Added RuleBase class to allow easier use of the library

LICENSE.md

@@ -1,6 +1,6 @@
 The MIT License (MIT)
 
-Copyright (c) 2015 [these people](https://github.com/sebs/es6-fuzz/graphs/contributors)
+Copyright (c) 2015 [these people](https://github.com/skanderturki/js-fuzzy-logic/graphs/contributors)
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

Readme.md

@@ -1,4 +1,4 @@
-# es6-fuzz 
+# js-fuzzy-logic ( forked from: es6-fuzz ) 
 
 > Fuzzy Logic in Javascript
 
@@ -21,12 +21,6 @@ Supported fuzzyfiers
 * [api docs](http://sebs.github.io/es6-fuzz)
 * [changelog](https://github.com/sebs/es6-fuzz/blob/master/docs/CHANGELOG.md)
 
-## Install and Usage
-
-es6-fuzz is available as a NPM package.
-
-```
-npm install es6-fuzz
 ```
 ## Example
 
@@ -57,6 +51,8 @@ var res = logic
 
 * hot
 
+## Example 3: Usage of the RuleBase class
+(see example-1-RuleBase.js)
 
 ## Usage with boon-js
 

docs/CHANGELOG.md

@@ -1,3 +1,12 @@
+2023-01-19
+==========
+  * 4.1.0
+  * Added batch evaluation api
+  * (churn): changelog
+  * feature: Add a class that allows client code to group evaluator rules in an array of 3-tuples,
+    each 3-tuple associates the evaluator to its output and evaluation result.
+
+
 2022-06-14
 ==========
 

example-1-RuleBase.js

@@ -0,0 +1,70 @@
+const Logic = require('./lib/logic')
+const Trapezoid = require('./lib/curve/trapezoid');
+const boon = require('boon-js');
+
+const RuleBase = require('./lib/RuleBase');
+
+const createLikelihoodLogic = () => {
+  var logicLikelihood = new Logic();
+  const lowLikelihood = new Trapezoid(0, 0, 2, 3);
+  const moderateLikelihood = new Trapezoid(2, 3, 7, 8);
+  const highLikelihood = new Trapezoid(7, 8, 10, 11);
+
+  logicLikelihood.init('low', lowLikelihood)
+  logicLikelihood.or('moderate', moderateLikelihood)
+  logicLikelihood.or('high', highLikelihood);
+
+  return logicLikelihood;
+}
+
+const createImpactLogic = () => {
+  var logicImpact = new Logic();
+  const lowImpact = new Trapezoid(0, 0, 2, 3);
+  const moderateImpact = new Trapezoid(2, 3, 7, 8);
+  const highImpact = new Trapezoid(7, 8, 10, 11);
+
+  logicImpact.init('low', lowImpact)
+  logicImpact.or('moderate', moderateImpact)
+  logicImpact.or('high', highImpact);
+
+  return logicImpact;
+}
+
+const assess = (likelihood, impact) => {
+  var logicLikelihood = createLikelihoodLogic();
+
+  var logicImpact = createImpactLogic();
+
+  const assessments = new RuleBase();
+
+  /////////////////////////////////////////////////////////////////////////////////////////////////
+  assessments.addRule(boon.getEvaluator('likelihood.low AND impact.low'), "very low");
+  assessments.addRule(boon.getEvaluator('likelihood.low AND impact.moderate'), "low");
+  assessments.addRule(boon.getEvaluator('likelihood.low AND impact.high'), "top low");
+   /////////////////////////////////////////////////////////////////////////////////////////////////
+  assessments.addRule(boon.getEvaluator('likelihood.moderate AND impact.low'), "low");
+  assessments.addRule(boon.getEvaluator('likelihood.moderate AND impact.moderate'), "top low");
+  assessments.addRule(boon.getEvaluator('likelihood.moderate AND impact.high'), "moderate");
+   /////////////////////////////////////////////////////////////////////////////////////////////////
+  assessments.addRule(boon.getEvaluator('likelihood.high AND impact.low'), "moderate");
+  assessments.addRule(boon.getEvaluator('likelihood.high AND impact.moderate'), "high");
+  assessments.addRule(boon.getEvaluator('likelihood.high AND impact.high'), "very high");
+  /////////////////////////////////////////////////////////////////////////////////////////////////
+
+  // Defuzzify //
+  const resLikelihood = logicLikelihood.defuzzify(likelihood, 'likelihood');
+  const resImpact = logicImpact.defuzzify(impact, 'impact');
+
+  const jsBoonInput = { ...resLikelihood.boonJsInputs, ...resImpact.boonJsInputs }
+
+  assessments.evaluateAllRules(jsBoonInput);
+
+  return assessments.getResult();
+}
+
+// Launch test cases
+
+console.log("Assessment result for {likelihood: 1, impact: 2}: " + assess( 1, 2));
+console.log("Assessment result for {likelihood: 1, impact: 8}: " + assess( 1, 8));
+console.log("Assessment result for {likelihood: 8, impact: 2}: " + assess( 8, 2));
+console.log("Assessment result for {likelihood: 9, impact: 10}: " + assess( 9, 10));

lib/RuleBase.js

@@ -0,0 +1,52 @@
+'use strict'
+
+/** 
+ * Helper class that allows client code to group evaluator rules in an array of 3-tuples,
+ * each 3-tuple associates the evaluator (built out of a rule) to its output and evaluation result.
+ * (For more information on to use it, please refer to example_1_RuleBase.js).
+*/
+class RuleBase {
+
+  /** 
+   * just creates an empty array to hold the 3-tuples 
+   * */
+  constructor() {
+    this.rules = [];
+  }
+
+  /** 
+   * adds a 3-tuples of { evaluator, evaluation, result } and the evaluation is 
+   * initialized to "false".
+   */
+  addRule(evaluator, result) {
+    this.rules.push( { evaluator: evaluator, evaluation: false, result: result} );
+  }
+
+  /**
+   * launches batch evaluation of all rules against the given input.
+   * This method has to be called before getResult().
+   * @param {*} input: the input object that contains a value for each fuzzy variable of the model.
+   */
+  evaluateAllRules(input){
+    for(let i = 0; i < this.rules.length; i++){
+      this.rules[i].evaluation = this.rules[i].evaluator(input);
+    }
+  }
+
+  /**
+   * gets the final result of the defuzzification process.
+   * It looks for the rule (should be only one if the model is correct) that 
+   * was evaluated to true.
+   */
+  getResult(){
+    for(let i = 0; i < this.rules.length; i++){
+      if( this.rules[i].evaluation == true )
+        return this.rules[i].result;
+    }
+    // If no rule evaluated to true then there is a problem with the model.
+    return(-1);
+  }
+
+}
+
+module.exports = RuleBase;