X-Git-Url: https://git.piment-noir.org/?a=blobdiff_plain;f=src%2Futils%2FStatisticUtils.ts;h=cef15f52a07045294f65d17fdccab44b85ae6f58;hb=aa63c9b772ff17bce2febf68a57720eab96d5f8e;hp=bb9a847091decf2ca488f83ad8c3d9d579d6e7fd;hpb=4884b8d37eebb90a39a8295f1b61cf822dcf0869;p=e-mobility-charging-stations-simulator.git

diff --git a/src/utils/StatisticUtils.ts b/src/utils/StatisticUtils.ts
index bb9a8470..cef15f52 100644
--- a/src/utils/StatisticUtils.ts
+++ b/src/utils/StatisticUtils.ts
@@ -1,55 +1,90 @@
-import { Utils } from './Utils';
+import { isEmptyArray } from './Utils.js'
 
+/**
+ * Computes the average of the given data set.
+ *
+ * @param dataSet - Data set.
+ * @returns The average of the given data set.
+ * @internal
+ */
+export const average = (dataSet: number[]): number => {
+  if (Array.isArray(dataSet) && dataSet.length === 0) {
+    return 0
+  }
+  if (Array.isArray(dataSet) && dataSet.length === 1) {
+    return dataSet[0]
+  }
+  return dataSet.reduce((accumulator, nb) => accumulator + nb, 0) / dataSet.length
+}
+
+/**
+ * Computes the median of the given data set.
+ *
+ * @param dataSet - Data set.
+ * @returns The median of the given data set.
+ * @internal
+ */
 export const median = (dataSet: number[]): number => {
-  if (Utils.isEmptyArray(dataSet)) {
-    return 0;
+  if (isEmptyArray(dataSet)) {
+    return 0
   }
-  if (Array.isArray(dataSet) === true && dataSet.length === 1) {
-    return dataSet[0];
+  if (Array.isArray(dataSet) && dataSet.length === 1) {
+    return dataSet[0]
   }
-  const sortedDataSet = dataSet.slice().sort((a, b) => a - b);
+  const sortedDataSet = dataSet.slice().sort((a, b) => a - b)
   return (
     (sortedDataSet[(sortedDataSet.length - 1) >> 1] + sortedDataSet[sortedDataSet.length >> 1]) / 2
-  );
-};
+  )
+}
 
 // TODO: use order statistics tree https://en.wikipedia.org/wiki/Order_statistic_tree
 export const nthPercentile = (dataSet: number[], percentile: number): number => {
   if (percentile < 0 && percentile > 100) {
-    throw new RangeError('Percentile is not between 0 and 100');
+    throw new RangeError('Percentile is not between 0 and 100')
   }
-  if (Utils.isEmptyArray(dataSet)) {
-    return 0;
+  if (isEmptyArray(dataSet)) {
+    return 0
   }
-  const sortedDataSet = dataSet.slice().sort((a, b) => a - b);
+  const sortedDataSet = dataSet.slice().sort((a, b) => a - b)
   if (percentile === 0 || sortedDataSet.length === 1) {
-    return sortedDataSet[0];
+    return sortedDataSet[0]
   }
   if (percentile === 100) {
-    return sortedDataSet[sortedDataSet.length - 1];
+    return sortedDataSet[sortedDataSet.length - 1]
   }
-  const percentileIndexBase = (percentile / 100) * (sortedDataSet.length - 1);
-  const percentileIndexInteger = Math.floor(percentileIndexBase);
-  if (!Utils.isNullOrUndefined(sortedDataSet[percentileIndexInteger + 1])) {
+  const percentileIndexBase = (percentile / 100) * (sortedDataSet.length - 1)
+  const percentileIndexInteger = Math.floor(percentileIndexBase)
+  if (sortedDataSet[percentileIndexInteger + 1] != null) {
     return (
       sortedDataSet[percentileIndexInteger] +
       (percentileIndexBase - percentileIndexInteger) *
         (sortedDataSet[percentileIndexInteger + 1] - sortedDataSet[percentileIndexInteger])
-    );
+    )
   }
-  return sortedDataSet[percentileIndexInteger];
-};
+  return sortedDataSet[percentileIndexInteger]
+}
 
-export const stdDeviation = (dataSet: number[]): number => {
-  let totalDataSet = 0;
-  for (const data of dataSet) {
-    totalDataSet += data;
-  }
-  const dataSetMean = totalDataSet / dataSet.length;
-  let totalGeometricDeviation = 0;
-  for (const data of dataSet) {
-    const deviation = data - dataSetMean;
-    totalGeometricDeviation += deviation * deviation;
-  }
-  return Math.sqrt(totalGeometricDeviation / dataSet.length);
-};
+/**
+ * Computes the sample standard deviation of the given data set.
+ *
+ * @param dataSet - Data set.
+ * @param dataSetAverage - Average of the data set.
+ * @returns The sample standard deviation of the given data set.
+ * @see https://en.wikipedia.org/wiki/Unbiased_estimation_of_standard_deviation
+ * @internal
+ */
+export const stdDeviation = (
+  dataSet: number[],
+  dataSetAverage: number = average(dataSet)
+): number => {
+  if (isEmptyArray(dataSet)) {
+    return 0
+  }
+  if (Array.isArray(dataSet) && dataSet.length === 1) {
+    return 0
+  }
+  return Math.sqrt(
+    dataSet.reduce((accumulator, num) => accumulator + Math.pow(num - dataSetAverage, 2), 0) /
+      (dataSet.length - 1)
+  )
+}