#' @title Interactive Network Visualization

#' @description An interactive function to assist in the visualization of the result from INDEED 

#'     functions non_partial_corr() or patial_corr(). The size and the color of each node can be 

#'     adjusted by users to represent either the Node_Degree, Activity_Score, Z_Score, or P_Value.

#'     The color of the edge is based on the binary value of either 1 corresponding to a positive 

#'     correlation depicted as green or a negative correlation of -1 depicted as red. Users also 

#'     have the option of having the width of each edge be proportional to its weight value. The 

#'     layout of the network can also be customized by choosing from the options: 'nice', 'sphere', 

#'     'grid', 'star', and 'circle'. Nodes can be moved and zoomed in on. Each node and edge will 

#'     display extra information when clicked on. Secondary interactions will be highlighted as 

#'     well when a node is clicked on. 

#' @param result This is the result from calling either non_partial_corr() or partial_corr(). 

#' @param nodesize This parameter determines what the size of each node will represent. The options 

#'     are 'Node_Degree', 'Activity_Score','P_Value' and 'Z_Score'. The title of the resulting 

#'     network will identify which parameter is selected to represent the node size. The default 

#'     is Node_Degree.

#' @param nodecolor This parameter determines what color each node will be based on a yellow to 

#'     blue color gradient. The options are 'Node_Degree', 'Activity_Score', 'P_Value', and '

#'     Z_Score'. A color bar will be created based on which parameter is chosen. The default is

#'     Activity_Score.

#' @param edgewidth This is a boolean value to indicate whether the edgewidth should be representative 

#'     of the weight connection (TRUE) or not (FALSE). The default is FALSE.

#' @param layout Users can choose from a a handful of network visualization templates including:

#'     'nice', 'sphere', 'grid', 'star', and 'circle'. The default is nice. 

#' @examples result = non_partial_cor(data = Met_GU, class_label = Met_Group_GU, id = Met_name_GU, 

#'                                    method = "pearson", p_val = pvalue_M_GU, permutation = 1000, 

#'                                    permutation_thres = 0.05, fdr = FALSE)

#'           network_display(result = result, nodesize = 'Node_Degree', nodecolor = 'Activity_Score', 

#'                           edgewidth = FALSE, layout = 'nice')

#' @return An interactive depiction of the network resulting from INDEED functions 

#'     non_partial_corr() or patial_corr().

#' @import igraph

#' @import visNetwork

#' @importFrom grDevices topo.colors 

#' @export

network_display <- function(result = NULL, nodesize= 'Node_Degree', nodecolor= 'Activity_Score', 

                            edgewidth= FALSE, layout= 'nice'){

    nodes <- result$activity_score

    links <- result$diff_network

    # Adding Z_Score to dataframe

    Z_Score <- abs(qnorm(1 - (nodes$P_value)/2)) # trasfer p-value to z-score

    nodes$zscore = Z_Score

    vis.nodes <- data.frame(id= nodes$Node, name= nodes$ID,font.size = 24, pval= nodes$P_value, 

                            ndegree= nodes$Node_Degree, ascore= nodes$Activity_Score,

                            zscore= nodes$zscore, stringsAsFactors = FALSE)

    vis.links <- data.frame(from=links$Node1, to=links$Node2, binary= links$Binary, 

                            weight= links$Weight)

    vis.nodes$shape  <- "dot"  

    vis.nodes$shadow <- TRUE # Nodes will drop shadow

    # Information that will be displayed when hovering over a node 

    vis.nodes$title <- paste0("<p>", paste('ID: ', vis.nodes$name), "<br>","<br>", 

                              paste('Node Degree: ', vis.nodes$ndegree),"<br>", 

                              paste('Activity Score: ', vis.nodes$ascore),"<br>", 

                              paste('P-value: ', vis.nodes$pval),"<br>",

                              paste('Z-score: ', round(vis.nodes$zscore, digits=3)),"</p>")

    # Setting up the Node Size

    if (missing(nodesize)){

      vis.nodes$size   <- (rank(-1 * vis.nodes$pval)+1)

        nodesize <- 'p-value significance '

    }

    else if (nodesize == 'Node_Degree'){

        vis.nodes$size   <- ((vis.nodes$ndegree)+1)*5

        nodesize <- 'Node Degree'

    } 

    else if(nodesize == 'Activity_Score'){

        vis.nodes$size   <- ((vis.nodes$ascore)+1)*5

        nodesize <- 'Activity Score'

    }

    else if(nodesize == 'P_Value'){

        vis.nodes$size   <- (rank(-1 * vis.nodes$pval)+1)

        nodesize <- 'p-value significance'

    }

    else if(nodesize == 'Z_Score'){

        vis.nodes$size   <- ((vis.nodes$zscore)+1)*10

        nodesize <- 'Z-Score'

    } else {

        vis.nodes$size   <- (rank(-1 * vis.nodes$pval)+1)

        nodesize <- 'p-value significance'

    }

    H <- "Higher"

    L <- "Lower"

    M <- "       "

