R/run_BAS_App.R
In jywang2016/rBAS: Implementation of the BAS algorithm and its mutation
#' Run shiny interface for BAS/BSAS algorithms
#'
#' @description `run_BAS_App` is built based on `shiny` and `shinythemes`. All you have to do is building your objective function
#' in R code. Then, you can change the parameters in Shiny interface and run BAS/BSAS algorithm.
#' @param func objective function; see example for more informations
#' @param constr constraints function; see example for more informations
#' @param theme shiny interface themes, default `united`; `theme` should be one of c("cerulean","cosmo","cyborg","darkly","flatly",
#' "journal","lumen","paper","readable","sandstone","simplex","slate","spacelab","superhero","united","yeti")
#' see \code{\link[shinythemes]{shinytheme}} for more information.
#' @import shiny
#' @import shinythemes
#' @import ggplot2
#' @importFrom reshape2 melt
#' @examples
#' #======== examples start =======================
#' # BSAS application on Michalewicz function
#' library(rBAS)
#' mich <- function(x){
#' y1 <- -sin(x[1])*(sin((x[1]^2)/pi))^20
#' y2 <- -sin(x[2])*(sin((2*x[2]^2)/pi))^20
#' return(y1+y2)
#' }
#' #run_BAS_App(func = mich)
#' #======== examples end =======================
#' @export
run_BAS_App <- function(func,constr = NULL, theme = 'united'){
shinyApp(
ui = tagList(
#shinythemes::themeSelector(),
navbarPage(
theme = shinytheme(theme),
title = "Shiny interface for BAS algorithms",
tabPanel("BAS",
sidebarPanel(
#report
#textInput(inputId = "txt", label = "Report Title for markdown :",
# value = "Report test1"),
#parms
#parm.init
textInput('init',label = 'Initial parameters-init:',value = ' '),
#parms.lower
textInput(inputId = 'lower',label = 'Lower of params-lower:',value = '-6,0'),
#parms.upper
textInput(inputId = 'upper',label = 'Upper of params-upper:',value = '-1,2'),
#parms.d0
numericInput('d0',label = 'Smallest antenna length-d0:',value = 0.001),
#parms.d1
numericInput('d1',label = 'Initial antenna length-d1:',value = 3),
#parms.eta_d
numericInput('eta_d',label = 'Attenuation constant-eta_d:',value = 0.95),
#parms.step
numericInput('step',label = 'Beetle step length-step:',value = 0.8),
#parms.eta_step
numericInput('eta_step',label = 'Attenuation constant for step-eta_step:',value = 0.95),
#parms.n
numericInput('n',label = 'Iteration numbers-n:',value = 200),
#parms.seed
numericInput('seed',label = 'Random seed-seed:',value = 1),
#parms.trace
#parms.steptol
numericInput('steptol',label = 'Step tolerance-steptol:',value = 0.01),
#parms.pen
numericInput('pen',label = 'penalty conefficient(A lager positive number):',value = 1e5),
#action
actionButton("action", "Run BAS", class = "btn-primary")
),
mainPanel(
tabsetPanel(
tabPanel(title = 'Optimization Progress',
h3("Optimization Progress:"),
verbatimTextOutput("progress")
),
tabPanel(title = 'Optimization Parameters',
h3("Optimization Parameters:"),
verbatimTextOutput("params")
),
tabPanel(title = 'Progress Plot',
h3('Progress Plot:'),
plotOutput('plot')
)
)
)
),
tabPanel("BSAS",
sidebarPanel(
#report
#textInput(inputId = "txt", label = "Report Title for markdown :",
# value = "Report test1"),
#parms
#parm.init
textInput('init2',label = 'Initial parameters-init:',value = ' '),
#parms.lower
textInput(inputId = 'lower2',label = 'Lower of params-lower:',value = '-6,0'),
#parms.upper
textInput(inputId = 'upper2',label = 'Upper of params-upper:',value = '-1,2'),
#parms.d0
numericInput('d02',label = 'Smallest antenna length-d0:',value = 0.001),
#parms.d1
numericInput('d12',label = 'Initial antenna length-d1:',value = 3),
#parms.eta_d
numericInput('eta_d2',label = 'Attenuation constant-eta_d:',value = 0.95),
