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objects in UI.R
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objects in UI.R
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##objects
##login items
login_screen<-fluidPage(tags$h1("EWARS Dashboard +"),
column(width=8,align="left",offset =0,
box(width =4,
wellPanel(tags$h3("Please login"),
textInput("user_name","user name",value="demo"),
passwordInput("pwd","Password",value="demo_2019"),
actionButton("lg_in","login",
style="color: white; background-color:#3c8dbc;
padding: 10px 15px; width: 150px; cursor: pointer;
font-size: 18px; font-weight: 300;")
)
)
)
)
output_graphs<-tabsetPanel(
tabPanel("Runnin",
fluidRow(
column(10,plotlyOutput("plot1",height ="20%",width="50%"))
)),
tabPanel("Evaluation",
fluidRow(
column(10,plotlyOutput("plot2",inline =F,height ="20%",width="50%"))
)),
tabPanel("Runnin +Evaluation",
fluidRow(
column(12,plotlyOutput("plot3",height ="20%",width="50%"))
)),
tabPanel("Sensitivity & PPV",
fluidRow(
column(5,
wellPanel(tableOutput("table1")))
)
),
tabPanel("Auto-calibration outputs",
fluidRow(
column(5,wellPanel(tableOutput("table2")))
)),
tabPanel("Output files",
uiOutput("output_files")
)
)
output_dis<-column(3,
selectInput(inputId = "district",
label = "District",
choices = c(15,20,3),
selected =4,
multiple =F))
output_dis1<-"inputPanel(fluidRow(
column(6,
selectInput(inputId = 'district_dB2',
label = 'District',
choices = 999,
selected =999,
multiple =F))))
"
output_dis2<-"inputPanel(
selectInput(inputId = 'district',
label = 'District',
choices = sel_districts(),
selected =sel_districts()[1],
multiple =F)
)"
dat_opts<- tabPanel("Data",
column(12,
shinydashboardPlus::box(width=12,
fileInput('dat', 'choose file to upload', accept=c('.xls','.xlsx','.csv')),
textInput("original_data_sheet_name", "Choice of sheet name for the original data", "Sheet1"),
checkboxInput("graph_per_district",
"Specify graph per district/municipality option",value =TRUE),
#checkboxInput("generating_surveillance_workbook",
#"Generate surveillance workbooks", value=FALSE),
checkboxInput("spline",
"Spline", value=FALSE),
selectInput(inputId = "run_per_district",
label = "District codes",
choices = c(15,20,3,999),
selected =999,
multiple =T),
checkboxInput("Run_all",
"Run all districts",
value =F))
))
sel_vars<-tabPanel("Variables & Runnin",
column(12,
shinydashboardPlus::box(width=12,
#selectInput('country_code', 'country code',
#c("XX"),
#selected="XX", width="35%"),
#textInput("psswd", "8 digit password", "12345678"),
selectInput("population",
"Variable for annual total Population",
"population",multiple =F),
selectInput("number_of_cases",
"Variable for the weekly number of outbreak",
"weekly_hospitalised_cases",multiple =F),
selectInput("alarm_indicators", selected =c("rainsum","meantemperature"),
"Alarm indicator(s)",
choices=c("rainsum","meantemperature"),multiple =T),
# when spline is selected show options to select varaibles
conditionalPanel("input.spline",
selectInput("spline_alarm_indicators", selected =c("rainsum","meantemperature"),
"Spline Alarm indicator(s)",
choices=c("rainsum","meantemperature"),multiple =T)),
sliderInput("stop_runinYear",
"Specify the year the run-in period stops",
value =2012,step =1,
min=1990,max=2030,sep=''),
sliderInput("stop_runinWeek",
"Specify the week the run-in period stops",
value =52,step =1,
min=52,max=52)
)))
calib1<- column(12,
shinydashboardPlus::box(
width = 12,
sliderInput(
"outbreak_week_length",
#"Outbreak weeks to declare outbreak period/stop outbreak",
"Outbreak period",
min = 1,
max = 24,
value = 3,
step = 1,
ticks = F,
dragRange = F
),
sliderInput(
"alarm_window",
