#74 -- add new library, create middle service

build.gradle

@@ -69,6 +69,7 @@ dependencies {
     implementation group: 'com.ibm.icu', name: 'icu4j', version: '63.1'
     implementation group: 'org.eclipse.jgit', name: 'org.eclipse.jgit',  version: '5.9.0.202009080501-r'
     implementation group: 'net.sourceforge.jFuzzyLogic', name: 'jFuzzyLogic', version: '1.2.1'
+    implementation group: 'com.fuzzylite', name: 'jfuzzylite', version: '6.0.1'
 
     implementation group: 'org.webjars', name: 'jquery', version: '3.6.0'
     implementation group: 'org.webjars', name: 'bootstrap', version: '4.6.0'

src/main/java/ru/ulstu/extractor/GitExtractorApplication.java

@@ -1,16 +1,88 @@
 package ru.ulstu.extractor;
 
+import com.fuzzylite.Engine;
+import com.fuzzylite.FuzzyLite;
+import com.fuzzylite.Op;
+import com.fuzzylite.activation.Highest;
+import com.fuzzylite.defuzzifier.Centroid;
+import com.fuzzylite.norm.s.Maximum;
+import com.fuzzylite.norm.t.AlgebraicProduct;
+import com.fuzzylite.rule.Rule;
+import com.fuzzylite.rule.RuleBlock;
+import com.fuzzylite.term.Trapezoid;
+import com.fuzzylite.variable.InputVariable;
+import com.fuzzylite.variable.OutputVariable;
 import org.springframework.boot.SpringApplication;
 import org.springframework.boot.autoconfigure.SpringBootApplication;
 import org.springframework.scheduling.annotation.EnableScheduling;
-import ru.ulstu.extractor.rule.service.FuzzyInference;
 
 @SpringBootApplication
 @EnableScheduling
 public class GitExtractorApplication {
     public static void main(String[] args) {
+        Engine engine = new Engine();
+        engine.setName("Git rules");
+        engine.setDescription("");
 
-        new FuzzyInference().run();
+        InputVariable obstacle = new InputVariable();
+        obstacle.setName("obstacle");
+        obstacle.setDescription("");
+        obstacle.setEnabled(true);
+        obstacle.setRange(0.000, 1.000);
+        obstacle.setLockValueInRange(false);
+        obstacle.addTerm(new Trapezoid("left", 0.000, 0.700));
+        obstacle.addTerm(new Trapezoid("right", 0.400, 1.000));
+        engine.addInputVariable(obstacle);
+
+        OutputVariable mSteer = new OutputVariable();
+        mSteer.setName("mSteer");
+        mSteer.setDescription("");
+        mSteer.setEnabled(true);
+        mSteer.setRange(0.000, 1.000);
+        mSteer.setLockValueInRange(false);
+        mSteer.setAggregation(new Maximum());
+        mSteer.setDefuzzifier(new Centroid(100));
+        mSteer.setDefaultValue(Double.NaN);
+        mSteer.setLockPreviousValue(false);
+        mSteer.addTerm(new Trapezoid("left", 0.000, 0.700));
+        mSteer.addTerm(new Trapezoid("right", 0.400, 1.000));
+        engine.addOutputVariable(mSteer);
+
+        RuleBlock mamdani = new RuleBlock();
+        mamdani.setName("mamdani");
+        mamdani.setDescription("");
+        mamdani.setEnabled(true);
+        mamdani.setConjunction(null);
+        mamdani.setDisjunction(null);
+        mamdani.setImplication(new AlgebraicProduct());
+        mamdani.setActivation(new Highest());
+        mamdani.addRule(Rule.parse("if obstacle is left then mSteer is right", engine));
+        mamdani.addRule(Rule.parse("if obstacle is right then mSteer is left", engine));
+        engine.addRuleBlock(mamdani);
+
+
+        StringBuilder status = new StringBuilder();
+        if (!engine.isReady(status))
+            throw new RuntimeException("[engine error] engine is not ready:n" + status);
+
+        InputVariable obstacle1 = engine.getInputVariable("obstacle");
+        OutputVariable steer = engine.getOutputVariable("mSteer");
+
+        for (int i = 10; i <= 50; ++i) {
+            double location = obstacle1.getMinimum() + i * (obstacle1.range() / 50);
+            obstacle1.setValue(location);
+            engine.process();
+            if (Double.isNaN(steer.getValue())) {
+                System.out.println("no decision");
+                continue;
+            }
+            FuzzyLite.logger().info(String.format(
+                    "obstacle.input = %s -> steer.output = %s",
+                    Op.str(location), Op.str(steer.getValue())));
+            FuzzyLite.logger().info(String.format(
+                    "obstacle.input = %s -> steer.output = %s",
+                    Op.str(location), steer.highestMembership(steer.getValue()).getSecond().getName()));
+        }
         SpringApplication.run(GitExtractorApplication.class, args);
     }
 }

src/main/java/ru/ulstu/extractor/rule/model/DbRule.java

@@ -7,9 +7,11 @@ import javax.persistence.Entity;
 import javax.persistence.EnumType;
 import javax.persistence.Enumerated;
 import javax.persistence.ManyToOne;
+import javax.persistence.Table;
 
