inst/shiny/C19/ui/tabs/3.tab_analysis.R
In Andreaierardi/disCOVIDer19: Covid_19 outbreak analysis
shinydashboard::tabItem(
tabName = "tab_3",
shinydashboard::valueBox(
"Data Analysis",
"Analysis",
icon = icon("chart-bar"),
color = "red",
width = NULL
),
fluidRow(
shinydashboard::box(width = 12,
status= "danger",
solidHeader = TRUE,
title = "Territory selection",
shiny::fluidPage(
shiny::fluidRow(
shiny::column(4,
shiny::selectizeInput(
inputId = "country", label = "Country",
choices = countryNames, selected = "Italy")
),
shiny::column(4,
shiny::selectizeInput(
inputId = "region", label = "Region",
choices = c("--- ALL ---" = "", regNames), selected = NULL)
),
shiny::column(4,
shiny::selectizeInput(
inputId = "province", label = "Province",
choices = c("--- ALL ---" = "", provNames), selected = NULL)
)
)
)
)
),
shinydashboard::box(width = 12,
status= "danger",
solidHeader = FALSE,
title = "Data cleaning",
shiny::fluidRow(
shiny::column(6,
shiny::radioButtons("direction_fill", label = "Direction",
choices = list("Forward" = "forward", "Backward" = "backward"),
selected = "forward")
),
shiny::column(6,
shiny::radioButtons("method_fill", label = "Method",
choices = list("Last Observation Carried Forward" = "locf", "Linear" = "linear"),
selected = "locf")
)
)
),
fluidRow(
shiny::textOutput("log")
),
shinydashboard::valueBox(
"Logistic model",
"Curve fitting on confirmed cases of infection's time series",
icon = icon("analytics"),
color = "navy",
width = NULL
),
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
shiny::htmlOutput("selected_info1")
),
fluidRow(
column(
4,
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
title = "Input",
fluidRow(
column(12,
shiny::sliderInput(inputId = "fitInterval", label = "Choose fitting interval",
min = init_date, max = fin_date, timeFormat = "%d %b",
step = 1, value = c(init_date, fin_date)),
shiny::checkboxInput(inputId = "swab_std", label = "Standardise positive cases by total swabs"),
shiny::checkboxGroupInput(inputId = "plot_type", label = "Plot type",
choices = list("Cumulative cases" = 1, "New cases" = 2),
selected = 1),
hr(),
h3("Residuals"),
shiny::selectInput(inputId = "plot_res_type", "Residuals plot type",
choices = c("Residuals" = "Residuals",
"Standardised residuals" = "Residuals_standardized",
"Autocorrelation" = "Autocorrelation",
"Square root of absolute residuals" = "Sqrt of abs of res vs fitted"),
selected = "Residuals")
)
)
)
),
column(
8,
shinydashboard::box(
color = "red",
status = "danger",
title = "Plot",
h4(shiny::htmlOutput("dates_sugg")),
hr(),
plotly::plotlyOutput("coolplot1") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
width = 12
)
)
),
# ----- summary row
fluidRow(
column(
5,
shinydashboard::tabBox(
width = 12,
title = "Output summary",
id = "tech_tab",
shiny::tabPanel(
"Fitting output",
status = "danger",
verbatimTextOutput("fit_smry")
),
shiny::tabPanel("Tests",
status = "danger",
verbatimTextOutput("resid_smry"))
)
),
column(
7,
shinydashboard::box(
width = 12,
status = "danger",
title = "Residuals",
plotly::plotlyOutput("plot_residual") %>% shinycssloaders::withSpinner(color =
"#dd4b39")
)
)
),
hr(),
# -------- ARIMA ------
shinydashboard::valueBox(
"ARIMA model",
"ARIMA(p,i,q) on log of confirmed cases of infection's time series",
icon = icon("analytics"),
color = "navy",
width = NULL
),
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
shiny::htmlOutput("selected_info2")
),
fluidRow(
column(
4,
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
title = "Input",
shiny::sliderInput(inputId = "arima_interval", label = "Choose fitting interval",
min = init_date, max = fin_date, timeFormat = "%d %b",
step = 1, value = c(init_date,fin_date)),
fluidRow(
column(12,
shiny::sliderInput(inputId = "forecast", label = "Choose forecast lags",
min = 1, max = 40, value = 10),
hr(),
shiny::sliderInput(inputId = "ARIMA_p", label = "Choose p",
min = 0, max = 10,step = 1,value=0),
shiny::sliderInput(inputId = "ARIMA_I", label = "Choose i",
min = 0, max = 3,step = 1,value=0),
