X-Git-Url: https://git.piment-noir.org/?a=blobdiff_plain;f=src%2Futils%2FUtils.ts;h=3d8c73bdf0cdbeec9516dd079832587a0696ebba;hb=6082281f1beebdf0126417b694c134ea4753442c;hp=f701cea041ab831d1b1ff323123e02c60b69b11b;hpb=878e026c886468c5d488b75a6d3636abea6fc07c;p=e-mobility-charging-stations-simulator.git

diff --git a/src/utils/Utils.ts b/src/utils/Utils.ts
index f701cea0..3d8c73bd 100644
--- a/src/utils/Utils.ts
+++ b/src/utils/Utils.ts
@@ -3,7 +3,6 @@ import util from 'node:util';
 
 import clone from 'just-clone';
 
-// import { Constants } from './internal';
 import { Constants } from './Constants';
 import { WebSocketCloseEventStatusString } from '../types';
 
@@ -191,7 +190,7 @@ export class Utils {
   }
 
   public static isCFEnvironment(): boolean {
-    return process.env.VCAP_APPLICATION !== undefined;
+    return !Utils.isNullOrUndefined(process.env.VCAP_APPLICATION);
   }
 
   public static isIterable<T>(obj: T): boolean {
@@ -222,18 +221,12 @@ export class Utils {
     return value == null;
   }
 
-  public static isEmptyArray(object: unknown | unknown[]): boolean {
-    if (Array.isArray(object) && object.length === 0) {
-      return true;
-    }
-    return false;
+  public static isEmptyArray(object: unknown): boolean {
+    return Array.isArray(object) && object.length === 0;
   }
 
-  public static isNotEmptyArray(object: unknown | unknown[]): boolean {
-    if (Array.isArray(object) && object.length > 0) {
-      return true;
-    }
-    return false;
+  public static isNotEmptyArray(object: unknown): boolean {
+    return Array.isArray(object) && object.length > 0;
   }
 
   public static isEmptyObject(obj: object): boolean {
@@ -255,9 +248,9 @@ export class Utils {
    * @param retryNumber - the number of retries that have already been attempted
    * @returns delay in milliseconds
    */
-  public static exponentialDelay(retryNumber = 0): number {
+  public static exponentialDelay(retryNumber = 0, maxDelayRatio = 0.2): number {
     const delay = Math.pow(2, retryNumber) * 100;
-    const randomSum = delay * 0.2 * Utils.secureRandom(); // 0-20% of the delay
+    const randomSum = delay * maxDelayRatio * Utils.secureRandom(); // 0-20% of the delay
     return delay + randomSum;
   }
 
@@ -341,4 +334,59 @@ export class Utils {
     }
     return '(Unknown)';
   }
+
+  public static median(dataSet: number[]): number {
+    if (Utils.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
+    );
+  }
+
+  // TODO: use order statistics tree https://en.wikipedia.org/wiki/Order_statistic_tree
+  public static percentile(dataSet: number[], percentile: number): number {
+    if (percentile < 0 && percentile > 100) {
+      throw new RangeError('Percentile is not between 0 and 100');
+    }
+    if (Utils.isEmptyArray(dataSet)) {
+      return 0;
+    }
+    const sortedDataSet = dataSet.slice().sort((a, b) => a - b);
+    if (percentile === 0 || sortedDataSet.length === 1) {
+      return sortedDataSet[0];
+    }
+    if (percentile === 100) {
+      return sortedDataSet[sortedDataSet.length - 1];
+    }
+    const percentileIndexBase = (percentile / 100) * (sortedDataSet.length - 1);
+    const percentileIndexInteger = Math.floor(percentileIndexBase);
+    if (!Utils.isNullOrUndefined(sortedDataSet[percentileIndexInteger + 1])) {
+      return (
+        sortedDataSet[percentileIndexInteger] +
+        (percentileIndexBase - percentileIndexInteger) *
+          (sortedDataSet[percentileIndexInteger + 1] - sortedDataSet[percentileIndexInteger])
+      );
+    }
+    return sortedDataSet[percentileIndexInteger];
+  }
+
+  public static 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);
+  }
 }