- n_y()
Pinv_FI <- 1/Finv_FI()
select_survey_type = input$select_survey_type
DP_w = input$DP_w
DP_M = input$DP_M
DPr = input$DPr
max_inf_size = input$max_inf_size
Prior_Pfree = input$Prior_Pfree
n_i = input$n_i
# Compute the iterations as an async operation
Pfree_iterations <- future({
Probability_of_freedom_iterations(progressMonitor1 = function(h) inter$execInterrupts(),
progressMonitor2 = function(h) progress$set(),
N_wood, n_wood, p_wood,TSe_w,
N_Monochamus, n_Monochamus, p_Monochamus,TSe_M,
host_area, RP, DPr_adj,
select_survey_type, DP_w, DP_M, DPr, max_inf_size,
Pinv_FI, Prior_Pfree,
n_r, n_y, n_i)
}) %...>% Pfree_iterations_val()
# After the promise has been evaluated set nclicks to 0 to allow for anlother run
# and close the progress monitor
Pfree_iterations <- finally(Pfree_iterations,
function(){
nclicks(0)
progress$close()
})
# Return something other than the promise so shiny remains responsive
NULL
})
# If cancell is clicked, interrupt computing and show notification
observeEvent(input$cancel,{
inter$interrupt("Error: Stop Future")
showNotification("Analysis cancelled")
})
# Get the 2.5, 50 and 97.5% fractiles
Pfree <- reactive({
req(Pfree_iterations_val())
Pinv_FI <- 1/Finv_FI()
Probability_of_freedom_fractiles(Pfree_iterations_val(),Pinv_FI,n_r(),n_y())
})
#############
# FIGURES FOR THE TAB "VIEW RESULTS"
# SSe - Country
output$SSe_c <- renderPlot({
# Validate and if not valid show an error message
# (need(all(input$file_n_w, any(input$1, input$2,input$3)),"Error message") did not work, so I had to use if...else...)
if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}
req(Pfree_iterations_val())
Plot_SSe_country(Y(),SSe(),n_r())
})
# Pfree - Country
output$Pfree_c <- renderPlot({
if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
# TAALLA
#need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}
req(Pfree_iterations_val())
Plot_Pfree_country(Finv_FI(),Pfree(),n_r())
})
# Pfree - Regions
output$Pfree_r <- renderPlot({
if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}
req(Pfree_iterations_val())
Plot_Pfree_regions(Finv_FI(),Pfree(),region_names())
})
# SSe - Regions
output$SSe_r <- renderPlot({
if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 1 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(input$file_n_w,"Provide information on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 1){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(input$file_n_M,"Provide information on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}else if(input$select_n_w_input_type == 2 & input$select_n_M_input_type == 2){
validate(
need(input$file_N_w, "Upload data on the number of inspected sites in the wood sampling component"),
need(all(input$n_w_min,input$n_w_mode,input$n_w_max,input$n_w_lambda),"Provide information on the number of wood objects sampled per inspection site"),
need(all(input$n_w_min<=input$n_w_mode,input$n_w_min<=input$n_w_max,input$n_w_mode<=input$n_w_max),"Check the information given on the number of wood objects sampled per inspection site"),
need(input$site_w, "Define the size of inspection site for wood sampling"),
need(input$TSe_w, "Define test sensitivity for wood sampling"),
need(input$file_N_M, "Upload data on the number of inspected sites in the Monochamus trapping component"),
need(all(input$n_M_min,input$n_M_mode,input$n_M_max,input$n_M_lambda), "Provide information on the number of Monochamus sampled per inspection site"),
need(all(input$n_M_min<=input$n_M_mode,input$n_M_min<=input$n_M_max,input$n_M_mode<=input$n_M_max),"Check the information given on the number of Monochamus sampled per inspection site"),
need(input$site_M, "Define the size of inspection site for Monochamus trapping"),
need(input$TSe_M,"Define test sensitivity for Monochamus trapping"),
