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old_code.R
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old_code.R
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prediction_panel_org <- tabPanel(
HTML("<b>Prediction and metagenomic inference</b>"),
selectInput("prediction_mode", "Select mode: ", choices = c("Automatic", "Customized"), selected = "Automatic"),
conditionalPanel(
condition = "input.prediction_mode == 'Automatic'",
sidebarPanel(
width = 12,
tags$label(h3("Input files and parameters")),
hr(),
tags$style(".buttonagency .bttn-primary{color: #3B3B3B; border-color: #7D7D7D; background-color: #E7E7E7; margin-top:1em;}"),
fileInput("network_auto", "Network", accept = ".RData"),
div(style = "font-size: 10px; padding: 0px 0px; margin-top:-1em", numericInput("iterations_auto", "Iterations", value = 1, min = 1, max = 50, step = 0.5)),
div(style = "font-size: 10px; padding: 0px 0px; margin-top:3em", fileInput("seqs_auto", "Sequences", accept = c(".fasta", ".fa", ".fas"))),
div(style = "font-size: 10px; padding: 0px 0px; margin-top:-1em", numericInput("error_network_auto", "Conditional probability allowed +- error", value = 0.3, min = 0, max = 1, step = 0.05)),
div(style = "font-size: 10px; padding: 0px 0px;", textInput("directory_auto", "Specify an output folder", placeholder = "experiment_1")),
# div(style = "font-size: 10px; padding: 0px 0px; margin-top:3em",directoryInput('directory_auto', label = 'Select an output folder')),
div(class = "buttonagency", style = "display:inline-block; margin-right:10px;", actionBttn(inputId = "button_auto", label = "Launch", style = "float", color = "primary", size = "sm", icon = icon("rocket"))),
div(class = "buttonagency", style = "display:inline-block; margin-right:10px;", actionBttn(inputId = "stop_button_auto", label = "Stop process", style = "float", color = "primary", size = "sm", icon = icon("window-close"))),
div(class = "buttonagency", style = "display:inline-block", actionBttn(inputId = "check_button_auto", label = "Check status", style = "float", color = "primary", size = "sm", icon = icon("check-square")))
),
mainPanel(
shinyjs::useShinyjs(),
tags$head(tags$style(HTML(".shiny-notification {width: 800px; position:fixed; top: calc(98% - 50px);; left: calc(50% - 400px);;}"))),
tags$head(tags$style("#automated_pred{text-align:justify; overflow-y:scroll; overflow-x:hidden; max-height: 575px; background: #F8F8F8;}")),
textOutput("automated_pred")
)
),
conditionalPanel(
condition = "input.prediction_mode == 'Customized'",
fluidRow(
column(
3,
wellPanel(
tags$label(h3("Input network")),
# hr(),
fileInput("network", "Network", accept = ".RData")
)
),
column(
6,
wellPanel(
tags$label(h3("Predict taxa values")),
# hr(),
textInput("taxas", "Taxas", value = "", placeholder = 'Example: Bacteria_X,Bacteria_Y. Write "all" for all taxas.'),
# textInput("evidence", "Evidence", value= "", placeholder = 'Example: season=S,tissue=AI'),
# verbatimTextOutput("directorypath"),
# shinyDirButton('directory', 'Select a folder', 'Please select a folder', FALSE),
# textInput("outputFolder", "Output folder", value= getwd()),
# div(style = "display:inline-block; float:right;", actionButton("button1", "Submit")))),
numericInput("iterations", "Iterations", value = 1, min = 1, max = 50, step = 0.5),
numericInput("error_network", "Conditional probability allowed +- error", value = 0.3, min = 0, max = 1, step = 0.05),
