# This is the server logic for a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#
# a = simfish()
set.seed(123)
library(shiny)
library(plyr)
library(dplyr)
library(tidyr)
library(ggplot2)
library(ggthemes)
library(roxygen2)
sapply(list.files(pattern="[.]R$", path="simfish/R/", full.names=TRUE), source)
# devtools::load_all('simfish')
shinyServer(function(input, output) {
simmedpop <- reactive({
if (input$species == 'Lorna Drum')
{
MaxAge <- 10
vbk <- 0.195
linf <- 550
t0 <- -0.808
mat50 <- 2
mat95 <- 3
alpha <- 0.00013
beta <- 2.63
Rzero <- 3e6
MaxMove <- 2
Move50 <- 3
Move95 <- 4
steepness <- 0.8
sigmaR <- 0.1
NatM <- 0.52
}
out <- simfish(SimYear = input$Years, VonKn = vbk, VonKs = vbk,
LinfN = linf, LinfS = linf, t0n = t0, t0s = t0,
mat50n = mat50, mat50s = mat50, mat95n = mat95,
mat95s = mat95, alphaN = alpha, betaN = beta,
alphaS = alpha, betaS = beta, MaxMovingN = MaxMove,
MaxMovingS = MaxMove, Move50n = Move50,
Move50s = Move50, Move95n = Move95, Move95s = Move95,
steepnessN = steepness, steepnessS = steepness,
sigmaRn = input$sigmaR, sigmaRs = input$sigmaR, RzeroN = Rzero,
RzeroS = Rzero, MaxAge = MaxAge, NatMn = NatM, NatMs = NatM,
sel50n = input$fish_select[1]/100*linf, sel50s = input$fish_select[1]/100*linf,
sel95n = input$fish_select[2]/100*linf, sel95s = input$fish_select[2]/100*linf,
surv50n = input$surv_select[1]/100*linf, surv50s = input$surv_select[1]/100*linf,
surv95n = input$surv_select[2]/100*linf, surv95s = input$surv_select[2]/100*linf,
HistoricalF = input$f_select)
# out <- simfish(SimYear = input$Years)
return(out)
})
output$biomass_trend <- renderPlot({
# out <- simfish(SimYear = input$Years)
simmedpop()$plots$biomass_plot
# out$plots$biomass_plot
})
output$length_freq <- renderPlot({
simmedpop()$plots$length_plot
})
output$life_plot <- renderPlot({
simmedpop()$plots$life_plot
})
output$recruitment_plot <- renderPlot({
simmedpop()$plots$recruitment_plot
})
output$froese_trend <- renderPlot({
simmedpop()$plots$cope_punt_plot
})
output$cpue_trend <- renderPlot({
simmedpop()$plots$cpue_plot
})
output$catch_trend <- renderPlot({
simmedpop()$plots$catch_plot
})
output$bio_table <- renderTable({
simmedpop()$biomass_data
})
})
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