 @Entity
-public class Rule extends BaseEntity {
+@Table(name = "rule")
+public class DbRule extends BaseEntity {
     @ManyToOne
     private AntecedentValue firstAntecedentValue;
 
@@ -24,10 +26,10 @@ public class Rule extends BaseEntity {
 
     private String consequent;
 
-    public Rule() {
+    public DbRule() {
     }
 
-    public Rule(AntecedentValue firstAntecedentValue,
+    public DbRule(AntecedentValue firstAntecedentValue,
                   TimeSeriesType firstAntecedent,
                   AntecedentValue secondAntecedentValue,
                   TimeSeriesType secondAntecedent,

src/main/java/ru/ulstu/extractor/rule/repository/RuleRepository.java

@@ -1,7 +1,7 @@
 package ru.ulstu.extractor.rule.repository;
 
 import org.springframework.data.jpa.repository.JpaRepository;
-import ru.ulstu.extractor.rule.model.Rule;
+import ru.ulstu.extractor.rule.model.DbRule;
 
-public interface RuleRepository extends JpaRepository<Rule, Integer> {
+public interface RuleRepository extends JpaRepository<DbRule, Integer> {
 }

src/main/java/ru/ulstu/extractor/rule/service/FuzzyInference.java

@@ -1,99 +0,0 @@
-package ru.ulstu.extractor.rule.service;
-
-import net.sourceforge.jFuzzyLogic.defuzzifier.DefuzzifierCenterOfGravity;
-import net.sourceforge.jFuzzyLogic.membership.MembershipFunctionTriangular;
-import net.sourceforge.jFuzzyLogic.rule.FuzzyRule;
-import net.sourceforge.jFuzzyLogic.rule.FuzzyRuleExpression;
-import net.sourceforge.jFuzzyLogic.rule.FuzzyRuleSet;
-import net.sourceforge.jFuzzyLogic.rule.FuzzyRuleTerm;
-import net.sourceforge.jFuzzyLogic.rule.LinguisticTerm;
-import net.sourceforge.jFuzzyLogic.rule.Variable;
-import net.sourceforge.jFuzzyLogic.ruleConnection.RuleConnectionMethodAndMin;
-import net.sourceforge.jFuzzyLogic.ruleImplication.RuleImplicationMethodMin;
-
-import java.util.Collections;
-import java.util.Comparator;
-import java.util.LinkedList;
-
-public class FuzzyInference {
-    public void run() {
-        FuzzyRule fuzzyRule1 = new FuzzyRule("rule 1");
-        FuzzyRule fuzzyRule2 = new FuzzyRule("rule 2");
-        FuzzyRule fuzzyRule3 = new FuzzyRule("rule 3");
-
-        Variable weather = new Variable("Погода");
-        weather.getLinguisticTerms().put("солнечно",
-                new LinguisticTerm("солнечно", new MembershipFunctionTriangular(0, 20, 30)));
-        weather.getLinguisticTerms().put("мороз",
-                new LinguisticTerm("мороз", new MembershipFunctionTriangular(-50, -10, 10)));
-        weather.setDefuzzifier(new DefuzzifierCenterOfGravity(weather));
-
-
-        Variable suit = new Variable("Одежда");
-        suit.getLinguisticTerms().put("легко одет",
-                new LinguisticTerm("легко одет", new MembershipFunctionTriangular(0, 5, 10)));
-        suit.getLinguisticTerms().put("тепло одет",
-                new LinguisticTerm("тепло одет", new MembershipFunctionTriangular(5, 10, 20)));
-        suit.setDefuzzifier(new DefuzzifierCenterOfGravity(suit));
-
-        Variable feel = new Variable("Ощущение");
-        feel.getLinguisticTerms().put("Холодно",
-                new LinguisticTerm("Холодно", new MembershipFunctionTriangular(0, 5, 10)));
-        feel.getLinguisticTerms().put("Жарко",
-                new LinguisticTerm("Жарко", new MembershipFunctionTriangular(5, 10, 20)));
-        feel.setDefuzzifier(new DefuzzifierCenterOfGravity(feel));
-
-        FuzzyRuleTerm weatherTerm1 = new FuzzyRuleTerm(weather, "солнечно", false);
-        FuzzyRuleTerm weatherTerm2 = new FuzzyRuleTerm(weather, "мороз", false);
-
-        FuzzyRuleTerm suitTerm1 = new FuzzyRuleTerm(suit, "легко одет", false);
-        FuzzyRuleTerm suitTerm2 = new FuzzyRuleTerm(suit, "тепло одет", false);
-
-        FuzzyRuleTerm feelCold = new FuzzyRuleTerm(feel, "Холодно", false);
-        FuzzyRuleTerm feelWarm = new FuzzyRuleTerm(feel, "Жарко", false);
-
-        FuzzyRuleExpression expression1 = new FuzzyRuleExpression(weatherTerm1, suitTerm2, new RuleConnectionMethodAndMin());
-        fuzzyRule1.setAntecedents(expression1);
-        fuzzyRule1.setConsequents(new LinkedList<>(Collections.singleton(feelWarm)));
-
-        FuzzyRuleExpression expression2 = new FuzzyRuleExpression(weatherTerm2, suitTerm1, new RuleConnectionMethodAndMin());
-        fuzzyRule2.setAntecedents(expression2);
-        fuzzyRule2.setConsequents(new LinkedList<>(Collections.singleton(feelCold)));
-
-        FuzzyRuleExpression expression3 = new FuzzyRuleExpression(weatherTerm1, suitTerm1, new RuleConnectionMethodAndMin());
-        fuzzyRule3.setAntecedents(expression3);
-        fuzzyRule3.setConsequents(new LinkedList<>(Collections.singleton(feelCold)));
-
-        fuzzyRule1.evaluate(new RuleImplicationMethodMin());
-        fuzzyRule2.evaluate(new RuleImplicationMethodMin());
-        //fuzzyRule3.evaluate(new RuleImplicationMethodMin());
-
-        FuzzyRuleSet set = new FuzzyRuleSet();
-        set.add(fuzzyRule1);
-        set.add(fuzzyRule2);
-        set.add(fuzzyRule3);
-        set.evaluate();
-
-        set.setVariable("Погода", 25);
-        set.setVariable("Одежда", 7);
-        // Evaluate fuzzy set
-        set.evaluate();
-
-        // Show output variable's chart
-        //set.getVariable("Ощущение").chartDefuzzifier(true);
-        System.out.println(set.getVariable("Ощущение").getLatestDefuzzifiedValue());
-        System.out.println(set);
-        System.out.println(set.getVariable("Ощущение"));
-        System.out.println(
-                feel.getLinguisticTerms()
-                        .entrySet()
-                        .stream()
-                        .max(Comparator.comparing(e -> e.getValue()
-                                .getMembershipFunction()
-                                .membership(set.getVariable("Ощущение").getLatestDefuzzifiedValue())))
-                        .get()
-                        .getValue().getTermName()
-        );
-        set.getVariable("Ощущение").chartDefuzzifier(true);
-    }
-}

