seolmatrix: Correlations suite for jamovi

#' @importFrom magrittr %>%
ahpsurveyClass <- if (requireNamespace('jmvcore', quietly = TRUE))
  R6::R6Class(
    "ahpsurveyClass",
    inherit = ahpsurveyBase,
    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>The R package <b>ahpsurvey</b> is described in the <a href="https://cran.r-project.org/web/packages/ahpsurvey/vignettes/my-vignette.html" target = "_blank">page</a>.</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$options$sumcr)
          self$results$sumcr$setNote("Note", "Mean CR<0.1 is acceptable for consistency ratio.")
        if (isTRUE(self$options$plot1)) {
          width <- self$options$width1
          height <- self$options$height1
          self$results$plot1$setSize(width, height)
        }
      },
      
      .run = function() {
        # Ready--------
        
        ready <- TRUE
        
        if (is.null(self$options$vars) ||
            length(self$options$vars) < 2)
          
          ready <- FALSE
        
        if (ready) {
          data <- private$.cleanData()
          results <- private$.compute(data)
          
          #populate 'Aggregated priorities'------------
          private$.populateApTable(results)
          # populate 'Aggregated individual judgements' table----
          private$.populateAjTable(results)
          # Consistency ratio of each decision-maker---------
          private$.populateCrOutputs(results)
          # populate sumcr table-----------
          private$.populateSumcrTable(results)
        }
      },
      
      
      .compute = function(data) {
        # get variables---------------------------------
        vars <- self$options$vars
        method <- self$options$method
        method1 <- self$options$method1
        
        ############################################################
        atts <- strsplit(self$options$atts, ',')[[1]]
        
        matahp <- ahpsurvey::ahp.mat(df = data,
                                     atts = atts,
                                     negconvert = T)
        
        ##########################################################
        
        # 'Aggregated priorities' table----------
        
        geo <- ahpsurvey::ahp.aggpref(matahp, atts, method = method)
        df <- data.frame(Value = geo)
        
        # Aggregated individual judgements table--------
        
        aj <- ahpsurvey::ahp.aggjudge(matahp, atts, aggmethod = method1)
        
        item <- as.matrix(aj)
        
        # Consistency ratio of each decision-maker-------
        
        cr <- ahpsurvey::ahp.cr(matahp, atts)
        
        cr1 <- data %>%
          ahpsurvey::ahp.mat(atts, negconvert = T) %>%
          ahpsurvey::ahp.cr(atts)
        
        tab <- as.vector(table(cr1 <= 0.1))
        
        # Individual preference plot1----------
        if (self$options$plot1 == TRUE) {
          me <- self$options$method2
          me2 <- self$options$method3
          
          m <- ahpsurvey::ahp.indpref(matahp, atts, method = me)
          m2 <- ahpsurvey::ahp.indpref(matahp, atts, method = me2)
          error <- data.frame(id = 1:length(matahp),
                              maxdiff = apply(abs(m - m2), 1, max))
          image <- self$results$plot1
          image$setState(error)
        }
        results <-
          list(
            'df' = df,
            'item' = item,
            'cr' = cr,
            'cr1' = cr1,
            'tab' = tab
          )
      },
      
      #Populate table----------------------------
      
      .populateSumcrTable = function(results) {
        table <- self$results$sumcr
        
        cr <- results$cr
        cr1 <- results$cr1
        tab <- results$tab
        
        mcr <- round(mean(cr), 3)
        ve <- c(tab, mcr)
        row <- list()
        row[['NO']] <- ve[[1]]
        row[['YES']] <- ve[[2]]
        row[['Mean CR']] <- ve[[3]]
        table$setRow(rowNo = 1, values = row)
      },
      
      .populateApTable = function(results) {
        table <- self$results$ap
        df <- results$df
        names <- dimnames(df)[[1]]
        table <- self$results$ap
        for (name in names) {
          row <- list()
          row[['value']] <- df[name, 1]
          table$addRow(rowKey = name, values = row)
        }
      },
      
      .populateAjTable = function(results) {
        table <- self$results$aj
        item <- results$item
        names <- dimnames(item)[[1]]
        dims <- dimnames(item)[[2]]
        table <- self$results$aj
        for (dim in dims) {
          table$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)
        }
      },
      