"Alarm window size",
value = 3,
min = 1,
max = 24,
step = 1
),
sliderInput(
"alarm_threshold",
#"Alarm threshold for alarm signal",
"Alarm threshold",
value = .12,
min = 0.0005,
max = 1,
step = 0.0001
)
,
selectInput(
"season_length",
"Seasons in a year",
choices = c(1,2,3,4,6,12),
selected=1,multiple =F
)
)
)
calib2<- column(12,
shinydashboardPlus::box(
width = 12,
sliderInput(
"z_outbreak",
#"Multiplier for standard deviation to vary endemic channel",
"Z-outbreak",
value = 1.25,
min = 1,
max = 4,
step = 0.01
),
sliderInput(
"outbreak_window",
"Outbreak window size",
value = 4,
min = 1,
max = 24,
step = 1
),
sliderInput(
"prediction_distance",
#"Distance between current week and target week to predict an outbreak signal",
"Prediction Distance (time lag)",
value = 2,
min = 1,
max = 24
),
sliderInput(
"outbreak_threshold",
#"Cut-off value to define the outbreak signal",
"Outbreak threshold",
value = 0.75,
min = 0.00005,
max = 1,
step = 0.0001)
)
)
calib1_auto<- column(12,
shinydashboardPlus::box(
width = 12,
sliderInput(
"outbreak_week_length",
"Outbreak weeks to declare outbreak period/stop outbreak",
min = 1,
max = 24,
value = c(2,6),
step = 1,
ticks = F,
dragRange = F
),
sliderInput(
"alarm_window",
"Alarm window size",
value = c(2,6),
min = 1,
max = 24,
step = 1
),
sliderInput(
"alarm_threshold",
"Alarm threshold for alarm signal",
value = c(0.05,0.6),
min = 0.0005,
max = 1,
step = 0.0001
),
sliderInput(
"season_length",
"Seasons in a year",
value = c(52,52),
min = 1,
max = 52,
step = 1 )
)
)
calib2_auto<-column(12,
shinydashboardPlus::box(
width = 12,
sliderInput(
"z_outbreak",
"Multiplier for standard deviation to vary endemic channel",
value = c(0.05,3),
min = 0.0001,
max = 4,
step = 0.001
),
sliderInput(
"outbreak_window",
"Outbreak window size",
value = c(2,10),
min = 1,
max = 24,
step = 1
),
sliderInput(
"prediction_distance",
"Distance between current week and target week to predict an outbreak signal",
value = c(3,12),
min = 1,
max = 24
),
sliderInput(
"outbreak_threshold",
"Cut-off value to define the outbreak signal",
value = c(0.05,0.6),
min = 0.00005,
max = 1,
step = 0.0001)
)
)
row_elements1.x<-fluidRow(column(3,
checkboxInput("automate",
"Automatic Calibration",
value =F)),
)
row_elements1<-fluidRow(column(3,
checkboxInput("automate",
"Automatic Calibration",
value =F)),
column(5,
selectInput(
"iterations",
"Auto iterations",
choices = c(100,500,1000,5000,10000),
selected=100,multiple =F
))
)
row_elements2<-fluidRow(
column(3,
tabsetPanel(id="input_pan",
dat_opts,
sel_vars,
tabPanel("calib1",calib1),
tabPanel("Calib2",calib2)
)),
column(7,output_graphs,
output_dis),
column(1,
actionButton('save_mode','Save Model',
style="color: forestgreen; background-color:grey(0.5);
padding: 10px 15px; height: 80px; cursor: pointer;
font-size: 20px; font-weight: 400;")
)
)
row_elements2_restricted<-fluidRow(
column(3,
tabsetPanel(id="input_pan",
dat_opts,
sel_vars,
tabPanel("calib1",calib1),
tabPanel("Calib2",calib2)
)),
column(8,output_graphs,
output_dis)
)
dashboad_elements_I<-tabPanel("Dashboard I",
fluidPage(
row_elements1,
row_elements2
)
) #actionButton("manual",icon=icon("refresh"),
#"Manual Calibration", value=T),
dashboad_elements_restricted_I<-tabPanel("Dashboard I",
fluidPage(
row_elements1,
row_elements2_restricted
)
)
#base_input<-"selectInput('District','District',choices =c(3,15,20,999),selected =999,multiple =F),
base_input<-"selectInput('year','Year',choices =2019:2030,selected =2019,multiple =F),
selectInput('week','Week',choices =1:53,selected =2,multiple =F),
numericInput('Cases','Weekly number of cases',value=NA),
numericInput('Population','Population',value=NA)"
