#R二元运算符闪亮的非数字参数

Question

我试图让问题对新输入更具反应性，这是给出错误的地方

Pwh_Design=reactive((input$Pwh+0.2*(input$Pso-input$Pwh)))

Gtd=Pwh_Design-P_operating_point_formation/(0-D_operating_point)

这是在服务器中。

整个应用程序：

用户界面：

library(shiny)

# Define UI for application that draws a histogram
shinyUI(fluidPage(

# Application title
titlePanel("OTIS Gas Lift"),
fluidRow(column(width = 6,
                numericInput(inputId = "Dmax",label = "Depth to mid perforation",value = 7500),
                numericInput("Pwh","Pwh",100),
                numericInput("Tres","Tres",182),
                numericInput("Pso","P Casing at Surface",870),
                numericInput("Psc","P Casing at Depth D1",1050),
                numericInput("D1","D1",7000),
                numericInput("P_across_valve","P_across_valve",100),
                numericInput("GL","Load Grad",0.5),
                numericInput("Pwf","Pwf",1760),
                numericInput("RGOR","Required GOR",400)
                ),
         column(width = 6,
         numericInput("FGOR","Formation GOR",200),
         numericInput("Twh","Twh",100),
         numericInput("Pko","kill pressure at Surface",920),
         numericInput("Pk","Kill Pressure at D2",1100),
         numericInput("D2","D2",7000),
         numericInput("T_inj","T_inj",100),
         numericInput("q","Desired Production Rate STB/d",600),
         numericInput("R","R",0.1534),
         numericInput("Gf","Flowing Grad before inj",0.4)
         )),
fluidRow(submitButton(text = "Apply Changes",width = "100%")),
splitLayout(tableOutput(outputId = "table"),plotOutput(outputId = "plot"))))

'''

这是服务器

library(shiny)

shinyServer(function(input, output) {
    Dmax=reactiveValues()       #to mid perforation ft

#one of those two next must be given

FGOR=reactiveValues()          #scf/STB Formation GOR
Pwh=reactiveValues()           #psig
Twh=reactiveValues()           #degree fahrenheit
Tres=reactiveValues()          #degree fahrenheit

#casing and kill gradients
Pso=reactiveValues()           #psig
Pcs=reactiveValues()          #psig at 7000ft
D1=reactiveValues()           #ft
Pko=reactiveValues()           #psig
Pk=reactiveValues()            #psig at 7000ft
D2=reactiveValues()           #ft

P_across_valve=reactiveValues()          #psig
T_inj=reactiveValues()         #degree fahrenheit
GL=reactiveValues()           #load gradient (kill fluid grad)
q=reactiveValues()    
Pwf=reactiveValues()          #psi or BHP
RGOR=reactiveValues()          #scf/STB required GOR
R=reactiveValues()

Gf=reactiveValues()            #flowing gradient before injection default value

library(ggplot2)
library(dplyr)
#plot basics
plot<-reactive(ggplot+
    coord_cartesian(xlim = c(0,input$Pwf+500))+
    scale_y_continuous(trans = "reverse")+
    scale_x_continuous(position = "top"))


#Flowing Gradient
#slope Gf
#point (pwf,Dmax)
#get p1 at depth 4000ft
p1=reactive(input$Pwf-input$Gf*(input$Dmax-4000))
flowing_gradient<-reactive(data.frame(D=c(4000,input$Dmax),P=c(p1,input$Pwf)))

plot0<-plot+
    geom_point(data = flowing_gradient,aes(x=P,y=D))+
    geom_line(data = flowing_gradient,aes(x=P,y=D))



#casing gradient
casing_gradient<-reactive(data.frame(D=c(0,input$D1),P=c(input$Pso,input$Pcs)))

plot1<-plot0+geom_point(data=casing_gradient,aes(x=P,y=D))+
    geom_line(data=casing_gradient,aes(x=P,y=D))

Gc=reactive((input$Pso-input$Pcs)/(0-input$D1))

#killing gradient
killing_gradient<-reactive(data.frame(D=c(0,input$D2),P=c(input$Pko,input$Pk)))

plot2<-plot1+geom_point(data=killing_gradient,aes(x=P,y=D))+
    geom_line(data=killing_gradient,aes(x=P,y=D))
Gk=reactive((input$Pko-input$Pk)/(0-input$D2))