#parms.step
numericInput('step2',label = 'Beetle step length-step:',value = 0.8),
#parms.eta_step
numericInput('eta_step2',label = 'Attenuation constant for step-eta_step:',value = 0.95),
#parms.n
numericInput('n2',label = 'Iteration numbers-n:',value = 100),
#parms.seed
numericInput('seed2',label = 'Random seed-seed:',value = 12),
#parms.trace
#parms.steptol
numericInput('steptol2',label = 'Step tolerance-steptol:',value = 0.01),
#parms.k
numericInput('k2',label = 'Number of beetles-k:',value = 5),
#parms.p_min
numericInput('p_min2',label = 'p_min(in [0,1)):',value = 0.2),
#parms.p_step
numericInput('p_step2',label = 'p_step(in [0,1)):',value = 0.2),
#parms.n_flag
numericInput('n_flag2',label = 'n_flag(positive integer):',value = 2),
#parms.pen
numericInput('pen2',label = 'penalty conefficient(A lager positive number):',value = 1e5),
#action
actionButton("action2", "Run BSAS", class = "btn-primary")
),
mainPanel(
tabsetPanel(
tabPanel(title = 'Optimization Progress',
h3("Optimization Progress:"),
verbatimTextOutput("progress2")
),
tabPanel(title = 'Optimization Parameters',
h3("Optimization Parameters:"),
verbatimTextOutput("params2")
),
tabPanel(title = 'Progress Plot',
h3('Progress Plot:'),
plotOutput('plot2')
)
)
)
),
tabPanel("BSAS-WPT",
sidebarPanel(
#parms
#parm.init
textInput('init3',label = 'Initial parameters-init:',value = ' '),
#parms.lower
textInput(inputId = 'lower3',label = 'Lower of params-lower:',value = '-6,0'),
#parms.upper
textInput(inputId = 'upper3',label = 'Upper of params-upper:',value = '-1,2'),
#parms.constr
#parms.c2
numericInput('c2',label = 'ratio of step-size and searching distance C2:',value = 5),
#parms.step
numericInput('step3',label = 'Beetle step length-step:',value = 1),
#parms.eta_step
numericInput('eta_step3',label = 'Attenuation constant for step-eta_step:',value = 0.95),
#parms.n
numericInput('n3',label = 'Iteration numbers-n:',value = 200),
#parms.seed
numericInput('seed3',label = 'Random seed-seed:',value = 11),
#parms.trace
#parms.steptol
numericInput('steptol3',label = 'Step tolerance-steptol:',value = 0.01),
#parms.k
numericInput('k3',label = 'Number of beetles-k:',value = 5),
#parms.p_min
numericInput('p_min3',label = 'p_min(in [0,1)):',value = 0.2),
#parms.p_step
numericInput('p_step3',label = 'p_step(in [0,1)):',value = 0.2),
#parms.n_flag
numericInput('n_flag3',label = 'n_flag(positive integer):',value = 2),
#parms.pen
numericInput('pen3',label = 'penalty conefficient(A lager positive number):',value = 1e5),
#action
actionButton("action3", "Run BAS-WPT", class = "btn-primary")
),
mainPanel(
tabsetPanel(
tabPanel(title = 'Optimization Progress',
h3("Optimization Progress:"),
verbatimTextOutput("progress3")
),
tabPanel(title = 'Optimization Parameters',
h3("Optimization Parameters:"),
verbatimTextOutput("params3")
),
tabPanel(title = 'Progress Plot',
h3('Progress Plot:'),
plotOutput('plot3')
)
)
)
),
tabPanel(title = "Authors",
uiOutput('aut')
)
)
),
server = function(input, output,session) {
# value
value <- reactiveValues()
# authors
output$aut <- renderUI({
tagList(tags$h3('Authors:'),
tags$h4('Jiangyu Wang : BSAS & Package Creator'),
a('Github Page', href = 'https://github.com/jywang2016'),
tags$h4('Shuai Li : BAS & BAS-WPT'),
a('Personal Homepage', href = 'http://www4.comp.polyu.edu.hk/~cssli/'),
'&',
a('Googlescholar',href = 'http://scholar.google.com/citations?hl=zh-CN&user=H8UOWqoAAAAJ'),
tags$h4('Xiangyuan Jiang : BAS & BAS-WPT'),
tags$hr(),
tags$h3('Contributors:'),
tags$h4('Xiaoxiao Li : second-order-BAS'),
tags$h4('Tiantian Wang : beetle-swarm-optimization'),
tags$h4('Yue Ruan : binary-BAS'),
