Merge branch 'master' into easybgminJASP

Merge branch 'master' into easybgminJASP

# Conflicts:
#	R/bayesiannetworkanalysis.R
#	inst/qml/BayesianNetworkAnalysis.qml

.github/workflows/unittests.yml

@@ -12,6 +12,7 @@ jobs:
 
   unit-tests:
 
+    if: github.event_name != 'pull_request' || github.event.pull_request.head.repo.full_name != github.event.pull_request.base.repo.full_name
     uses: jasp-stats/jasp-actions/.github/workflows/unittests.yml@master
     with:
       needs_JAGS:   false

R/networkanalysis.R

@@ -38,7 +38,7 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
 
   .networkAnalysisCentralityTable  (mainContainer, network, options)
   .networkAnalysisClusteringTable  (mainContainer, network, options)
-  .networkAnalysisPlotContainer    (mainContainer, network, options)
+  .networkAnalysisPlotContainer    (mainContainer, network, options, dataset)
   .networkAnalysisWeightMatrixTable(mainContainer, network, options)
 
   # done last so that all other results are shown already
@@ -95,8 +95,11 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
 
     # check if data must be binarized
     if (options[["estimator"]] %in% c("isingFit", "isingSampler")) {
-      idx <- colnames(dataset) != options[["groupingVariable"]]
-      dataset[idx] <- bootnet::binarize(dataset[idx], split = options[["split"]], verbose = FALSE, removeNArows = FALSE)
+
+      for (i in seq_along(dataset)) {
+        idx <- colnames(dataset[[i]]) != options[["groupingVariable"]]
+        dataset[[i]][idx] <- bootnet::binarize(dataset[[i]][idx], split = options[["split"]], verbose = FALSE, removeNArows = FALSE)
+      }
 
       if (options[["estimator"]] == "isingFit") {
         # required check since isingFit removes these variables from the analyses
@@ -177,12 +180,13 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
   if (is.null(mainContainer)) {
     mainContainer <- createJaspContainer(dependencies = c(
       # data
-      "variables", "groupingVariable", "mgmVariableType",
+      "variables", "groupingVariable",
       # what kind of network is estimated
       "estimator",
       # arguments for the estimator
       "correlationMethod", "tuningParameter", "criterion", "isingEstimator",
       "nFolds", "split", "rule", "sampleSize", "thresholdBox", "thresholdString", "thresholdValue",
+      "mgmContinuousVariables", "mgmCategoricalVariables", "mgmCountVariables",
       # general arguments
       "weightedNetwork", "signedNetwork", "missingValues"
     ))
@@ -199,7 +203,9 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
   if (is.null(mainContainer[["generalTable"]])) {
     tb <- createJaspTable(gettext("Summary of Network"), position = 1, dependencies = c(
       # These are dependencies because specifying them incorrectly is communicated as footnotes on this table
-      "computedLayoutX", "computedLayoutY", "bootstrap", "bootstrapSamples", "minEdgeStrength"
+      "computedLayoutX", "computedLayoutY", "bootstrap", "bootstrapSamples", "minEdgeStrength",
+      # these trigger recomputation in addition to footnotes
+      "mgmContinuousVariables", "mgmCategoricalVariables", "mgmCountVariables"
     ))
     if (length(dataset) > 1L)
       tb$addColumnInfo(name = "info", title = gettext("Network"), type = "string")
@@ -462,7 +468,7 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
 }
 
 # plots ----
-.networkAnalysisPlotContainer <- function(mainContainer, network, options) {
+.networkAnalysisPlotContainer <- function(mainContainer, network, options, dataset) {
 
   plotContainer <- mainContainer[["plotContainer"]]
   if (is.null(plotContainer)) {
@@ -471,7 +477,7 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
     mainContainer[["plotContainer"]] <- plotContainer
   }
 
-  .networkAnalysisNetworkPlot   (plotContainer, network, options)
+  .networkAnalysisNetworkPlot   (plotContainer, network, options, dataset = dataset)
   .networkAnalysisCentralityPlot(plotContainer, network, options)
   .networkAnalysisClusteringPlot(plotContainer, network, options)
 }
@@ -669,7 +675,7 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
     ))
 }
 
-.networkAnalysisNetworkPlot <- function(plotContainer, network, options, method = "frequentist") {
+.networkAnalysisNetworkPlot <- function(plotContainer, network, options, method = "frequentist", dataset = NULL) {
 
 
   # Adjust options based on method
@@ -763,7 +769,10 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
       idx[options[["variables"]] %in% options[[nms[[i]]]]] <- i
     # idx[i] is 1 if variable[i] %in% mgmContinuousVariables, 2 if in mgmCategoricalVariables, etc.
 
