X-Git-Url: https://git.piment-noir.org/?a=blobdiff_plain;f=src%2Futils%2FStatisticUtils.ts;h=9f50b8eaa12b08037ef9c49b042ac96a62463bef;hb=840ca85d7c40a6ee6f3a85a50e68dbea2f90acb8;hp=7f338ff9d08d88651a6d012b036ef73f43946ec5;hpb=8f60746ca1192bfcab03d890016a4704703a701a;p=e-mobility-charging-stations-simulator.git

diff --git a/src/utils/StatisticUtils.ts b/src/utils/StatisticUtils.ts
index 7f338ff9..9f50b8ea 100644
--- a/src/utils/StatisticUtils.ts
+++ b/src/utils/StatisticUtils.ts
@@ -1,76 +1,53 @@
-import { isEmptyArray, isNullOrUndefined } from './Utils';
+import { mean } from 'rambda'
 
-/**
- * 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;
-};
+export const min = (...args: number[]): number =>
+  args.reduce((minimum, num) => (minimum < num ? minimum : num), Infinity)
 
-/**
- * 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 (isEmptyArray(dataSet)) {
-    return 0;
-  }
-  if (Array.isArray(dataSet) === true && dataSet.length === 1) {
-    return dataSet[0];
-  }
-  const sortedDataSet = dataSet.slice().sort((a, b) => a - b);
-  return (
-    (sortedDataSet[(sortedDataSet.length - 1) >> 1] + sortedDataSet[sortedDataSet.length >> 1]) / 2
-  );
-};
+export const max = (...args: number[]): number =>
+  args.reduce((maximum, num) => (maximum > num ? maximum : num), -Infinity)
 
 // 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 (isEmptyArray(dataSet)) {
-    return 0;
+  if (Array.isArray(dataSet) && dataSet.length === 0) {
+    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 (!isNullOrUndefined(sortedDataSet[percentileIndexInteger + 1])) {
+  const base = (percentile / 100) * (sortedDataSet.length - 1)
+  const baseIndex = Math.floor(base)
+  // eslint-disable-next-line @typescript-eslint/no-unnecessary-condition
+  if (sortedDataSet[baseIndex + 1] != null) {
     return (
-      sortedDataSet[percentileIndexInteger] +
-      (percentileIndexBase - percentileIndexInteger) *
-        (sortedDataSet[percentileIndexInteger + 1] - sortedDataSet[percentileIndexInteger])
-    );
+      sortedDataSet[baseIndex] +
+      (base - baseIndex) * (sortedDataSet[baseIndex + 1] - sortedDataSet[baseIndex])
+    )
   }
-  return sortedDataSet[percentileIndexInteger];
-};
+  return sortedDataSet[baseIndex]
+}
 
-export const stdDeviation = (
-  dataSet: number[],
-  dataSetAverage: number = average(dataSet),
-): number => {
+/**
+ * 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 = mean(dataSet)): number => {
+  if (Array.isArray(dataSet) && (dataSet.length === 0 || dataSet.length === 1)) {
+    return 0
+  }
   return Math.sqrt(
-    dataSet.reduce((accumulator, num) => {
-      return accumulator + Math.pow(num - dataSetAverage, 2);
-    }, 0) / dataSet.length,
-  );
-};
+    dataSet.reduce((accumulator, num) => accumulator + Math.pow(num - dataSetAverage, 2), 0) /
+      (dataSet.length - 1)
+  )
+}