library(shiny)
library(magrittr)
library(ggplot2)
library(plotly)
library(DT)

# Define UI for application that draws a histogram
klasyui <- function(id){
  ns <- NS(id)
  fluidPage(
  
  # Application title
  titlePanel("Klasyfikator"),
  
  # Sidebar with a slider input for number of bins 
  sidebarLayout(
    sidebarPanel(
      sliderInput("slider1",
                  "Wiek pacjenta",
                  min = 1,
                  max = 100,
                  value = 1),
      selectInput("select1",strong("Zaburzenia polykania"),choices = list("Nie"=0,"Tak"=1),selected=0),
      selectInput("select2",strong("Bol przy polykaniu"),choices = list("Nie"=0,"Tak"=1),selected=0),
      selectInput("select3",strong("Kaszel"),choices = list("Nie"=0,"Tak"=1),selected=0),
      selectInput("select4",strong("Dusznosci i swiszczacy oddech"),choices = list("Nie"=0,"Tak"=1),selected=0),
      selectInput("select5",strong("Odkrztuszanie wydzieliny z krwia i chrypka"),choices = list("Nie"=0,"Tak"=1),selected=0),
      selectInput("select6",strong("Guz w obrebie gruczolu piersiowego"),choices = list("Nie"=0,"Tak"=1),selected=0),
      selectInput("select7",strong("Zmiany skorne wokol brodawki."),choices = list("Nie"=0,"Tak"=1),selected=0),
      selectInput("select8",strong("Wyciek z brodawki (zwlaszcza krwisty)"),choices = list("Nie"=0,"Tak"=1),selected=0)
      
    ),
    
    # Show a plot of the generated distribution
    mainPanel(
      plotlyOutput("distPlot")
    )
  )
)

}

#ploc krtani piersi,zdrowy
# Define server logic required to draw a histogram
klasyserver <- function(input, output,session) {
  
  output$distPlot <- renderPlotly({
    k=(0.01*as.numeric(input$slider1)+0.1*as.numeric(input$select1)+0.1*as.numeric(input$select2))*100
    if(k>100){
      k=100
    }
    p=(0.01*as.numeric(input$slider1)+0.1*as.numeric(input$select3)+0.1*as.numeric(input$select4)+0.1*as.numeric(input$select5))*100
    if(p>100){
      p=100
    }
    #print(p*100)
    pi=(0.01*as.numeric(input$slider1)+0.1*as.numeric(input$select6)+0.1*as.numeric(input$select7)+0.1*as.numeric(input$select8))*100
    if(pi>100){
      pi=100
    }
    #print(pi*100)
    z=100-(k+p+pi)/3
    x=c("Rak krtani","Rak piersi","Rak pluc","Zdrowy")
    y=c(k,pi,p,z)
    d=data.frame(x,y)
    print(d)
    #z=0.0029*as.numeric(input$slider1)
    
    g=ggplot(d, aes(x,y,fill=x))+ 
      geom_col()+
      labs(x="",y="Prawdopodobienstwo [%]")
    ggplotly(g)
    
    
  })
}