-    ll <- lengths(options[c("mgmContinuousVariables", "mgmCategoricalVariables", "mgmCountVariables")])
+    # order of variables need not match dataset, and thus the order of types may be wrong
+    newOrder <- match(colnames(dataset[[1L]]), options[["variables"]])
+    # now we have variables[newOrder] == colnames(dataset[[1L]])
+    idx <- idx[newOrder]
 
     if (options[["mgmVariableTypeShown"]] == "nodeShape") {
       #         gaussian, categorical, poisson
@@ -1010,6 +1019,11 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
       }
     }
 
+    # order of variables need not match dataset, and thus the order of types may be wrong
+    newOrder <- match(colnames(dataset[[1L]]), variables)
+    # now we have variables[newOrder] == colnames(dataset[[1L]])
+    type <- type[newOrder]
+
     if (any(type == "")) {
       message <- gettext("Please drag all variables to a particular type under \"Analysis options\".")
       e <- structure(class = c("mgmError", "error", "condition"), list(message = message, call = sys.call(-1)))
@@ -1112,10 +1126,19 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
   # for every dataset do the analysis
   for (nw in seq_along(dataset)) {
 
+    data <- dataset[[nw]]
+
+    # mgm requires integer instead of factor
+    if (options[["estimator"]] == "mgm") {
+      for (i in seq_along(data))
+        if (!is.numeric(data[[i]]))
+          data[[i]] <- as.integer(data[[i]])
+    }
+
     jaspBase::.suppressGrDevice(
       msg <- capture.output(
         network <- bootnet::estimateNetwork(
-          data    = dataset[[nw]],
+          data    = data,
           default = .networkAnalysisJaspToBootnetEstimator(options[["estimator"]]),
           .dots   = .dots
         )

inst/qml/BayesianNetworkAnalysis.qml

@@ -300,7 +300,7 @@ VariablesForm
 			CheckBox	{ name: "manualColor";	label: qsTr("Manual colors");	id: manualColor	}
 			DropDown
 			{
-				enabled: !manualColors.checked
+				enabled: !manualColor.checked
 				id: paletteSelector
 				name: "nodePalette"
 				label: qsTr("Node palette")
@@ -410,7 +410,7 @@ VariablesForm
 		Group
 		{
 			title: qsTr("Measures shown in centrality plot")
-			enabled: plotCentrality.checked
+			enabled: centralityPlot.checked
 			CheckBox	{	name: "betweenness";		    label: qsTr("Betweenness");			    checked: true	}
 			CheckBox	{	name: "closeness";			    label: qsTr("Closeness");			      checked: true	}
 			CheckBox	{	name: "strength";				    label: qsTr("Strength");			      checked: true	}

inst/qml/NetworkAnalysis.qml

@@ -213,9 +213,9 @@ Form
 				source: ["variables"]
 			}
 
-			AssignedVariablesList { name: "mgmContinuousVariables";		title: qsTr("Continuous Variables");	allowedColumns: ["scale"]}
-			AssignedVariablesList { name: "mgmCategoricalVariables";	title: qsTr("Categorical Variables");	allowedColumns: ["ordinal"]}
-			AssignedVariablesList { name: "mgmCountVariables";			title: qsTr("Count Variables");			allowedColumns: ["nominal"]}
+			AssignedVariablesList { name: "mgmContinuousVariables";		title: qsTr("Continuous Variables");	}
+			AssignedVariablesList { name: "mgmCategoricalVariables";	title: qsTr("Categorical Variables");	}
+			AssignedVariablesList { name: "mgmCountVariables";			title: qsTr("Count Variables");			}
 		}
 	}
 
@@ -383,7 +383,7 @@ Form
 		{
 			name: "mgmVariableTypeShown";
 			title: qsTr("Show Variable Type")
-			visible: [7].includes(estimator.currentIndex)
+			visible: [6].includes(estimator.currentIndex)
 			RadioButton { value: "hide";		label: qsTr("Don't show")						}
 			RadioButton { value: "nodeColor";	label: qsTr("Using node color")					}
 			RadioButton { value: "nodeShape";	label: qsTr("Using node shape"); checked: true	}

po/QML-es.po

@@ -134,7 +134,7 @@ msgstr "Excluir por lista"
 
 msgctxt "NetworkAnalysis|"
 msgid "Sample Size"
-msgstr "Tamaño de la Muestra"
+msgstr "Tamaño de la muestra"
 
