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app.R
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if(!require(shiny)) install.packages('shiny')
if(!require(htmlwidgets)) install.packages('htmlwidgets')
if(!require(shinythemes))install.packages('shinythemes')
if(!require(network)) install.packages('network')
if(!require(blockmodeling)) install.packages('blockmodeling')
if(!require(igraph)) install.packages('igraph')
if(!require(visNetwork))install.packages('visNetwork')
if(!require(intergraph))install.packages('intergraph')
if(!require(DT))install.packages('DT')
if(!require(shinybusy))install.packages('shinybusy')
if(!require(shinyjs))install.packages('shinyjs')
library(shiny)
library(shinyjs)
library(htmlwidgets)
library(shinythemes)
library(blockmodeling)
library(intergraph)
library(igraph)
library(network)
library(visNetwork)
library(DT)
library(shinybusy)
# Sect. 1 Inputs ####
ui <- fluidPage(
useShinyjs(), # Initialise Shinyjs
includeCSS("./style.css"), # CSS Styles
theme = shinytheme("united"),
tags$head(
tags$link(
rel = "shortcut icon",
href = "https://www.fdv.uni-lj.si/App_Themes/Fdv/TemplateImages/icons/favicon.ico")),
tags$head(
tags$title("Generalised blockmodeling")
),
tags$style(type="text/css", "#Info {white-space: pre-wrap;}"),
## 0. Decorations with HTML/CSS ####
titlePanel({
withTags({
div(class="Header",
table(
tr(
td(width = "267px",
img(class = "HeaderLogo",
src="https://www.uni-lj.si/images/mobile/logo_m.png"),
),
td(
div(style="h1","Generalised blockmodeling"),
),
), # /tr
), # /table
div(class="titleRect",
div(class="title2",.noWS = c('outside', 'after-begin', 'before-end'),
'This app provides some useful tools for Offering an accessible GUI for generalised blockmodeling of single-relation, one-mode networks. The user can execute blockmodeling without having to write a line code by using the app\'s visual helps. Moreover, there are several ways to visualisations networks and their partitions. Finally, the results can be exported as if they were produced by writing code. To lean more about how this can be helpful to you, you can check the descriptions of the package',
a(href="https://cran.r-project.org/package=blockmodeling", "blockmodeling"),
'by Ale\u0161 \u017Diberna'
)# /div "title2"
) # /div "titleRect"
) # div "Header"
})
}),
add_busy_spinner(
spin = 'breeding-rhombus',
color = '#978E83',
timeout = 100,
position = 'top-right',
onstart = TRUE,
margins = c(10, 10)
),
# Sidebar
tabsetPanel(
tabPanel(title = "Data upload",
fluidRow(
column(3,
## 1. File-upload options ####
# "FileInputOpt1"
withTags({
div(h4(b("File-upload options")))
}),
### 1.1 Use a sample ####
### "Sample"
checkboxInput(inputId = "Sample",
label = 'Use a sample',
value = F),
conditionalPanel(
condition = "input.Sample == false",
### 1.2 Select type of input ####
## "type"
selectInput(inputId = "type",
label = "Type of data?",
choice = c("Adjacency Matrix*"=1,"Edges list"=2, "Incidence matrix"=3,"Pajek"=4),
selected = 1,
multiple = FALSE
),
conditionalPanel(
condition = "input.type != 4",
#### 1.2.1 Upload list ####
### "List"
fileInput(inputId = "List",
label = "Upload the selected list as a plain-text file",
multiple = F,
accept = c("text/plain", ".csv",".tab"),
buttonLabel = "Browse",
placeholder = "Your list here"),
#### 1.2.2 Headers edge list file ####
### "ListHeader"
checkboxInput(inputId = "ListHeader",
label = 'Headers?',
value = T,
),
)
)
),
column(4,offset = 1,