#balance point
d1=reactive((input$Pwf-input$Pso-input$Gf*input$Dmax)/(Gc-input$Gf))
d_balance_point=d1


#operating_point
d1=reactive((input$Pso-input$Pwf+input$Gf*input$Dmax-input$P_across_valve)/(input$Gf-Gc))
D_operating_point=d1

P_operating_point_casing=reactive(input$Pso+D_operating_point*Gc)
P_operating_point_formation=reactive(input$Pwf-input$Gf*(input$Dmax-D_operating_point))

plot3<-plot2+geom_point(aes(x=P_operating_point_formation,y=D_operating_point))


#Tubing grad
tubing_grad<-reactive(data.frame(D=c(0,D_operating_point),P=c(input$Pwh,P_operating_point_formation)))


plot4<-plot3+geom_point(data = tubing_grad,aes(x=P,y=D))+
    geom_line(data = tubing_grad,aes(x=P,y=D))


#Tubing_design_grad
Pwh_Design=reactive((input$Pwh+0.2*(input$Pso-input$Pwh)))

Gtd=Pwh_Design-P_operating_point_formation/(0-D_operating_point)        #Tubing design grad
tubing_design_grad<-data.frame(D=c(0,D_operating_point),P=c(Pwh_Design,P_operating_point_formation))

plot5<-plot4+geom_point(data = tubing_design_grad,aes(x=P,y=D))+
    geom_line(data = tubing_design_grad,aes(x=P,y=D))


#first valve
D_valve1=reactive((input$Pwh-input$Pko)/(Gk-input$GL))

PK_valve1=reactive(D_valve1*Gk+input$Pko)

PTD_valve1=Gtd*D_valve1+Pwh_Design

df<-reactive(data.frame(D=c(0,D_valve1),P=c(input$Pwh,PK_valve1)))
#ploting
plot6<-plot5+geom_point(data = df, aes(x=P,y=D))+
    geom_line(data = df, aes(x=P,y=D))

df<-data.frame(D=c(D_valve1,D_valve1),P=c(PTD_valve1,PK_valve1))

plot7<-plot6+geom_point(data = df, aes(x=P,y=D))+
    geom_line(data = df, aes(x=P,y=D))

plot<-plot7

Final_table<-data.frame(depth=D_valve1,
                        Pc=PK_valve1,
                        Pt=PTD_valve1)

dvalve=D_valve1
PTDvalve=PTD_valve1
Pcvalve=PK_valve1
D_valve=D_valve1
PTD_valve=PTD_valve1


while (dvalve<D_operating_point) {
    dvalve=reactive((PTDvalve-input$Pso-dvalve*input$GL)/(Gc-input$GL))
    Pcvalve=reactive(input$Pso+Gc*dvalve)
    if(dvalve<D_operating_point){
        df<-data.frame(D=c(D_valve,dvalve),P=c(PTD_valve,Pcvalve))
        plot<-plot+geom_point(data = df, aes(x=P,y=D))+
            geom_line(data = df, aes(x=P,y=D))
        
        PTDvalve=Gtd*dvalve+Pwh_Design
        
        df<-data.frame(D=c(dvalve,dvalve),P=c(PTDvalve,Pcvalve))
        plot<-plot+geom_point(data = df, aes(x=P,y=D))+
            geom_line(data = df, aes(x=P,y=D))
        
        
        valve<-c(dvalve,Pcvalve,PTDvalve)
        Final_table<-rbind(Final_table,valve)
        D_valve=dvalve
        PTD_valve=PTDvalve
    }}

output$plot<-renderPlot(plot)

valve<-c(D_operating_point,P_operating_point_casing,P_operating_point_formation)
Final_table<-rbind(Final_table,valve)


GTemp=reactive((input$Tres-input$Twh)/input$Dmax)