shiny::sliderInput(inputId = "ARIMA_q", label = "Choose q",
min = 0, max = 10,step = 1,value=0)
)
)
)),
column(
8,
shinydashboard::box(
color = "red",
status = "danger",
title = "ARIMA forecast",
h3(shiny::htmlOutput("parameters_sugg")),
hr(),
plotly::plotlyOutput("arima_coolplot1") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
)
),
fluidRow(
column(
3,
shinydashboard::box(
color = "red",
status = "danger",
title = "Autocorrelations",
plotly::plotlyOutput("arima_coolplot2") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
),
column(
3,
shinydashboard::box(
color = "red",
status = "danger",
title = "Partial autocorrelations",
plotly::plotlyOutput("arima_coolplot3") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
),
column(
6,
shinydashboard::box(
color = "red",
status = "danger",
title = "Arima Check residuals",
shiny::plotOutput("arima_coolplot4") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
)
),
fluidRow(
column(
6,
shinydashboard::box(
color = "red",
status = "danger",
title = "Arima Data Output",
shiny::verbatimTextOutput("arima_shell_output") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
),
#background-color: #f5f5f5; */
column(
6,
shinydashboard::box(
color = "red",
status = "danger",
title = "Arima residuals output",
tags$head(tags$style(HTML('
pre
{
background-color: #ffffff;
}
'))),
shiny::verbatimTextOutput("arima_shell_resid") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
)
),
#====== FFT ======
shinydashboard::valueBox(
"Fourier Analysis",
"Periodic behaviour analysis",
icon = icon("analytics"),
color = "navy",
width = NULL
),
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
shiny::htmlOutput("selected_info3")
),
fluidRow(
column(
2,
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
title = "Input",
shiny::sliderInput(inputId = "FFT_interval", label = "Choose fitting interval",
min = init_date, max = fin_date, timeFormat = "%d %b",
step = 1, value = c(init_date,fin_date))
)),
column(
5,
shinydashboard::box(
color = "red",
status = "danger",
title = "FFT of daily cases",
shiny::plotOutput("FFT_day_cases") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
width = 12
)
),
column(
5,
shinydashboard::box(
color = "red",
status = "danger",
title = "FFT of the derivate of the daily cases",
shiny::plotOutput("FFT_day_cases_diff") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
width = 12
)
)
#background-color: #f5f5f5; */
),
#====== R0 ======
shinydashboard::valueBox(
"Reproduction number",
"R(t) estimation",
icon = icon("analytics"),
color = "navy",
width = NULL
),
# shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# shiny::htmlOutput("selected_info4")
# ),
#
fluidRow(
#
column(
3,
# shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# title = "Input",
# shiny::sliderInput(inputId = "Gamma_1", label = "Shape parameter",
# min = 0, max = 5 ,step = 0.5,value=1.40),
# shiny::sliderInput(inputId = "Gamma_2", label = "Rate parameter",
# min = 0, max = 5,step = 0.5,value=0.75)
# )
),
column(
9,
# shinydashboard::box(
# color = "red",
# status = "danger",
# title = "R(t)",
# shiny::plotOutput("R_t_evaluation") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
# width = 12
# )
)
),
# fluidRow(
# column(
# 6,
# shinydashboard::box(
# color = "red",
# status = "danger",
# title = "R(t)",
# shiny::plotOutput("R_t_goodness_of_fit") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
# width = 12
# )
# ),
#
# #background-color: #f5f5f5; */
#
#
# column(
# 6,
# shinydashboard::box(
# color = "red",
# status = "danger",
# title = "FFT of R(t)",
# shiny::plotOutput("R_t_evaluation_FFT") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
# width = 12
# )
# )
# ),
#background-color: #f5f5f5; */
#====== SEIR ======
shinydashboard::valueBox(
"SEIR model",
"Compartmental model based on confirmed cases of infection and recovery",
icon = icon("analytics"),
color = "navy",
width = NULL
),
##------------
## DA ELIINARE !!!!
fluidRow(
column(12,
shinydashboard::box(
background = "black",
"Working in progress..."
