inst/bn/customDashboard/inst/cd/ui.R
In SAFE-ICU/wiseR: A Shiny Application for End-to-End Bayesian Decision Network Analysis and Web-Deployment
library('bnlearn')
library('rhandsontable')
library('shiny')
library('shinydashboard')
library('dplyr')
library('visNetwork')
library('shinyWidgets')
library('tools')
library('shinyalert')
library('shinycssloaders')
library('rintrojs')
library('arules')
library('psych')
library("DT")
library("linkcomm")
library('igraph')
library("shinyBS")
library("HydeNet")
source('error.bar.R')
source('graph.custom.R')
source('custom.Modules.R')
source('dashboardthemes.R')
nm<-read.csv("name.txt")
th<-read.csv("theme.txt")
myDashboardHeader <- function (..., title = NULL, titleWidth = NULL, disable = FALSE,
.list = NULL) {
items <- c(list(...), .list)
# lapply(items, tagAssert, type = "li", class = "dropdown")
titleWidth <- validateCssUnit(titleWidth)
custom_css <- NULL
if (!is.null(titleWidth)) {
custom_css <- tags$head(tags$style(HTML(gsub("_WIDTH_",
titleWidth, fixed = TRUE, "\n @media (min-width: 768px) {\n .main-header > .navbar {\n margin-left: _WIDTH_;text-align: left;\n }\n .main-header .logo {\n width: _WIDTH_;\n }\n }\n "))))
}
tags$header(class = "main-header", custom_css, style = if (disable)
"display: none;", span(class = "logo", title), tags$nav(class = "navbar navbar-static-top",
role = "navigation", span(shiny::icon("bars"), style = "display:none;"),
# a(href = "#", class = "sidebar-toggle", `data-toggle` = "offcanvas",
# role = "button", span(class = "sr-only", "Toggle navigation")),
div(class = "navbar-custom-menu", tags$ul(class = "nav navbar-nav",
items))))
}
dashboardPage(skin = "blue",
myDashboardHeader(title = nm$x,
titleWidth = "400"
#,tags$li(class = "dropdown", bsButton("homeIntro", label = NULL, icon = icon("question-circle", lib="font-awesome"), style = "primary", size = "large"))
),
dashboardSidebar(width = 50,
sidebarMenu(id = "sidebarMenu",
menuItem(text = "",
icon = shiny::icon("globe"),
tabName = "Structure"
)
)
),
dashboardBody(id ="dashboardBody",
# Include shinyalert Ui
useShinyalert(),
shinyDashboardThemes(
theme = th$x
),
# Include introjs UI
rintrojs::introjsUI(),
#shinythemes::themeSelector(),
#theme = shinytheme("united"),
tags$script(HTML("$('body').addClass('fixed');")),
shinydashboard::tabItems(
shinydashboard::tabItem(tabName = "Structure",
tabBox(id = "visula_tabs",
width = 12,
tabPanel("Bayesian Network",
fluidPage(
shiny::fluidRow(
shiny::column(2, dropdownButton(
fluidRow(column(6,actionButton("exactInference","Learn Exact Inference",class="butt")),column(6,materialSwitch(inputId = "exact", label = "Enable Exact Inferences", status = "primary", right = TRUE))),
hr(),
h4("Select evidence to add to the model"),
shiny::fluidRow(shiny::column(6,actionButton('insertBtn', 'Insert', class = "butt")),
shiny::column(6,actionButton('removeBtn', 'Remove', class = "butt"))
),
shiny::fluidRow(shiny::column(6,tags$div(id = 'placeholder1')),
shiny::column(6,tags$div(id = 'placeholder2'))
),
hr(),
h4("Select an event of interest"),
shiny::h5("Event Node:"),
shiny::selectInput("event",
label = NULL,
""),
shiny::h4("Display inference plot"),
shiny::fluidRow(shiny::column(5,actionButton('plotBtn', 'without error bars', class = "butt")),shiny::column(4,actionButton('plotStrengthBtn', 'with error bars', class = "butt"))),
hr(),
shiny::h4("No. of resampling iterations for error bars"),
textInput("numInterval", label = NULL,placeholder = 25),
