2021-01-16 02:13:21 +01:00
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library(shiny)
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library(magrittr)
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library(ggplot2)
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library(plotly)
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library(DT)
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# Define UI for application that draws a histogram
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klasyui <- function(id){
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ns <- NS(id)
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fluidPage(
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# Application title
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titlePanel("Klasyfikator"),
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# Sidebar with a slider input for number of bins
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sidebarLayout(
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sidebarPanel(
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sliderInput("slider1",
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"Wiek pacjenta",
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min = 1,
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max = 100,
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value = 1),
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selectInput("select1",strong("Zaburzenia polykania"),choices = list("Nie"=0,"Tak"=1),selected=0),
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selectInput("select2",strong("Ból przy polykaniu"),choices = list("Nie"=0,"Tak"=1),selected=0),
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selectInput("select3",strong("Kaszel"),choices = list("Nie"=0,"Tak"=1),selected=0),
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selectInput("select4",strong("Dusznosci i swiszczacy oddech"),choices = list("Nie"=0,"Tak"=1),selected=0),
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selectInput("select5",strong("Odkrztuszanie wydzieliny z krwia i chrypka"),choices = list("Nie"=0,"Tak"=1),selected=0),
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selectInput("select6",strong("Guz w obrebie gruczolu piersiowego"),choices = list("Nie"=0,"Tak"=1),selected=0),
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selectInput("select7",strong("Zmiany skorne wokol brodawki."),choices = list("Nie"=0,"Tak"=1),selected=0),
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selectInput("select8",strong("Wyciek z brodawki (zwlaszcza krwisty)"),choices = list("Nie"=0,"Tak"=1),selected=0)
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),
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# Show a plot of the generated distribution
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mainPanel(
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plotlyOutput("distPlot")
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)
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)
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)
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}
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#ploc krtani piersi,zdrowy
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# Define server logic required to draw a histogram
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klasyserver <- function(input, output,session) {
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output$distPlot <- renderPlotly({
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k=(0.01*as.numeric(input$slider1)+0.1*as.numeric(input$select1)+0.1*as.numeric(input$select2))*100
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if(k>100){
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k=100
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}
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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
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if(p>100){
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p=100
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}
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#print(p*100)
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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
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if(pi>100){
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pi=100
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}
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#print(pi*100)
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z=100-(k+p+pi)/3
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x=c("Rak krtani","Rak piersi","Rak płuc","Zdrowy")
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y=c(k,pi,p,z)
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d=data.frame(x,y)
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print(d)
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#z=0.0029*as.numeric(input$slider1)
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g=ggplot(d, aes(x,y,fill=x))+
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geom_col()+
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2021-01-16 02:33:32 +01:00
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labs(x="",y="Prawdopodobie<EFBFBD>stwo [%]")
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2021-01-16 02:13:21 +01:00
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ggplotly(g)
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})
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}
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