Use median instead of average to avoid outliers

scripts/performance-report.ts

@@ -150,7 +150,7 @@ export async function generatePerformanceReport(path: string) {
             data: {
                 datasets: [
                     {
-                        label: '${valueLabel} (average of 10 runs)',
+                        label: '${valueLabel} (median of 10 runs)',
                         data: ${JSON.stringify(data)}
                     },
                     {
@@ -289,12 +289,12 @@ export async function readEntries(path: string, values: string[]): Promise<{ val
  * This function walks through all value labels and each history element for that value label and applies the following:
  * * If the entry represents the measurement of a single run (i.e. ends with `_X`) and has the same entry label as the previous entry, track it to be combined into one entry.
  * * If the entry does not represent a single run (i.e. does not end with `_X`) or has a different entry label, conclude the previous collection and start a new one.
- * Concluding the previous collection means computing the average and the best of ten value and putting it into a single `ValueHistoryEntry` that combines all runs of the current
+ * Concluding the previous collection means computing the median and the best of ten value and putting it into a single `ValueHistoryEntry` that combines all runs of the current
  * collection. The first element of the collection determines the label of the entire collection.
  * 
  * @param values raw values as read from performance metrics files (key is the label of the value, value is the history of values),
  *               whereas the ValueHistory.history` of each entry must be sorted ascending by date and run.
- * @returns post processed values with the averages and best of ten values of multiple runs.
+ * @returns post processed values with the median values and best of ten values of multiple runs.
  */
 export function processValues(values: Map<string, ValueHistory>): Map<string, ValueHistory> {
     const processedValues = new Map<string, ValueHistory>();
@@ -345,7 +345,7 @@ function toCombinedValueHistoryEntry(entries: ValueHistoryEntry[]): ValueHistory
     const combinesRuns = entries.map(entry => entry.entryLabel);
     const matchArray = combinesRuns[0].match(matchUntilUnderscoreOrDot);
     const entryLabel = matchArray ? matchArray[0] + (entries.length > 1 ? '[]' : '') : combinesRuns[0];
-    const value = averageValue(values);
+    const value = medianValue(values);
     const best = bestValue(values);
     return {
         entryLabel,
@@ -355,8 +355,13 @@ function toCombinedValueHistoryEntry(entries: ValueHistoryEntry[]): ValueHistory
     }
 }
 
-function averageValue(values: number[]): number {
-    return values.reduce((a, b) => a + b, 0) / values.length;
+function medianValue(values: number[]): number {
+    const mid = Math.floor(values.length / 2);
+    const sortedValues = values.sort();
+    if (values.length % 2 === 0) {
+        return (sortedValues[mid - 1] + sortedValues[mid]) / 2;
+    }
+    return sortedValues[mid];
 }
 
 function bestValue(values: number[]): number {