library(shinydashboard)
dashboardPage(
skin = "green",
dashboardHeader(title = "SDMBench"),
dashboardSidebar(
sidebarMenu(
menuItem("Data", tabName = "get_data"),
menuItem("General Models", tabName = "gen_methods"),
menuItem("MaxEnt", tabName = "profile_methods"),
menuItem("Deep Learning", tabName = "dl_methods")
),
tags$hr(),
checkboxInput("custom_data", "Use custom data?", FALSE),
tags$p("* at the moment just for General Models", style = "margin-left: 15px;"),
fileInput(
"file1",
"Upload custom data",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
actionButton(
"go_custom",
"Parse custom data",
icon = icon("play
"),
style = "width: 200px;font-weight:bold;border: 2px;"
),
tags$hr(),
textInput("text", "Species name:"),
numericInput(
"limit",
"Max number of records:",
1000,
min = 1,
max = 200000
),
selectInput(
"climate_type",
"Climate type:",
c("Default" = "default",
"Future" = "future")
),
textInput("projected_model", "Climate projection*", value = "BC"),
# TODO edit
numericInput("rcp", "rcp (26, 45, 60 or 85):", 45),
numericInput("years", "Years into future (50 or 75):", 50),
numericInput("climate_resolution", "Climate resolution:", 10),
checkboxInput("sample", "Undersample?", FALSE),
tags$p("* check worldclim website for list", style = "margin-left: 15px;"),
selectInput(
"data_partitioning_type",
"Partitioning:",
c(
"Default" = "default",
"Block" = "block",
"Checkerboard1" = "checkerboard1",
"Checkerboard2" = "checkerboard2"
)
),
actionButton(
"go",
"Get Data",
icon = icon("download"),
style = "width: 200px;font-weight:bold;border: 2px;"
),
tags$hr(),
checkboxGroupInput(
"checkGroup",
h5("Algorithm selection"),
choices = list(
"Random Forest" = "classif.randomForest",
"Logistic Regression" = "classif.logreg",
"Decision Tree" = "classif.rpart",
"Support Vector Machines" = "classif.ksvm",
"Gradient Boosting Machine" = "classif.gbm",
"ada Boosting" = "classif.ada",
"Multinomial Regression" = "classif.multinom",
"eXtreme Gradient Boosting" = "classif.xgboost",
"Naive Bayes" = "classif.naiveBayes",
"K-Nearest Neighbours" = "classif.IBk"
),
selected = "classif.randomForest"
),
actionButton("go_bmr", "General Models", style = "width: 200px;"),
actionButton("go_maxent", "MaxEnt", style = "width: 200px;"),
actionButton("go_dl", "Neural Network", style = "width: 200px;")
),
dashboardBody(
shinyjs::useShinyjs(),
tags$head(
tags$link(rel = "stylesheet", type = "text/css", href = "custom.css")
),
tabItems(
tabItem(tabName = "get_data",
fluidRow(
box(
leaflet::leafletOutput("occ_map"),
title = "Occurence Map",
collapsible = TRUE,
collapsed = TRUE,
status = "success",
solidHeader = TRUE,
width = 12
)
),
fluidRow(
box(
div(style = 'overflow-x: scroll', tableOutput('table')),
title = "Climate Variables",
collapsible = TRUE,
collapsed = TRUE,
status = "info",
solidHeader = TRUE,
width = 12
)
)),
tabItem(
tabName = "gen_methods",
fluidRow(
box(
tableOutput("bmr_results"),
title = "Benchmarking Results",
solidHeader = TRUE,
status = "success"
),
box(
plotOutput("bmr_plot1"),
title = "Benchmarking Results (plot)",
solidHeader = TRUE,
status = "info"
)
),
fluidRow(
box(
leaflet::leafletOutput("model_map_1"),
title = "SDM Map 1",
collapsible = TRUE,
collapsed = TRUE
),
box(
leaflet::leafletOutput("model_map_2"),
title = "SDM Map 2",
collapsible = TRUE,
collapsed = TRUE
)
),
fluidRow(
box(
leaflet::leafletOutput("model_map_3"),
title = "SDM Map 3",
collapsible = TRUE,
collapsed = TRUE
),
box(
leaflet::leafletOutput("model_map_4"),
title = "SDM Map 4",
collapsible = TRUE,
collapsed = TRUE
)
),
fluidRow(
box(
leaflet::leafletOutput("model_map_5"),
title = "SDM Map 5",
collapsible = TRUE,
collapsed = TRUE
),
box(
leaflet::leafletOutput("model_map_6"),
title = "SDM Map 6",
collapsible = TRUE,
collapsed = TRUE
)
),
fluidRow(
box(
leaflet::leafletOutput("model_map_7"),
title = "SDM Map 7",
collapsible = TRUE,
collapsed = TRUE
),
box(
leaflet::leafletOutput("model_map_8"),
title = "SDM Map 8",
collapsible = TRUE,
collapsed = TRUE
)
),
fluidRow(
box(
leaflet::leafletOutput("model_map_9"),
title = "SDM Map 9",
collapsible = TRUE,
collapsed = TRUE
),
box(
leaflet::leafletOutput("model_map_10"),
title = "SDM Map 10",
collapsible = TRUE,
collapsed = TRUE
)
)
),
tabItem(tabName = "profile_methods",
fluidRow(
box(
textOutput("maxent_auc"),
title = "MaxEnt AUC",
status = "success",
solidHeader = TRUE
),
box(
leaflet::leafletOutput("maxent_map"),
title = "MaxEnt Map",
collapsible = TRUE,
collapsed = TRUE
)
)),
tabItem(tabName = "dl_methods",
fluidRow(
box(
textOutput("dl_auc"),
plotOutput("dl_history"),
title = "Deep Learning Performance",
status = "success",
solidHeader = TRUE
),
box(
leaflet::leafletOutput("dl_map"),
title = "Deep Learning Map",
collapsible = TRUE,
collapsed = TRUE
)
))
)
)
)
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