In R, why is one function working and the other not working when they are both very similar numeric-CodePudding

In running the below MWE code as presented, it runs interpolation scenarios fine. However if I comment-out the first custom interpol() function that is currently uncommented, and uncomment the second interpol() function, the results do not plot. WHY?? They are so similar in output form!

I ran both interpol() versions in R studio console to test. They both work as they should. They are both vectors when I ran is.vector(), they are both numeric when I ran is.numeric().

Obviously the 2nd interpol() doesn't interpolate, it calculates a sumproduct (testing sumproduct for evolution of this code). Under the default scenario, it generates a vector of 10 elements, each element = 5. Why in the world would this not plot out just like the first interpol()?

MWE code:

library(shiny)
library(shinyMatrix)
library(dplyr)
library(ggplot2)

interpol <- function(a, b) { # a = periods, b = matrix inputs
  c    <- rep(NA, a)
  c[1] <- b[1]
  c[a] <- b[2]
  c    <- approx(seq_along(c)[!is.na(c)], c[!is.na(c)], seq_along(c))$y
  return(c)
}

# interpol <- function(a, b) { # a = periods, b = matrix inputs
#   c    <- rep(NA, a)
#   c[]  <- sum(b[,1]) %*% sum(b[,2])
#   return(c)
# }

ui <- fluidPage(
  sliderInput('periods', 'X-axis periods:', min=1, max=10, value=10),
  matrixInput(
    "myMatrixInput",
    label = "Values to sumproduct paired under each scenario heading:",
    value =  matrix(c(1, 5), 1, 2, dimnames = list(NULL, rep("Scenario 1", 2))),
    cols = list(extend = TRUE,  delta = 2, names = TRUE,  delete = TRUE, multiheader = TRUE),
    rows = list(extend = FALSE, delta = 1, names = FALSE, delete = FALSE),
    class = "numeric"),
  plotOutput("plot")
)

server <- function(input, output, session) {
  
  observeEvent(input$myMatrixInput, {
    tmpMatrix <- input$myMatrixInput
    
    # Remove any empty matrix columns
    empty_columns <- sapply(tmpMatrix, function(x) all(is.na(x) | x == ""))
    tmpMatrix <- tmpMatrix[, !empty_columns, drop=FALSE]
    
    # Assign column header names
    colnames(tmpMatrix) <- paste("Scenario", rep(1:ncol(tmpMatrix), each = 2, length.out = ncol(tmpMatrix)))
    
    isolate( # isolate update to prevent infinite loop
      updateMatrixInput(session, inputId = "myMatrixInput", value = tmpMatrix)
    )
  })
  
  plotData <- reactive({
    tryCatch(
      lapply(seq_len(ncol(input$myMatrixInput)/2),
             function(i){
               tibble(
                 Scenario = colnames(input$myMatrixInput)[i*2-1],
                 X = seq_len(input$periods),
                 Y = interpol(input$periods, input$myMatrixInput[1,(i*2-1):(i*2)])
               )
             }) %>% bind_rows(),
      error = function(e) NULL
    )
  })
  
  output$plot <- renderPlot({
    req(plotData())
    plotData() %>% ggplot()   geom_line(aes(
      x = X,
      y = Y,
      colour = as.factor(Scenario)
    ))
  })
  
}

shinyApp(ui, server)

CodePudding user response：

To make it easier to explain I would refer the first function as interpol1 and the second function as interpol2.

In lapply where you are calling the function (interpol(input$periods, input$myMatrixInput[1,(i*2-1):(i*2)])) input$myMatrixInput[1,(i*2-1):(i*2)] returns a numeric vector and not matrix. In interpol1 you use b[1] and b[2] to subset the values of b which is correct way to subset a vector but in interpol2 you use b[,1] and b[,2] to subset the vector which is incorrect and returns an error Error in b[, 1] : incorrect number of dimensions. I think you were expecting b to be a matrix hence you used b[, 1].

One fix would be to keep the input as matrix which can be done by using -

Y = interpol1(input$periods, input$myMatrixInput[1,(i*2-1):(i*2), drop = FALSE])

This should work for both the functions interpol1 and interpol2.