tags$style(HTML(pickerInput_select)),
tags$style(HTML(pickerInput_deselect)),
uiOutput("selector", container = div),
div(class = "buttonagency", actionBttn(inputId = "button1", label = "Submit", style = "float", color = "primary", size = "sm"))
)
),
column(
3,
wellPanel(tags$label(h3("Display conditional probability tables")),
# hr(),
textInput("nodes", "Nodes", value = "", placeholder = "Example: Bacteria_X,Bacteria_Y,season,tissue"),
# numericInput("shiny_width", "Width", value= "1000"),
# numericInput("shiny_heigth", "Heigth", value= "1000"),
height = 12,
div(class = "buttonagency", actionBttn(inputId = "button2", label = "Submit", style = "float", color = "primary", size = "sm"))
)
)
),
mainPanel(tags$hr(style = "margin-left: -1em; max-width: none; max-heigth: 100vh; width: 100vw; heigth: auto; object-fit: contain;"),
div(style = "align: center", tabsetPanel(
type = "pills",
tabPanel(
strong("Predicted value"),
tags$hr(style = "margin-left: -1em; max-width: none; max-heigth: 100vh; width: 100vw; heigth: auto; object-fit: contain;"),
dataTableOutput("predicted_value")
),
tabPanel(
strong("Conditional probability table"),
tags$hr(style = "margin-left: -1em; max-width: none; max-heigth: 100vh; width: 100vw; heigth: auto; object-fit: contain;"),
uiOutput("selector_cpt", container = div),
downloadButton("save_cpt_all", "Download all tables", class = "butt"),
tags$head(tags$style(".butt{background-color:#F7F7F7;} .butt{color: black;}")),
downloadButton("save_cpt", "Download current table", class = "butt"),
tags$head(tags$style("#conditional_table{overflow: auto; padding: 20px; text-align:justify; overflow-y:scroll; overflow-x:scroll; max-height: 575px; background: #F8F8F8;}")),
verbatimTextOutput("conditional_table")
),
tabPanel(
strong("Infer metagenome"),
tags$hr(style = "margin-left: -1em; max-width: none; max-heigth: 100vh; width: 100vw; heigth: auto; object-fit: contain;"),
fileInput("counts", "Raw counts text file", accept = ".txt"),
div(style = "font-size: 10px; padding: 0px 0px; margin-top:-4em", uiOutput("example_counts")),
div(style = "font-size: 10px; padding: 0px 0px; margin-top:2em", fileInput("seqs", "Sequences fasta file", accept = c(".fa", ".fasta"))),
div(style = "font-size: 10px; padding: 0px 0px; margin-top:-4em", uiOutput("example_seqs")),
# shinyDirButton('directory', 'Select an output folder', 'Please select a folder'),
div(style = "font-size: 10px; padding: 0px 0px; margin-top:2em", directoryInput("directory", label = "Select an output folder")),
span(tags$i(h6(HTML("<b>Remember to remove white spaces in fasta headers.</b>"))), style = "color:#52C4DD"),
tags$style(".buttonpicrust .bttn-primary{color: #3B3B3B; border-color: #7D7D7D; background-color: #E7E7E7;}"),
div(class = "buttonpicrust", style = "font-size: 10px; padding: 0px 0px; margin-top:2em;", actionBttn(inputId = "button_picrust", label = "Launch", style = "float", color = "primary", size = "sm", icon = icon("rocket"))),
mainPanel(fluidRow(
align = "center", shinyjs::useShinyjs(), style = "background-color:#F8F8F8;",
textOutput("predicted_metagenome")
), width = 12)
)
)),
style = "width: 1000px; height: 1000px"
)
)
)
##########################
observeEvent(input$network_plot, {
if (is.null(input$network_plot)) {
return(NULL)
}
inFile <- isolate({
input$network_plot
})
file <- inFile$datapath
load(file, envir = .GlobalEnv)
Graph_output <- reactiveValues(graph = NULL)