CT_data<-data.frame(Temp=c(61:300),Ct=c(0.998,0.996,0.994,0.991,0.989,0.987,0.985,0.983,0.981,0.979,0.977,0.975,0.973,0.971,0.969,0.967,0.965,0.963,0.961,0.959,0.957,0.955,0.953,0.951,0.949,0.947,0.945,0.943,0.941,0.939,0.938,0.936,0.934,0.932,0.93,0.928,0.926,0.924,0.923,0.921,0.919,0.917,0.915,0.914,0.912,0.91,0.908,0.906,0.905,0.903,0.901,0.899,0.898,0.896,0.894,0.893,0.891,0.889,0.887,0.886,0.884,0.882,0.881,0.879,0.877,0.876,0.874,0.872,0.871,0.869,0.686,0.866,0.864,0.863,0.861,0.86,0.858,0.856,0.855,0.853,0.852,0.85,0.849,0.847,0.845,0.844,0.842,0.841,0.839,0.838,0.836,0.835,0.833,0.832,0.83,0.829,0.827,0.826,0.825,0.823,0.822,0.82,0.819,0.817,0.816,0.814,0.813,0.812,0.81,0.809,0.807,0.806,0.805,0.803,0.802,0.8,0.799,0.798,0.796,0.795,0.794,0.792,0.791,0.79,0.788,0.787,0.786,0.784,0.783,0.782,0.78,0.779,0.778,0.776,0.775,0.774,0.772,0.771,0.77,0.769,0.767,0.766,0.765,0.764,0.762,0.761,0.76,0.759,0.757,0.756,0.755,0.754,0.752,0.751,0.75,0.749,0.748,0.746,0.745,0.744,0.743,0.742,0.74,0.739,0.738,0.737,0.736,0.735,0.733,0.732,0.731,0.73,0.729,0.728,0.727,0.725,0.724,0.723,0.722,0.721,0.72,0.719,0.718,0.717,0.715,0.714,0.713,0.712,0.711,0.71,0.709,0.708,0.707,0.706,0.705,0.704,0.702,0.701,0.7,0.699,0.698,0.697,0.696,0.695,0.694,0.693,0.692,0.691,0.69,0.689,0.688,0.687,0.686,0.685,0.684,0.683,0.682,0.681,0.68,0.679,0.678,0.677,0.676,0.675,0.674,0.673,0.672,0.671,0.67,0.699,0.668,0.667,0.666,0.665,0.664,0.663,0.662,0.662,0.661,0.66))


Final_table<-Final_table %>% mutate(reactive(Pbt=input$Pc*(1-input$R)+Pt*input$R),
                                    reactive(TEMP=input$Twh+GTemp*depth),
                                    Temp=ceiling(TEMP))
Final_table<-merge(x=Final_table,y=CT_data,by = "Temp",all.x = T)
Final_table<-Final_table%>%select(depth,Pc,Pt,Pbt,TEMP,Ct)

Final_table<-Final_table %>% mutate(Pb=Pbt*Ct,
                                    Pvo=reactive(Pb/(1-input$R)))
output$table<-tableOutput(Final_table)})

我尝试使用 () 中包含的反应式赋值创建任何变量，但它给出了这个错误4

“警告：错误：在没有活动反应上下文的情况下不允许操作。

• 您试图做一些只能在反应式消费者内部完成的事情。 58: 错误：如果没有活动的反应上下文，则不允许操作。
• 您试图做一些只能在反应式消费者内部完成的事情。”

我很确定我在调用它们时只对反应性分配的变量这样做了

编辑

在我尝试解决它给出的问题后：

警告：data.frame 中的错误：参数暗示不同的行数：1、0 1：运行应用程序

每当我按下操作按钮时 新服务器

library(shiny)
library(ggplot2)
library(dplyr)
shinyServer(function(input, output) {
plot<-reactiveVal(NULL)
Final_table<-reactiveVal(data.frame())

observeEvent(input$submit,{
    plot(ggplot()+
             coord_cartesian(xlim = c(0,input$Pwf+500))+
             scale_y_continuous(trans = "reverse")+
             scale_x_continuous(position = "top"))
    
    #Flowing Gradient
    #slope Gf
    #point (pwf,Dmax)
    #get p1 at depth 4000ft
    p1=input$Pwf-input$Gf*(input$Dmax-4000)
    flowing_gradient<-data.frame(D=c(4000,input$Dmax),P=c(p1,input$Pwf))
    
    plot(plot()+
             geom_point(data = flowing_gradient,aes(x=P,y=D))+
             geom_line(data = flowing_gradient,aes(x=P,y=D)))
    
    
    
    #casing gradient
    casing_gradient<-data.frame(D=c(0,input$D1),P=c(input$Pso,input$Pcs))
    
    plot(plot()+geom_point(data=casing_gradient,aes(x=P,y=D))+
             geom_line(data=casing_gradient,aes(x=P,y=D)))
    
