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app.R
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app.R
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library(shiny)
library(dplyr)
library(prophet)
library(ggplot2)
library(DT)
library(shinythemes)
library(shinyjs)
# UI ------------------------------
ui <- fluidPage(
theme = shinytheme("united"),
shinyjs::useShinyjs(),
titlePanel("Prophet Forecasting"),
# Sidebar
fluidPage(sidebarPanel(width=3,
tabsetPanel(
## Tab prophet parameters
tabPanel(HTML("Parameters"),
### paramter: growth
radioButtons("growth","",
c('linear'), inline = TRUE),
### parameter: yearly.seasonality
checkboxInput("yearly","yearly.seasonality", value = TRUE),
### parameter: weekly.seasonality
checkboxInput("monthly","weekly.seasonality", value = TRUE),
### parameter: n.changepoints
numericInput("n.changepoints","n.changepoints", value = 25),
### parameter: seasonality.prior.scale
numericInput("seasonality_scale","seasonality.prior.scale", value = 10),
### parameter: changepoint.prior.scale
numericInput("changepoint_scale","changepoint.prior.scale", value = 0.05, step = 0.01),
### parameter: holidays.prior.scale
numericInput("holidays_scale","holidays.prior.scale", value = 10),
### parameter: mcmc.samples
numericInput("mcmc.samples", "mcmc.samples", value = 0),
### parameter: interval.width
numericInput("interval.width", "interval.width", value= 0.8, step = 0.1),
### parameter: uncertainty.samples
numericInput("uncertainty.samples","uncertainty.samples", value = 1000)
),
## Tab predict parameters -------------------------
tabPanel(HTML("Prediction <br> Setting"),
## make_future_dataframe() parameters ------------------
### paramater: periods
numericInput("periods","periods",value=10),
### parameter: freq
selectInput("freq","freq",
choices = c('day', 'week', 'month', 'quarter','year'))
))
),
# Main panel -------------------------
mainPanel(
fluidRow(
## upload file -----------------
column(width = 6,
fileInput("ts_file","Upload File (*.csv)",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")))),
fluidRow(
## plot button -----------------
column(width = 6,
shinyjs::disabled(actionButton("plot_btn2", "Fit & Plot",
style = "width:80%; margin-top: 25px;")))
),
fluidRow(column(width = 12,
uiOutput("msg"))),
fluidRow(column(width = 12,
uiOutput("msg2"))),
fluidRow(column(width = 12)
),
## plot/results tabs --------------------------------
fluidRow(column(width=12,
tabsetPanel(
tabPanel("Forecast Plot",
conditionalPanel("input.plot_btn2",
div(id = "output-container1",
tags$img(src = "spinner.gif",
id = "loading-spinner"),
plotOutput("ts_plot")
)
)
),
tabPanel("Prophet Plot Components",
conditionalPanel("input.plot_btn2",
div(id = "output-container2",
tags$img(src = "spinner.gif",
id = "loading-spinner"),
plotOutput("prophet_comp_plot")
)
)
)
# tabPanel("Forecast Results",
# conditionalPanel("output.data",
# uiOutput("dw_button")
# ),
# conditionalPanel("input.plot_btn2",
# div(id = "output-container3",
# tags$img(src = "spinner.gif",
# id = "loading-spinner"),
# dataTableOutput("data")))
# )
)
)
),
## test output --------
verbatimTextOutput("test")
)
)
)
# Server
server <- function(input, output, session) {
## function: duplicatedRecative values
duplicatedRecative <- function(signal){
values <- reactiveValues(val="")
observe({
values$val <- signal()
})
reactive(values$val)
}
## read csv file data
dat <- reactive({
req(input$ts_file)
file_in <- input$ts_file
# read csv
read.csv(file_in$datapath, header = T)
})
## Toggle submit button state according to data
observe({
if(!(c("ds","y") %in% names(dat()) %>% mean ==1))
shinyjs::disable("plot_btn2")
else if(c("ds","y") %in% names(dat()) %>% mean ==1)
shinyjs::enable("plot_btn2")
})
## logistic_check -------------------
# logistic_check <- eventReactive(input$plot_btn2, {
# # req(dat())
# if( (input$growth == "logistic") & !("cap" %in% names(dat())) )
# {
# return("error")
# }
# else
# return("no_error")
# })
## create prophet model -----------
prophet_model <- eventReactive(input$plot_btn2,{
req(dat(),
input$n.changepoints,
input$seasonality_scale, input$changepoint_scale,
input$holidays_scale, input$mcmc.samples,
input$mcmc.samples, input$interval.width,
input$uncertainty.samples)
# if(input$growth == "logistic"){
# validate(
# need(try("cap" %in% names(dat())),
# "Error: for logistic 'growth', the input dataframe must have a column 'cap' that specifies the capacity at each 'ds'."))
# }
# mutate dataframe
datx <- dat() %>%
mutate(y = log(y))
kk <- prophet(datx,
growth = input$growth,
changepoints = NULL,
n.changepoints = input$n.changepoints,
yearly.seasonality = input$yearly,
weekly.seasonality = input$monthly,
seasonality.prior.scale = input$seasonality_scale,
changepoint.prior.scale = input$changepoint_scale,
holidays.prior.scale = input$holidays_scale,
mcmc.samples = input$mcmc.samples,
interval.width = input$interval.width,
uncertainty.samples = input$uncertainty.samples,
fit = T)
return(kk)
})
## dup reactive
p_model <- duplicatedRecative(prophet_model)
## Make dataframe with future dates for forecasting
future <- eventReactive(input$plot_btn2,{
req(p_model(),input$periods, input$freq)
make_future_dataframe(p_model(),
periods = input$periods,
freq = input$freq,
include_history = T
)
})
## dup reactive --------------
p_future <- duplicatedRecative(future)
## predict future values -----------------------
forecast <- reactive({
req(prophet_model(),p_future())
predict(prophet_model(),p_future())
})
## dup reactive --------------
#p_forecast <- duplicatedRecative(forecast)
## plot forecast -------------
output$ts_plot <- renderPlot({
g <- plot(p_model(), forecast())
g+theme_classic()
})
## plot prophet components --------------
output$prophet_comp_plot <- renderPlot({
prophet_plot_components(p_model(),forecast())
})
## create datatable from forecast dataframe --------------------
# output$data <- renderDataTable({
# # req(logistic_check()!="error")
# datatable(forecast()) %>%
# formatRound(columns=2:17,digits=4)
# })
## error msg ------------------------
output$msg <- renderUI({
if(c("ds","y") %in% names(dat()) %>% mean !=1)
"Invalid Input: dataframe should have at least two columns named (ds & y)"
})
}
# Run the application ---------------------------
shinyApp(ui = ui, server = server)