## Plot the network
plotInput <<- function() {
# nodes <- str_replace_all(input$nodes_plot, c("/" = ".", " " = ".", "-" = "."))
# nodes <- strsplit(nodes, ",")[[1]]
# for (i in 1:length(nodes)) {
# nodes[i] <- sub("/",".", nodes[i])
# nodes[i] <- sub(" ",".", nodes[i])
# nodes[i] <- str_replace(nodes[i], "-",".")
# }
nodes <- names(fittedbn)
# nodes = nodes[11:length(nodes)]
subgr <<- bnlearn::subgraph(fittedbn, nodes)
tryit <- try(strength.viewer(
bayesianNetwork = subgr,
bayesianNetwork.boot.strength = arc_st_mi,
bayesianNetwork.arc.strength.label = TRUE,
bayesianNetwork.arc.strength.tooltip = TRUE,
# bayesianNetwork.edge.scale.min = 1,
# bayesianNetwork.edge.scale.max = 1,
edges.dashes = FALSE,
bayesianNetwork.layout = "layout_nicely"
))
if (inherits(tryit, "try-error")) {
gr <- bn.to.igraph(subgr)
p <- visIgraph(gr)
# data <- toVisNetworkData(igraph_network)
# visNetwork(nodes = data$nodes, edges = data$edges)
} else {
p <- strength.viewer(
bayesianNetwork = subgr,
bayesianNetwork.boot.strength = arc_st_mi,
bayesianNetwork.arc.strength.label = TRUE,
bayesianNetwork.arc.strength.tooltip = TRUE,
# bayesianNetwork.edge.scale.min = 1,
# bayesianNetwork.edge.scale.max = 1,
edges.dashes = FALSE,
bayesianNetwork.layout = "layout_nicely",
)
}
# Graph_output$graph <- p
}
Tab_inputs <- reactiveValues(
nodes = NULL,
edges = NULL,
Ord_edg0 = NULL,
Sel_group = "None",
refresh = NULL,
# write = NULL
)
# Reset
observeEvent(eventExpr = input$button_plot, ignoreNULL = FALSE, {
shinyjs::reset("Edit_menu")
updateSidebar("sidebar")
nodes <<- NULL
nodes_info <<- NULL
edges <<- NULL
edges_info <<- NULL
# Reseteamos todas las variables filt
'Filt <<- reactiveValues(sel_tab_n = NULL,
sel_tab_e = NULL,
sel_menu = NULL,
grade = 0,
direction = "All")'
Filt$sel_tab_n <<- NULL
Filt$sel_tab_e <<- NULL
Filt$sel_menu <<- NULL
Filt$sel_by <<- NULL
Filt$grade <<- 0
Filt$number <<- 0
Filt$direction <<- "All"
Tab_inputs$nodes <<- NULL
Tab_inputs$edges <<- NULL
Sel_edg <- NULL
Sel_nod <- NULL
# shinyjs::reset("Filter_Tab_N")
# shinyjs::reset("Filter_Tab_E")
# shinyjs::reset("Filter_Tab_Menu")
# Undo()
updateCheckboxGroupInput(
inputId = "Filter_Tab_N",
choices = list("Emphasize" = "Emph", "Show/Hide" = "S/H"),
selected = NULL
)
updateCheckboxGroupInput(
inputId = "Filter_Tab_E",
choices = list("Emphasize" = "Emph", "Show/Hide" = "S/H"),
selected = NULL
)
updateCheckboxGroupInput(
inputId = "Filter_Menu",
choices = list("Emphasize" = "Emph", "Show/Hide" = "S/H"),
selected = NULL
)
updateCheckboxGroupInput(
inputId = "Filter_Menu_By",
choices = list("Selected" = "By_sel", "Group" = "By_group", "Number of interactions" = "By_num"),
selected = NULL
)
DT::dataTableProxy("Tab_nodes") %>% # Reordenamos
clearSearch()
DT::dataTableProxy("Tab_edges") %>% # Reordenamos
clearSearch()
})
observeEvent(input$button_plot, ignoreNULL = FALSE, {
# print("*2")
Tab_inputs$refresh <- input$button_plot
})
## Link button to print image
p_button <- eventReactive(Tab_inputs$refresh, print(plotInput()))
# cpt_button <- eventReactive(input$button2, table_cpt())
# #
# Net representation
output$network_proxy <- renderVisNetwork(
# if(! is.null(Graph_output$graph)){
p_button() %>%
# Graph_output$graph %>%
# Permite seleccionar nodos (file:data)
visEvents(
type = "on",
# Al seleccionar guardamos los ids de nodos y edges
select = "function(data) {