    Gc=(input$Pso-input$Pcs)/(0-input$D1)
    
    #killing gradient
    killing_gradient<-data.frame(D=c(0,input$D2),P=c(input$Pko,input$Pk))
    
    plot(plot()+geom_point(data=killing_gradient,aes(x=P,y=D))+
             geom_line(data=killing_gradient,aes(x=P,y=D)))
    Gk=(input$Pko-input$Pk)/(0-input$D2)
    
    #balance point
    d1=(input$Pwf-input$Pso-input$Gf*input$Dmax)/(Gc-input$Gf)
    d_balance_point=d1
    
    
    #operating_point
    d1=(input$Pso-input$Pwf+input$Gf*input$Dmax-input$P_across_valve)/(input$Gf-Gc)
    D_operating_point=d1
    
    P_operating_point_casing=input$Pso+D_operating_point*Gc
    P_operating_point_formation=input$Pwf-input$Gf*(input$Dmax-D_operating_point)
    
    plot(plot()+geom_point(aes(x=P_operating_point_formation,y=D_operating_point)))
    
    
    #Tubing grad
    tubing_grad<-data.frame(D=c(0,D_operating_point),P=c(input$Pwh,P_operating_point_formation))
    
    
    plot(plot()+geom_point(data = tubing_grad,aes(x=P,y=D))+
             geom_line(data = tubing_grad,aes(x=P,y=D)))
    
    
    #Tubing_design_grad
    Pwh_design=input$Pwh+0.2*(input$Pso-input$Pwh)
    
    Gtd=(Pwh_design-P_operating_point_formation)/(0-D_operating_point)        #Tubing design grad
    tubing_design_grad<-data.frame(D=c(0,D_operating_point),P=c(Pwh_design,P_operating_point_formation))
    
    plot(plot()+geom_point(data = tubing_design_grad,aes(x=P,y=D))+
             geom_line(data = tubing_design_grad,aes(x=P,y=D)))
    
    
    #first valve
    D_valve1=(input$Pwh-input$Pko)/(Gk-input$GL)
    
    PK_valve1=D_valve1*Gk+input$Pko
    
    PTD_valve1=Gtd*D_valve1+Pwh_design
    
    df<-data.frame(D=c(0,D_valve1),P=c(input$Pwh,PK_valve1))
    #ploting
    plot(plot()+geom_point(data = df, aes(x=P,y=D))+
             geom_line(data = df, aes(x=P,y=D)))
    
    df<-data.frame(D=c(D_valve1,D_valve1),P=c(PTD_valve1,PK_valve1))
    
    plot(plot()+geom_point(data = df, aes(x=P,y=D))+
             geom_line(data = df, aes(x=P,y=D)))
    
    
    
    
    Final_table(data.frame(depth=D_valve1,
                           Pc=PK_valve1,
                           Pt=PTD_valve1))
    
    dvalve=D_valve1
    PTDvalve=PTD_valve1
    Pcvalve=PK_valve1
    D_valve=D_valve1
    PTD_valve=PTD_valve1
    
    
    while (dvalve<D_operating_point) {
        dvalve=(PTDvalve-input$Pso-dvalve*input$GL)/(Gc-input$GL)
        Pcvalve=input$Pso+Gc*dvalve
        if(dvalve<D_operating_point){
            df<-data.frame(D=c(D_valve,dvalve),P=c(PTD_valve,Pcvalve))
            plot(plot()+geom_point(data = df, aes(x=P,y=D))+
                     geom_line(data = df, aes(x=P,y=D)))
            
            PTDvalve=Gtd*dvalve+Pwh_design
            
            df<-data.frame(D=c(dvalve,dvalve),P=c(PTDvalve,Pcvalve))
            plot(plot()+geom_point(data = df, aes(x=P,y=D))+
                     geom_line(data = df, aes(x=P,y=D)))
            
            
            valve<-c(dvalve,Pcvalve,PTDvalve)
            Final_table(rbind(Final_table(),valve))
            D_valve=dvalve
            PTD_valve=PTDvalve
        }}
    
    valve<-c(D_operating_point,P_operating_point_casing,P_operating_point_formation)
    Final_table(rbind(Final_table(),valve))
    