)
)
)
##------------
#shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# shiny::htmlOutput("selected_info5")
#),
# fluidRow(
#
# column(
# 4,
# shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# title = "Input",
# shiny::sliderInput(inputId = "rate_IT", label = "Mean incubation time",
# min = 0, max = 10, step = 0.1, value = 5.2),
# shiny::sliderInput(inputId = "rate_SRT", label = "Mean timespan from symptoms to recovery",
# min = 0, max = 10, step = 0.1, value=round(log(5)/2) ,1),
# shiny::actionButton(inputId = "est_R0", "If epidemic continued as in initial stages"),
# shiny::actionButton(inputId = "est_Rt", "all times Rt. Refer to previous tab for Rt parameters choice"),
# shiny::sliderInput(inputId = "R0_exp_est_end", label = "If estimating initial R0, number of days to estimate",
# min = 1, max = 20, step = 1, value = 5),
# shiny::sliderInput(inputId = "future", label = "Forecast lags",
# min = 0, max = 100, step = 1, value = 0),
# shiny::checkboxInput(inputId = "plot_data", label = "Show true data points", value = TRUE)
# ),
#
# shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# title = "R0",
# shiny::verbatimTextOutput("SEIR_R0")
# )
#
# ),
#
# column(
# 8,
# shinydashboard::box(
# color = "red",
# status = "danger",
# title = "SEIR plot",
# highcharter::highchartOutput("SEIR_plot") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
# width = 12
# )
# )
#
# )
# fluidRow(
# column(12,
# shinydashboard::box(
# color = "red",
# status = "danger",
# solidHeader = TRUE,
# title = "Input",
# width = 12,
#
# helpText("Under construction...")
# #h5("Incubation time"),
# #hr(),
# #shiny::sliderInput("IT_mean", "Mean", min = 2, max = 10, value = 6),
# #shiny::sliderInput("IT_std", "St. deviation", min = 0.5, max = 1.5, value = 1)
# )
#
# ),
# column(4
# )
# )
)
Andreaierardi/disCOVIDer19 documentation built on Nov. 3, 2020, 2:24 a.m.
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shinydashboard::tabItem(
tabName = "tab_3",
shinydashboard::valueBox(
"Data Analysis",
"Analysis",
icon = icon("chart-bar"),
color = "red",
width = NULL
),
fluidRow(
shinydashboard::box(width = 12,
status= "danger",
solidHeader = TRUE,
title = "Territory selection",
shiny::fluidPage(
shiny::fluidRow(
shiny::column(4,
shiny::selectizeInput(
inputId = "country", label = "Country",
choices = countryNames, selected = "Italy")
),
shiny::column(4,
shiny::selectizeInput(
inputId = "region", label = "Region",
choices = c("--- ALL ---" = "", regNames), selected = NULL)
),
shiny::column(4,
shiny::selectizeInput(
inputId = "province", label = "Province",
choices = c("--- ALL ---" = "", provNames), selected = NULL)
)
)
)
)
),
shinydashboard::box(width = 12,
status= "danger",
solidHeader = FALSE,
title = "Data cleaning",
shiny::fluidRow(
shiny::column(6,
shiny::radioButtons("direction_fill", label = "Direction",
choices = list("Forward" = "forward", "Backward" = "backward"),
selected = "forward")
),
shiny::column(6,
shiny::radioButtons("method_fill", label = "Method",
choices = list("Last Observation Carried Forward" = "locf", "Linear" = "linear"),
selected = "locf")
)
)
),
fluidRow(
shiny::textOutput("log")
),
shinydashboard::valueBox(
"Logistic model",
"Curve fitting on confirmed cases of infection's time series",
icon = icon("analytics"),
color = "navy",
width = NULL
),
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
shiny::htmlOutput("selected_info1")
),
fluidRow(
column(
4,
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
title = "Input",
fluidRow(
column(12,
shiny::sliderInput(inputId = "fitInterval", label = "Choose fitting interval",
min = init_date, max = fin_date, timeFormat = "%d %b",
step = 1, value = c(init_date, fin_date)),
shiny::checkboxInput(inputId = "swab_std", label = "Standardise positive cases by total swabs"),
shiny::checkboxGroupInput(inputId = "plot_type", label = "Plot type",
choices = list("Cumulative cases" = 1, "New cases" = 2),
selected = 1),