Shiny.onInputChange('current_nodes_selection', data.nodes);
Shiny.onInputChange('current_edges_selection', data.edges);
}",
# deselectNode = "function(data) {
# Shiny.onInputChange('deselect_nodes', data.nodes);
# }" ,
doubleClick = "function(data) {
Shiny.onInputChange('doubleClick_nodes_selection', data.nodes);
Shiny.onInputChange('doubleClick_edges_selection', data.edges);
}",
# input$network_proxy_initialized pasa a true al generar la red completamente, pero solo funciona la primera vez, por tanto al iniciar la red la fijamos en FALSE
afterDrawing = "function(data) {
Shiny.onInputChange('network_proxy_initialized', false);
}",
# Al deseleccionar, deseleccionamos en la tabla:
) %>%
# Fija los parámetros por defecto de la primara representación
visNodes(
color = list(
background = DT$color_background,
border = DT$color_border,
highlight = list(
background = DT$color_highlight,
border = DT$color_border
)
),
physics = DT$bounce,
shape = DT$shape
) %>%
visEdges(scaling = list(
min = DT$scaling_min,
max = DT$scaling_max,
label = list(
enabled = DT$scaling_label_enabled,
min = DT$scaling_label_min,
max = DT$scaling_label_max
)
)) %>%
visInteraction(multiselect = TRUE, selectConnectedEdges = FALSE) %>%
visOptions(highlightNearest = FALSE, nodesIdSelection = FALSE, autoResize = TRUE)
# %>% visPhysics(stabilization = FALSE)
# }
)
observeEvent(eventExpr = input$network_proxy_initialized, ignoreNULL = FALSE, {
# print("*4")
# Tab_inputs$write = TRUE
visNetworkProxy("network_proxy") %>%
visGetNodes() %>%
visGetEdges() %>%
visGetSelectedNodes() %>%
visGetSelectedEdges()
})
## Funciones
Select_nodes <- function() { # Get selected nodes ids
# visNetworkProxy("network_proxy") %>%
# visGetSelectedNodes() # Return input$network_proxy_selectedNodes
nod <- input$network_proxy_selectedNodes
if (is.null(nod)) {
Sel_nodes <- nodes$id
} else {
Sel_nodes <- nod
}
return(Sel_nodes)
}
Get_nodes <- function() { # Get all nodes ids
visNetworkProxy("network_proxy") %>%
visGetNodes() # return input$network_proxy_nodes
}
Nodes_info <- function() { # Get all nodes info
# Get_nodes()
nodes_in <- input$network_proxy_nodes
nodes_out <- data.frame()
for (i in c(1:length(nodes_in))) {
nod <- nodes_in[[i]]
if (nrow(nodes_out) == 0) {
nodes_out <- data.frame(nod)
} else {
nodes_out <- merge(x = nodes_out, y = nod, all = TRUE)
}
}
return(nodes_out)
}
Select_edges <- function() { # Get selected edges ids
# visNetworkProxy("network_proxy") %>%
# visGetSelectedEdges() # Return input$network_proxy_selectedEdges
edg <- input$network_proxy_selectedEdges
if (is.null(edg)) {
Sel_edges <- edges$id
} else {
Sel_edges <- edg
}
return(Sel_edges)
}
Get_edges <- function() { # Get all edges ids
visNetworkProxy("network_proxy") %>%
visGetEdges() # return input$network_proxy_edges
}
Edges_info <- reactive({
# Get_edges()
edges_in <- input$network_proxy_edges
edges_out <- data.frame()
for (i in c(1:length(edges_in))) {
nod <- edges_in[[i]]
if (nrow(edges_out) == 0) {
edges_out <- data.frame(nod)
} else {
edges_out <- merge(x = edges_out, y = nod, all = TRUE)
}
}
return(edges_out)
})
Nodes_table <- function() {
# print(input$network_proxy_nodes[1])
nodes <<- Nodes_info()
nodes_info <<- data.frame( # Info nodos
nodes,
size = DT$size,
# Info color
color.background = DT$color_background,
color.border = DT$color_border,
color.highlight.background = DT$color_highlight,
color.highlight.border = DT$color_border,