## 2. Customise file elaboration ####
# "FileInputOpt2"
withTags({
div(h4(b("Customise file elaboration")))
}),
### 2.1 Separator ####
## "sep"
radioButtons(inputId = "sep",
label = "Separator",
choiceNames = c("tab","comma","semicolon","other"),
choiceValues = c("\t",",",";","Other")
),
conditionalPanel(
condition = "input.sep == 'Other'",
#### 2.1.1 Other separator ####
### "OtherSep"
textAreaInput(inputId = "OtherSep",
label = 'You selected "other", please indicate the right separator',
cols = 3,
value = "",
),
),
### 2.2 Trim blanks ####
## "whites"
checkboxInput(inputId = "whites",
label = 'Trim extra blanks',
value = TRUE),
conditionalPanel(
condition = "input.type == 4",
### 2.3 Type of Pajek file ####
## "PajekInput"
radioButtons(inputId = "PajekInput",
label = "Type of Pajek file",
selected = ".net",
choiceNames = c(".mat",".net"),
choiceValues = c("PajekMatrix","PajekNetwork")
),
### 2.4 Upload Pajek file ####
## "PajekFile"
fileInput(inputId = "PajekFile",
label = "Upload a Pajek file",
multiple = F,
buttonLabel = "Browse",
placeholder = "Your Pajek file here",
accept = c(".mat",".net")
),
), # if input.type == 4
), # columnt 3
column(4,
## 3. Specify network properties ####
# "NetworkOpt"
withTags({
div(h4(b("Specify network properties")))
}),
### 3.1 Values/Weights ####
## "ValuedMatrix"
checkboxInput(inputId = "ValuedMatrix",
label = 'Valued/Weighted network',
value = TRUE,
),
#### 3.1.1 Values/Weights name ####
# "ValuesName"
# conditionalPanel(
# condition = "input.ValuedMatrix == true",
# textInput(inputId = "ValuesName",
# label = "How do you want the weights to be called?",
# value = "weights",
# placeholder = "weights, values, counts, etc...")
# ),
withTags(div(
h6(b(i("Only change the settings below if needed"))),
)),
### 3.2 Direction ####
# "directionality"
checkboxInput(inputId = "directionality",
label = 'Directional edges',
value = TRUE,
),
### 3.3 Self-links ####
# "loops"
checkboxInput(inputId = "loops",
label = 'Self-links',
value = TRUE,
),
### 3.4 Delete isolated nodes ####
checkboxInput(inputId = "DelIsolated",
label = 'Delete isolated nodes',
value = FALSE),
### 3.5 Add attribute ####
conditionalPanel(
condition = "input.Sample == false",
### "AddAttr"
checkboxInput(inputId = 'AddAttr',
label = 'Add a vertex attribute?',
value = F),
conditionalPanel(
condition = 'input.AddAttr==true',
conditionalPanel(
condition = 'input.Sample==false',
#### 3.5.1 Attribute values
#### "AddAttrFile"
fileInput(inputId = "AddAttrFile",
label = 'Values from file',
placeholder = 'A text file containining the values',
multiple = F,
accept = 'text/plain'
),
#### 3.5.2 Attribute name
#### 'AddAttrName'
textInput(inputId = "AddAttrName",
label = 'Attribute name',
placeholder = 'Do not use blanks',
value = NULL),
),
),
),
),
### 3.6 Button "Read data" ####
# "aj"
actionButton(inputId = "aj",
label = "Read Data",
icon = icon(name = "upload",
lib = "font-awesome")
)
),# Fluid row
## 4. Show the network's summary ####
# "summary"
verbatimTextOutput("summary"),
### 4.1 Summary with adj ####
## "NetworkSummaryOpt"
withTags({
div(h4(b("An extra option")))
}),
# "IncludeAdj"
checkboxInput(inputId = "IncludeAdj",
label = 'Include the edgelist matrix?',
value = F,
width = "100%"
),
), # Tab panel Data
tabPanel(title = "Generalised blockmodeling",
## 5. Block-modeling ####
sidebarLayout(
sidebarPanel(width = 9,
withTags({
div(h3(b("Customise blockmodeling")))
}),
hr(),
fluidRow(
column(4,
### 5.1 Approaches ####
withTags(h4(b('Approaches'))),
