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Update app.R
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app.R
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@@ -3,112 +3,153 @@ library(dplyr)
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library(data.table)
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library(xgboost)
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library(caret)
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ui <- fluidPage(
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# Application title
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titlePanel("TimStuff Fastball/Offspeed Calculator"),
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# Sidebar with
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sidebarLayout(
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sidebarPanel(
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c("R","L")),
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numericInput("velo",
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"Velocity /mph",90),
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numericInput("ivb",
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"Induced Vertical Break (IVB) /in.",16),
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numericInput("hb",
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"Horizontal Break (HB) /in. (Pitcher's Perspective)",6),
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numericInput("spinrate",
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"Spin Rate /rpm",2300),
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numericInput("ext",
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"Extension /ft",6),
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numericInput("spinaxisdiff",
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"Spin Axis Difference (-180 - 180) /degrees",0),
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numericInput("x0","Horizntal Release Point /ft. (Batter's Perspective)",0),
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numericInput("z0","Vertical Release Point /ft. (Batter's Perspective)", 0),
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),
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#
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mainPanel(
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)
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# Define server logic required to draw a histogram
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server <- function(input, output) {
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observeEvent(input$pitch,{
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TimStuff <- (50 - (prediction - -0.002239657)/ 0.01043216 * 10)
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})
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output$
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data$SADiff <- input$spinaxisdiff
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})
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}
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})
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}
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# Run the application
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shinyApp(ui = ui, server = server)
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library(data.table)
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library(xgboost)
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library(caret)
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library(shinythemes)
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calculate_timstuff <- function(data, pitch_type) {
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data_matrix <- as.matrix(data)
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if (pitch_type == "Offspeed") {
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mod <- xgb.load('Off.model')
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prediction <- predict(mod, data_matrix)
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timstuff <- (50 - (prediction - -0.002239657) / 0.01043216 * 10)
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} else {
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mod <- xgb.load('FB.model')
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prediction <- predict(mod, data_matrix)
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timstuff <- (50 - (prediction - -0.0011801) / 0.007989927 * 10)
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}
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return(timstuff)
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}
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ui <- fluidPage(
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theme = shinytheme("flatly"),
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# Application title
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titlePanel("TimStuff Fastball/Offspeed Calculator"),
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# Sidebar with inputs
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sidebarLayout(
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sidebarPanel(
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width = 4,
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radioButtons("pitch", "Pitch Type", choices = c("Fastball", "Offspeed"), inline = TRUE),
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radioButtons("phand", "Hand", choices = c("R", "L"), inline = TRUE),
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numericInput("velo", "Velocity (mph)", value = 90, min = 70, max = 110, step = 1),
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numericInput("ivb", "Induced Vertical Break (in)", value = 16, min = -20, max = 30, step = 0.1),
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numericInput("hb", "Horizontal Break (in)", value = 6, min = -20, max = 20, step = 0.1),
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numericInput("spinrate", "Spin Rate (rpm)", value = 2300, min = 1000, max = 3500, step = 10),
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numericInput("ext", "Extension (ft)", value = 6, min = 5, max = 8, step = 0.1),
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numericInput("spinaxisdiff", "Spin Axis Difference (°)", value = 0, min = -180, max = 180, step = 1),
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numericInput("x0", "Horizontal Release Point (ft)", value = 0, min = -5, max = 5, step = 0.1),
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numericInput("z0", "Vertical Release Point (ft)", value = 5, min = 3, max = 8, step = 0.1),
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selectInput("feature_to_vary", "Select Feature to Vary:",
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choices = c("Velocity" = "start_speed",
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"Induced Vertical Break" = "IVB",
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"Horizontal Break" = "HB",
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"Spin Rate" = "spin_rate",
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"Extension" = "EAA",
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"Spin Axis Difference" = "SADiff",
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"Horizontal Release Point" = "x0",
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"Vertical Release Point" = "z0"))
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),
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# Main panel with output
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mainPanel(
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width = 8,
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wellPanel(
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h3("Results"),
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verbatimTextOutput("stuff"),
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plotOutput("feature_impact", height = "400px") # Placeholder for future visualization
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)
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)
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)
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server <- function(input, output) {
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observeEvent(input$pitch, {
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output$stuff <- renderText({
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data <- data.frame(
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start_speed = input$velo,
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IVB = input$ivb,
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HB = ifelse(input$phand == "L", -input$hb, input$hb),
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EAA = input$ext / 6.3,
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x0 = ifelse(input$phand == "L", -input$x0, input$x0),
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z0 = input$z0,
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spin_rate = input$spinrate,
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SADiff = input$spinaxisdiff
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)
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data <- as.matrix(data)
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if (input$pitch == "Offspeed") {
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mod <- xgb.load('Off.model')
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prediction <- predict(mod, data)
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TimStuff <- (50 - (prediction - -0.002239657) / 0.01043216 * 10)
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} else {
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mod <- xgb.load('FB.model')
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prediction <- predict(mod, data)
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TimStuff <- (50 - (prediction - -0.0011801) / 0.007989927 * 10)
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}
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paste("TimStuff:", round(TimStuff, 2), "\n20-80 Scale, 50 is Average, 1 SD is 10")
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})
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# Add this new reactive expression
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# Add this new reactive expression
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feature_range <- reactive({
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ranges <- list(
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start_speed = c(70, 110),
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IVB = c(-20, 30),
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HB = c(-20, 20),
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spin_rate = c(1000, 3500),
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EAA = c(5/6.3, 8/6.3),
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SADiff = c(-180, 180),
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x0 = c(-5, 5),
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z0 = c(3, 8)
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)
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ranges[[input$feature_to_vary]]
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})
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# Update the feature_impact plot
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output$feature_impact <- renderPlot({
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# Create base data frame with current inputs
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base_data <- data.frame(
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start_speed = input$velo,
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IVB = input$ivb,
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HB = ifelse(input$phand == "L", -input$hb, input$hb),
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EAA = input$ext / 6.3,
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x0 = ifelse(input$phand == "L", -input$x0, input$x0),
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z0 = input$z0,
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spin_rate = input$spinrate,
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SADiff = input$spinaxisdiff
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)
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# Generate sequence for the selected feature
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feature_seq <- seq(feature_range()[1], feature_range()[2], length.out = 100)
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# Calculate TimStuff for the sequence
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varied_data <- do.call(rbind, replicate(100, base_data, simplify = FALSE))
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varied_data[[input$feature_to_vary]] <- feature_seq
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timstuff <- calculate_timstuff(varied_data, input$pitch)
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# Create plot data
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plot_data <- data.frame(
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Feature = names(base_data)[which(names(base_data) == input$feature_to_vary)],
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Value = feature_seq,
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TimStuff = timstuff
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)
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# Create plot
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ggplot(plot_data, aes(x = Value, y = TimStuff)) +
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geom_line(color = "blue", size = 1) +
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geom_point(aes(x = base_data[[input$feature_to_vary]],
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y = calculate_timstuff(base_data, input$pitch)),
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color = "red", size = 3) +
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theme_minimal() +
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ylim(0,100) +
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labs(title = paste("Impact of", input$feature_to_vary, "on TimStuff"),
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x = input$feature_to_vary, y = "TimStuff") +
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theme(text = element_text(size = 14))
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})
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})
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}
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# Run the application
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shinyApp(ui = ui, server = server)
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