color.hover.background = DT$color_background,
color.hover.border = DT$color_border,
# Info labels
font.color = DT$font_color,
font.size = DT$font_size,
font.face = DT$font_face,
font.strokeWidth = DT$font_strokeWidth,
font.strokeColor = DT$font_strokeColor,
font.align = DT$N_font_align
# Shadow
# shadow.enabled = DT$shadow_enabled,
# shadow.color = DT$shadow_color,
# shadow.size = DT$shadow_size,
# shadow.x = DT$shadow_x,
# shadow.y = DT$shadow_y
)
Tab_inputs$nodes <- nodes[, c("id", "label")]
Ord_nod_tab <<- Tab_inputs$nodes
# Definimos los grupos de nodos a saleccionar posteriormente
Groups <<- list(All = nodes$id, None = NULL)
}
Edges_table <- function() {
Get_edges()
edges <<- Edges_info()
edges_info <<- data.frame(
edges,
# Scaling
scaling.min = DT$scaling_min,
scaling.max = DT$scaling_max,
scaling.label.enabled = DT$scaling_label_enabled,
scaling.label.min = DT$scaling_label_min,
scaling.label.max = DT$scaling_label_max,
# Info color
color.color = DT$color_border,
color.highlight = DT$color_border,
color.opacity = 1,
# Info labels
font.color = DT$font_color,
font.size = DT$font_size,
font.face = DT$font_face,
font.strokeWidth = DT$font_strokeWidth,
font.strokeColor = DT$font_strokeColor,
font.align = DT$E_font_align
# Shadow
# shadow.enabled = DT$shadow_enabled,
# shadow.color = DT$shadow_color,
# shadow.size = DT$shadow_size,
# shadow.x = DT$shadow_x,
# shadow.y = DT$shadow_y
)
Tab_inputs$edges <- edges[, c("id", "value", "from", "to")]
Ord_edg_tab <<- Tab_inputs$edges # Tab_inputs$edges
# Rep <<- 1
}
observeEvent(eventExpr = input$network_proxy_edges, ignoreNULL = TRUE, {
# print("*5")
Nodes_table()
Edges_table()
if (isFALSE(input$E_label)) {
S_edges <- edges_info$id
visNetworkProxy("network_proxy") %>%
visUpdateEdges(edges = data.frame(id = S_edges, label = " "))
}
# Tab_inputs$refresh <<- 0
})
######
# Tab information
# Funciones
## Ordenar
OrderNodes <- function() {
if (isFALSE(input$Reorder_N) | is.null(input$network_proxy_selectedNodes)) {
Ord_nod_tab <<- nodes[, c("id", "label")] # Tab_inputs$nodes
} else {
Ind_nodes <- which(Ord_nod_tab$id %in% input$network_proxy_selectedNodes)
Sel_tab <- (merge(
x = data.frame(
ord = (1:length(input$network_proxy_selectedNodes)),
node = input$network_proxy_selectedNodes
),
y = data.frame(
ind = Ind_nodes,
node = Ord_nod_tab$id[Ind_nodes]
)
))
Sel_nodes <- (Sel_tab[with(Sel_tab, order(Sel_tab$ord, decreasing = TRUE)), ])$ind
Non_select <- which(!Ord_nod_tab$id %in% input$network_proxy_selectedNodes)
Order <- c(Sel_nodes, Non_select)
Ord_nod_tab <<- Ord_nod_tab[Order, ]
}
}
# Outpur Tab
observe({
# Tab_inputs$refresh
Tab_inputs$nodes
input$Data
Sel_nod0 <- which(Ord_nod_tab$id %in% Sel_nod)
output$Tab_nodes <- DT::renderDataTable({
D_T <- DT::datatable(Ord_nod_tab,
options = list(scrollX = TRUE),
editable = list(target = "column", disable = list(columns = c(1))), # Permite editar
escape = FALSE,
filter = "top",
selection = list(
mode = "multiple",
selected = Sel_nod0,
target = "row"
),
callback = htmlwidgets::JS( ## https://stackoverflow.com/questions/66129627/create-an-r-shiny-binding-to-a-double-click-event-on-a-dt-datatable
"table.on('dblclick', 'td',",
" function() {",
" var row = table.cell(this).index().row;",
" var col = table.cell(this).index().column;",
" Shiny.setInputValue('dt_dblclick', {dt_row: row, dt_col: col});",
" }",
");",