### "blckmdlngApproach"
selectInput(inputId = "blckmdlngApproach",
label = "Select approach",
choices = c("Binary"="bin",
"Valued"="val",
"Sum of squares homogeneity"="ss",
"Absolute deviations homogeneity"="ad"),
multiple=FALSE
),
#### 5.1.1 M parameter for valued blockmodeling ####
#### "ParamM"
conditionalPanel(
condition ="input.blckmdlngApproach == 'val'",
numericInput(inputId = "ParamM",
label = 'Select the M parameter',
value = NULL,
min = 0,
step = 1
)
),
#### 5.1.2 Threshold parameter for binary blockmodeling ####
#### "ParamThreshold", "ThresholdSelected"
conditionalPanel(
condition ='input.blckmdlngApproach == "bin"',
# Asks whether the user wants to set a threshold
checkboxInput(inputId = "ThresholdSelected",
label = 'Use a binarisation threshold',
value = F,
width = "100%"),
),
conditionalPanel(
condition ="input.ThresholdSelected == true && input.blckmdlngApproach == 'bin'",
numericInput(inputId = "ParamThreshold",
label = 'Threshold parameter',
value = NULL,
min = 0,
step = 1)
),
hr(),
### 5.2 Block types ####
withTags(h4(b('Block types'))),
#### 5.2.1 Block-type parameters
##### 5.2.1 (A) Density parameter for block-type 'den' ####
##### "ParamDensity"
shinyjs::hidden(
numericInput(inputId = "ParamDensity",
label = 'Select the density',
value = NULL,
step = 1)
),
##### 5.2.1 (B) Average parameter for block-type 'avg' ####
##### "ParamAverage"
shinyjs::hidden(
numericInput(inputId = "ParamAverage",
label = 'Select the average',
value = NULL,
step = 1)
),
#### 5.2.2 Show/Hide Block-types weights' menu ####
#### 'blockTypeWeights_Show'
checkboxInput(inputId = 'blockTypeWeights_Show',
label = 'Show/Hide block-types weights\' menu',
value = F),
#### 5.2.3 Types of of allowed blocktypes ####
##### 5.2.3 (A) Pre-specified - Menu ####
#### "blckmdlngPrespecified_Show"
checkboxInput(inputId = "blckmdlngPrespecified_Show",
label = 'Show/Hide menu to pre-specify the allowed blocktypes',
value = FALSE
),
##### 5.2.3 (B) Non pre-specified ####
#### "blckmdlngBlockTypes"
conditionalPanel(
condition = 'input.blckmdlngPrespecified_Switch == false',
selectInput(inputId = "blckmdlngBlockTypes",
label = "Allowed blocktypes",
choices = NULL,
multiple = TRUE
),
#### 5.2.3 (C) Number of clusters (non pre-specified) ####
### "blckmdlngNumClusters"
numericInput(inputId = "blckmdlngNumClusters",
label = 'How many clusters to use in the generation of partitions?',
value = 3,
min = 1,
step = 1
),
), # Conditional blckmdlngPrespecified_Switch
),
column(4,
### 5.3 Other options ####
withTags(h4(b('Other options'))),
withTags(h4('Computation')),
#### 5.3.1 Number of repetitions ####
#### "blckmdlngRepetitions"
numericInput(inputId = "blckmdlngRepetitions",
label = 'How many repetitions/different starting partitions to check?',
value = 2,
min = 1,
step = 1
),
#### 5.3.2 Random Seed ####
### "blckmdlngRandomSeed"
numericInput(inputId = "blckmdlngRandomSeed",
label = 'Insert a random seed to use it',
value = NULL,
min = 0,
step = 1
),
#### 5.3.3 Multi-core processing ####
#### "MultiCore"
checkboxInput(inputId = "MultiCore",
label = 'Should the parallel computation be used?',
value = FALSE
),
),
column(4,
withTags(h4('Results')),
#### 5.3.4 Restore-memory max size
numericInput(inputId = 'Restore_MaxMemory',
label = 'Results to store in buffer memory',
value = 3,
min = 1,
max = 10,
step = 1),
#### 5.3.5 Number of results to save ####
#### "blckmdlngMaxSavedResults"
numericInput(inputId = "blckmdlngMaxSavedResults",