## nest Risk mapping in dashboard II
## risk mapping elements
output_graphs_spat_Agg<-tabsetPanel(
tabPanel("Spatial_Plots",
uiOutput("Error"),
uiOutput("Spat_Plot")
)
,
tabPanel("Time_series",
uiOutput("Time_series_Plots")
),
tabPanel("Risk_maps",
fluidRow(
column(12,tmapOutput("plot3_spat"))
))
)
output_graphs_spat_point<-tabsetPanel(
tabPanel("Spatial_Plots",
fluidRow(
uiOutput("Error"),
column(12,tmapOutput("Spat_Plot"))
)
)
,
tabPanel("Risk_maps",
fluidRow(
uiOutput("plot3_spat")
))
)
output_year_spat<-column(3,
sliderInput(inputId = "Year_plot_spat",
label = "Year",
min = 2008,
max=2030,
value =2012,
sep='',
step=1),
sliderInput(inputId = "Week_plot_spat",
label = "Week",
min = 1,
max=52,
step=1,
sep='',
value =35)
)
dat_opts_spat<- tabPanel("Spatial data Upload",
column(12,
shinydashboardPlus::box(width=12,
##choose point/ lat long data
fileInput('shape_file', 'District sub-district boundary file (.shp file)',
accept=c('.shp','.dbf','.shx','.prj'),
multiple =T),
## choose aggregated or point data
selectInput("spat_Input_Type", selected =c("sub_district"),
"Geographic data input (point or aggregated)",
choices=c("point (LatLon)","sub_district"),multiple =F),
fileInput('dat_spat', 'Choose surveillance data with spatial inputs', accept=c('.xls','.xlsx','.csv')),
uiOutput("Spat_error"),
selectInput("population_spat",
"Variable for annual total Population",
"population",multiple =F),
selectInput("number_of_cases_spat",
"Variable for the weekly number of outbreak",
"weekly_hospitalised_cases",multiple =F),
selectInput("alarm_indicators_spat", selected =c("rainsum","meantemperature"),
"Alarm indicator(s)",
choices=c("rainsum","meantemperature"),multiple =T),
# when spline is selected show options to select variables
sliderInput("stop_runinYear_spat",
"Specify the year the run-in period stops",
value =2012,step =1,
min=1990,max=2030,sep=''),
sliderInput("stop_runinWeek_spat",
"Specify the week the run-in period stops",
value =52,step =1,
min=1,max=52)
)
))
row_elements_spat<-fluidRow(
column(4,
tabsetPanel(id="input_pan_spat",
dat_opts_spat
# sel_vars
)),
column(8,
uiOutput("spat_Display")
,
output_year_spat)
)
dashboad_elements_Risk_mapping<-tabPanel("Risk mapping",
fluidPage(
row_elements_spat
)
)
dashboad_elements_II<-tabPanel("Dashboard II",
column(3,
tabsetPanel(
tabPanel("Parameters",
wellPanel(tags$h3("Alarm Indicators:"),
uiOutput('a_vars')),
wellPanel(br(),
tableOutput("alr_vars")),
wellPanel(tags$h3("Spline Indicators:"),
uiOutput('s_vars')))
)
),
column(9,
tabsetPanel(
tabPanel("Input Data",
fluidPage(fluidRow(uiOutput("input_dataset")),
inputPanel(
fluidRow(
column(3,
actionButton('ins_dat','Update table'))),
column(3,offset =6,
actionButton('Refresh_DB','Refresh'))
),
DT::dataTableOutput("data_dis")
)),
tabPanel("Prediction tables",
# inputPanel(uiOutput("sel_diss")),
DT::dataTableOutput("pred_dis")
),
tabPanel("Outbreak",
#inputPanel(uiOutput("sel_diss")),
plotOutput("db2_plot1",width ="700px",height ="320px")
),
tabPanel("Probability",
#inputPanel(uiOutput("sel_diss1")),
plotOutput("db2_plot2",width ="700px",height ="320px")
),
tabPanel("Outbreak and Probability",
#inputPanel(uiOutput("sel_diss1")),
plotOutput("db2_plot3",width ="700px",height ="320px")
),
tabPanel("Response",
#inputPanel(uiOutput("sel_diss1")),
plotOutput("db2_plot4")
),
dashboad_elements_Risk_mapping
)
)
)
dashboad_elements_III<-tabPanel("Help",
tags$br(),
tags$br(),
tags$div(
HTML(paste(tags$strong("Early Warning and Response System for Dengue Outbreaks: Operational Guide using the web-based Dashboard"),
tags$a(href="https://drive.google.com/file/d/1MJWocIyu3Ecdy950w0Z2d9i50hceEFA1/view?usp=sharing", target="_blank", tags$br(),tags$b(" Operational Guide")),