"table.on('click', 'td',",
" function() {",
" var row = table.cell(this).index().row;",
" var col = table.cell(this).index().column;",
" Shiny.setInputValue('dt_click', {dt_row: row, dt_col: col});",
" }",
");"
)
)
})
})
'
observeEvent(input$dt_dblclick, {
print("DOBLE CLICK")
print(input$dt_dblclick)
})
observeEvent(input$dt_click, {
print(" CLICK")
print(input$dt_click)
})'
# Selecciona en la red los nodos de la Tab_nodes
observeEvent(eventExpr = input$Tab_nodes_cell_clicked, ignoreNULL = FALSE, { # Se activa cuando hacemos click en la tabla
if (length(input$Tab_nodes_cell_clicked) > 0) {
S_nodes <- {
nod <- input$Tab_nodes_rows_selected
tab <- Ord_nod_tab
if (is.null(nod)) {
S_nodes <- NULL
} else {
sel <- input$Tab_nodes_cell_clicked$row
n1 <- nod[which(nod == sel)]
n2 <- nod[which(nod != sel)]
S_nodes <- append(tab[n1, "id"], tab[n2, "id"])
}
S_nodes
}
S_edges <- input$network_proxy_selectedEdges
S_nodes <- rev(S_nodes)
if (is.null(S_edges) && is.null(S_nodes)) {
visNetworkProxy("network_proxy") %>%
visUnselectAll()
} else {
visNetworkProxy("network_proxy") %>%
visSetSelection(
nodesId = S_nodes,
edgesId = S_edges,
unselectAll = TRUE,
highlightEdges = FALSE
)
}
}
# Actualizamos
visNetworkProxy("network_proxy") %>%
visGetSelectedNodes() %>%
visGetSelectedEdges()
})
# Ordenamos la tabla para posicionar los seleccionados primero
observe({
OrderNodes()
})
# Seleccionar filas que se corresponden con los nodos seleccionados en la red
observe({
Sel_nod <<- input$network_proxy_selectedNodes
input$Reorder_N
if (is.null(input$network_proxy_selectedNodes)) {
DT::dataTableProxy("Tab_nodes") %>% # Reordenamos
replaceData(data = Ord_nod_tab, clearSelection = FALSE, resetPaging = FALSE) %>%
# Eliminamos la selección
selectRows(NULL)
} else {
DT::dataTableProxy("Tab_nodes") %>% # Reordenamos
replaceData(data = Ord_nod_tab, clearSelection = FALSE, resetPaging = FALSE) %>% # Seleccionamos
selectRows(which(Ord_nod_tab$id %in% input$network_proxy_selectedNodes))
}
})
### Edicion de las etiquetas de los nodos ###
# Edición de las Etiquetas de los nodos
observeEvent(eventExpr = input$Tab_nodes_cell_edit, {
Nodes_edit <- input$Tab_nodes_cell_edit
if (colnames(Ord_nod_tab)[Nodes_edit$col] == "label") {
ID <- Ord_nod_tab[Nodes_edit$row, "id"]
visNetworkProxy("network_proxy") %>%
visUpdateNodes(nodes = data.frame(
id = ID,
label = Nodes_edit$value
))
nodes[which(nodes$id == ID), "label"] <<- Nodes_edit$value
nodes_info[which(nodes_info$id == ID), "label"] <<- Nodes_edit$value
}
})
# Edges
## Escogemos el número de decimales
output$Value_decimals <- renderUI({
if (!is.null(Tab_inputs$edges$value)) {
sig_count <- function(n) {
num <- gsub("^[^(1-9)]*", "", x = n)
num <- gsub("\\.", "", x = num)
nchar(num)
}
Sig <- max(sapply(X = Tab_inputs$edges$value, FUN = sig_count))
sliderInput(
inputId = "Value_decimals", label = "Significant digits",
step = 1, min = 1, max = Sig, value = Sig
)
}
})
# Funciones
# Ordenar
OrderEdges <- function() {
if (isFALSE(input$Reorder_E) | is.null(input$network_proxy_selectedEdges)) {
Ord_edg_tab <<- edges[, c("id", "value", "from", "to")]
} else {
Ind_edges <- which(Ord_edg_tab$id %in% input$network_proxy_selectedEdges)
Sel_tab <- (merge(
x = data.frame(
ord = (1:length(input$network_proxy_selectedEdges)),
edge = input$network_proxy_selectedEdges
),
y = data.frame(
ind = Ind_edges,
edge = Ord_edg_tab$id[Ind_edges]