      # COnsistency ration of each decision-maker-----
      
      .populateCrOutputs = function(results) {
        cr <- results$cr
        
        if (self$options$cr
            && self$results$cr$isNotFilled()) {
          
          self$results$cr$setRowNums(rownames(self$data))
          self$results$cr$setValues(cr)
          
        }
      },
      
      .plot1 = function(image, ggtheme, theme, ...) {
        if (is.null(image$state))
          return(FALSE)
        
        error <- image$state
        library(ggplot2)
        plot1 <- ggplot2::ggplot(data = error, ggplot2::aes(x = id, y = maxdiff)) +
          geom_point() +
          geom_hline(yintercept = 0.05,
                     linetype = "dashed",
                     color = "red") +
          geom_hline(yintercept = 0, color = "gray50") +
          scale_x_continuous("Respondent ID") +
          scale_y_continuous("Maximum difference")
        plot1 + ggtheme
        print(plot1)
        TRUE
      },

      ### Helper functions =================================
      
      .cleanData = function() {
        items <- self$options$vars
        
        data <- list()
        
        for (item in items)
          data[[item]] <-
          jmvcore::toNumeric(self$data[[item]])
        
        attr(data, 'row.names') <-
          seq_len(length(data[[1]]))
        attr(data, 'class') <- 'data.frame'
        data <- jmvcore::naOmit(data)
        
        return(data)
      }
    )
  )

# if(self$options$plot2==TRUE){
#
#   thres <- 0.1
#   atts <- strsplit(self$options$atts, ',')[[1]]
#
#   cr <- data %>%
#     ahp.mat(atts, negconvert = T) %>%
#     ahp.cr(atts)
#
#
#   cr.df <- data %>%
#     ahp.mat(atts, negconvert = TRUE) %>%
#     ahp.cr(atts) %>%
#     data.frame() %>%
#     mutate(rowid = 1:length(cr), cr.dum = as.factor(ifelse(cr <= thres, 1, 0))) %>%
#     select(cr.dum, rowid)
#
#
#   cityahp <- data %>%
#     ahp.mat(atts, negconvert = T)
#
#   eigentrue <- ahp.indpref(cityahp, atts, method = "eigen")
#
#   d <- data %>%
#     ahpsurvey::ahp.mat(atts = atts, negconvert = TRUE) %>%
#     ahpsurvey::ahp.indpref(atts, method = "eigen") %>%
#     dplyr::mutate(rowid = 1:nrow(eigentrue)) %>%
#     dplyr::left_join(cr.df, by = 'rowid') %>%
#     tidyr::gather(atts, key = "var", value = "pref")
#
#   state<-list(d, cr)
#   image <- self$results$plot2
#   image$setState(state)
# }
#



# .plot2 = function(image,ggtheme, theme,...) {
#
#   if (is.null(image$state))
#     return(FALSE)
#
#   atts <- strsplit(self$options$atts, ',')[[1]]
#   thres <- 0.1
#
#   d <- image$state[[1]]
#   cr <- image$state[[2]]
#
#  plot2 <- d |> ggplot(aes(x = var, y = pref)) +
#     geom_violin(alpha = 0.6, width = 0.8, color = "transparent", fill = "gray") +
#     geom_jitter(alpha = 0.6, height = 0, width = 0.1, aes(color = cr.dum)) +
#     geom_boxplot(alpha = 0, width = 0.3, color = "#808080") +
#     scale_x_discrete("Attribute", label = atts) +
#     scale_y_continuous("Weight (dominant eigenvalue)",
#                        labels = scales::percent,
#                        breaks = c(seq(0,0.7,0.1))) +
#     guides(color=guide_legend(title=NULL))+
#     scale_color_discrete(breaks = c(0,1),
#                          labels = c(paste("CR >", thres),
#                                     paste("CR <", thres))) +
#     labs(NULL, caption = paste("n =", nrow(data), ",", "Mean CR =",
#                                round(mean(cr),3)))+
#     #theme_minimal()
#
#     theme(
#       axis.text.x = element_text(size = 12, color = "black")  # adjust size and darkness of x-axis text
#       #axis.text.x.bottom = element_text(angle = 90, hjust = 1)  # rotate x-axis text by 90 degrees
#     )
#
#   plot2+ggtheme
#
#     if (self$options$angle > 0) {
#     plot2 <- plot2 + ggplot2::theme(
#       axis.text.x = ggplot2::element_text(
#         angle = self$options$angle, hjust = 1
#       )
#     )
#   }
#
#
#   print(plot2)
#   TRUE
#
# },