library(shiny)
library(ggplot2)

source("www/auxiliar_functions.R")

# Define server logic required to draw a histogram
shinyServer(function(input, output) {

    output$distPlot <- renderPlot({
      
      if (input$Distribucion == "Normal") {
        p <- ggplot() + 
          geom_function(colour="indianred1", fun=dnorm, lwd=2,
                        args=list(mean=input$mu_normal, sd=input$sigma)) + 
          xlim(input$min_normal, input$max_normal) +
          theme(legend.position = "none") + 
          labs(x="X", y="Density", 
               title=bquote(paste("X ~ N(",
                                  mu, "=", .(input$mu_normal),
                                  ", ",
                                  sigma^2, "=", .(input$sigma), ")")))
        print(p)
      }
      
      if (input$Distribucion == "Gamma") {
        p <- ggplot() + 
          geom_function(color="dodgerblue2", fun=dgamma_glm, lwd=2,
                        args=list(mu=input$mu_gamma, phi=input$phi_gamma)) + 
          xlim(input$min_gamma, input$max_gamma) +
          theme(legend.position = "none") + 
          labs(x="X", y="Density", 
               title=bquote(paste("X ~ Gamma(",
                                  mu, "=", .(input$mu_gamma),
                                  ", ",
                                  phi, "=", .(input$phi_gamma), ")")))
        print(p)
      }
      
      if (input$Distribucion == "Inv. gaussian") {
        p <- ggplot() + 
          geom_function(color="darkslategray3", fun=dinvgaus_glm, lwd=2,
                        args=list(mu=input$mu_invgaus, phi=input$phi_invgaus)) + 
          xlim(input$min_invgaus, input$max_invgaus) +
          theme(legend.position = "none") + 
          labs(x="X", y="Density", 
               title=bquote(paste("X ~ InvGaussian(",
                                  mu, "=", .(input$mu_invgaus),
                                  ", ",
                                  phi, "=", .(input$phi_invgaus), ")")))
        print(p)
      }
      
      if (input$Distribucion == "Binomial") {
        xs <- seq(from=0, to=input$m)
        ys <- dbinom(x=xs, size=input$m, prob=input$mu_binom)
        
        p <- ggplot(data=data.frame(x=xs, y=ys,
                                    yend=rep(0, input$m+1)),
                    aes(x=x, y=y, xend=x, yend=yend)) + 
          geom_point(colour="mediumpurple1") +
          geom_segment(colour="mediumpurple1") +
          theme(legend.position = "none") + 
          labs(x="X", y="Probability", 
               title=bquote(paste("X ~ Binomial(",
                                  n, "=", .(input$m),
                                  ", ",
                                  mu, "=", .(input$mu_binom), ")")))
        print(p)
      }
      
      if (input$Distribucion == "Poisson") {
        xs <- seq(from=0, to=input$max_pois)
        ys <- dpois(x=xs, lambda=input$mu_pois)
        
        p <- ggplot(data=data.frame(x=xs, y=ys,
                                    yend=rep(0, input$max_pois+1)),
                    aes(x=x, y=y, xend=x, yend=yend)) + 
          geom_point(colour="lightsalmon2") +
          geom_segment(colour="lightsalmon2") +
          theme(legend.position = "none") + 
          labs(x="X", y="Probability", 
               title=bquote(paste("X ~ Poisson(",
                                  mu, "=", .(input$mu_pois),
                                  # ", ",
                                  # mu, "=", .(input$mu_binom), 
                                  ")")))
        print(p)
      }
      
      if (input$Distribucion == "Negative binomial") {
        xs <- seq(from=0, to=input$max_negbin)
        ys <- dnbinom(x=xs, mu=input$mu_negbin, size=input$k)

        p <- ggplot(data=data.frame(x=xs, y=ys,
                                    yend=rep(0, input$k+1)),
                    aes(x=x, y=y, xend=x, yend=yend)) + 
          geom_point(colour="olivedrab3") +
          geom_segment(colour="olivedrab3") +
          theme(legend.position = "none") + 
          labs(x="X", y="Probability", 
               title=bquote(paste("X ~ NegBin(",
                                  mu, "=", .(input$mu_negbin),
                                  ", ",
                                  k, "=", .(input$k), ")")))
        print(p)
      }
      

    }, res = 96)

})