tags$h4('Xiaojuan Mo : multi-bar mechanism optimization')
)
})
# BAS
progress_reactive <- eventReactive(input$action,{
if(input$init == ' '){
init <- NULL
}else{
init <- as.numeric(unlist(strsplit(input$init,",")))
}
if(length(input$lower)!=0){
lower <- as.numeric(unlist(strsplit(input$lower,",")))
}
if(length(input$upper)!=0){
upper <- as.numeric(unlist(strsplit(input$upper,",")))
}
result <- BASoptim(fn = func, init = init,
lower = lower,
upper = upper,
constr = constr,
d0 = input$d0, d1 = input$d1, eta_d = input$eta_d,
step = input$step, eta_step = input$eta_step,
n = input$n, steptol = input$steptol,
seed = input$seed,
pen = input$pen)
value[['result']] <- result
})
output$progress <- renderPrint({
progress_reactive()
})
output$params <- renderPrint({
c(value[['result']][1],value[['result']][2])
})
output$plot <- renderPlot({
df_f <- value[['result']]$df$f
df_fb <- value[['result']]$df$fbest
plot_d <- data.frame(Iter = 1:length(df_f),
f = df_f,
fbest = df_fb)
plot_d2 <- melt(data = plot_d,id = 'Iter')
ggplot(plot_d2,aes(x = Iter, y = value, color = variable)) +
geom_line(size = 1,alpha = 0.8)+
geom_point()+
theme_bw()+
theme(
legend.position = c(0.9,0.8)
)+
labs(x = 'Iterations',y = 'Objective function values',color = 'Results')
})
# BSAS
progress_reactive2 <- eventReactive(input$action2,{
if(input$init2 == ' '){
init2 <- NULL
}else{
init2 <- as.numeric(unlist(strsplit(input$init2,",")))
}
if(length(input$lower2)!=0){
lower2 <- as.numeric(unlist(strsplit(input$lower2,",")))
}
if(length(input$upper2)!=0){
upper2 <- as.numeric(unlist(strsplit(input$upper2,",")))
}
result2 <- BSASoptim(fn = func, init = init2,
lower = lower2,
upper = upper2,
constr = constr,
d0 = input$d02, d1 = input$d12, eta_d = input$eta_d2,
step = input$step2, eta_step = input$eta_step2,
n = input$n2, steptol = input$steptol2,
seed = input$seed2,
p_min = input$p_min2, p_step = input$p_step2,
n_flag = input$n_flag2,
k = input$k2,
pen = input$pen2)
value[['result2']] <- result2
})
output$progress2 <- renderPrint({
progress_reactive2()
})
output$params2 <- renderPrint({
c(value[['result2']][1],value[['result2']][2])
})
output$plot2 <- renderPlot({
df_f <- value[['result2']]$df$f
plot_d <- data.frame(Iter = 1:length(df_f),
f = df_f)
ggplot(plot_d,aes(x = Iter, y = f)) +
geom_line(size = 1,alpha = 0.8,color = 'steelblue')+
geom_point(alpha = 0.6, color = 'steelblue')+
theme_bw()+
labs(x = 'Iterations',y = 'Objective function values')
})
#BSAS-WPT
progress_reactive3 <- eventReactive(input$action3,{
if(input$init3 == ' '){
init3 <- NULL
}else{
init3 <- as.numeric(unlist(strsplit(input$init3,",")))
}
if(length(input$lower3)!=0){
lower3 <- as.numeric(unlist(strsplit(input$lower3,",")))
}
if(length(input$upper3)!=0){
upper3 <- as.numeric(unlist(strsplit(input$upper3,",")))
}
result3 <- BSAS_WPT(fn = func, init = init3,
lower = lower3,
upper = upper3,
c2 = input$c2,
constr = constr,
step = input$step3, eta_step = input$eta_step3,
n = input$n3,
steptol = input$steptol3,
seed = input$seed3,
p_min = input$p_min3, p_step = input$p_step3,
n_flag = input$n_flag3,
k = input$k3,
pen = input$pen3)
value[['result3']] <- result3
})
output$progress3 <- renderPrint({
progress_reactive3()
})
output$params3 <- renderPrint({
c(value[['result3']][1],value[['result3']][2])
})
output$plot3 <- renderPlot({
df_f <- value[['result3']]$df$f
plot_d <- data.frame(Iter = 1:length(df_f),
f = df_f)
ggplot(plot_d,aes(x = Iter, y = f)) +
geom_line(size = 1,alpha = 0.8,color = 'steelblue')+
geom_point(alpha = 0.6, color = 'steelblue')+
theme_bw()+
labs(x = 'Iterations',y = 'Objective function values')
})
}
)
}
jywang2016/rBAS documentation built on May 21, 2019, 1:43 a.m.