src/main/java/ru/ulstu/extractor/rule/service/FuzzyInferenceService.java

@@ -0,0 +1,97 @@
+package ru.ulstu.extractor.rule.service;
+
+import com.fuzzylite.Engine;
+import com.fuzzylite.activation.Highest;
+import com.fuzzylite.norm.t.AlgebraicProduct;
+import com.fuzzylite.rule.Rule;
+import com.fuzzylite.rule.RuleBlock;
+import com.fuzzylite.term.Triangle;
+import com.fuzzylite.variable.InputVariable;
+import com.fuzzylite.variable.OutputVariable;
+import org.springframework.stereotype.Service;
+import ru.ulstu.extractor.rule.model.AntecedentValue;
+import ru.ulstu.extractor.rule.model.DbRule;
+
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+@Service
+public class FuzzyInferenceService {
+    private final static String RULE_TEMPLATE = "if %s is %s AND %s is %s then state is %s";
+    private final RuleService ruleService;
+    private final AntecedentValueService antecedentValueService;
+
+    public FuzzyInferenceService(RuleService ruleService,
+                                 AntecedentValueService antecedentValueService) {
+        this.ruleService = ruleService;
+        this.antecedentValueService = antecedentValueService;
+    }
+
+    public List<String> getRulesFromDb() {
+        List<DbRule> dbDbRules = ruleService.getList();
+        return dbDbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
+    }
+
+    private String getFuzzyRule(DbRule dbRule) {
+        return String.format(RULE_TEMPLATE,
+                dbRule.getFirstAntecedent().name(),
+                dbRule.getFirstAntecedentValue().getAntecedentValue(),
+                dbRule.getSecondAntecedent().name(),
+                dbRule.getSecondAntecedentValue().getAntecedentValue(),
+                dbRule.getConsequent());
+    }
+
+    private RuleBlock getRuleBlock(Engine engine, Map<String, Double> variableValues, List<AntecedentValue> antecedentValues) {
+        variableValues.forEach((key, value) -> {
+            InputVariable input = new InputVariable();
+            input.setName(key);
+            input.setDescription("");
+            input.setEnabled(true);
+            input.setRange(0.000, 1.000);
+            input.setLockValueInRange(false);
+            for (int i = 0; i < antecedentValues.size(); i++) {
+                input.addTerm(new Triangle(antecedentValues.get(i).getAntecedentValue(), i, i + 2));
+            }
+            engine.addInputVariable(input);
+        });
+
+
+        RuleBlock mamdani = new RuleBlock();
+        mamdani.setName("mamdani");
+        mamdani.setDescription("");
+        mamdani.setEnabled(true);
+        mamdani.setConjunction(null);
+        mamdani.setDisjunction(null);
+        mamdani.setImplication(new AlgebraicProduct());
+        mamdani.setActivation(new Highest());
+        getRulesFromDb().forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
+        return mamdani;
+    }
+
+    private Engine getFuzzyEngine() {
+        Engine engine = new Engine();
+        engine.setName("Git rules");
+        engine.setDescription("");
+        return engine;
+    }
+
+    public String run() {
+        Engine engine = getFuzzyEngine();
+        List<AntecedentValue> antecedentValues = antecedentValueService.getList();
+        Map<String, Double> variableValues = new HashMap<>();
+        engine.addRuleBlock(getRuleBlock(engine, variableValues, antecedentValues));
+        return getConsequent(engine, variableValues);
+    }
+
+    private String getConsequent(Engine engine, Map<String, Double> variableValues) {
+        OutputVariable outputVariable = engine.getOutputVariable("state");
+        for (Map.Entry<String, Double> variableValue : variableValues.entrySet()) {
+            InputVariable inputVariable = engine.getInputVariable(variableValue.getKey());
+            inputVariable.setValue(variableValue.getValue());
+        }
+        engine.process();
+        return outputVariable.highestMembership(outputVariable.getValue()).getSecond().getName();
+    }
+}