label = 'How many results to save?',
value = 10,
min = 1,
step = 10),
#### 5.3.6 Saving initial parameters ####
fluidRow(
column(5,
#### "blckmdlngInitialParams"
checkboxInput(inputId = "blckmdlngInitialParams",
label = 'Should the initial parameters be saved?',
value = TRUE),
),
column(7,
withTags(i("Saving the additional parameters can take up more memory, but also preserve precious information")),
),
),
#### 5.3.6 Returning all ####
fluidRow(
column(7,
#### "blckmdlngAll"
checkboxInput(inputId = "blckmdlngAll",
label = 'Should solution be shown for all partitions (not only the best one)?*',
value = TRUE),),
column(5,
withTags(i("Disable for very complex calculation and/or low-end machines")),
),
),
### 5.8 Which best partition to print ####
conditionalPanel(
condition = 'input.blckmdlngAll==true',
fluidRow(
column(7,
### "whichIM"
condition = "input.blckmdlngAll==true",
numericInput(inputId = "whichIM",
label = 'Which "best" partition should be printed?*',
value = 1,
min = 1,
step = 1),
), # / col
column(5,
br(''),withTags(i('*Affects also error matrix and mean matrix')),
), # / col
), # / Fluid row
), # / Conditional panel
#### 5.3.7 Printing extra info ####
#### "blckmdlngPrintRep"
checkboxInput(inputId = "blckmdlngPrintRep",
label = 'Should some information about each optimization be printed?',
value = TRUE),
), # Column 4
), # / Col layout
), # / Sidebar panel
mainPanel(width = 3,
### 5.6 Start blockmodeling ####
### "blckmdlngRun"
withTags(h4(b("Start blockmodeling"))),
actionButton(inputId = "blckmdlngRun",
label = "Process data",
icon = icon(name = "calculator",
lib = "font-awesome")
),
hr(),
### 5.7 Restore from memory ####
withTags(h4(b("Restore from memory"))),
checkboxInput(inputId = 'Restore_Switch',
label = 'Check to restore previous results',
value = F),
conditionalPanel(
condition = 'input.Restore_Switch==true',
numericInput(inputId = 'Restore_Selector',
label = 'Memory slot to restore',
value = 1,min = 1,max = 10),
withTags(h5(style='color=#ff0000',
b(i('Press "Process data" to restore'))
)),
),
hr(),
### 5.7 Upload results ####
withTags(h4(b("Upload results"))),
checkboxInput(inputId = "blckmdlngRDS",
label = "Upload blockmodelling results",
value = F),
### 5.9 Load blockmodeling results from RDS ####
### "blckmdlngRDS", "blckmdlngFileRDS"
#### Upload results as RDS file
conditionalPanel(
condition = 'input.blckmdlngRDS==true',
fileInput(inputId = "blckmdlngFileRDS",
label = NULL,
multiple = F,
buttonLabel = "Browse",
placeholder = "Your RDS file here",
accept = c(".RDS")
),
withTags(h5(i('Use the "Read Data" button under the "Data upload" tab to read the matrix from this file'))),
),# Conditional panel RDS
hr(),
### 5.10 Download blockmodeling RDS ####
### "DownloadBlckRDS"
withTags(h4(b("Downloads"))),
withTags(h5(b("Download results"))),
p(
downloadButton(outputId = "DownloadBlckRDS",
label = "Download blockmodeling results",
icon = icon(name = "download",
lib = "font-awesome")
),
conditionalPanel(
condition = 'input.blckmdlngPrespecified_Switch==true',
withTags(i('After processing the data it will be possible to download the custom blockmodel')),
downloadButton(outputId = 'downloadCustomBlck',
label = 'Download custom blockmodel',
icon = icon(name = "download",
lib = "font-awesome")
),
),
),
p(
### 5.11 Download vector partitions ####
### "DownloadClu"
downloadButton(outputId = "DownloadClu",
label = "Download partitions as vector",
icon = icon(name = "download",
lib = "font-awesome")
),
),