need(any(input$select_d_w_input_type==1,all(input$d_w_min,input$d_w_mode,input$d_w_max,input$d_w_lambda)),"Porvide information on the density of wood objects suitable for sampling"),
need(any(input$select_d_M_input_type==1,all(input$d_M_min,input$d_M_mode,input$d_M_max,input$d_M_lambda)),"Porvide information on the density of Monochamus adults"),
need(all(input$d_w_min<=input$d_w_mode,input$d_w_min<=input$d_w_max,input$d_w_mode<=input$d_w_max),"Check the information given on the density of wood objects suitable for sampling"),
need(all(input$d_M_min<=input$d_M_mode,input$d_M_min<=input$d_M_max,input$d_M_mode<=input$d_M_max),"Check the information given on the density of Monochamus adults"),
need(input$file_host_area,"Upload data on the area with host plants"),
need(input$file_entry_sites,"Upload data on the area of entry sites"),
need(input$select_survey_type, "Select survey type"),
need(all(input$DP_w, input$DP_M, any(input$DPr, input$max_inf_size)),"Define design prevalences"),
need(input$Prior_Pfree, "Determine the prior porbability of freedom"),
need(all(input$Finv_min,input$Finv_max), "Determine the range of mean time between invasions to be considered"),
need(input$n_i,"Determine the number of iterations")
)
}
req(Pfree_iterations_val())
Plot_SSe_regions(Y(),SSe(),region_names())
})
##########
# DOWNLOAD RESULTS
# SSe tables
SSetableInput <- reactive({
a <- as.data.frame(SSe()[,,1])
b <- as.data.frame(SSe()[,,2])
c <- as.data.frame(SSe()[,,3])
colnames(a)[seq(1,ncol(a)-1,1)] <- c(region_names())
colnames(a)[ncol(a)] <- "Country"
colnames(b) <- colnames(a)
colnames(c) <- colnames(a)
switch(input$SSe_table_to_dl,
"2.5%" = a,
"50%" = b,
"97.5%" = c
)
})
output$download_SSe_tables <- downloadHandler(
filename = function(){
paste(input$SSe_table_to_dl, 'csv', sep = ".")},
content = function(file){
write.csv(SSetableInput(), file, row.names = c(Y()))
})
output$download_SSe_fractiles <- downloadHandler(
filename = function(){
paste("SSe_fractiles.rds")},
content = function(file){
saveRDS(SSe(), file=file)
})
output$download_SSe_iterations <- downloadHandler(
filename = function(){
paste("SSe_iterations.rds")},
content = function(file){
saveRDS(SSe_iterations(), file=file)
})
# Pfree tables
PfreetableInput <- reactive({
a <- as.data.frame(Pfree()[,,1])
b <- as.data.frame(Pfree()[,,2])
c <- as.data.frame(Pfree()[,,3])
colnames(a)[seq(1,ncol(a)-1,1)] <- c(region_names())
colnames(a)[ncol(a)] <- "Country"
colnames(b) <- colnames(a)
colnames(c) <- colnames(a)
switch(input$Pfree_table_to_dl,
"2.5%" = a,
"50%" = b,
"97.5%" = c)
})
output$download_Pfree_tables <- downloadHandler(
filename = function(){
paste(input$Pfree_table_to_dl,"csv", sep = ".")},
content = function(file){
write.csv(PfreetableInput(), file, row.names = c(Finv_FI()))
})
output$download_Pfree_fractiles <- downloadHandler(
filename = function(){
paste("Pfree_fractiles.rds")},
content = function(file){
saveRDS(Pfree(), file=file)
})
output$download_Pfree_iterations <- downloadHandler(
filename = function(){
paste("Pfree_iterations.rds")},
content = function(file){
saveRDS(Pfree_iterations_val(), file=file)
})
# Download figures
FigInput <- reactive({
switch(input$fig_to_dl,
"Sensitivity - Country" = Plot_SSe_country(Y(),SSe(),n_r()),
"Probability of freedom - Country" = Plot_Pfree_country(Finv_FI(),Pfree(),n_r()),
"Sensitivity - Regions" = Plot_SSe_regions(Y(),SSe(),region_names()),
"Probability of freedom - Regions" = Plot_Pfree_regions(Finv_FI(),Pfree(),region_names())
)})
output$download_fig <- downloadHandler(
filename = function(){
paste(input$fig_to_dl,"png",sep = ".")
},
content = function(file){
ggsave(FigInput(), file = file)
})
}
############################################################
shinyApp(ui=ui,server=server)
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