selectInput('plotFont',label = "axis label font size",choices = c(0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,5.5,6,6.5,7,7.5,8,8.5,9,9.5,10),selected = 1.5),
selectInput('valueFont',label = "plot value font size",choices = c(0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,5.5,6,6.5,7,7.5,8,8.5,9,9.5,10),selected = 1.5),
label = "Inference Learning",circle = F, status = "primary", icon = icon("bar-chart-o"), width = "500px",tooltip = tooltipOptions(title = "Learn Inferences")
)),
shiny::column(9,shinyWidgets::radioGroupButtons(inputId = "bayesianOption",
choices = c("Bayesian Network","Fitted Local Distributions", "Infer Decisions"),
selected = "Bayesian Network",
justified = FALSE
))
),
shiny::conditionalPanel(
"input.bayesianOption=='Bayesian Network'",
shiny::column(11,
shiny::fluidRow(
shiny::column(2,
div(
h5("Nth Neigbors(of selection)"))),
shiny::column(2,style="padding-right:0px",
shiny::selectInput("neighbornodes",label = NULL,choices = "")),
shiny::column(1,
div(style = "position:absolute;right:0em;",
h5("Modules:"))),
shiny::column(1,style="padding-right:0px",
shiny::selectInput("moduleSelection",label = NULL,"graph")),
shiny::column(2,style="margin-right:20px",dropdownButton(
shiny::fluidRow(shiny::column(6,selectInput('moduleAlgo',label = NULL,choices = c("ward.D","ward.D2", "single", "complete", "average", "mcquitty", "median","centroid"))),shiny::column(1,bsButton("Bcommunities","Build Modules", style="primary"))),
label = "Module Detection",circle = F, status = "primary", width = "300px",tooltip = tooltipOptions(title = "Build modules in the graph")
)),
shiny::column(2,style = "margin-right:8px",
dropdownButton(
div(id="Bgraph",
h4('Group of variables:'),
shiny::fluidRow(shiny::column(6,selectizeInput('varselect',label = "Variables","",multiple = T)),
shiny::column(3,selectInput('varshape',label = "Shape","")),
shiny::column(3, actionButton('group','Group', style="margin-top:25px;"))
),
hr(),
h4('Vector of index:'),
shiny::fluidRow(shiny::column(6,textInput('varselectvector',label = "Variables")),
shiny::column(3,selectInput('varshape2',label = "Shape","")),
shiny::column(3, actionButton('group2','Group', style="margin-top:25px;"))
),
shiny::fluidRow(shiny::column(6,selectInput('modGroup',label = "modules",choices = "")),
shiny::column(3,selectInput('varshape3',label = "Shape","")),
shiny::column(3, actionButton('group3','Group', style="margin-top:25px;"))
),
shiny::fluidRow(shiny::column(6,h4('Visible Neighbors'),div(id = "graphChain",
sliderInput("degree", label = NULL,
min = 1, max = 10,
value = 2
))),
shiny::column(6,h4('Nth Neighbors'), div(id = "NChain",
sliderInput("degreeN", label = NULL,
min = 1, max = 10,
value = 2
)))
),
hr(),
div(id="graphLayout",
h4("Select Graph Layout"),
shiny::selectInput('graph_layout',label = NULL,"layout_nicely")),
selectInput('bayesFont',label = "Node Font",choices = c(1:100),selected = 20)
),
label = "Visual Settings",circle = F, status = "primary", icon = icon("gear"), width = "400px",tooltip = tooltipOptions(title = "graph settings")
)
),
shiny::column(1, bsButton('graphBtn', 'Refresh', icon = icon("refresh"),style = "primary"))),
withSpinner(visNetworkOutput("netPlot",height = "480px"), color= "#2E86C1")
)
),
shiny::conditionalPanel(
"input.bayesianOption=='Infer Decisions'",
dropdownButton(
sliderInput("NumBar", label = "No. of bars",min = 0, max = 1,value = 1,step=1),
actionButton("sortPlot","Sort X-axis"),