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#' Run shiny interface for BAS/BSAS algorithms
#'
#' @description `run_BAS_App` is built based on `shiny` and `shinythemes`. All you have to do is building your objective function
#' in R code. Then, you can change the parameters in Shiny interface and run BAS/BSAS algorithm.
#' @param func objective function; see example for more informations
#' @param constr constraints function; see example for more informations
#' @param theme shiny interface themes, default `united`; `theme` should be one of c("cerulean","cosmo","cyborg","darkly","flatly",
#' "journal","lumen","paper","readable","sandstone","simplex","slate","spacelab","superhero","united","yeti")
#' see \code{\link[shinythemes]{shinytheme}} for more information.
#' @import shiny
#' @import shinythemes
#' @import ggplot2
#' @importFrom reshape2 melt
#' @examples
#' #======== examples start =======================
#' # BSAS application on Michalewicz function
#' library(rBAS)
#' mich <- function(x){
#' y1 <- -sin(x[1])*(sin((x[1]^2)/pi))^20
#' y2 <- -sin(x[2])*(sin((2*x[2]^2)/pi))^20
#' return(y1+y2)
#' }
#' #run_BAS_App(func = mich)
#' #======== examples end =======================
#' @export
run_BAS_App <- function(func,constr = NULL, theme = 'united'){
shinyApp(
ui = tagList(
#shinythemes::themeSelector(),
navbarPage(
theme = shinytheme(theme),
title = "Shiny interface for BAS algorithms",
tabPanel("BAS",
sidebarPanel(
#report
#textInput(inputId = "txt", label = "Report Title for markdown :",
# value = "Report test1"),
#parms
#parm.init
textInput('init',label = 'Initial parameters-init:',value = ' '),
#parms.lower
textInput(inputId = 'lower',label = 'Lower of params-lower:',value = '-6,0'),
#parms.upper
textInput(inputId = 'upper',label = 'Upper of params-upper:',value = '-1,2'),
#parms.d0
numericInput('d0',label = 'Smallest antenna length-d0:',value = 0.001),
#parms.d1
numericInput('d1',label = 'Initial antenna length-d1:',value = 3),
#parms.eta_d
numericInput('eta_d',label = 'Attenuation constant-eta_d:',value = 0.95),
#parms.step
numericInput('step',label = 'Beetle step length-step:',value = 0.8),
#parms.eta_step
numericInput('eta_step',label = 'Attenuation constant for step-eta_step:',value = 0.95),
#parms.n
numericInput('n',label = 'Iteration numbers-n:',value = 200),
#parms.seed
numericInput('seed',label = 'Random seed-seed:',value = 1),
#parms.trace
#parms.steptol
numericInput('steptol',label = 'Step tolerance-steptol:',value = 0.01),
#parms.pen
numericInput('pen',label = 'penalty conefficient(A lager positive number):',value = 1e5),
#action
actionButton("action", "Run BAS", class = "btn-primary")
),
mainPanel(
tabsetPanel(
tabPanel(title = 'Optimization Progress',
h3("Optimization Progress:"),
verbatimTextOutput("progress")
),
tabPanel(title = 'Optimization Parameters',
h3("Optimization Parameters:"),
verbatimTextOutput("params")
),
tabPanel(title = 'Progress Plot',
h3('Progress Plot:'),
plotOutput('plot')
)
)
)
),
tabPanel("BSAS",
sidebarPanel(
#report
#textInput(inputId = "txt", label = "Report Title for markdown :",
# value = "Report test1"),
#parms
#parm.init
textInput('init2',label = 'Initial parameters-init:',value = ' '),
#parms.lower
textInput(inputId = 'lower2',label = 'Lower of params-lower:',value = '-6,0'),
#parms.upper
textInput(inputId = 'upper2',label = 'Upper of params-upper:',value = '-1,2'),
#parms.d0
numericInput('d02',label = 'Smallest antenna length-d0:',value = 0.001),
#parms.d1
numericInput('d12',label = 'Initial antenna length-d1:',value = 3),
#parms.eta_d
numericInput('eta_d2',label = 'Attenuation constant-eta_d:',value = 0.95),