)
))
Sel_edges <- (Sel_tab[with(Sel_tab, order(Sel_tab$ord, decreasing = TRUE)), ])$ind
Non_select <- which(!Ord_edg_tab$id %in% input$network_proxy_selectedEdges)
Order <- c(Sel_edges, Non_select)
Ord_edg_tab <<- Ord_edg_tab[Order, ]
}
}
# Output de la tabla edges:
output$Tab_edges <- DT::renderDataTable({
Sel_edg0 <- which(Ord_edg_tab$id %in% Sel_edg)
DT_edg <<- DT::datatable( # Tab_inputs$Ord_edg0,
Ord_edg_tab,
# Tab_inputs$edges,
# Ord_edg0,
options = list(scrollX = TRUE),
editable = FALSE, # No permite editar por el usuario
escape = FALSE,
filter = "top",
selection = list(
mode = "multiple",
selected = Sel_edg0, # Fijamos la selección inicial
target = "row"
)
)
if (!is.null(input$Value_decimals)) {
DT_edg %>%
formatSignif(columns = c("value"), digits = input$Value_decimals)
}
})
# Cambiamos las etiquetas de los edges
observeEvent(eventExpr = input$Value_decimals, ignoreNULL = TRUE, {
if (isTRUE(input$E_label)) {
lab <- sapply(X = edges_info$value, FUN = signif, input$Value_decimals)
edges_info$label <<- sapply(X = lab, FUN = as.character)
visNetworkProxy("network_proxy") %>%
visUpdateEdges(edges = data.frame(
id = edges_info$id,
label = edges_info$label
))
}
})
# Selecciona los edges que une dos nodos seleccionados.
observeEvent(eventExpr = input$network_proxy_selectedNodes, {
if (!is.null(input$network_proxy_selectedNodes)) {
e1 <- edges[edges$from %in% input$network_proxy_selectedNodes, ]
e2 <- e1[e1$to %in% input$network_proxy_selectedNodes, ]
if (nrow(e2) > 0) {
S_edges <- unique(append(input$network_proxy_selectedEdges, e2$id))
S_nodes <- input$network_proxy_selectedNodes
visNetworkProxy("network_proxy") %>%
visSetSelection(
nodesId = S_nodes,
edgesId = S_edges,
unselectAll = FALSE,
highlightEdges = FALSE
)
}
# Actualizamos
visNetworkProxy("network_proxy") %>%
visGetSelectedNodes() %>%
visGetSelectedEdges()
}
})
# Selecciona en la red los edges de la Tab_edges
observeEvent(eventExpr = input$Tab_edges_cell_clicked, ignoreNULL = FALSE, {
S_edges <- {
edg <- input$Tab_edges_rows_selected
tab <- Ord_edg_tab
if (is.null(edg)) {
S_edges <- NULL
} else {
S_edges <- tab[edg, "id"]
}
S_edges
}
S_nodes <- input$network_proxy_selectedNodes
if (is.null(S_nodes) && is.null(S_edges)) {
visNetworkProxy("network_proxy") %>%
visUnselectAll()
} else {
visNetworkProxy("network_proxy") %>%
visSetSelection(
nodesId = S_nodes,
edgesId = S_edges,
unselectAll = TRUE,
highlightEdges = FALSE
)
}
# Actualizamos
visNetworkProxy("network_proxy") %>%
visGetSelectedNodes() %>%
visGetSelectedEdges()
})
# Ordenamos la tabla para posicionar los seleccionados primero
observe({
Tab_inputs$edges
input$Value_decimals
OrderEdges()
visNetworkProxy("network_proxy") %>%
visGetSelectedEdges()
})
# Seleccionar filas que se corresponden con los edges seleccionados en la red
observe({
Sel_edg <<- input$network_proxy_selectedEdges
Tab_inputs$edges
input$Value_decimals
input$Reorder_E
if (is.null(input$network_proxy_selectedEdges)) {
DT::dataTableProxy("Tab_edges") %>%
replaceData(data = Ord_edg_tab, clearSelection = TRUE) %>%
selectRows(NULL)
} else {
DT::dataTableProxy("Tab_edges") %>%
replaceData(data = Ord_edg_tab, clearSelection = FALSE) %>%
selectRows(which(Ord_edg_tab$id %in% input$network_proxy_selectedEdges))
}
})
# Informacion nodos
### Texto a mostrar ###
# id del nodo tras el doble click
output$N1 <- renderPrint({