label = "Plot",circle = F, status = "primary", icon = icon("gear"), width = "400px",tooltip = tooltipOptions(title = "plot settings")
),
withSpinner(plotOutput("distPlot",height = "450px"), color="#2E86C1")
),
shiny::conditionalPanel(
"input.bayesianOption=='Fitted Local Distributions'",
selectInput("paramSelect",label = "Variable",""),
withSpinner(plotOutput("parameterPlot",height = "450px"),color="#2E86C1")
)
)
),
tabPanel("Decision Networks",
shinyWidgets::radioGroupButtons(inputId = "decisionOption",
choices = c("Decision Network","Policy Table"),
selected = "Decision Network",
justified = FALSE
),
conditionalPanel(
"input.decisionOption=='Decision Network'",
shiny::fluidRow(
shiny::column(2,dropdownButton(
shiny::fluidRow(shiny::column(6,selectInput("parents",label = "Create payoff Node For:",choices = "",multiple = F))),
shiny::fluidRow(shiny::column(10,rHandsontableOutput("payoff"))),
br(),
shiny::fluidRow(shiny::column(6,actionButton("buildDecisionNet2",'build decision net', class = "butt"))),
h5("Set Decision Node"),
shiny::fluidRow(shiny::column(6,selectInput("decisionNode",label = NULL,choices = c())),shiny::column(6,actionButton("set_decision","Set Node",class = "butt"))),
br(),
shiny::fluidRow(shiny::column(6,actionButton("set_policy","Best Policy",class="butt"))),
br(),
label = "Build Network",circle = F, status = "primary", icon = icon("gear"), width = "500px",tooltip = tooltipOptions(title = "Build Network")
))),
shinycssloaders::withSpinner(visNetworkOutput("decisionPlot",height = "450px"),color="#2E86C1")
),
conditionalPanel(
"input.decisionOption=='Policy Table'",
shinycssloaders::withSpinner(DT::dataTableOutput("policyPlot",height = "150px"),color="#2E86C1")
)
)
)
)
)
)
)
SAFE-ICU/wiseR documentation built on Oct. 18, 2021, 8:40 a.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
library('bnlearn')
library('rhandsontable')
library('shiny')
library('shinydashboard')
library('dplyr')
library('visNetwork')
library('shinyWidgets')
library('tools')
library('shinyalert')
library('shinycssloaders')
library('rintrojs')
library('arules')
library('psych')
library("DT")
library("linkcomm")
library('igraph')
library("shinyBS")
library("HydeNet")
source('error.bar.R')
source('graph.custom.R')
source('custom.Modules.R')
source('dashboardthemes.R')
nm<-read.csv("name.txt")
th<-read.csv("theme.txt")
myDashboardHeader <- function (..., title = NULL, titleWidth = NULL, disable = FALSE,
.list = NULL) {
items <- c(list(...), .list)
# lapply(items, tagAssert, type = "li", class = "dropdown")
titleWidth <- validateCssUnit(titleWidth)
custom_css <- NULL
if (!is.null(titleWidth)) {
custom_css <- tags$head(tags$style(HTML(gsub("_WIDTH_",
titleWidth, fixed = TRUE, "\n @media (min-width: 768px) {\n .main-header > .navbar {\n margin-left: _WIDTH_;text-align: left;\n }\n .main-header .logo {\n width: _WIDTH_;\n }\n }\n "))))
}
tags$header(class = "main-header", custom_css, style = if (disable)
"display: none;", span(class = "logo", title), tags$nav(class = "navbar navbar-static-top",
role = "navigation", span(shiny::icon("bars"), style = "display:none;"),
# a(href = "#", class = "sidebar-toggle", `data-toggle` = "offcanvas",
# role = "button", span(class = "sr-only", "Toggle navigation")),
div(class = "navbar-custom-menu", tags$ul(class = "nav navbar-nav",
items))))
}
dashboardPage(skin = "blue",
myDashboardHeader(title = nm$x,
titleWidth = "400"
#,tags$li(class = "dropdown", bsButton("homeIntro", label = NULL, icon = icon("question-circle", lib="font-awesome"), style = "primary", size = "large"))