#parms.step
numericInput('step2',label = 'Beetle step length-step:',value = 0.8),
#parms.eta_step
numericInput('eta_step2',label = 'Attenuation constant for step-eta_step:',value = 0.95),
#parms.n
numericInput('n2',label = 'Iteration numbers-n:',value = 100),
#parms.seed
numericInput('seed2',label = 'Random seed-seed:',value = 12),
#parms.trace
#parms.steptol
numericInput('steptol2',label = 'Step tolerance-steptol:',value = 0.01),
#parms.k
numericInput('k2',label = 'Number of beetles-k:',value = 5),
#parms.p_min
numericInput('p_min2',label = 'p_min(in [0,1)):',value = 0.2),
#parms.p_step
numericInput('p_step2',label = 'p_step(in [0,1)):',value = 0.2),
#parms.n_flag
numericInput('n_flag2',label = 'n_flag(positive integer):',value = 2),
#parms.pen
numericInput('pen2',label = 'penalty conefficient(A lager positive number):',value = 1e5),
#action
actionButton("action2", "Run BSAS", class = "btn-primary")
),
mainPanel(
tabsetPanel(
tabPanel(title = 'Optimization Progress',
h3("Optimization Progress:"),
verbatimTextOutput("progress2")
),
tabPanel(title = 'Optimization Parameters',
h3("Optimization Parameters:"),
verbatimTextOutput("params2")
),
tabPanel(title = 'Progress Plot',
h3('Progress Plot:'),
plotOutput('plot2')
)
)
)
),
tabPanel("BSAS-WPT",
sidebarPanel(
#parms
#parm.init
textInput('init3',label = 'Initial parameters-init:',value = ' '),
#parms.lower
textInput(inputId = 'lower3',label = 'Lower of params-lower:',value = '-6,0'),
#parms.upper
textInput(inputId = 'upper3',label = 'Upper of params-upper:',value = '-1,2'),
#parms.constr
#parms.c2
numericInput('c2',label = 'ratio of step-size and searching distance C2:',value = 5),
#parms.step
numericInput('step3',label = 'Beetle step length-step:',value = 1),
#parms.eta_step
numericInput('eta_step3',label = 'Attenuation constant for step-eta_step:',value = 0.95),
#parms.n
numericInput('n3',label = 'Iteration numbers-n:',value = 200),
#parms.seed
numericInput('seed3',label = 'Random seed-seed:',value = 11),
#parms.trace
#parms.steptol
numericInput('steptol3',label = 'Step tolerance-steptol:',value = 0.01),
#parms.k
numericInput('k3',label = 'Number of beetles-k:',value = 5),
#parms.p_min
numericInput('p_min3',label = 'p_min(in [0,1)):',value = 0.2),
#parms.p_step
numericInput('p_step3',label = 'p_step(in [0,1)):',value = 0.2),
#parms.n_flag
numericInput('n_flag3',label = 'n_flag(positive integer):',value = 2),
#parms.pen
numericInput('pen3',label = 'penalty conefficient(A lager positive number):',value = 1e5),
#action
actionButton("action3", "Run BAS-WPT", class = "btn-primary")
),
mainPanel(
tabsetPanel(
tabPanel(title = 'Optimization Progress',
h3("Optimization Progress:"),
verbatimTextOutput("progress3")
),
tabPanel(title = 'Optimization Parameters',
h3("Optimization Parameters:"),
verbatimTextOutput("params3")
),
tabPanel(title = 'Progress Plot',
h3('Progress Plot:'),
plotOutput('plot3')
)
)
)
),
tabPanel(title = "Authors",
uiOutput('aut')
)
)
),
server = function(input, output,session) {
# value
value <- reactiveValues()
# authors
output$aut <- renderUI({
tagList(tags$h3('Authors:'),
tags$h4('Jiangyu Wang : BSAS & Package Creator'),
a('Github Page', href = 'https://github.com/jywang2016'),
tags$h4('Shuai Li : BAS & BAS-WPT'),
a('Personal Homepage', href = 'http://www4.comp.polyu.edu.hk/~cssli/'),
'&',
a('Googlescholar',href = 'http://scholar.google.com/citations?hl=zh-CN&user=H8UOWqoAAAAJ'),
tags$h4('Xiangyuan Jiang : BAS & BAS-WPT'),
tags$hr(),
tags$h3('Contributors:'),
tags$h4('Xiaoxiao Li : second-order-BAS'),
tags$h4('Tiantian Wang : beetle-swarm-optimization'),
tags$h4('Yue Ruan : binary-BAS'),