hr(),
h3("Residuals"),
shiny::selectInput(inputId = "plot_res_type", "Residuals plot type",
choices = c("Residuals" = "Residuals",
"Standardised residuals" = "Residuals_standardized",
"Autocorrelation" = "Autocorrelation",
"Square root of absolute residuals" = "Sqrt of abs of res vs fitted"),
selected = "Residuals")
)
)
)
),
column(
8,
shinydashboard::box(
color = "red",
status = "danger",
title = "Plot",
h4(shiny::htmlOutput("dates_sugg")),
hr(),
plotly::plotlyOutput("coolplot1") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
width = 12
)
)
),
# ----- summary row
fluidRow(
column(
5,
shinydashboard::tabBox(
width = 12,
title = "Output summary",
id = "tech_tab",
shiny::tabPanel(
"Fitting output",
status = "danger",
verbatimTextOutput("fit_smry")
),
shiny::tabPanel("Tests",
status = "danger",
verbatimTextOutput("resid_smry"))
)
),
column(
7,
shinydashboard::box(
width = 12,
status = "danger",
title = "Residuals",
plotly::plotlyOutput("plot_residual") %>% shinycssloaders::withSpinner(color =
"#dd4b39")
)
)
),
hr(),
# -------- ARIMA ------
shinydashboard::valueBox(
"ARIMA model",
"ARIMA(p,i,q) on log of confirmed cases of infection's time series",
icon = icon("analytics"),
color = "navy",
width = NULL
),
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
shiny::htmlOutput("selected_info2")
),
fluidRow(
column(
4,
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
title = "Input",
shiny::sliderInput(inputId = "arima_interval", label = "Choose fitting interval",
min = init_date, max = fin_date, timeFormat = "%d %b",
step = 1, value = c(init_date,fin_date)),
fluidRow(
column(12,
shiny::sliderInput(inputId = "forecast", label = "Choose forecast lags",
min = 1, max = 40, value = 10),
hr(),
shiny::sliderInput(inputId = "ARIMA_p", label = "Choose p",
min = 0, max = 10,step = 1,value=0),
shiny::sliderInput(inputId = "ARIMA_I", label = "Choose i",
min = 0, max = 3,step = 1,value=0),
shiny::sliderInput(inputId = "ARIMA_q", label = "Choose q",
min = 0, max = 10,step = 1,value=0)
)
)
)),
column(
8,
shinydashboard::box(
color = "red",
status = "danger",
title = "ARIMA forecast",
h3(shiny::htmlOutput("parameters_sugg")),
hr(),
plotly::plotlyOutput("arima_coolplot1") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
)
),
fluidRow(
column(
3,
shinydashboard::box(
color = "red",
status = "danger",
title = "Autocorrelations",
plotly::plotlyOutput("arima_coolplot2") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
),
column(
3,
shinydashboard::box(
color = "red",
status = "danger",
title = "Partial autocorrelations",
plotly::plotlyOutput("arima_coolplot3") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
),
column(
6,
shinydashboard::box(
color = "red",
status = "danger",
title = "Arima Check residuals",
shiny::plotOutput("arima_coolplot4") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
)
),
fluidRow(
column(
6,
shinydashboard::box(
color = "red",
status = "danger",
title = "Arima Data Output",
shiny::verbatimTextOutput("arima_shell_output") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
),
#background-color: #f5f5f5; */
column(
6,
shinydashboard::box(
color = "red",
status = "danger",
title = "Arima residuals output",
tags$head(tags$style(HTML('
pre
{
background-color: #ffffff;
}
'))),
shiny::verbatimTextOutput("arima_shell_resid") %>% shinycssloaders::withSpinner(color =
"#dd4b39"),
width = 12
)
)
),
#====== FFT ======
shinydashboard::valueBox(
"Fourier Analysis",
"Periodic behaviour analysis",
icon = icon("analytics"),
color = "navy",
width = NULL
),
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
shiny::htmlOutput("selected_info3")
),
fluidRow(
column(
2,
shinydashboard::box(
width = 12,
status = "danger",
solidHeader = TRUE,
title = "Input",
shiny::sliderInput(inputId = "FFT_interval", label = "Choose fitting interval",
min = init_date, max = fin_date, timeFormat = "%d %b",
step = 1, value = c(init_date,fin_date))
)),
column(
5,