    
    GTemp=(input$Tres-input$Twh)/input$Dmax
    
    CT_data<-data.frame(Temp=c(61:300),Ct=c(0.998,0.996,0.994,0.991,0.989,0.987,0.985,0.983,0.981,0.979,0.977,0.975,0.973,0.971,0.969,0.967,0.965,0.963,0.961,0.959,0.957,0.955,0.953,0.951,0.949,0.947,0.945,0.943,0.941,0.939,0.938,0.936,0.934,0.932,0.93,0.928,0.926,0.924,0.923,0.921,0.919,0.917,0.915,0.914,0.912,0.91,0.908,0.906,0.905,0.903,0.901,0.899,0.898,0.896,0.894,0.893,0.891,0.889,0.887,0.886,0.884,0.882,0.881,0.879,0.877,0.876,0.874,0.872,0.871,0.869,0.686,0.866,0.864,0.863,0.861,0.86,0.858,0.856,0.855,0.853,0.852,0.85,0.849,0.847,0.845,0.844,0.842,0.841,0.839,0.838,0.836,0.835,0.833,0.832,0.83,0.829,0.827,0.826,0.825,0.823,0.822,0.82,0.819,0.817,0.816,0.814,0.813,0.812,0.81,0.809,0.807,0.806,0.805,0.803,0.802,0.8,0.799,0.798,0.796,0.795,0.794,0.792,0.791,0.79,0.788,0.787,0.786,0.784,0.783,0.782,0.78,0.779,0.778,0.776,0.775,0.774,0.772,0.771,0.77,0.769,0.767,0.766,0.765,0.764,0.762,0.761,0.76,0.759,0.757,0.756,0.755,0.754,0.752,0.751,0.75,0.749,0.748,0.746,0.745,0.744,0.743,0.742,0.74,0.739,0.738,0.737,0.736,0.735,0.733,0.732,0.731,0.73,0.729,0.728,0.727,0.725,0.724,0.723,0.722,0.721,0.72,0.719,0.718,0.717,0.715,0.714,0.713,0.712,0.711,0.71,0.709,0.708,0.707,0.706,0.705,0.704,0.702,0.701,0.7,0.699,0.698,0.697,0.696,0.695,0.694,0.693,0.692,0.691,0.69,0.689,0.688,0.687,0.686,0.685,0.684,0.683,0.682,0.681,0.68,0.679,0.678,0.677,0.676,0.675,0.674,0.673,0.672,0.671,0.67,0.699,0.668,0.667,0.666,0.665,0.664,0.663,0.662,0.662,0.661,0.66))
    
    
    Final_table(Final_table() %>% mutate(Pbt=Pc*(1-input$R)+Pt*input$R,
                                         TEMP=input$Twh+GTemp*depth,
                                         Temp=ceiling(TEMP)))
    Final_table(merge(x=Final_table(),y=CT_data,by = "Temp",all.x = T))
    Final_table(Final_table()%>%select(depth,Pc,Pt,Pbt,TEMP,Ct))
    
    Final_table(Final_table() %>% mutate(Pb=Pbt*Ct,
                                         Pvo=Pb/(1-input$R)))
})

output$plot<-renderPlot({
    isolate(plot())
})

output$table<-renderTable({
    isolate(Final_table())
})

})

Answer 1

这是一个直到第一个 plot 的 MRE，用于说明如何处理反应性对象。请注意在访问响应式值时使用 ()。

library(shiny)
library(tidyverse)

# Define UI for application that draws a histogram
ui <- fluidPage(
    
    # Application title
    titlePanel("OTIS Gas Lift"),
    fluidRow(column(width = 6,
                    numericInput(inputId = "Dmax",label = "Depth to mid perforation",value = 7500),
                    numericInput("Pwh","Pwh",100),
                    numericInput("Tres","Tres",182),
                    numericInput("Pso","P Casing at Surface",870),
                    numericInput("Psc","P Casing at Depth D1",1050),
                    numericInput("D1","D1",7000),
                    numericInput("P_across_valve","P_across_valve",100),
                    numericInput("GL","Load Grad",0.5),
                    numericInput("Pwf","Pwf",1760),
                    numericInput("RGOR","Required GOR",400)
    ),
    column(width = 6,
           numericInput("FGOR","Formation GOR",200),
           numericInput("Twh","Twh",100),
           numericInput("Pko","kill pressure at Surface",920),
           numericInput("Pk","Kill Pressure at D2",1100),
           numericInput("D2","D2",7000),
           numericInput("T_inj","T_inj",100),
           numericInput("q","Desired Production Rate STB/d",600),
           numericInput("R","R",0.1534),
           numericInput("Gf","Flowing Grad before inj",0.4)
    )),
    fluidRow(actionButton('submit' ,label = "Apply Changes",width = "100%")),
    splitLayout(tableOutput(outputId = "table"),plotOutput(outputId = "plot"))
    )