withTags(h5(b("Other downloads"))),
### 5.12 Download image matrix ####
conditionalPanel(
condition = "input.dropIM == true",
p(
# "DownloadIMtext"
downloadButton(outputId = "DownloadIMtext",
label = "Download image matrix as txt",
inline=T,
icon = icon(name = "table",
lib = "font-awesome")
),
),
),
# "DownloadIMrds"
p(
downloadButton(outputId = "DownloadIMrds",
label = "Download image matrix as RDS",
inline=T,
icon = icon(name = "table",
lib = "font-awesome")
),
),
# "DropIM"
checkboxInput(inputId = "dropIM",
label = 'Drop one-element dimensions',
value = TRUE,
width = '100%'),
), # / main panel
),# / Sidebar Layout
mainPanel(
width=12,
### 5.4 Set block-types weights - Menu ####
conditionalPanel(
condition = 'input.blockTypeWeights_Show==true',
sidebarPanel(width = 12,
### 'blockTypeWeights_Switch',
checkboxInput(inputId = 'blockTypeWeights_Switch',
label = 'Use block-type weights',
value = F),
withTags(h4(b('Set custom block-types\' weights'))),
fluidRow(
### 'blockTypeWeights_com', 'blockTypeWeights_nul'
column(4,
withTags(h5(b('Basic'))),
numericInput(inputId = 'blockTypeWeights_com',
label = 'Complete',value = 1,min = 0),
numericInput(inputId = 'blockTypeWeights_nul',
label = 'Null',value = 1,min = 0),
numericInput(inputId = 'blockTypeWeights_dnc',
label = '"Do not care"',value = 1,min = 0),
),
### 'blockTypeWeights_rre','blockTypeWeights_cre'
column(4,
withTags(h5(b('Regular'))),
numericInput(inputId = 'blockTypeWeights_rre',
label = 'Row-regular',value = 1,min = 0),
numericInput(inputId = 'blockTypeWeights_cre',
label = 'Column-regular',value = 1,min = 0),
numericInput(inputId = 'blockTypeWeights_reg',
label = 'f-Regular',value = 1,min = 0),
),
### 'blockTypeWeights_dnc', 'blockTypeWeights_reg'
column(4,
withTags(h5(b('Advanced'))),
# numericInput(inputId = 'blockTypeWeights_rdo',
# label = 'Row-dominant',value = 1,min = 0),
# numericInput(inputId = 'blockTypeWeights_cdo',
# label = 'Column-dominant',value = 1,min = 0),
numericInput(inputId = 'blockTypeWeights_den',
label = 'Density',value = 1,min = 0),
numericInput(inputId = 'blockTypeWeights_avg',
label = 'Average',value = 1,min = 0),
),# /column
), # /fluidRow
), # /sidebarPanel
), # / Conditional Panel Show
### 5.5 Pre-specified block types ####
conditionalPanel(
condition = 'input.blckmdlngPrespecified_Show == true',
sidebarLayout(
sidebarPanel(
# width = 12,
##### 5.5.1 Pre-specified switch ####
#### "blckmdlngPrespecified_Switch"
withTags(h5(b('Check the box to use the block model'))),
checkboxInput(inputId = "blckmdlngPrespecified_Switch",
label = 'Use pre-specified blocktypes?',
value = FALSE),
withTags(i('Even if the menu is hidden, your choice is remembered')),
#### 5.5.2 DT table options ####
fluidRow(
column(width = 6,
##### 5.5.2 (A) Clusters' size ####
##### 'CustoomBlockModel_NumberCluster'
numericInput(inputId = "CustoomBlockModel_NumberCluster",
label = 'Number of cluster',
value = 3,
min = 2,
step = 1),
actionButton(inputId = 'SetSizeDT',
label = 'Confirm',
icon = icon(name = "window-maximize",
lib = "font-awesome")
),
), # column
column(width = 6,
##### 5.5.2 (B) Block types ####
##### 'TowardsDT'
selectInput(inputId = "TowardsDT",
label = "Select the allowed blocktypes",
choices = NULL,
selected = c("nul","com"),
multiple = TRUE
),
actionButton(inputId = "LoadBlocksIntoDT",
label = "Load blocks",
icon = icon(name = "clone",
lib = "font-awesome")
),
),# End of column with inputs
), # End of fluid row
hr(),
