update description

contribs/application/src/main/java/org/matsim/application/analysis/population/TripChoiceAnalysis.java

@@ -199,11 +199,8 @@ public void writeChoiceEvaluation(Path path) throws IOException {
 			csv.printRecord("Info", "Value");
 
 			csv.printRecord("Accuracy", round(tp / total));
-			csv.printRecord("Precision (micro avg.)", round(tp / tpfp));
 			csv.printRecord("Precision (macro avg.)", round(precision.orElse(0)));
-			csv.printRecord("Recall (micro avg.)", round(tp / tpfn));
 			csv.printRecord("Recall (macro avg.)", round(recall.orElse(0)));
-			csv.printRecord("F1 Score (micro avg.)", round(2 * tp / (tpfp + tpfn)));
 			csv.printRecord("F1 Score (macro avg.)", round(f1.orElse(0)));
 			csv.printRecord("Cohen’s Kappa", round(computeCohenKappa(confusionMatrix)));
 		}

contribs/simwrapper/src/main/java/org/matsim/simwrapper/dashboard/TripDashboard.java

@@ -317,7 +317,7 @@ private void createChoiceTab(Layout layout, String[] args) {
 				- Precision is the fraction of instances correctly classified as belonging to a specific class out of all instances the model predicted to belong to that class.
 				- Recall is the fraction of instances in a class that the model correctly classified out of all instances in that class.
 				- The macro-average computes the metric independently for each class and then take the average (hence treating all classes equally).
-				- The micro-average will aggregate the contributions of all classes to compute the average metric.
+				- The micro-averages of Precision, Recall and F1 score are identical to the accuracy.
 				- Cohen's Kappa is a measure of agreement between two raters that corrects for chance agreement. 1.0 indicates perfect agreement, 0.0 or less indicates agreement by chance.
 				""";
 		});
@@ -326,7 +326,6 @@ private void createChoiceTab(Layout layout, String[] args) {
 			viz.title = "Choice Evaluation";
 			viz.description = "Metrics for mode choice.";
 			viz.showAllRows = true;
-			viz.height = 6d;
 			viz.dataset = data.compute(TripAnalysis.class, "mode_choice_evaluation.csv", args);
 		});
 
@@ -343,7 +342,7 @@ private void createChoiceTab(Layout layout, String[] args) {
 			viz.xAxisTitle = "Predicted";
 			viz.yAxisTitle = "True";
 			viz.y = "True/Pred";
-			viz.flipAxes = "True";
+			viz.flipAxes = false;
 			viz.dataset = data.compute(TripAnalysis.class, "mode_confusion_matrix.csv", args);
 		});
 

contribs/simwrapper/src/main/java/org/matsim/simwrapper/viz/Heatmap.java

@@ -43,7 +43,7 @@ public class Heatmap extends Viz {
 	 * and y axes. Can be useful if your data is stored
 	 * one way, but you want it displayed the other.
 	 */
-	public String flipAxes;
+	public Boolean flipAxes;
 
 	public Heatmap() {
 		super("heatmap");