library(shiny)

server <- function(input, output) {
    
    #define plot object that can be accessed inside of reactive() or observe()
    plot_rv <- reactiveVal(NULL) 
    flowing_gradient_rv <- reactiveVal(NULL)

    #inside this observer we can create regular local objects (only accesible inside the observer) like when creating functions.
    #notice the code wrapped in curly braces {} to be able to pass multiple lines of code into `observeEvent()` second argument.
    #input$submit corresponds to the action button created in the ui.
    observeEvent(input$submit, {
        
    plot_rv(ggplot() +
        coord_cartesian(xlim = c(0, input$Pwf + 500)) +
        scale_y_continuous(trans = "reverse") +
        scale_x_continuous(position = "top"))
    
    
    #Flowing Gradient
    #slope Gf
    #point (pwf,Dmax)
    #get p1 at depth 4000ft
    
    #input values are now available without calling reactive since we already are "inside" the observer
    p1 <- input$Pwf - input$Gf * (input$Dmax - 4000)
    flowing_gradient <- data.frame(D = c(4000, input$Dmax), P = c(p1, input$Pwf))
    
    #to use flowing_gradient outside this observer we use flowing_gradient reactiveVal
    flowing_gradient_rv(flowing_gradient)
    
    
    plot_rv(plot_rv() +
        geom_point(data = flowing_gradient,aes(x=P,y=D))+
        geom_line(data = flowing_gradient,aes(x=P,y=D))
    )
    
    })
    
    #to show the plots
    output$plot <- renderPlot({
        plot_rv()
    })
    
    output$table <- renderTable(
        flowing_gradient_rv()
    )
    
}

shinyApp(ui, server)

Edit：被编辑的应用当前正在运行。

library(shiny)
library(tidyverse)

# Define UI for application that draws a histogram
ui <- fluidPage(

  # Application title
  titlePanel("OTIS Gas Lift"),
  fluidRow(
    column(
      width = 6,
      numericInput(inputId = "Dmax", label = "Depth to mid perforation", value = 7500),
      numericInput("Pwh", "Pwh", 100),
      numericInput("Tres", "Tres", 182),
      numericInput("Pso", "P Casing at Surface", 870),
      numericInput("Psc", "P Casing at Depth D1", 1050),
      numericInput("D1", "D1", 7000),
      numericInput("P_across_valve", "P_across_valve", 100),
      numericInput("GL", "Load Grad", 0.5),
      numericInput("Pwf", "Pwf", 1760),
      numericInput("RGOR", "Required GOR", 400)
    ),
    column(
      width = 6,
      numericInput("FGOR", "Formation GOR", 200),
      numericInput("Twh", "Twh", 100),
      numericInput("Pko", "kill pressure at Surface", 920),
      numericInput("Pk", "Kill Pressure at D2", 1100),
      numericInput("D2", "D2", 7000),
      numericInput("T_inj", "T_inj", 100),
      numericInput("q", "Desired Production Rate STB/d", 600),
      numericInput("R", "R", 0.1534),
      numericInput("Gf", "Flowing Grad before inj", 0.4)
    )
  ),
  fluidRow(actionButton("submit", label = "Apply Changes", width = "100%")),
  splitLayout(tableOutput(outputId = "table"), plotOutput(outputId = "plot"))
)


library(shiny)

library(shiny)
library(ggplot2)
library(dplyr)
server <- function(input, output) {
  plot <- reactiveVal(NULL)
  Final_table <- reactiveVal(data.frame())

  observeEvent(input$submit, {
    plot(ggplot() +
      coord_cartesian(xlim = c(0, input$Pwf + 500)) +
      scale_y_continuous(trans = "reverse") +
      scale_x_continuous(position = "top"))

