R/ahp.b.R

In hyunsooseol/seolmatrix: Correlations suite for jamovi

ahpClass <- if (requireNamespace('jmvcore', quietly = TRUE))
  R6::R6Class(
    "ahpClass",
    inherit = ahpBase,
    private = list(
      .htmlwidget = NULL,
      #==========================================================
      .init = function() {
        private$.htmlwidget <- HTMLWidget$new()
        
        if (is.null(self$data) | is.null(self$options$vars)) {
          self$results$instructions$setVisible(visible = TRUE)
          
        }
        
        self$results$instructions$setContent(private$.htmlwidget$generate_accordion(
          title = "Instructions",
          content = paste(
            '<div style="border: 2px solid #e6f4fe; border-radius: 15px; padding: 15px; background-color: #e6f4fe; margin-top: 10px;">',
            '<div style="text-align:justify;">',
            '<ul>',
            '<li>Each row and column represents an item and a decision maker for the input data format.</li>',
            '<li>More than 10 items or 20 decision makers are NOT allowed.</li>',
            '<li>Each item would be graded 1-9 score by each decision maker.</li>',
            '<li>Feature requests and bug reports can be made on my <a href="https://github.com/hyunsooseol/seolmatrix/issues" target="_blank">GitHub</a>.</li>',
            '</ul></div></div>'
            
          )
          
        ))
        
        if (self$options$cir)
          self$results$cir$setNote("Note", "value<0.1 is acceptable for consistency ratio.")
      },
      
      
      .run = function() {
        if (length(self$options$vars) < 1)
          return()
        # get variables---------------------------------
        vars <- self$options$vars
        nVars <- length(vars)
        mydata <- self$data
        mydata <- jmvcore::naOmit(mydata)
        for (v in vars)
          mydata[[v]] <- jmvcore::toNumeric(mydata[[v]])
        
        # compute AHP-------
        res <- easyAHP::easyAHP(mydata)$Makers
        # item matrix--------
        
        item <- res$Matrix
        item <- as.matrix(item)
        names <- dimnames(item)[[1]]
        dims <- dimnames(item)[[2]]
        table <- self$results$itemmat
        for (dim in dims) {
          table$addColumn(name = paste0(dim), type = 'number')
        }
        
        for (name in names) {
          row <- list()
          for (j in seq_along(dims)) {
            row[[dims[j]]] <- item[name, j]
          }
          table$addRow(rowKey = name, values = row)
        }
        
        # item weights----------------
        weights <- res$Weights
        weights <- as.data.frame(weights)
        names <- dimnames(weights)[[1]]
        # item weights table-----------
        table <- self$results$weights
        for (name in names) {
          row <- list()
          row[['value']] <- weights[name, 1]
          table$addRow(rowKey = name, values = row)
        }
        
        # Confidence Index and Confidence Ratio--------
        Index <- res$CI
        Ratio <- res$CR
        cir <- rbind(Index, Ratio)
        names <- dimnames(cir)[[1]]
        # Confidence index and ratio table-------
        table <- self$results$cir
        for (name in names) {
          row <- list()
          row[['value']] <- cir[name, 1]
          table$addRow(rowKey = name, values = row)
        }
      }
    )
  )