sep = ""))
),
# tags$div(
# HTML(paste(tags$strong("Addendum: Automatised Early Warning And Respons System"),
# tags$a(href="https://drive.google.com/open?id=1VCZbxO6Qfy7oyt_2O1T_XGa-VNhjaCsF", target="_blank", tags$br(),tags$b("Automatised Early Warning And Respons System")),
# sep = ""))
#),
tags$div(
HTML(paste(tags$strong("Demo Excel workbook"),
tags$a(href="https://drive.google.com/file/d/1ujlq5oZVSF8dg7A3KN6Csw-5LsEWqYzF/view?usp=sharing", target="_blank", tags$br(),tags$b("Demo data")),
sep = ""))),
tags$div(
HTML(paste(tags$strong("Risk mapping demo files"),
tags$a(href="https://drive.google.com/drive/folders/1GXZ6vwEONEqxvUjLB4QMG0aduKkyIGIF?usp=sharing", target="_blank", tags$br(),tags$b("Risk mapping demo files")),
sep = ""))),
tags$br(),
tags$br()
)
dashboad_elements_IV<-tabPanel("R scripts and Files",
tags$br(),
tags$br(),
tags$div(
HTML(paste(tags$strong("R scripts and Files"),
tags$a(href="https://umeauniversity-my.sharepoint.com/:f:/g/personal/odse0001_ad_umu_se/EpwpHBzDg2pIr6pZPIMtEnoBvVJUHSL2NZ97RoOQi6sx7A?e=225F2c", target="_blank", tags$br(),tags$b("App R scripts and files")),
sep = ""))
)
)
## admin page
add_user<-tabPanel("Add users",
fluidPage(fluidRow(
inputPanel(textInput("First_name","First Name"),
textInput("Last_name","Last name"),
textInput("users_name","User name"),
passwordInput("pass_word","Password"),
textInput("email","email address"),
selectInput(inputId = 'role',
label = 'Role',
choices = c("Admin","District Manager"),
selected ="District Manager",
multiple =F),
conditionalPanel('input.role=="District Manager"',
selectInput(inputId = 'district_manage',
label = 'District access',
choices =c(9999,99999) ,
selected =9999,
multiple =T)),
actionButton("Enter_user","Add user",
style="color: white; background-color:#3c8dbc;
padding: 10px 15px; width: 150px; cursor: pointer;
font-size: 18px; font-weight: 300;")
))),
fluidRow(
column(8,
DT::dataTableOutput("users_dat")),
column(4,
DT::dataTableOutput("users_districts"))
))
remove_user<-tabPanel("Delete users",
fluidPage(
inputPanel(fluidRow(column(10,
selectInput(inputId = 'user_de',
label = 'Users to delete',
choices = "john doe",
selected ="john doe",
multiple =T,width =unit(5,'in'))))),
fluidRow(column(4,
actionButton("Delete_user","Delete",
style="color: white; background-color:#3c8dbc;
padding: 10px 15px; width: 150px; cursor: pointer;
font-size: 18px; font-weight: 300;"))
)))
admin_page<-tabPanel("Admin page",
tabsetPanel(
add_user,
remove_user)
)
source("new_model_UI_elements.R")
ui_yes<-fluidPage(fluidRow(
column(3,offset =5,
uiOutput("title_txt")),
column(2,offset =11,
uiOutput("logged_in_user"),
uiOutput('logout'))
),
fluidRow(navbarPage("",
#dashboad_elements_I,
#dashboad_elements_II,
# admin_page,
#dashboad_elements_Risk_mapping,
dashboad_elements_New_model,
dashboad_elements_New_model_pros,
admin_page,
dashboad_elements_III,
dashboad_elements_IV
# admin page
)
)
)
ui_yes_Restricted<-fluidPage(fluidRow(
column(3,offset =5,
uiOutput("title_txt")),
column(2,offset =11,
uiOutput("logged_in_user"),
uiOutput('logout'))
),
fluidRow(navbarPage("",
dashboad_elements_New_model_pros,
dashboad_elements_III,
dashboad_elements_IV
# admin page
)
)
)
## UI nologin
UI_NO_login<-fluidPage(fluidRow(
column(3,offset =5,
uiOutput("title_txt")),
#column(2,offset =11,
#uiOutput("logged_in_user"),
#uiOutput('logout'))
),
fluidRow(navbarPage("",
dashboad_elements_I,
dashboad_elements_II,
#admin_page,
#dashboad_elements_Risk_mapping,
dashboad_elements_New_model,
dashboad_elements_New_model_pros,
dashboad_elements_III,
dashboad_elements_IV
# admin page
)
)
)