),
dashboardSidebar(width = 50,
sidebarMenu(id = "sidebarMenu",
menuItem(text = "",
icon = shiny::icon("globe"),
tabName = "Structure"
)
)
),
dashboardBody(id ="dashboardBody",
# Include shinyalert Ui
useShinyalert(),
shinyDashboardThemes(
theme = th$x
),
# Include introjs UI
rintrojs::introjsUI(),
#shinythemes::themeSelector(),
#theme = shinytheme("united"),
tags$script(HTML("$('body').addClass('fixed');")),
shinydashboard::tabItems(
shinydashboard::tabItem(tabName = "Structure",
tabBox(id = "visula_tabs",
width = 12,
tabPanel("Bayesian Network",
fluidPage(
shiny::fluidRow(
shiny::column(2, dropdownButton(
fluidRow(column(6,actionButton("exactInference","Learn Exact Inference",class="butt")),column(6,materialSwitch(inputId = "exact", label = "Enable Exact Inferences", status = "primary", right = TRUE))),
hr(),
h4("Select evidence to add to the model"),
shiny::fluidRow(shiny::column(6,actionButton('insertBtn', 'Insert', class = "butt")),
shiny::column(6,actionButton('removeBtn', 'Remove', class = "butt"))
),
shiny::fluidRow(shiny::column(6,tags$div(id = 'placeholder1')),
shiny::column(6,tags$div(id = 'placeholder2'))
),
hr(),
h4("Select an event of interest"),
shiny::h5("Event Node:"),
shiny::selectInput("event",
label = NULL,
""),
shiny::h4("Display inference plot"),
shiny::fluidRow(shiny::column(5,actionButton('plotBtn', 'without error bars', class = "butt")),shiny::column(4,actionButton('plotStrengthBtn', 'with error bars', class = "butt"))),
hr(),
shiny::h4("No. of resampling iterations for error bars"),
textInput("numInterval", label = NULL,placeholder = 25),
selectInput('plotFont',label = "axis label font size",choices = c(0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,5.5,6,6.5,7,7.5,8,8.5,9,9.5,10),selected = 1.5),
selectInput('valueFont',label = "plot value font size",choices = c(0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,5.5,6,6.5,7,7.5,8,8.5,9,9.5,10),selected = 1.5),
label = "Inference Learning",circle = F, status = "primary", icon = icon("bar-chart-o"), width = "500px",tooltip = tooltipOptions(title = "Learn Inferences")
)),
shiny::column(9,shinyWidgets::radioGroupButtons(inputId = "bayesianOption",
choices = c("Bayesian Network","Fitted Local Distributions", "Infer Decisions"),
selected = "Bayesian Network",
justified = FALSE
))
),
shiny::conditionalPanel(
"input.bayesianOption=='Bayesian Network'",
shiny::column(11,
shiny::fluidRow(
shiny::column(2,
div(
h5("Nth Neigbors(of selection)"))),
shiny::column(2,style="padding-right:0px",
shiny::selectInput("neighbornodes",label = NULL,choices = "")),
shiny::column(1,
div(style = "position:absolute;right:0em;",
h5("Modules:"))),
shiny::column(1,style="padding-right:0px",
shiny::selectInput("moduleSelection",label = NULL,"graph")),
shiny::column(2,style="margin-right:20px",dropdownButton(
shiny::fluidRow(shiny::column(6,selectInput('moduleAlgo',label = NULL,choices = c("ward.D","ward.D2", "single", "complete", "average", "mcquitty", "median","centroid"))),shiny::column(1,bsButton("Bcommunities","Build Modules", style="primary"))),
label = "Module Detection",circle = F, status = "primary", width = "300px",tooltip = tooltipOptions(title = "Build modules in the graph")
)),
shiny::column(2,style = "margin-right:8px",
dropdownButton(
div(id="Bgraph",
h4('Group of variables:'),
shiny::fluidRow(shiny::column(6,selectizeInput('varselect',label = "Variables","",multiple = T)),