#### 5.5.3 File upload for pre-specified block-types' array ####
##### 5.5.3 (A) Type of uploaded array ####
# "ArrayInput"
radioButtons(inputId = "ArrayInput",
label = "Type of file to upload?",
selected = ".RDS",
choiceValues = c(".RDS",".RData"),
choiceNames = c("R Data Serialized","R Data"),
inline = T
),
##### 5.5.3 (B) Upload array as RDS file ####
conditionalPanel(
condition = 'input.ArrayInput==".RDS"',
fileInput(inputId = "PrespecifiedArrayRDS",
label = "Upload a RDS file",
multiple = F,
buttonLabel = "Browse",
placeholder = "Your R file here",
accept = c(".RDS")
),
),# Conditional panel RDS
##### 5.5.3 (C) Upload array as RData file ####
conditionalPanel(
condition = 'input.ArrayInput==".RData"',
fileInput(inputId = "PrespecifiedArrayRData",
label = "Upload a RData file",
multiple = F,
buttonLabel = "Browse",
placeholder = "Your R file here",
accept = c(".RData")
),
), # Conditional panel RData
withTags(i("An array with four dimensions. The first is as long as the maximum number of allowed block types for a given block. The second dimension is the number of relations. The third and the fourth represent rows' and columns' clusters. For more information see", a(href="https://cran.r-project.org/web/packages/blockmodeling/blockmodeling.pdf#page=10",'here',target="_blank"))),
##### 5.5.3 (D) Button to upload the array
##### 'UploadArray'
hr(),
actionButton(inputId = 'UploadArray',
label = 'Load the array to see the block model',
icon = icon(name = 'upload',
lib = 'font-awesome')
),
##### 5.5.3 (E) Switch to edit the uploaded array
##### 'EditUploadedArray'
checkboxInput(inputId = 'EditUploadedArray',
label = 'Ignore the uploaded array',
value = F
),
withTags(h5('Only turn on',i('after'),'loading a block model from file')),
), # / Sidebar
mainPanel(
#### 5.5.4 DT Table ####
DT::dataTableOutput(outputId = 'CustomBlockModel',width = '100%'),
fluidRow(
column(width = 3,
hr(),
),
column(width = 4,
actionButton(inputId = 'ResetSelectionDT',
label = 'Reset selection',
icon = icon(name = 'recycle',
lib = "font-awesome")),
),
column(width = 3,
actionButton(inputId = 'SelectAllDT',
label = 'Select all',
icon = icon(name = 'check',
lib = "font-awesome")),
),
column(width = 2,
withTags(p('')),
),
), # / fluidrow
),
),
), # / conditional panel blckmdlngPrespecified_Show==T
### 5.13 Show the blockmodeling's results ####
### "Tableblckmdlng", "Summaryblckmdlng"
withTags({
div(h4(b("Summary of blockmodeling results")))
}),
tabsetPanel(
tabPanel(title = "Table",
tableOutput("Tableblckmdlng"),
),
tabPanel(title = "Summary",
verbatimTextOutput("Summaryblckmdlng"),
),
tabPanel(title = "Image matrix",
tableOutput("TableIM")
),
tabPanel(title = "Error matrix",
fluidRow(
column(4,tableOutput("TableEM")),
column(5, withTags(p(''))),
column(3,
numericInput(inputId = 'DigitsEM',
label = 'How many digits to show?',
value = 3,min = 0,step = 1),
),
),
),
tabPanel(title = "Mean matrix",
fluidRow(
column(4,tableOutput("TableMean")),
column(5, withTags(p(''))),
column(3,
numericInput(inputId = 'DigitsMean',
label = 'How many digits to show?',
value = 3,min = 0,step = 1),
),
),
),
),
), # mainPanel
# ), # Sidebar layout
), # Tab panel2
## 6. Show the Adjacency Matrix ####
## "adjOptType","adj","adjPlot"
tabPanel(title = "Adjacency matrix",
sidebarLayout(
sidebarPanel(width = 4,
### 6.1 Select network ####
withTags(h4(b("Select matrix"))),
radioButtons(inputId = "adjSelector",
label = "Which matrix do you want to use?",
choiceNames = c("original"),
choiceValues = c(1)
),