    # Flowing Gradient
    # slope Gf
    # point (pwf,Dmax)
    # get p1 at depth 4000ft
    p1 <- input$Pwf - input$Gf * (input$Dmax - 4000)
    flowing_gradient <- data.frame(D = c(4000, input$Dmax), P = c(p1, input$Pwf))

    plot(plot() +
      geom_point(data = flowing_gradient, aes(x = P, y = D)) +
      geom_line(data = flowing_gradient, aes(x = P, y = D)))



    # casing gradient
    casing_gradient <- data.frame(D = c(0, input$D1), P = c(input$Pso, input$Pcs))

    plot(plot() + geom_point(data = casing_gradient, aes(x = P, y = D)) +
      geom_line(data = casing_gradient, aes(x = P, y = D)))

    Gc <- (input$Pso - input$Psc) / (0 - input$D1)
    

    # killing gradient
    killing_gradient <- data.frame(D = c(0, input$D2), P = c(input$Pko, input$Pk))

    plot(plot() + geom_point(data = killing_gradient, aes(x = P, y = D)) +
      geom_line(data = killing_gradient, aes(x = P, y = D)))
    Gk <- (input$Pko - input$Pk) / (0 - input$D2)

    # balance point
    d1 <- (input$Pwf - input$Pso - input$Gf * input$Dmax) / (Gc - input$Gf)
    
    d_balance_point <- d1
    
    

    
    # operating_point
    d1 <- (input$Pso - input$Pwf + input$Gf * input$Dmax - input$P_across_valve) / (input$Gf - Gc)
    D_operating_point <- d1
    
    

    P_operating_point_casing <- input$Pso + D_operating_point * Gc
    P_operating_point_formation <- input$Pwf - input$Gf * (input$Dmax - D_operating_point)

    plot(plot() + geom_point(aes(x = P_operating_point_formation, y = D_operating_point)))


    # Tubing grad
    tubing_grad <- data.frame(D = c(0, D_operating_point), P = c(input$Pwh, P_operating_point_formation))


    plot(plot() + geom_point(data = tubing_grad, aes(x = P, y = D)) +
      geom_line(data = tubing_grad, aes(x = P, y = D)))


    # Tubing_design_grad
    Pwh_design <- input$Pwh + 0.2 * (input$Pso - input$Pwh)

    Gtd <- (Pwh_design - P_operating_point_formation) / (0 - D_operating_point)# Tubing design grad
    
    tubing_design_grad <- data.frame(D = c(0, D_operating_point), P = c(Pwh_design, P_operating_point_formation))

    plot(plot() + geom_point(data = tubing_design_grad, aes(x = P, y = D)) +
      geom_line(data = tubing_design_grad, aes(x = P, y = D)))


    # first valve
    D_valve1 <- (input$Pwh - input$Pko) / (Gk - input$GL)

    PK_valve1 <- D_valve1 * Gk + input$Pko

    PTD_valve1 <- Gtd * D_valve1 + Pwh_design
    

    df <- data.frame(D = c(0, D_valve1), P = c(input$Pwh, PK_valve1))
    # ploting
    plot(plot() + geom_point(data = df, aes(x = P, y = D)) +
      geom_line(data = df, aes(x = P, y = D)))

    df <- data.frame(D = c(D_valve1, D_valve1), P = c(PTD_valve1, PK_valve1))

    plot(plot() + geom_point(data = df, aes(x = P, y = D)) +
      geom_line(data = df, aes(x = P, y = D)))

    Final_table(data.frame(
      depth = D_valve1,
      Pc = PK_valve1,
      Pt = PTD_valve1
    ))

    dvalve <- D_valve1
    PTDvalve <- PTD_valve1
    Pcvalve <- PK_valve1
    D_valve <- D_valve1
    PTD_valve <- PTD_valve1


    while (dvalve < D_operating_point) {
      dvalve <- (PTDvalve - input$Pso - dvalve * input$GL) / (Gc - input$GL)
      Pcvalve <- input$Pso + Gc * dvalve
      if (dvalve < D_operating_point) {
        df <- data.frame(D = c(D_valve, dvalve), P = c(PTD_valve, Pcvalve))
        plot(plot() + geom_point(data = df, aes(x = P, y = D)) +
          geom_line(data = df, aes(x = P, y = D)))