if (is.null(input$doubleClick_nodes_selection)) {
NULL
} else {
fittedbn[[input$doubleClick_nodes_selection]]
}
})
output$Node_info <- renderUI({
if (is.null(input$doubleClick_nodes_selection)) {
NULL
} else {
verbatimTextOutput("N1")
}
})
output$E1 <- renderText({
edge_id <- input$doubleClick_edges_selection
from <- edges[edges$id == edge_id, "from"]
to <- edges[edges$id == edge_id, "to"]
value <- edges[edges$id == edge_id, "value"]
paste0(
"Causal Relationships : \n ",
from, " → ", to,
"\nEdge Strength : \n ",
value
)
})
output$Edge_info <- renderUI({
if (is.null(input$doubleClick_edges_selection)) {
NULL
} else {
verbatimTextOutput("E1")
}
})
######
# Panel de edicion
## Nodos
observeEvent(eventExpr = input$current_nodes_selection, ignoreNULL = FALSE, {
visNetworkProxy("network_proxy") %>%
visGetSelectedNodes() %>%
visGetSelectedEdges()
})
observeEvent(eventExpr = input$Tab_nodes_cell_clicked, ignoreNULL = FALSE, {
visNetworkProxy("network_proxy") %>%
visGetSelectedNodes() %>%
visGetSelectedEdges()
})
# Shape
observeEvent(eventExpr = input$N_shape, {
if (!is.null(nodes)) {
S_nodes <- Select_nodes()
visNetworkProxy("network_proxy") %>%
visUpdateNodes(nodes = data.frame(id = S_nodes, shape = input$N_shape))
}
})
# Size
observeEvent(eventExpr = input$N_size, {
if (!is.null(nodes)) {
S_nodes <- Select_nodes()
N_nodes <- which(nodes_info$id %in% S_nodes)
nodes_info[N_nodes, "size"] <<- input$N_size
visNetworkProxy("network_proxy") %>%
visUpdateNodes(nodes = data.frame(id = S_nodes, size = input$N_size))
}
})
Auto_size_all <- function(nod) {
connections <- length(which(edges["from"] == nod | edges["to"] == nod))
return(connections)
}
Auto_size_from <- function(nod) {
connections <- length(which(edges["from"] == nod))
return(connections)
}
Auto_size_to <- function(nod) {
connections <- length(which(edges["to"] == nod))
return(connections)
}
observe({
if (isTRUE(input$N_autosize)) {
if (!is.null(nodes)) {
if (input$N_autosize_type == "E_F") {
connections <- sapply(nodes$id, Auto_size_from)
} else {
if (input$N_autosize_type == "E_T") {
connections <- sapply(nodes$id, Auto_size_to)
} else {
connections <- sapply(nodes$id, Auto_size_all)
}
}
max1 <- max(connections)
min1 <- min(connections)
min0 <- input$N_size_range[1]
max0 <- input$N_size_range[2]
r <- (max0 - min0) / max1
sizes <- list()
for (c in connections) {
f <- min0 + (c * r)
sizes <- append(sizes, round(f))
}
visNetworkProxy("network_proxy") %>%
visUpdateNodes(nodes = data.frame(id = nodes$id, size = unlist(sizes)))
}
} else {
visNetworkProxy("network_proxy") %>%
visUpdateNodes(nodes = data.frame(id = nodes$id, size = nodes_info$size))
}
})
# Border Width
observeEvent(eventExpr = input$N_borderWidth, {
if (!is.null(nodes)) {
S_nodes <- Select_nodes()
visNetworkProxy("network_proxy") %>%
visUpdateNodes(nodes = data.frame(id = S_nodes, borderWidth = input$N_borderWidth))
}
})
## Selected Border Width
observeEvent(eventExpr = input$N_borderWidthSelected, {
if (!is.null(nodes)) {
S_nodes <- Select_nodes()
visNetworkProxy("network_proxy") %>%
visUpdateNodes(nodes = data.frame(id = S_nodes, borderWidthSelected = input$N_borderWidthSelected))
}
})
# Background color
observeEvent(eventExpr = input$N_color_background, {
if (!is.null(nodes)) {
S_nodes <- Select_nodes()
N_nodes <- which(nodes_info$id %in% S_nodes)
nodes_info[N_nodes, "color.background"] <<- input$N_color_background