shiny::column(3,selectInput('varshape',label = "Shape","")),
shiny::column(3, actionButton('group','Group', style="margin-top:25px;"))
),
hr(),
h4('Vector of index:'),
shiny::fluidRow(shiny::column(6,textInput('varselectvector',label = "Variables")),
shiny::column(3,selectInput('varshape2',label = "Shape","")),
shiny::column(3, actionButton('group2','Group', style="margin-top:25px;"))
),
shiny::fluidRow(shiny::column(6,selectInput('modGroup',label = "modules",choices = "")),
shiny::column(3,selectInput('varshape3',label = "Shape","")),
shiny::column(3, actionButton('group3','Group', style="margin-top:25px;"))
),
shiny::fluidRow(shiny::column(6,h4('Visible Neighbors'),div(id = "graphChain",
sliderInput("degree", label = NULL,
min = 1, max = 10,
value = 2
))),
shiny::column(6,h4('Nth Neighbors'), div(id = "NChain",
sliderInput("degreeN", label = NULL,
min = 1, max = 10,
value = 2
)))
),
hr(),
div(id="graphLayout",
h4("Select Graph Layout"),
shiny::selectInput('graph_layout',label = NULL,"layout_nicely")),
selectInput('bayesFont',label = "Node Font",choices = c(1:100),selected = 20)
),
label = "Visual Settings",circle = F, status = "primary", icon = icon("gear"), width = "400px",tooltip = tooltipOptions(title = "graph settings")
)
),
shiny::column(1, bsButton('graphBtn', 'Refresh', icon = icon("refresh"),style = "primary"))),
withSpinner(visNetworkOutput("netPlot",height = "480px"), color= "#2E86C1")
)
),
shiny::conditionalPanel(
"input.bayesianOption=='Infer Decisions'",
dropdownButton(
sliderInput("NumBar", label = "No. of bars",min = 0, max = 1,value = 1,step=1),
actionButton("sortPlot","Sort X-axis"),
label = "Plot",circle = F, status = "primary", icon = icon("gear"), width = "400px",tooltip = tooltipOptions(title = "plot settings")
),
withSpinner(plotOutput("distPlot",height = "450px"), color="#2E86C1")
),
shiny::conditionalPanel(
"input.bayesianOption=='Fitted Local Distributions'",
selectInput("paramSelect",label = "Variable",""),
withSpinner(plotOutput("parameterPlot",height = "450px"),color="#2E86C1")
)
)
),
tabPanel("Decision Networks",
shinyWidgets::radioGroupButtons(inputId = "decisionOption",
choices = c("Decision Network","Policy Table"),
selected = "Decision Network",
justified = FALSE
),
conditionalPanel(
"input.decisionOption=='Decision Network'",
shiny::fluidRow(
shiny::column(2,dropdownButton(
shiny::fluidRow(shiny::column(6,selectInput("parents",label = "Create payoff Node For:",choices = "",multiple = F))),
shiny::fluidRow(shiny::column(10,rHandsontableOutput("payoff"))),
br(),
shiny::fluidRow(shiny::column(6,actionButton("buildDecisionNet2",'build decision net', class = "butt"))),
h5("Set Decision Node"),
shiny::fluidRow(shiny::column(6,selectInput("decisionNode",label = NULL,choices = c())),shiny::column(6,actionButton("set_decision","Set Node",class = "butt"))),
br(),
shiny::fluidRow(shiny::column(6,actionButton("set_policy","Best Policy",class="butt"))),
br(),
label = "Build Network",circle = F, status = "primary", icon = icon("gear"), width = "500px",tooltip = tooltipOptions(title = "Build Network")
))),
shinycssloaders::withSpinner(visNetworkOutput("decisionPlot",height = "450px"),color="#2E86C1")
),
conditionalPanel(
"input.decisionOption=='Policy Table'",
shinycssloaders::withSpinner(DT::dataTableOutput("policyPlot",height = "150px"),color="#2E86C1")
)
)
)
)
)
)
)
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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