tags$h4('Xiaojuan Mo : multi-bar mechanism optimization')
)
})
# BAS
progress_reactive <- eventReactive(input$action,{
if(input$init == ' '){
init <- NULL
}else{
init <- as.numeric(unlist(strsplit(input$init,",")))
}
if(length(input$lower)!=0){
lower <- as.numeric(unlist(strsplit(input$lower,",")))
}
if(length(input$upper)!=0){
upper <- as.numeric(unlist(strsplit(input$upper,",")))
}
result <- BASoptim(fn = func, init = init,
lower = lower,
upper = upper,
constr = constr,
d0 = input$d0, d1 = input$d1, eta_d = input$eta_d,
step = input$step, eta_step = input$eta_step,
n = input$n, steptol = input$steptol,
seed = input$seed,
pen = input$pen)
value[['result']] <- result
})
output$progress <- renderPrint({
progress_reactive()
})
output$params <- renderPrint({
c(value[['result']][1],value[['result']][2])
})
output$plot <- renderPlot({
df_f <- value[['result']]$df$f
df_fb <- value[['result']]$df$fbest
plot_d <- data.frame(Iter = 1:length(df_f),
f = df_f,
fbest = df_fb)
plot_d2 <- melt(data = plot_d,id = 'Iter')
ggplot(plot_d2,aes(x = Iter, y = value, color = variable)) +
geom_line(size = 1,alpha = 0.8)+
geom_point()+
theme_bw()+
theme(
legend.position = c(0.9,0.8)
)+
labs(x = 'Iterations',y = 'Objective function values',color = 'Results')
})
# BSAS
progress_reactive2 <- eventReactive(input$action2,{
if(input$init2 == ' '){
init2 <- NULL
}else{
init2 <- as.numeric(unlist(strsplit(input$init2,",")))
}
if(length(input$lower2)!=0){
lower2 <- as.numeric(unlist(strsplit(input$lower2,",")))
}
if(length(input$upper2)!=0){
upper2 <- as.numeric(unlist(strsplit(input$upper2,",")))
}
result2 <- BSASoptim(fn = func, init = init2,
lower = lower2,
upper = upper2,
constr = constr,
d0 = input$d02, d1 = input$d12, eta_d = input$eta_d2,
step = input$step2, eta_step = input$eta_step2,
n = input$n2, steptol = input$steptol2,
seed = input$seed2,
p_min = input$p_min2, p_step = input$p_step2,
n_flag = input$n_flag2,
k = input$k2,
pen = input$pen2)
value[['result2']] <- result2
})
output$progress2 <- renderPrint({
progress_reactive2()
})
output$params2 <- renderPrint({
c(value[['result2']][1],value[['result2']][2])
})
output$plot2 <- renderPlot({
df_f <- value[['result2']]$df$f
plot_d <- data.frame(Iter = 1:length(df_f),
f = df_f)
ggplot(plot_d,aes(x = Iter, y = f)) +
geom_line(size = 1,alpha = 0.8,color = 'steelblue')+
geom_point(alpha = 0.6, color = 'steelblue')+
theme_bw()+
labs(x = 'Iterations',y = 'Objective function values')
})
#BSAS-WPT
progress_reactive3 <- eventReactive(input$action3,{
if(input$init3 == ' '){
init3 <- NULL
}else{
init3 <- as.numeric(unlist(strsplit(input$init3,",")))
}
if(length(input$lower3)!=0){
lower3 <- as.numeric(unlist(strsplit(input$lower3,",")))
}
if(length(input$upper3)!=0){
upper3 <- as.numeric(unlist(strsplit(input$upper3,",")))
}
result3 <- BSAS_WPT(fn = func, init = init3,
lower = lower3,
upper = upper3,
c2 = input$c2,
constr = constr,
step = input$step3, eta_step = input$eta_step3,
n = input$n3,
steptol = input$steptol3,
seed = input$seed3,
p_min = input$p_min3, p_step = input$p_step3,
n_flag = input$n_flag3,
k = input$k3,
pen = input$pen3)
value[['result3']] <- result3
})
output$progress3 <- renderPrint({
progress_reactive3()
})
output$params3 <- renderPrint({
c(value[['result3']][1],value[['result3']][2])
})
output$plot3 <- renderPlot({
df_f <- value[['result3']]$df$f
plot_d <- data.frame(Iter = 1:length(df_f),
f = df_f)
ggplot(plot_d,aes(x = Iter, y = f)) +
geom_line(size = 1,alpha = 0.8,color = 'steelblue')+
geom_point(alpha = 0.6, color = 'steelblue')+
theme_bw()+
labs(x = 'Iterations',y = 'Objective function values')
})
}
)
}
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