    # Setting Up Node Color

    if (missing(nodecolor)){

        vis.nodes<- vis.nodes[order(vis.nodes$ascore, decreasing=TRUE), ]

        vis.nodes$color.background <- topo.colors(length(vis.nodes$ascore), alpha=1)

        vis.nodes$color.highlight.background <- topo.colors(length(vis.nodes$ascore), alpha=1)

        nodecolor <- 'Activity Score'

    }

    else if (nodecolor == 'Node_Degree'){

        vis.nodes<- vis.nodes[order(vis.nodes$ndegree, decreasing=TRUE), ]

        vis.nodes$color.background <- topo.colors(length(vis.nodes$ndegree), alpha=1)

        vis.nodes$color.highlight.background <- topo.colors(length(vis.nodes$ndegree), alpha=1)

        nodecolor <- 'Node Degree'

    } 

    else if(nodecolor == 'Activity_Score'){

        vis.nodes<- vis.nodes[order(vis.nodes$ascore, decreasing=TRUE), ]

        vis.nodes$color.background <- topo.colors(length(vis.nodes$ascore), alpha=1)

        vis.nodes$color.highlight.background <- topo.colors(length(vis.nodes$ascore), alpha=1)

        nodecolor <- 'Activity Score'

    }

    else if(nodecolor == 'P_Value'){

        vis.nodes<- vis.nodes[order(vis.nodes$pval, decreasing=FALSE), ]

        vis.nodes$color.background <- topo.colors(length(vis.nodes$pval), alpha=1)

        vis.nodes$color.highlight.background <- topo.colors(length(vis.nodes$pval), alpha=1)

        nodecolor <- 'p-value'

        H <- "Lower"

        L <- "Higher"

        M <- "       "

    }

    else if(nodecolor == 'Z_Score'){

      vis.nodes<- vis.nodes[order(vis.nodes$zscore, decreasing=TRUE), ]

      vis.nodes$color.background <- topo.colors(length(vis.nodes$zscore), alpha=1)

      vis.nodes$color.highlight.background <- topo.colors(length(vis.nodes$zscore), alpha=1)

      nodecolor <- 'Z-Score'

    }

    else {

        vis.nodes<- vis.nodes[order(vis.nodes$ascore, decreasing=TRUE), ]

        vis.nodes$color.background <- topo.colors(length(vis.nodes$ascore), alpha=1)

        vis.nodes$color.highlight.background <- topo.colors(length(vis.nodes$ascore), alpha=1)

        nodecolor <- 'Activity Score'

    }

    vis.nodes$borderWidth <- 2 # Node border width

    vis.nodes$label  <- vis.nodes$name # Node label

    vis.nodes$color.highlight.border <- "darkred"

    vis.nodes$color.border <- "black"

    # Setting up edge width parameter 

    if (edgewidth == TRUE ){vis.links$width <- abs(vis.links$weight) * 3

    } else {vis.links$width <- 3}

    # Information that will be displayed when hovering over the edge

    vis.links$title <- paste0("<p>", paste('Edge Weight: ', 

                                           round(abs(vis.links$weight), digits= 3)), "</p>")

    vis.links$color[vis.links$binary == 1] <- "green"    # line color  

    vis.links$color[vis.links$binary == -1] <- "red" 

    vis.links$arrowStrikethrough <- FALSE

    vis.links$smooth <- TRUE    # should the edges be curved?

    vis.links$shadow <- TRUE    # edge shadow

    # Setting up layout of network 

    if (missing(layout)){l <- "layout_nicely"}

    else if (layout == 'nice'){l <- "layout_nicely"}

    else if (layout == 'sphere'){l <- "layout_on_sphere"}

    else if (layout == 'star'){l <- "layout_as_star"}

    else if (layout == 'grid'){l <- "layout_on_grid"}

    else if (layout == 'circle'){l <- "layout_in_circle"

    } else {l <- "layout_nicely"}

    lnodes <- data.frame(label= c(H, M, L), position = "left", shape= c("circle"), 

                         color= c("blue", "green", "yellow"))

    ledges <- data.frame(color= c("green", "red"), label= c("Positive Change in Correlation", 

                                                            "Negative Change in Correlation"), 

                         font.align= "top", arrows= c("NA", "NA"), width= 4)

    net <- visNetwork(vis.nodes, vis.links, width = "100%", height = "800px", main= "INDEED", 

                      submain= paste("Node size represents: ", nodesize)) %>%

        visOptions( highlightNearest= TRUE, nodesIdSelection= TRUE)  %>% 

        visIgraphLayout(layout=l) %>%

        visInteraction( dragView= TRUE, dragNodes= TRUE, zoomView= TRUE, navigationButtons= FALSE, 

                        hideEdgesOnDrag= FALSE, multiselect = TRUE) %>%

        visLegend(addEdges= ledges, addNodes= lnodes, position= "right", useGroups= FALSE, ncol=1, 

                  main= paste("Node color based on ", nodecolor), width= 0.2, zoom = TRUE)

    print(net)

}