        PTDvalve <- Gtd * dvalve + Pwh_design

        df <- data.frame(D = c(dvalve, dvalve), P = c(PTDvalve, Pcvalve))
        plot(plot() + geom_point(data = df, aes(x = P, y = D)) +
          geom_line(data = df, aes(x = P, y = D)))


        valve <- c(dvalve, Pcvalve, PTDvalve)
        Final_table(rbind(Final_table(), valve))
        D_valve <- dvalve
        PTD_valve <- PTDvalve
      }
    }

    valve <- c(D_operating_point, P_operating_point_casing, P_operating_point_formation)
    Final_table(rbind(Final_table(), valve))


    GTemp <- (input$Tres - input$Twh) / input$Dmax

    CT_data <- data.frame(Temp = c(61:300), Ct = c(0.998, 0.996, 0.994, 0.991, 0.989, 0.987, 0.985, 0.983, 0.981, 0.979, 0.977, 0.975, 0.973, 0.971, 0.969, 0.967, 0.965, 0.963, 0.961, 0.959, 0.957, 0.955, 0.953, 0.951, 0.949, 0.947, 0.945, 0.943, 0.941, 0.939, 0.938, 0.936, 0.934, 0.932, 0.93, 0.928, 0.926, 0.924, 0.923, 0.921, 0.919, 0.917, 0.915, 0.914, 0.912, 0.91, 0.908, 0.906, 0.905, 0.903, 0.901, 0.899, 0.898, 0.896, 0.894, 0.893, 0.891, 0.889, 0.887, 0.886, 0.884, 0.882, 0.881, 0.879, 0.877, 0.876, 0.874, 0.872, 0.871, 0.869, 0.686, 0.866, 0.864, 0.863, 0.861, 0.86, 0.858, 0.856, 0.855, 0.853, 0.852, 0.85, 0.849, 0.847, 0.845, 0.844, 0.842, 0.841, 0.839, 0.838, 0.836, 0.835, 0.833, 0.832, 0.83, 0.829, 0.827, 0.826, 0.825, 0.823, 0.822, 0.82, 0.819, 0.817, 0.816, 0.814, 0.813, 0.812, 0.81, 0.809, 0.807, 0.806, 0.805, 0.803, 0.802, 0.8, 0.799, 0.798, 0.796, 0.795, 0.794, 0.792, 0.791, 0.79, 0.788, 0.787, 0.786, 0.784, 0.783, 0.782, 0.78, 0.779, 0.778, 0.776, 0.775, 0.774, 0.772, 0.771, 0.77, 0.769, 0.767, 0.766, 0.765, 0.764, 0.762, 0.761, 0.76, 0.759, 0.757, 0.756, 0.755, 0.754, 0.752, 0.751, 0.75, 0.749, 0.748, 0.746, 0.745, 0.744, 0.743, 0.742, 0.74, 0.739, 0.738, 0.737, 0.736, 0.735, 0.733, 0.732, 0.731, 0.73, 0.729, 0.728, 0.727, 0.725, 0.724, 0.723, 0.722, 0.721, 0.72, 0.719, 0.718, 0.717, 0.715, 0.714, 0.713, 0.712, 0.711, 0.71, 0.709, 0.708, 0.707, 0.706, 0.705, 0.704, 0.702, 0.701, 0.7, 0.699, 0.698, 0.697, 0.696, 0.695, 0.694, 0.693, 0.692, 0.691, 0.69, 0.689, 0.688, 0.687, 0.686, 0.685, 0.684, 0.683, 0.682, 0.681, 0.68, 0.679, 0.678, 0.677, 0.676, 0.675, 0.674, 0.673, 0.672, 0.671, 0.67, 0.699, 0.668, 0.667, 0.666, 0.665, 0.664, 0.663, 0.662, 0.662, 0.661, 0.66))


    Final_table(Final_table() %>% mutate(
      Pbt = Pc * (1 - input$R) + Pt * input$R,
      TEMP = input$Twh + GTemp * depth,
      Temp = ceiling(TEMP)
    ))
    Final_table(merge(x = Final_table(), y = CT_data, by = "Temp", all.x = T))
    Final_table(Final_table() %>% select(depth, Pc, Pt, Pbt, TEMP, Ct))

    Final_table(Final_table() %>% mutate(
      Pb = Pbt * Ct,
      Pvo = Pb / (1 - input$R)
    ))
  })

  output$plot <- renderPlot({
    plot()
  })

  output$table <- renderTable({
    Final_table()
  })
}

shinyApp(ui, server)