src/main/java/ru/ulstu/extractor/rule/service/RuleService.java

@@ -2,7 +2,7 @@ package ru.ulstu.extractor.rule.service;
 
 import org.springframework.stereotype.Service;
 import ru.ulstu.extractor.rule.model.AddRuleForm;
-import ru.ulstu.extractor.rule.model.Rule;
+import ru.ulstu.extractor.rule.model.DbRule;
 import ru.ulstu.extractor.rule.repository.RuleRepository;
 import ru.ulstu.extractor.ts.model.TimeSeriesType;
 import ru.ulstu.extractor.ts.service.TimeSeriesService;
@@ -23,12 +23,12 @@ public class RuleService {
         this.antecedentValueService = antecedentValueService;
     }
 
-    public List<Rule> getList() {
+    public List<DbRule> getList() {
         return ruleRepository.findAll();
     }
 
     public void saveRule(AddRuleForm addRuleForm) {
-        ruleRepository.save(new Rule(antecedentValueService.getById(addRuleForm.getFirstAntecedentValueId()),
+        ruleRepository.save(new DbRule(antecedentValueService.getById(addRuleForm.getFirstAntecedentValueId()),
                 TimeSeriesType.valueOf(addRuleForm.getFirstAntecedentId()),
                 antecedentValueService.getById(addRuleForm.getSecondAntecedentValueId()),
                 TimeSeriesType.valueOf(addRuleForm.getSecondAntecedentId()),

src/main/resources/templates/listRules.html

@@ -14,15 +14,15 @@
         </tr>
         </thead>
         <tbody>
-        <tr th:each="rule: ${rules}">
+        <tr th:each="dbRule: ${rules}">
             <td><span class="badge badge-info">Если</span></td>
-            <td><span class="badge badge-success" th:text="${rule.firstAntecedent.description}"></span></td>
+            <td><span class="badge badge-success" th:text="${dbRule.firstAntecedent.description}"></span></td>
-            <td><span class="badge badge-success" th:text="${rule.firstAntecedentValue.antecedentValue}"></span></td>
+            <td><span class="badge badge-success" th:text="${dbRule.firstAntecedentValue.antecedentValue}"></span></td>
             <td><span class="badge badge-info">и</span></td>
-            <td><span class="badge badge-success" th:text="${rule.secondAntecedent.description  }"></span></td>
+            <td><span class="badge badge-success" th:text="${dbRule.secondAntecedent.description  }"></span></td>
-            <td><span class="badge badge-success" th:text="${rule.secondAntecedentValue.antecedentValue}"></span></td>
+            <td><span class="badge badge-success" th:text="${dbRule.secondAntecedentValue.antecedentValue}"></span></td>
             <td><span class="badge badge-info">то</span></td>
-            <td><span class="badge badge-warning" th:text="${rule.consequent}"></span></td>
+            <td><span class="badge badge-warning" th:text="${dbRule.consequent}"></span></td>
         </tr>
         </tbody>
     </table>