p(id='BlckNotRunYet_Plot',style="color:red;",
'Run the blockmodeling to be able to select\nthe partitioned network'
),
### 6.2 Select type of output ####
conditionalPanel(
condition = "input.adjSelector == 1",
withTags(h4(b("Select output"))),
radioButtons(inputId = "adjOptType",
label = "Type of visualisation",
choiceNames = c("table","plot"),
choiceValues = c("t","p")
),
conditionalPanel(
condition = "input.adjOptType == 't'",
withTags(h4(b("Export adjacency matrix"))),
### 6.4 Download adjacency matrix ####
downloadButton(outputId = "downloadAdj",
label = 'Download',
icon = icon(name = "download",
lib = "font-awesome")
),
), # /input.adjOptType
), # /input.adjSelector
### 6.3 Which best partition to print ####
### "whichIM_adjPlot"
conditionalPanel(
condition = "input.blckmdlngAll==true",
conditionalPanel(
condition = 'input.adjSelector==2',
numericInput(inputId = "whichIM_adjPlot",
label = 'Which "best" partition should be printed?',
value = 1,
min = 1,
step = 1,
),
),
),
### 6.4 Margin size
## 'MatrixPlotMargin'
numericInput(inputId = 'MatrixPlotMargin',
label = 'Set the plot\'s margin',
value = 1.6,
min = 0,
step = .1
),
),
mainPanel(
### 6.3 Table output original matrix ####
tableOutput("adj"),
### 6.4 Output plot-matrix ####
plotOutput(outputId = "adjPlot"),
),
), #</Sidebarlayout>
), # Tabpanel
tabPanel(title = "Network Plot",
## 7 Various sys of network plots ####
conditionalPanel(
### 7.1 "Network" and "igraph" sys ####
condition = "input.PlotSys != 3",
plotOutput("NetworkPlot",
height = 640,width = 800),
),
conditionalPanel(
condition = "input.PlotSys == 3",
### 7.2 "visNetwork" sys ####
visNetworkOutput("igraphPlot",
height = 640,width = 800),
),
## 8. Plotting options####
# "PlotOpt"
withTags({
div(h4(b("Plotting options")))
}),
hr(),
fluidRow(
### 8.1 Select matrix to plot ####
## "PlotSelector"
column(6,
withTags(i("Select network")),
radioButtons(inputId = "PlotSelector",
label = "Which matrix to use?",
inline = T,
choiceNames = c("original"),
choiceValues = c(1),
),
p(id='BlckNotRunYet_Plot',style="color:red;",
'Run the blockmodeling to be able to select\nthe partitioned network'
),
),
### 8.2 Select plotting sys ####
## "PlotSys"
column(6,
withTags(i("Select output")),
radioButtons(inputId = "PlotSys",
label = "Which package to use for plotting?",
choiceNames = c("network","igraph","visNetwork"),
choiceValues = c(1,2,3),
inline = TRUE,
selected = 2
),
),
column(3,
conditionalPanel(
condition = 'input.PlotSelector==2',
#### 8.2.1 Which best partition to print ####
### "whichIM_Plot"
numericInput(inputId = "whichIM_Plot",
label = 'Which "best" partition should be used for plotting?',
value = 1,
min = 1,
step = 1,
),
), # /conditionalPanel
), # /column
), # /fluidRow
### 8.3 Options for the "network" plotting sys ####
conditionalPanel(
condition = "input.PlotSys == 1",
withTags({
div(h4(b("network Plotting Options")))
}),
## Layout with mutiple coloumns
hr(),
fluidRow(
column(3,
withTags(h5(b("General options"))),
#### 8.3.1 Mode ####
## "PlotMode"
radioButtons(inputId = "PlotMode",
label = 'Nodes arrangement',
choiceNames = c("Fruchterman-Reingold algorithm","Circle"),
choiceValues = c("fruchtermanreingold","circle"),
inline = TRUE
),
#### 8.3.2 Isolate ####
### "PlotIsolate"
checkboxInput(inputId = "PlotIsolate",
label = 'Isolated nodes',
value = TRUE
),
#### 8.3.3 Interactive ####
### "PlotInteractive"
# checkboxInput(inputId = "PlotInteractive",
# label = 'Should the plot be plot be interactive?*',