shinydashboard::box(
color = "red",
status = "danger",
title = "FFT of daily cases",
shiny::plotOutput("FFT_day_cases") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
width = 12
)
),
column(
5,
shinydashboard::box(
color = "red",
status = "danger",
title = "FFT of the derivate of the daily cases",
shiny::plotOutput("FFT_day_cases_diff") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
width = 12
)
)
#background-color: #f5f5f5; */
),
#====== R0 ======
shinydashboard::valueBox(
"Reproduction number",
"R(t) estimation",
icon = icon("analytics"),
color = "navy",
width = NULL
),
# shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# shiny::htmlOutput("selected_info4")
# ),
#
fluidRow(
#
column(
3,
# shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# title = "Input",
# shiny::sliderInput(inputId = "Gamma_1", label = "Shape parameter",
# min = 0, max = 5 ,step = 0.5,value=1.40),
# shiny::sliderInput(inputId = "Gamma_2", label = "Rate parameter",
# min = 0, max = 5,step = 0.5,value=0.75)
# )
),
column(
9,
# shinydashboard::box(
# color = "red",
# status = "danger",
# title = "R(t)",
# shiny::plotOutput("R_t_evaluation") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
# width = 12
# )
)
),
# fluidRow(
# column(
# 6,
# shinydashboard::box(
# color = "red",
# status = "danger",
# title = "R(t)",
# shiny::plotOutput("R_t_goodness_of_fit") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
# width = 12
# )
# ),
#
# #background-color: #f5f5f5; */
#
#
# column(
# 6,
# shinydashboard::box(
# color = "red",
# status = "danger",
# title = "FFT of R(t)",
# shiny::plotOutput("R_t_evaluation_FFT") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
# width = 12
# )
# )
# ),
#background-color: #f5f5f5; */
#====== SEIR ======
shinydashboard::valueBox(
"SEIR model",
"Compartmental model based on confirmed cases of infection and recovery",
icon = icon("analytics"),
color = "navy",
width = NULL
),
##------------
## DA ELIINARE !!!!
fluidRow(
column(12,
shinydashboard::box(
background = "black",
"Working in progress..."
)
)
)
##------------
#shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# shiny::htmlOutput("selected_info5")
#),
# fluidRow(
#
# column(
# 4,
# shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# title = "Input",
# shiny::sliderInput(inputId = "rate_IT", label = "Mean incubation time",
# min = 0, max = 10, step = 0.1, value = 5.2),
# shiny::sliderInput(inputId = "rate_SRT", label = "Mean timespan from symptoms to recovery",
# min = 0, max = 10, step = 0.1, value=round(log(5)/2) ,1),
# shiny::actionButton(inputId = "est_R0", "If epidemic continued as in initial stages"),
# shiny::actionButton(inputId = "est_Rt", "all times Rt. Refer to previous tab for Rt parameters choice"),
# shiny::sliderInput(inputId = "R0_exp_est_end", label = "If estimating initial R0, number of days to estimate",
# min = 1, max = 20, step = 1, value = 5),
# shiny::sliderInput(inputId = "future", label = "Forecast lags",
# min = 0, max = 100, step = 1, value = 0),
# shiny::checkboxInput(inputId = "plot_data", label = "Show true data points", value = TRUE)
# ),
#
# shinydashboard::box(
# width = 12,
# status = "danger",
# solidHeader = TRUE,
# title = "R0",
# shiny::verbatimTextOutput("SEIR_R0")
# )
#
# ),
#
# column(
# 8,
# shinydashboard::box(
# color = "red",
# status = "danger",
# title = "SEIR plot",
# highcharter::highchartOutput("SEIR_plot") %>% shinycssloaders::withSpinner(color = "#dd4b39"),
# width = 12
# )
# )
#
# )
# fluidRow(
# column(12,
# shinydashboard::box(
# color = "red",
# status = "danger",
# solidHeader = TRUE,
# title = "Input",
# width = 12,
#
# helpText("Under construction...")
# #h5("Incubation time"),
# #hr(),
# #shiny::sliderInput("IT_mean", "Mean", min = 2, max = 10, value = 6),
# #shiny::sliderInput("IT_std", "St. deviation", min = 0.5, max = 1.5, value = 1)
# )
#
# ),
# column(4
# )
# )
)
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