 msgctxt "NetworkAnalysis|"
 msgid "Maximum"
@@ -254,7 +254,7 @@ msgstr "Opciones de Bootstrap"
 
 msgctxt "NetworkAnalysis|"
 msgid "Settings"
-msgstr "Configuraciones"
+msgstr "Configuración"
 
 msgctxt "NetworkAnalysis|"
 msgid "Bootstrap network"
@@ -326,27 +326,27 @@ msgstr "Color del grupo"
 
 msgctxt "NetworkAnalysis|"
 msgid "red"
-msgstr "rojo"
+msgstr "Rojo"
 
 msgctxt "NetworkAnalysis|"
 msgid "blue"
-msgstr "azul"
+msgstr "Azul"
 
 msgctxt "NetworkAnalysis|"
 msgid "yellow"
-msgstr "amarillo"
+msgstr "Amarillo"
 
 msgctxt "NetworkAnalysis|"
 msgid "green"
-msgstr "verde"
+msgstr "Verde"
 
 msgctxt "NetworkAnalysis|"
 msgid "purple"
-msgstr "violeta"
+msgstr "Violeta"
 
 msgctxt "NetworkAnalysis|"
 msgid "orange"
-msgstr "anaranjado"
+msgstr "Anaranjado"
 
 msgctxt "NetworkAnalysis|"
 msgid "Group"
@@ -718,27 +718,27 @@ msgstr "Color del grupo"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "red"
-msgstr "rojo"
+msgstr "Rojo"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "blue"
-msgstr "azul"
+msgstr "Azul"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "yellow"
-msgstr "amarillo"
+msgstr "Amarillo"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "green"
-msgstr "verde"
+msgstr "Verde"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "purple"
-msgstr "violeta"
+msgstr "Violeta"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "orange"
-msgstr "anaranjado"
+msgstr "Anaranjado"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "Variables in network"

po/QML-gl.po

@@ -54,7 +54,7 @@ msgstr "CIR"
 
 msgctxt "NetworkAnalysis|"
 msgid "red"
-msgstr "vermello"
+msgstr "Vermello"
 
 msgctxt "NetworkAnalysis|"
 msgid "EBIC"
@@ -106,7 +106,7 @@ msgstr "STARS"
 
 msgctxt "NetworkAnalysis|"
 msgid "green"
-msgstr "verde"
+msgstr "Verde"
 
 msgctxt "NetworkAnalysis|"
 msgid "Min edge strength"
@@ -278,15 +278,15 @@ msgstr "Regresións univariantes"
 
 msgctxt "NetworkAnalysis|"
 msgid "orange"
-msgstr "laranxa"
+msgstr "Laranxa"
 
 msgctxt "NetworkAnalysis|"
 msgid "Edge labels"
 msgstr "Etiquetas das beiras"
 
 msgctxt "NetworkAnalysis|"
 msgid "purple"
-msgstr "morado"
+msgstr "Morado"
 
 msgctxt "NetworkAnalysis|"
 msgid "name for y-coordinates"
@@ -302,7 +302,7 @@ msgstr "Medidas amosadas na gráfica de centrado"
 
 msgctxt "NetworkAnalysis|"
 msgid "yellow"
-msgstr "amarelo"
+msgstr "Amarelo"
 
 msgctxt "NetworkAnalysis|"
 msgid "Parametric"
@@ -406,7 +406,7 @@ msgstr "Opcións de Bootstrap"
 
 msgctxt "NetworkAnalysis|"
 msgid "Settings"
-msgstr "Configuracións"
+msgstr "Configuración"
 
 msgctxt "NetworkAnalysis|"
 msgid "In plot number: "
@@ -514,7 +514,7 @@ msgstr "Valores Ausentes"
 
 msgctxt "NetworkAnalysis|"
 msgid "Sample Size"
-msgstr "Tamaño da Mostra"
+msgstr "Tamaño da mostra"
 
 msgctxt "NetworkAnalysis|"
 msgid "Maximum"
@@ -718,27 +718,27 @@ msgstr "Cor do grupo"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "red"
-msgstr "vermello"
+msgstr "Vermello"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "blue"
-msgstr "azul"
+msgstr "Azul"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "yellow"
-msgstr "amarelo"
+msgstr "Amarelo"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "green"
-msgstr "verde"
+msgstr "Verde"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "purple"
-msgstr "morado"
+msgstr "Morado"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "orange"
-msgstr "laranxa"
+msgstr "Laranxa"
 
 msgctxt "BayesianNetworkAnalysis|"
 msgid "Variables in network"